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![AD620
Rev. H | Page 15 of 20
Precision V-I Converter
The AD620, along with another op amp and two resistors,
makes a precision current source (Figure 40). The op amp
buffers the reference terminal to maintain good CMR. The
output voltage, VX, of the AD620 appears across R1, which
converts it to a current. This current, less only the input bias
current of the op amp, then flows out to the load.
AD620RG
–VS
VIN+
VIN–
LOAD
R1
IL
Vx
I =L
R1
=
IN+[(V ) – (V )] GIN–
R1
6
5
+ V –X
42
1
8
3 7
+VS
AD705
00775-0-044
Figure 40. Precision Voltage-to-Current Converter (Operates on 1.8 mA, ±3 V)
GAIN SELECTION
The AD620 gain is resistor-programmed by RG, or more
precisely, by whatever impedance appears between Pins 1 and 8.
The AD620 is designed to offer accurate gains using 0.1% to 1%
resistors. Table 5 shows required values of RG for various gains.
Note that for G = 1, the RG pins are unconnected (RG = ∞). For
any arbitrary gain, RG can be calculated by using the formula:
1
4.49
−
Ω
=
G
k
RG
To minimize gain error, avoid high parasitic resistance in series
with RG; to minimize gain drift, RG should have a low TC—less
than 10 ppm/°C—for the best performance.
Table 5. Required Values of Gain Resistors
1% Std Table
Value of RG(Ω)
Calculated
Gain
0.1% Std Table
Value of RG(Ω )
Calculated
Gain
49.9 k 1.990 49.3 k 2.002
12.4 k 4.984 12.4 k 4.984
5.49 k 9.998 5.49 k 9.998
2.61 k 19.93 2.61 k 19.93
1.00 k 50.40 1.01 k 49.91
499 100.0 499 100.0
249 199.4 249 199.4
100 495.0 98.8 501.0
49.9 991.0 49.3 1,003.0
INPUT AND OUTPUT OFFSET VOLTAGE
The low errors of the AD620 are attributed to two sources,
input and output errors. The output error is divided by G when
referred to the input. In practice, the input errors dominate at
high gains, and the output errors dominate at low gains. The
total VOS for a given gain is calculated as
Total Error RTI = input error + (output error/G)
Total Error RTO = (input error × G) + output error
REFERENCE TERMINAL
The reference terminal potential defines the zero output voltage
and is especially useful when the load does not share a precise
ground with the rest of the system. It provides a direct means of
injecting a precise offset to the output, with an allowable range
of 2 V within the supply voltages. Parasitic resistance should be
kept to a minimum for optimum CMR.
INPUT PROTECTION
The AD620 safely withstands an input current of ±60 mA for
several hours at room temperature. This is true for all gains and
power on and off, which is useful if the signal source and
amplifier are powered separately. For longer time periods, the
input current should not exceed 6 mA.
For input voltages beyond the supplies, a protection resistor
should be placed in series with each input to limit the current to
6 mA. These can be the same resistors as those used in the RFI
filter. High values of resistance can impact the noise and AC
CMRR performance of the system. Low leakage diodes (such as
the BAV199) can be placed at the inputs to reduce the required
protection resistance.
AD620
R
REF
R
+SUPPLY
–SUPPLY
VOUT
+IN
–IN
00775-0-052
Figure 41. Diode Protection for Voltages Beyond Supply
RF INTERFERENCE
All instrumentation amplifiers rectify small out of band signals.
The disturbance may appear as a small dc voltage offset. High
frequency signals can be filtered with a low pass R-C network
placed at the input of the instrumentation amplifier. Figure 42
demonstrates such a configuration. The filter limits the input](https://image.slidesharecdn.com/582e5d95-6876-4ea7-984f-0283cfcb29a5-160120211803/85/Techtiles-FDR-54-320.jpg)
![AD620
Rev. H | Page 19 of 20
OUTLINE DIMENSIONS
COMPLIANT TO JEDEC STANDARDS MS-001
CONTROLLING DIMENSIONS ARE IN INCHES; MILLIMETER DIMENSIONS
(IN PARENTHESES) ARE ROUNDED-OFF INCH EQUIVALENTS FOR
REFERENCE ONLY AND ARE NOT APPROPRIATE FOR USE IN DESIGN.
CORNER LEADS MAY BE CONFIGURED AS WHOLE OR HALF LEADS.
070606-A
0.022 (0.56)
0.018 (0.46)
0.014 (0.36)
SEATING
PLANE
0.015
(0.38)
MIN
0.210 (5.33)
MAX
0.150 (3.81)
0.130 (3.30)
0.115 (2.92)
0.070 (1.78)
0.060 (1.52)
0.045 (1.14)
8
1
4
5 0.280 (7.11)
0.250 (6.35)
0.240 (6.10)
0.100 (2.54)
BSC
0.400 (10.16)
0.365 (9.27)
0.355 (9.02)
0.060 (1.52)
MAX
0.430 (10.92)
MAX
0.014 (0.36)
0.010 (0.25)
0.008 (0.20)
0.325 (8.26)
0.310 (7.87)
0.300 (7.62)
0.195 (4.95)
0.130 (3.30)
0.115 (2.92)
0.015 (0.38)
GAUGE
PLANE
0.005 (0.13)
MIN
Figure 50. 8-Lead Plastic Dual In-Line Package [PDIP]
Narrow Body (N-8).
Dimensions shown in inches and (millimeters)
CONTROLLING DIMENSIONS ARE IN INCHES; MILLIMETER DIMENSIONS
(IN PARENTHESES) ARE ROUNDED-OFF INCH EQUIVALENTS FOR
REFERENCE ONLY AND ARE NOT APPROPRIATE FOR USE IN DESIGN.
0.310 (7.87)
0.220 (5.59)
0.005 (0.13)
MIN
0.055 (1.40)
MAX
0.100 (2.54) BSC
15°
0°
0.320 (8.13)
0.290 (7.37)
0.015 (0.38)
0.008 (0.20)
SEATING
PLANE
0.200 (5.08)
MAX
0.405 (10.29) MAX
0.150 (3.81)
MIN
0.200 (5.08)
0.125 (3.18)
0.023 (0.58)
0.014 (0.36) 0.070 (1.78)
0.030 (0.76)
0.060 (1.52)
0.015 (0.38)
1 4
58
Figure 51. 8-Lead Ceramic Dual In-Line Package [CERDIP]
(Q-8)
Dimensions shown in inches and (millimeters)
CONTROLLING DIMENSIONS ARE IN MILLIMETERS; INCH DIMENSIONS
(IN PARENTHESES) ARE ROUNDED-OFF MILLIMETER EQUIVALENTS FOR
REFERENCE ONLY AND ARE NOT APPROPRIATE FOR USE IN DESIGN.
COMPLIANT TO JEDEC STANDARDS MS-012-AA
012407-A
0.25 (0.0098)
0.17 (0.0067)
1.27 (0.0500)
0.40 (0.0157)
0.50 (0.0196)
0.25 (0.0099)
45°
8°
0°
1.75 (0.0688)
1.35 (0.0532)
SEATING
PLANE
0.25 (0.0098)
0.10 (0.0040)
4
1
8 5
5.00 (0.1968)
4.80 (0.1890)
4.00 (0.1574)
3.80 (0.1497)
1.27 (0.0500)
BSC
6.20 (0.2441)
5.80 (0.2284)
0.51 (0.0201)
0.31 (0.0122)
COPLANARITY
0.10
Figure 52. 8-Lead Standard Small Outline Package [SOIC_N]
Narrow Body (R-8)
Dimensions shown in millimeters and (inches)](https://image.slidesharecdn.com/582e5d95-6876-4ea7-984f-0283cfcb29a5-160120211803/85/Techtiles-FDR-58-320.jpg)
![ADXL335
Rev. 0 | Page 14 of 16
OUTLINE DIMENSIONS
111808-A
1
0.65
BSC
BOTTOM VIEWTOP VIEW
16
58
9
12
13
4
EXPOSED
PAD
PIN 1
INDICATOR
2.55
2.40 SQ
2.25
0.55
0.50
0.45
SEATING
PLANE
1.50
1.45
1.40
0.05 MAX
0.02 NOM
0.15 REF
COPLANARITY
0.08
0.15 MAX
PIN 1
INDICATOR
4.15
4.00 SQ
3.85
0.35
0.30
0.25
FOR PROPER CONNECTION OF
THE EXPOSED PAD, REFER TO
THE PIN CONFIGURATION AND
FUNCTION DESCRIPTIONS
SECTION OF THIS DATA SHEET.
Figure 27. 16-Lead Lead Frame Chip Scale Package [LFCSP_LQ]
4 mm × 4 mm Body, 1.45 mm Thick Quad
(CP-16-14)
Dimensions shown in millimeters
ORDERING GUIDE
Model Measurement Range Specified Voltage Temperature Range Package Description Package Option
ADXL335BCPZ1
±3 g 3 V −40°C to +85°C 16-Lead LFCSP_LQ CP-16-14
ADXL335BCPZ–RL1
±3 g 3 V −40°C to +85°C 16-Lead LFCSP_LQ CP-16-14
ADXL335BCPZ–RL71
±3 g 3 V −40°C to +85°C 16-Lead LFCSP_LQ CP-16-14
EVAL-ADXL335Z1
Evaluation Board
1
Z = RoHS Compliant Part.](https://image.slidesharecdn.com/582e5d95-6876-4ea7-984f-0283cfcb29a5-160120211803/85/Techtiles-FDR-73-320.jpg)
Techtiles-FDR
- 1. The George WashingtonUniversity School of Engineering & Applied Sciences Department of Biomedical Engineering Techtiles A Physiological Measurement System in Clothing Final Design Review William Gottschalk | Aamir Husain | Leo Parsons Prepared for Dr. David Nagel 10 December 2014 ECE 4290W
- 2. Abstract (WG) The proposedsystem, “Techtiles: A Physiological Measurement System in Clothing,” is a wearable system that will allow for users to record their physiological readings, in an attempt to monitor their physical well-being. The system will wirelessly monitor the user’s heart rate, respiratory rate, steps taken, distance traveled, and energy expended. The heart rate will be determined through the use of an ECG, the respiratory rate using a stretch resistor, and the distance traveled by using a 3-axis accelerometer. These analog signals will then be sent to a micro-controller, which will quantize and process the data. Algorithms will be uploaded onto the micro-controller to perform various calculations to calibrate, and determine other pertinent user data. Using a bluetooth module, the processed data will then be sent via a wireless serial connection to the user’s smartphone. An android application was written to receive the data, and display it in a presentable manner; both quantitatively and graphically. The user will also be able to save data and information about their workouts, and store personal information within the application. of2 58
- 3. TABLE OF CONTENTS Abstract(WG) 2..................................................................................................................... Introduction (AH, WG: 50%) 6............................................................................................... Background & Market Justification 6............................................................................... System Level Requirements and Specifications (AH, WG, LP: 33%) 7................................ Overall System Design (AH, WG, LP: 30%) 8....................................................................... Theory of Operation 8...................................................................................................... Approach to Overall Design 10....................................................................................... Current Design 10..................................................................................................... Evolution of Current Design 10.................................................................................. Module Level Requirements and Specifications 13.............................................................. Sensor Integration Sub-System (AH) 13.......................................................................... Data Processing Sub-System (WG) 14........................................................................... Wireless Transmission and GUI Sub-System (LP) 16...................................................... Module Design 17................................................................................................................. Sensor Integration Sub-System (AH) 17.......................................................................... Fabric Technology and Overall Appearance 17........................................................ Detecting Heart Rate 18............................................................................................ Detecting Movement 19............................................................................................ Detecting Respiration 20........................................................................................... Data Processing Sub-System (WG) 21........................................................................... Considerations Taken in Micro-Controller Selection 21............................................. Micro-Controller Selection 21.................................................................................... ECG Data Analysis and Calibration 21...................................................................... Stretch Sensor Data Analysis 22............................................................................... Accelerometer Data Analysis and Calibration 22...................................................... Distance Traveled Calculation 22.............................................................................. Energy Expenditure Calculation 23........................................................................... Battery Selection 23................................................................................................... Wireless Modem Selection 23................................................................................... Wireless Transmission & User Interface Sub-System (LP) 24......................................... Mobile Device App 24............................................................................................... Wireless Connectivity 24........................................................................................... Data Transmission 25................................................................................................ Data Storage 25......................................................................................................... Data Display 25......................................................................................................... Module and System Testing 25............................................................................................. Overall System Testing 25............................................................................................... Sensor Integration Sub-System Testing (AH) 26............................................................. Conductive Fabric 26................................................................................................ Electrocardiogram 26................................................................................................ Accelerometer 26...................................................................................................... Stretch Sensor 26...................................................................................................... of3 58
- 4. Data Processing Sub-SystemTesting (WG) 27............................................................... Algorithm Accuracy 27.............................................................................................. Battery Life 27............................................................................................................ Wireless Serial Data Transmission 27........................................................................ Wireless Transmission & User Interface Sub-System Testing (LP) 28............................. Bluetooth Connectivity 28.......................................................................................... Data Transmission 28................................................................................................ Data Storage 29......................................................................................................... Data Display 29......................................................................................................... Android Application Layout 29.................................................................................. Economic Analysis (AH) 29................................................................................................... Implementation Plan 30......................................................................................................... Hardware (AH) 30............................................................................................................ Software (WG) 30............................................................................................................ Summary and Conclusions (AH) 32...................................................................................... Applicable Standards (AH, WG: 50%) 32............................................................................. Qualifications of Key Personnel 35........................................................................................ Aamir Husain Qualifications (AH) 35............................................................................... William Gottschalk Qualifications (WG) 35...................................................................... Leo Parsons Qualifications (LP) 35................................................................................. Intellectual Contributions 35.................................................................................................. Aamir Husain Intellectual Contributions (AH) 35............................................................. William Gottschalk Intellectual Contributions (WG) 36.................................................... Leo Parsons Intellectual Contributions (LP) 36............................................................... Teaming Arrangements 36.................................................................................................... Appendix A: Product Data Sheets 37................................................................................... Appendix B: Economic Analysis 38...................................................................................... Appendix C: Project Timeline & Milestones (AH) 45............................................................. Appendix D: Module Matrices 47.......................................................................................... Appendix D: System Diagrams 48........................................................................................ Appendix E: Mechanical Drawings (AH) 50.......................................................................... Appendix F: Program Flow Diagrams (WG: 75%, LP: 25%) 52............................................ Appendix G: Component Comparisons and Other Useful Tables 57................................... References 58....................................................................................................................... of4 58
- 5. LIST OF FIGURES LISTOF TABLES Figure 1: Sensor Sub-System Signal Flow Diagram 8............................................................... Figure 2: Data Processing Signal Flow Diagram 9.................................................................... Figure 3: Third Order Low Pass Filter (ECG) 19........................................................................ Figure 4: Two Lead ECG 19...................................................................................................... Figure 5: Stretch Sensor 20....................................................................................................... Figure 6: Third Order Low Pass Filter (Stretch Sensor) 20........................................................ Figure 7: Actual and Estimated Weekly Burn Rate 41.............................................................. Figure 8: Gantt Chart Part 1 45................................................................................................. Figure 9: Gantt Chart Part 2 45................................................................................................. Figure 10: Gantt Chart Part 3 46............................................................................................... Figure 11: Gantt Chart Part 4 46............................................................................................... Figure 12: Overall System Design 48........................................................................................ Figure 13: Arduino Pro Mini Schematic 49................................................................................ Figure 14: Housing 3-D Model 50............................................................................................. Figure 15: Housing Schematic (Bottom Piece) 50.................................................................... Figure 16: Housing Schematic (Top Piece) 51.......................................................................... Figure 17: Mobile Device Flow Diagram 52.............................................................................. Figure 18: Overall Micro-ControllerSoftware Flow Diagram 53................................................. Figure 19: ECG Software Flowchart 54..................................................................................... Figure 20: Accelerometer Software Flow Diagram 55............................................................... Figure 21: Respiration RateSoftware Flowchart 56................................................................... Table 1: System Level Requirements & Specifications 7.......................................................... Table 2: Sensor Integration Sub-System Requirements & Specifications 13........................... Table 3: Data Processing Sub-System Requirements & Specifications 15............................... Table 4: GUI Sub-System Requirements & Specifications 17................................................... Table 5: Applicable Standards 34............................................................................................. Table 6: Cost Analysis for Prototype Design 38........................................................................ Table 7: Estimated Labor Hours 38........................................................................................... Table 8: Large Scale Manufacturing Costs 39.......................................................................... Table 9: Actual and Estimated Weekly Burn Rate 40................................................................ Table 10: Bill of Materials 43..................................................................................................... Table 11: Software Parts List 44................................................................................................ Table 12: Module Matrix for Sensor Integration Sub-System 47............................................... Table 13: Module Matrix for Data Processing Sub-System 47.................................................. Table 14: Module Matrix for GUI Design Sub-System 47.......................................................... Table 15: Energy Expenditure Relations 57.............................................................................. Table 16: Battery Selection 57................................................................................................... Table 17: Wireless Modem Selection 57................................................................................... of5 58
- 6. Introduction (AH, WG:50%) Background & Market Justification Physiological monitoring has become increasingly popular with the availability of advanced technology. Biometric devices have a wide range of applications including, but not limited to, the military, sports programs, hospitals, and research laboratories. Soldiers, astronauts, law-enforcement officers, miners, deep-sea fisherman, and any other professions where there is a risk of bodily harm can benefit from an unobtrusive physiological measurement device. Employers who choose to equip their personnel with these monitors can keep a close watch on their employees vitals, as to reduce the potential loss of life. A subset of biometric devices is wearable biomedical technology. “Wearables”, which has become more of a buzzword in the past few years, are devices which are directly incorporated into what the user wears eg. clothing, headphones, sleeves, glasses, etc. With1 medical technology prices decreasing, companies have opted to equip their products with various biometric sensors. The Motorola Moto 360 wristwatch is just one of the devices currently on the market that advertise health monitoring capabilities. However like the Moto 3602 or the Microsoft Band, another wearable device, most other wearables on the market keep track of one or two things: heart rate and steps. Users who want more information must look elsewhere and purchase separate products. Techtiles, our proposed system, aims to consolidate sensors which are normally not found together on one singular device. The main purpose of this device is to track a user’s heart activity, breathing and movement, and process the data to compute heart rate, respiration rate, steps taken, distance travelled, and energy burned. The data will be obtained by using three sensors embedded in a moisture-wicking compression shirt and the information gained from it will be displayed on a mobile device running an Android operating system. Unlike many other devices on the market, Techtiles also utilizes conductive fiber as a key component of some of the sensor integration module of the device. According to a report conducted by TechNavio, the global patient monitoring system market will be worth an estimated $9.3 billion dollars in 2014.3 “Medical devices purchased by consumers used to self-monitor health conditions will account for more than 80% of wireless devices in 2016.”4 Monitoring devices, along with the boom in wearable technology is creating a large demand for innovative products which can do more than just measure heart rate. Devices similar to our product like the Moto 360 cost around $200. Other products currently not on the market such as Athos and Hexoskin range from about $200-$400 per unit. Our device will cost an estimated $285 based on the economic analysis done in this report. This day in age, people like to be able know as much as they can with the simplest tools available to them. Techtiles provides this need as it combines multiple physiological readings into one device which can be worn of6 58
- 7. continuously without gettingin the way of the user’s daily life. System Level Requirements and Specifications (AH, WG, LP: 33%) Table 1: System Level Requirements & Specifications Requirements Specifications Detect physiological measurands 3 biosensors: ECG, stretch resistor, accelerometer Display physiological data on mobile device User-friendly GUI with data and data analytics via graphs and numerical values Operate at no less than five hours in active mode (continuous recording) 1000 mAh Lithium Polymer Ion Battery Conserve power when not in use Low power state activated if device is not active for more than 5 minutes Lightweight and comfortable for the user Constructed with cotton/spandex/nylon compression fabric weighing no more than 2 pounds Store data locally Data stored as text file on mobile device Unobtrusive to user Hardware components (excluding the shirt) occupy no more than 6cm x 6cm x 3cm volume Mobile OS compatible Runs on Android 4.0 and higher Must pair with, and transmit data wirelessly to a personal device Class 1 Bluetooth 2.4GHz UHF radio waves of7 58
- 8. Overall System Design(AH, WG, LP: 30%) Theory of Operation The physiological measurement system in clothing, also known as Techtiles, aims to provide a user with real-time information about their biological responses. Specifically, this device is intended to detect heart rate, breathing and movement and to display this information via a user-friendly mobile device application. The data from these sensors are then used to determine the user’s beats per minute, respiration rate, steps taken, distance travelled and calories burned. The device can be broken down into three main sub- systems, each one heavily reliant on the other two to function properly as a whole. These sub-systems are described in greater detail in the following section. The first sub-system focuses on building the interface between the user and the device. This involves the integration of sensors into a shirt, creating a “smart fiber,” which are then connected to a small micro-controller which manipulates the incoming analog signals to readable digital outputs. Three different sensors are used to obtain data: an electrocardiogram (ECG), a three-axis accelerometer and a stretch resistor. Detailed descriptions of each sensor are described later on in the “Module Design” section of this report. A basic ECG consists of electrodes, a power source, and some kind of filter to adjust the incoming signal from the heart. The ECG recognizes and records all electrical activity created within the heart. During a single heartbeat, an electrical impulse is generated at the AV Figure 1: Sensor Sub-System Signal Flow Diagram Analog values are transmitted from the body to the three sensors. The sensors then send analog voltages to the micro-controller for processing. node, located at the upper right side of heart. The signal then travels in a downward diagonal direction towards the bottom of the left ventricle, passing through the AV node and bundle of His.5 The electrodes pick up a distinct, wave- like signal which is quite small, between 1 - 10 mV, which needs to be amplified considerably for it to be readable and digitally representable. This is6 accomplished through high pass and low pass filters and amplifiers to produce the familiar PQRST wave of the heart contraction. Specifically for this device, it was decided that just two electrodes will be used to pick up ECG waveforms rather than other higher lead ECGs. The signal is amplified with a differential amplifier and then passed through to the micro controller for further filtering. The amplifier itself is described in greater detail in “Sensor Integration Sub- System” in the “Module Design” section of this report. An accelerometer measures the vibration or acceleration of motion of an object. Inside the sensor, any exerted force moves a piezoelectric metal. of8 58
- 9. Depending on themagnitude of the force, the metal produces a proportional charge, which is also proportional to the magnitude of acceleration. The accelerometer is used to determine the number of steps taken and it is also used in tandem with the other sensors in determining energy expended. A stretch sensor is an effective way to monitor respiration in this kind of device. The rise and fall of the chest can be measured as a change in resistance as the sensor stretches and relaxes, moving its internal c o m p o n e n t s c l o s e r together or further apart. The sensor used in this device is made entirely of conductive fabric which can stretch in one direction. This ensures that user is more comfortable when using the product and that it is more durable. The fabric of the shirt must also be comfortable for the user. Therefore, it is mostly composed of a cotton/spandex/ nylon blend, a moisture-wicking compression fabric. This allows for the device to be worn tightly on the body without sacrificing comfort or efficiency. The data processing sub-system is tasked with receiving and processing analog data from the accelerometer, stretch sensor, and electrocardiogram. The analog signals are digitized, and then formatted into usable data so that further analysis and calculations can be conducted. The Arduino Pro Mini micro- controller is the centerpiece of the device, equipped with eight analog to digital channels which will allow it to quantize the analog data from each respective sensor.13 The micro- controller, sensors, and additional hardware will all be powered using a Lithium Polymer Ion Battery. Using the Arduino IDE, the micro-controller is programmed to format the data into a usable form, and to perform various calculations to obtain the user’s steps taken, distance traveled, heart rate, respiration rate, and energy expended. The processed data is then be transmitted wirelessly via bluetooth to the user’s mobile device. Figure 2: Data Processing Signal Flow Diagram Analog data from the sensors enters the micro controller and is converted to a digital signal. This signal is filtered, analyzed, then sent to a bluetooth device which transmits the data wirelessly. The final sub-system will be the graphic user interface, allowing the user direct access to the data generated by the device. The transmitted data is received wirelessly through an application designed for Android smartphones. One of the main motives of Techtiles is for a final design that is small and mobile. Our users should be able to use our device wherever and without restrictions. This lead to the decision to create our user interface into a mobile application rather than on a personal computer. Also a benefit to designing the GUI for mobile phones, is the Bluetooth capability that all modern smartphones are built with. Furthermore, it was decided that the application would be designed using the Android operating system due to it’s open source platform. The most of9 58
- 10. important goal ofthis sub-system is to develop an application as intuitive as possible for the user. When the user open the application for the first time, they should know how to navigate menus without confusion. Approach to Overall Design Current Design The current system design can be broken into three major components: the shirt containing sensors, the micro- controller, and the mobile application. The first major component contains a heart rate sensor, a respiration sensor, and an accelerometer. These sensors are used to determine values for heart rate, respiration rate, steps taken, distance travelled and energy expended. The heart rate sensor uses electrodes constructed from silver coated nylon, a highly conductive fabric. The respiration sensor is also made of the same material. The accelerometer, micro-controller, ECG hardware and the lithium polymer ion battery are all housed in a 3.49 in x 2 in x 0.35 in casing which is fitted into a pocket in the back side of the shirt. The shirt itself is a moisture-wicking fitness compression shirt which fits snugly on the body. This ensures a more accurate reading from the sensors. The second major component is the micro-controller. The Arduino Pro Mini was chosen based upon it’s small size, low price, and sufficient clock speed. It digitizes all of the analog data from the sensors and then filters and calibrates it. Finally, the micro controller processes the data, and analyzes it. Two modes of operation have been programmed into the micro-controller. In sleep mode, the micro controller waits for the user to begin a new session. Once the user begins a new session, the device enters active mode, in which it constantly transmits data wirelessly to a compatible bluetooth device. This is done through the use of a bluetooth mate to gain bluetooth capabilities and allow for a wireless serial connection. A mobile device wirelessly receives the processed data through a designed application. This data will be stored and displayed on the user-friendly application. The GUI is in the form of an Android App, which is able to display the data numerically and via graph. The data files is stored within the internal storage of the mobile device and be available to be viewed by the user through the app. Evolution of Current Design For the first stages of the device, a variety of sensors were taken into consideration to find as many biometric measurands as possible. Blood pressure sensors, galvanic skin response, and thermometers were considered at some point during the design process. However some of these sensors were shown to be unfeasible to implement in a small, durable form factor for the specified device, and so they were removed from the system design plan. The ECG was originally ordered from Sparkfun for prototyping. However, this board was too large for the final product and had extra features like an LED and headphone jack which were not needed in the final design. It was then decided that a simple two lead ECG would be build using the AD620 differential amplifier. of10 58
- 11. To measure breathing,a strain gauge was initially chosen as the sensor. However given that strain gauges are recommended more for measuring strain on solid objects like metal beams, a stretch sensor seemed to be a more appropriate sensor to use for the device. Conductive fabric was chosen for its durability and comfort for this sensor rather than other bulky hardware. The housing for the hardware components was first idealized as being a small case which would fit into the user’s pocket. Determining that this led to possible risk of damaging the connection between the shirt and the housing, it was decided that the housing be placed directly onto the shirt in an unobtrusive location — the lower back. Initially, the Arduino due was used to test the accelerometer. However, it was quickly ruled out as a result of it’s large size, and input voltage. In order to meet the requirements, a smaller micro controller was necessary, which operated within the range of the sensor outputs. It also needed to be able to be powered wirelessly, have a relatively low current consumption, and over seven analog to digital channels. Through process of elimination, the Arduino Fio and pro mini were the only two micro controllers researched that met the specified requirements. Ultimately, the Arduino pro mini was selected due to it’s smaller size, and price. Initially, the bluetooth bee was used to demonstrate bluetooth connectivity for the sub-system demo. To meet the specified requirements, the bluetooth bee was eliminated as a result of it’s cumbersome size, and large current consumption. As a result, the bluetooth mate was selected as the best wireless module for the system. The app is designed to enable the phone’s Bluetooth capability and receive the transmitted data directly to the app, where it will be stored and displayed. The app is designed using Android Studio and coded in Java. User data is also displayed in an organized and comprehensible manner. The most recent results as well as all previously recorded data will be stored and accessible. The app will require login credentials that the user will set during their first interaction with the app. This is how the app will recognize which data to pull from the device’s internal storage when the history is opened. The app will also be programmed to remember previous login and bluetooth pairings after its first launch, so the user will not have to repeat this process with each activation. The initial proposal for the graphic user interface was to be a personal computer program, which the user could run on a laptop or PC. After researching into this type of GUI verses a mobile application, it appeared a mobile app would do much better on the market due to the growth of the industry. In addition to this, all modern smartphones have built in technology, which offers us direct contact to the device with no third party needed. This would be imperative for the data transmission part of our system. After coming to this decision, it was important to pick the right operating system to run our application on. Our goal is to create an App that we can design, test, and eventually publish. Android offers a much better testing and p u b l i s h i n g p l a t f o r m f o r a p p development. This decision will avoid of11 58
- 12. obstacles that iOStypically encounters through testing and publication. of12 58
- 13. Module Level Requirementsand Specifications Sensor Integration Sub-System (AH) Table 2: Sensor Integration Sub-System Requirements & Specifications Module Requirements Specifications Overall Low voltage input Operating voltage of 3.3 V Low power consumption All devices together draw 6 mA Unobtrusive to user All sensors occupy 50 cm2 of shirt surface Fabric Lightweight Weighs 10oz per ft2 Provide adequate means of measuring sensor data while being comfortable to wear Tight fitting shirt made with a blend of moisture wicking cotton/spandex/nylon ECG Detect PQRST waves Silver coated nylon electrodes with a resistance of less than 3 Ω Obtain a useable signal so it can be processed by micro-controller 2 lead differential amplifier able to detect input voltages between 0.5 - 5 mV and have an overall gain between 800-1000 over a frequency of 0.5 - 100 Hz Low power consumption Current draw of no 250 µA Filter out noise Remove frequencies below 0.5 Hz and above 100 Hz Stretch Sensor Detect respiration Silver coated nylon stretchable fabric which functions as a resistor Obtain a useable signal so it can be processed by micro-controller Detects between 0.5 - 3 cm of deformation along lengthwise axis of resistor Low power consumption Current draw of 5 mA Filter out noise Remove frequencies below 0.1 Hz and above 100Hz Accelerometer Detect steps taken and magnitude of acceleration 3 axis accelerometer with range of detecting +/- 3g Low power consumption Current draw of 400 µA Filter out noise High pass filter at 100 Hz of13 58
- 14. Data Processing Sub-System(WG) Module Requirements Specifications Overall Micro-controller must have sufficent ADC channels to quantize all analog data Eight 10 bit ADC Channels Dimensions under 3” x 2” x 1” 2.5” x 2” x .7” Powered wirelessly for up to 5 hours 1000mAh Lithium Polymer Ion Battery Transmit data wirelessly to a personal device Class 1 Bluetooth, 2.4GHz UHF radio waves, 11520 baud rate Arduino Pro Mini Micro-controller Adequate ADC channels to receive input from all sensors 8 ADC channels Allow input voltages in the range of the sensors output voltages 3.35V-12V Dimensions within 1” x 2” .7” x 1.3” Must sample analog data at a sufficent rate to properly represent the analog data Sampling Rate ≥ 20 Hz Low Power consumption 3.3V operating voltage, 8 MHz clock speed Lithium Polymer Ion Battery Dimensions within 2” x 1.5” x 0.5” 2” x 1.32” x 0.23” Must power electrical components wirelessly for 5 hours 1000mAh Lithium Polymer Ion Battery Bluetooth Mate Gold Establish wireless serial connection to a personal device at up to 10m Class 1 Bluetooth Radio Modem, 2.4~2.524GHz UHF radio waves Operate within operating range of micro-controller 3.3V-6V Dimensions under 2” x 1” 1.75” x .65” Programming Determine the amount of steps taken by a user Accurate to within 5% of user steps Determine heart rate Accurate to within 5% of the user's beats per minute Determine the respiration rate in breaths per minute Accurate to within 5% of user breaths per minute Determine distance traveled Accurate to within 10% of actual traversed distance Module of14 58
- 15. Table 3: DataProcessing Sub-System Requirements & Specifications Determine energy expended Accurate to within 10% of calories burned per hour Calibrations Alert user when the device is incorrectly calibrated or equipped Error message displayed on user's device Requirements SpecificationsModule of15 58
- 16. Wireless Transmission andGUI Sub-System (LP) Module Requirements Specifications Overall Design a Mobile Smart Phone Application Android based using Android Studio with Java language Application size must be within Android restrictions Size must be less than 50MB Programmed Capabilities App must be able to enable phones Bluetooth capabilities Android Smartphones use Bluetooth Smart technology which has a range of roughly 50 Meters App must receive data being transmitted 0.27 Mbps Typical Data Throughput App must store data Using Android Internal Storage; 1GB of Storage Space Layout App Home Page Ask for User log in and password Log-in Credentials No restrictions on number of characters; No limit to number of tries; Must alert user if password is authorized or denied App Profile Page Displays instantaneous numerical value of the distance traveled (miles), calories burnt, and steps measured, for the current day App Respiratory Sensor Page Respiratory output over time App Accelerometer Page Number of steps value; distance traveled (miles); Graph: Peak Acceleration (y axis) vs Calories Burnt (x axis) App Heart Rate Page Graph: Beats per minute (y axis), Time in minutes; intervals of 5 (x axis) History of Results Page List of all received files of data organized by time recorded; data size of each file will also be displayed (kilobytes) User Capabilities User must be able to input custom settings Weight (lbs.); Height (Inches); Gender (Male/Female) Module of16 58
- 17. Table 4: GUISub-System Requirements & Specifications Module Design Sensor Integration Sub-System (AH) This module involves the interface between the user and the product itself. Three separate sensors are used to detect the user’s heart rate, breathing, and movement. The sensors themselves are embedded in a moisture wicking fabric designed specifically for comfort during heavy activity or just long periods of general use. The housing for the hardware components can be found in Appendix E. Fabric Technology and Overall Appearance The final product consists of a shirt with a designated integrated band just below the chest where the sensors will be located. The fabric itself is moisture wicking and antimicrobial so that it can withstand heavy activity and feel more comfortable to wear. A few different types of fabric were considered for the initial design. Normal fabrics typically fit more loosely on the body, but for these sensors to work properly and to reduce the amount of noise as much as possible, the fabric needed to be tight fitting yet comfortable. Compression fabric was the choice material to use as it meets all of these requirements. Compression clothing is typically made with synthetic fibers or a cotton/ spandex/nylon blend, which provides moisture wicking capability due to its non-absorbent properties. Perspiration on the body passes through the inside of clothing (rather than inside of it) to the surface, allowing it to evaporate. The shirt can be constructed out of thin (approximately 8-9 oz per square foot)7 or thick (approximately 13-14 oz per square foot) compression fabric, depending on whether the user would prefer clothing that would keep them warmer or cooler. The lighter option was Access to previously stored data Previously recorded data are organized by date & time and called upon when user goes into the history menu and selects preferred data User can manage and delete stored data Using the application's delete function, user will be able to remove individual files from the mobile device's internal storage User can view data in ranges User can view data in real time of record or can select an overview of 1 day, 1 week, 1 month, 1 year, or all records Requirements SpecificationsModule of17 58
- 18. used for thisproduct; heat retaining properties were deemed irrelevant for the time being and keeping the shirt lightweight was a top priority. Stainless steel fibers are woven into the fabric to keep all circuitry as unobtrusive as possible. For the shirt to retain its stretch capabilities, these fibers are stitched in a zig-zag pattern which functions analogously to a spring. As the fabric stretches, the steel thread straightens into a line and then returns back to a zig- zag pattern once the fabric is brought back to its normal position. For this system, the sleeveless, moisture wicking compression shirt made by Tesla Gears© was chosen for its affordability and quality of material. With a flat-taped seam design, it minimizes chaffing and irritation for the wearer. It is stretchable in all directions and is also anti-microbial. The fabric is made up of a 92% polyester / 8% spandex blend and is machine washable, making it durable enough for heavy use. More information about the technology and design of the shirt can be found on the Tesla Gears© website: teslagearsph.com. Detecting Heart Rate Heart rate can be measured with instruments such as a pulse oximeter, ultrasound, electrocardiogram, or the old fashioned way - with ones fingers. Because ultrasound requires little to no movement to get a good reading and the need for sticky gels, this method was not considered for this device. Pulse oximeters were also deemed unsuitable for this device since it would require placement near or on an extremity to get reliable readings. For this project, it was decided that the best way to detect heart rate, especially during movement, was with a two-lead echocardiogram (ECG). In an ECG, electrodes are placed on the body in such a way that they can pick up the heart’s electrical activity. Higher lead ECG designs, although slightly more accurate and provide more detailed information about the PQRST complex ,8 were deemed unnecessary for the final product because of its relatively higher complexity compared to just two leads. Multiple leads would require more wires which must be accounted for in the clothing, which results in reduced durability. The incoming signals from the electrodes are passed through a differential amplifier which amplifies only the difference between two input signals. This is helpful in eliminating some degree of noise that is equally present in both inputs such as power line interference at around 60 Hz. The AD620 differential amplifier was chosen for this device. It offers low power consumption, low noise and a large adjustable gain range. Most importantly, it requires a low supply voltage. More information on the details of this differential amplifier is given in its data sheet in Appendix A. The ECG signal is filtered with analog low pass filters generated using computer software made by Texas Instruments. The normal PQRST wave generated by the heart lies within a frequency range of 0.5 to 150 Hz. A third9 order low pass filter is used to remove any frequencies above the 150 Hz boundary. The op amp used for the filter is the LMC7101BIM5. Resistor and capacitor values are shown in Figure 3. of18 58
- 19. " Figure 3: ThirdOrder Low Pass Filter (ECG) Cutoff frequency is at 150 Hz. The circuit uses two single-supply op amps. The circuit in Figure 4 shows the setup of the ECG. Two inputs (electrodes) are required for the amplifier to operate. The electrodes themselves are stitched into the compression shirt in such a way so that they are positioned on opposite sides of the heart. The signal from the electrodes passes through the difference amplifier which then goes for further filtering. For user protection, the circuit is isolated by two 5 k# resistors placed before the inputs of the amplifier. This ensures the user will be able to safely use the device. " Figure 4: Two Lead ECG See text for details. The electrodes are constructed out of conductive fabric (Silver coated nylon yarn) which have shown to perform as well as standard metal ECG electrodes but are more durable and can handle being laundered. The Shieldex10 MedTex™ P-180 conductive fabric was used in this design. It is an affordable yet high quality fabric with a very low surface resistance (<5 #). It is made out of a 78% nylon / 22% elastomer blend and is stretchable in one direction. More information on this fabric is given in its data sheet in Appendix A. Detecting Movement This product is designed to observe the user’s activity by measuring the number of steps taken and distance travelled during a recording session. A three axis accelerometer was chosen because of its ability to measure acceleration in a three-dimensional environment. Sudden changes in the sensor’s orientation in the x, y and z directions determine in real time if the user has taken a step. Other components that are often coupled with accelerometers such as gyroscopes were determined unnecessary for this design since it would provide excess information and higher power usage. When walking or running, the average person experiences between one and three Gs of force. Therefore it was decided that an11 accelerometer which can detect forces of up to +/- 3 G was sufficient for this product rather than other models which can detect a wider or narrower range of forces. This device uses an ADXL335 triple axis accelerometer. It has an incredibly low power consumption at 320 µA and can be powered by a 3.3 V power supply. The board has three separate output pins for the x, y and z directions, as well as a pin for low power state activation when the device is not being used. More information on the ADXL335 can be found in its data sheet in of19 58
- 20. Appendix A. Setupof this sensor did not require any extra components as all required parts were built into the board. Detecting Respiration Breathing is measured with a simple stretch sensor located on the sides of the chest. Upon inspiration, a stretch in the clothing will increase the separation distance between any two conductive components in the sensor, thus decreasing its conductivity and increasing its total resistance.12 Exhalation restores these components to their original position and restores its baseline resistance. Breathing rate can be calculated by recording the frequency of the change in resistance. Like the ECG electrodes, this sensor is also constructed from layers of stretchy conductive thread which is stitched directly into the clothing. Conductive fiber was chosen as the ideal material for a few reasons. The first is that it is the most comfortable and unobtrusive to the user. Second, it can be almost seamlessly integrated into the compression fabric as they are both similar materials. Third, its properties can be easily modified by altering the length of the resistor or by modifying the number of layers. Other pre-made stretch resistors were either uncomfortable to wear or were unable to be as properly integrated into a wearable fabric form. Stretch resistors in general draw little current, and so there was not a major emphasis on finding one that had a smaller current draw than another, unless there was a considerable difference. " Figure 5: Stretch Sensor See text for details. To increase the sensitivity of the resistor and to give it a greater overall resistance, two stretch resistors were placed in series, one on each side of the chest. With a basic voltage divider, respiration can be observed by measuring the voltage drop across the stretch resistor. For the circuit in Figure 5, a 1 k# resistor was used to create the voltage divider. The sensor is powered by a 3.3 V power supply. The voltage drop across the stretch resistor is measured at node Vout and is sent to the micro controller for further processing. The signal from the stretch resistor is passed through a low pass filter similar to the one used in the ECG. The only difference is that the cutoff frequency is at 50 Hz since respiration occurs at a low rate. Resistor and capacitor values are given in Figure 6. " Figure 6: Third Order Low Pass Filter (Stretch Sensor) See text for details. of20 58
- 21. Data Processing Sub-System(WG) This sub-system is tasked with receiving and processing analog data from a 3-axis accelerometer, stretch sensor, and an electrocardiogram. The analog signals will be digitized, and formatted into usable data so that further analysis, and calculations can be conducted. The data will then be transmitted wirelessly to a bluetooth compatible device. Considerations Taken in Micro-Controller Selection S e v e r a l p a r a m e t e r s w e r e considered in determining the micro- controller to best meet the requirements. The micro-controller had to be capable of receiving input voltages within the range of the output voltages of the sensors. In order to properly process all of the analog data, seven ADC channels were necessary. Another consideration taken into account, was the size of the micro- controller. The clock speed was c o n s i d e r e d i n l i m i t i n g p o w e r consumption, and providing sufficient processing power. Micro-Controller Selection The Arduino Due, and Uno micro- controllers were eliminated from consideration due to their large size, undesirable input voltage, unnecessary computing power, and high cost. The Pro Mini and Fio were relatively similar, both operating at 3.3V and a clock speed of 8MHz. The Fio had three more ADC channels than the Pro Mini, but only seven were needed, a consideration which both micro-controllers met. Ultimately, the pro mini’s cost and size made it the most ideal micro-controller for the purposes of this project. The Pro Mini is 39.87% the cost of the Arduino Fio, and occupies 31.82% of the volume. Given that the operating conditions were very comparable between the two micro- controllers, the Arduino Pro Mini was the superior choice. ECG Data Analysis and Calibration An algorithm was written to determine a user’s heart rate based upon their filtered ECG waveform. The program works through the utilization of an internal clock, and the incrementing of a counter every time the algorithm encounters an R-wave. The R-wave was utilized because it is the most easily differentiated from the rest of the PQRST waveform, due to it’s large amplitude. The occurrence of an R-wave is interpreted to be a heartbeat. The filtered ECG signal is first digitized through the use of an analog to digital converter. The algorithm then checks to see if calibration has been completed. If uncalibrated, the amplitude of an R-wave is taken by using the max function, and then set to be equal to a floating variable. A threshold is then established a standardized value below the maximum R- w a v e e n c o u n t e r e d . O n c e t h e calibration condition has been met, the algorithm compares current value to the threshold value. If the current value is equal to or greater than the threshold, a temporary variable is set to a value of one. In the other case, if the current value is less than the threshold, and second temporary variable is set equal to one, a counter is incremented and the first temporary variable is set back to zero. Every six seconds, a variable of21 58
- 22. storing the calculatedvalue of BPM is set equal to the count*10. Count is then set back to zero, along with the internal clock. The value of BPM is constantly printed wirelessly via a bluetooth serial connection in active mode. The Pan Tompkins algorithm may be utilized, if the accuracy and precision of the analyzed ECG data is undesirable due to the presence excessive noise. Stretch Sensor Data Analysis An algorithm was written to extrapolate the user’s respiration rate based upon variations in voltage across a stretch resistor. The program works by using an internal clock, and incrementing a counter every time the user inhales, and another for every time the user e x h a l e s . U p o n i n h a l a t i o n , t h e compression fabric is stretched, and the resistance increases. This in effect, increases the voltage drop across the stretch resistor. The output of the stretch sensor is filtered through a low pass filter to omit higher frequencies. The first derivative of the filtered data is then taken. Two new variables are declared, one to hold the previous value of the stretch sensor derivative, and one to hold the current value. The previous and current values are compared, and if the previous value is positive and the current value is negative, the inhalation counter is incremented. The respiration rate is calculated as the amount of inhalations, over a minute. Accelerometer Data Analysis and Calibration An algorithm was written to calibrate the accelerometer, determine the magnitude of an acceleration vector, the amount of steps taken by the user, distance traveled, and energy expended. Initially the algorithm determines the overall magnitude of the acceleration vectors. It then checks to see if the calibration condition has been met. If uncalibrated, based upon the max amplitude of the magnitude vector, a threshold is set a standardized integer below the max value. When the user moves, one step is registered as two peaks, since the overall magnitude vector is being utilized. As a result of this, two other variables must be declared; one to count the encountered peaks, and one to check if the current value is over the threshold. The step counter is only incremented when two peaks are counted, and the current value is under the threshold. The two variables are then reinitialized to zero after each cycle. Distance Traveled Calculation Ideally, if the sensors yielded p e r f e c t l y a c c u r a t e a n d p r e c i s e measurements the second derivative of the calibrated accelerometer data would yield the position of an object. Unfortunately, due to the constant gravity experienced by the accelerometer, the vector is the sum of the acceleration data and the gravitational acceleration it experiences. If one tries to account for this fact, and subtract the 1G acceleration due to gravity from the accelerometer readings then the data will be too noisy to be useful. Therefore, other parameters are utilized to calculate the position of the user. Distance traveled by the user will be calculated based upon the accelerometer data, the number of user steps taken, and the user’s input height. Based upon the magnitude of the of22 58
- 23. accelerometer data, andthe rate of steps taken by the user, the user will be assumed to be resting, walking, jogging, or running. For each cadence, a different step length will be calculated based upon the input height of the user and the accelerometer data. Using these calculations, and the number of steps taken, a good approximation of the distance traversed by a user can be achieved. The calculated traversed distance will then be cross referenced with the second derivative of the accelerometer data, in order to account for inaccuracy of the sensors. A Kalman filter was also considered, since it is considered to be the “theoretically ideal filter for combining noisy sensors to get clean, accurate estimates.” It also accounts for the known physical properties of the system. Unfortunately, the algorithm is very labor intensive on the processor, which does not have the proper clock speed to implement the filter and apply it to all of the necessary data. This is mainly due to it’s use of large matrices, and mathematical complexity. Energy Expenditure Calculation Energy expended by the user will be determined by user input data, including their height and weight, which will be calculated to yield a good approximation of their BMI. Based upon the acceleration data, the number and frequency of user steps taken, the metabolic equivalent of the user’s current activity can be calculated at set intervals. Depending on the current m e t a b o l i c a c t i v i t y, t h e e n e r g y expenditure can be calculated in Calories per second as a constant, multiplied by the user’s weight in pounds, and the metabolic equivalent value. Energy Expenditure (Calories/Second)=(. 000643)*(User Weight (lbs))*(MET) A13 table of energy values are given in Appendix G (Table 15). Battery Selection S e v e r a l p a r a m e t e r s w e r e considered in selecting the ideal battery to meet the requirements. The battery was required to be under 1.5cm3, and power all of the electronic components for at least five hours in active mode. It had to also output a voltage within the operating voltage range of the micro- controller. The upper limit of the device current consumption was determined to be 85mA. Based on the parameters taken into consideration, the coin cell and nickel hydride batteries were eliminated. While the coin cell boasts the smallest volume, and lowest price, it has the least amount of capacity and would only power the device for roughly three hours in active mode. The nickel hydride battery has a comparable voltage to the LiPo. It also has a higher capacity for a lower price, however, it outputs a nominal cell voltage of 1.2V which is far too little to power the device. Ultimately it became clear that the LiPo battery was the best choice for the device. A table of compared batteries is given in Appendix G (Table 16). Wireless Modem Selection A modem is necessary to pair with, and form a wireless serial connection between the micro-controller and the user’s smartphone. The serial connection of23 58
- 24. allows for theprocessed data to be transmitted wirelessly, so that the data can be formatted and displayed in the GUI. Several parameters were considered in modem selection in order to meet the requirements. A table of wireless modems is given in Appendix G (Table 17). B a s e d o n t h e p a r a m e t e r s considered, the XBee PCB Antenna - Series 2 was eliminated. It had a much higher current consumption than both of the bluetooth mates by 160%. An additional dongle would also be needed to attach the XBee to the Arduino Pro Mini, therefore encompassing a larger space than the bluetooth mates. In determining between the two bluetooth m a t e s , t h e y h a v e v e r y s i m i l a r specifications. The two main contrasts were the price, and transmission range. The requirement to meet was that, the device should transmit wirelessly to ones phone up to 5m, which both modems met. Therefore the distinguishing parameter was the price of the modems. The bluetooth mate silver is ten dollars cheaper, and as a result, is the selected modem. Wireless Transmission & User Interface Sub-System (LP) The objective of this sub-system is to wirelessly receive the processed data on a mobile device. This data is then stored and displayed in a user-friendly graphic user interface. The GUI will be in the form of an Android App, which will be able to display the data numerically and via graph. The app should store the data and display easy to navigate results. Mobile Device App The graphic user interface that will display the recorded data will be a mobile Android app. The app will be designed using the Android Studio and coded in Java. Android operating system was chosen over the likes of other systems, such as iOS, due to it’s open source platform. This app displays numerical data as well as graphs displaying the recorded results. Graphs show and compare the different readings from each of the signals. The data will be displayed in a user-friendly manner, so the user can read and analyze their own results. The app will also be able to save a user’s individual results using the mobile device’s internal storage, so the data can be called upon in a later time. The execution process of the app is displayed in Figure 17. Wireless Connectivity The connection from the remote unit is done via Bluetooth technology. This creates a direct connection from the device straight to the mobile device. With the current generation of smartphone mobile devices all containing built in Bluetooth technology, this is the most user-friendly and direct way to connect the two devices. The app will be designed to enable the smartphone’s Bluetooth capability and connect to the remote device. Using the “android.bluetooth” API in Android Studio, this function is designed to instantaneously run when the app is opened. The app will display a list of the detected bluetooth devices, and the user selects the Techtiles Bluetooth device to connect. Once this connection is made, the application will return to the main menu and is ready to of24 58
- 25. receive the datafrom the device. An Android phone uses low energy Bluetooth technology which allows a range of roughly 50 meters. Data Transmission Doing so via the Bluetooth connection, the data recorded by the sensors and processed through the micro-controller is transmitted to the mobile device. The app is able to receive this data using a BluetoothSocket. This allows the android to open up to receiving and transmitting data with the connected device. By using an InputStream the app will solely receive the data being transmitted from the device. The data is then received and ready to be interpreted within the mobile app so the application may store and display the data to the user. The data will be received at 0.27 Mbps, which is the standard for Android smartphones. Data Storage Once the data is received, the application will store the data using the mobile device’s internal storage. Using the FileOutputStream function the app will take the data thread created and save that thread under a filename. Each thread will be named the date it was recorded, so it can be placed into the user’s history and be viewed at any later time. The user will also have the ability to delete any individual files if he or she wish from the app. This function is executed through a delete function within the app that will allow files to be removed from the mobile device’s internal storage. The internal storage of android will allow the application up to 1 GB of data. That data will always be accessible to the user as long the application remains on their mobile device. Data Display The user will have the option to view the received data in multiple ways. The app will consist of different pages for each sensor. The respiratory output will display a graph that shows the recording of respiratory readings over duration of the time used. The accelerometer page will display an instantaneous value of the number of steps as well as the mileage of distance traveled. Also, a graph will display the Peak Acceleration versus Calories Burnt. The Heart Rate page will consist of a graph analyzing Beats per minute versus Time. Each page will be it’s own class and call from the data stream to be displayed. Module and System Testing Overall System Testing After testing of each sub-system is complete, testing for the overall system will consist of making sure all sub- systems work properly with each other. The shirt will be worn by a test subject and begin to take measurements. Heart rate, respiration rate, steps counted, distance travelled and energy burned will all be tracked with other devices or by observation for reference. The results displayed on the app for these criteria should fall within 5% or 10% of the values calculated for reference, depending on the parameter. of25 58
- 26. Sensor Integration Sub-System Testing(AH) Each sensor will undergo multiple tests to ensure that 1) the proper product was chosen for the device and 2) the sensor functioned as intended. All circuit components will first be built using a simulation program to make sure the designed circuit can be realized. Once properly simulated, the circuits are built on a breadboard for component testing and then attached to a permanent board later on. Conductive Fabric The Silver coated Nylon was first tested to see if it could indeed conduct electricity properly. This was done by simply connecting it as a resistor in a basic circuit with a 3.3 V power supply and seeing if there is current across the fabric. Testing showed that the fabric was indeed conductive as the circuit was complete and functional. The Silver coated Nylon fabric was also tested as an electrode for the ECG. Two swatches of fabric were cut and placed on a test subject and checked to see if a proper ECG waveform can be obtained. The ideal size for the electrode came to be approximately 2 in x 3 in. The stainless steel thread was tested for conductance by using it as a switch in a simple circuit. It’s resistance was also measured to make sure it was almost negligible (between 0 and 2 ohms) at longer lengths. Electrocardiogram The two-lead ECG will be tested as a whole as well as by its individual components. Resistor values were be checked to make sure they are the same as the design. The AD620 differential amplifier was also tested for proper gain and output. This was determined by first passing simple sine waves (10 Hz, 20 mVrms & 10 mVrms) as inputs and observing the resulting output, which should show a gain of approximately 800-1000. This test was then followed by applying a simulated heartbeat to the sensor and observing the output, which showed the same gain as previously mentioned. Finally, the ECG will then be hooked up to a test subject to see if a proper heart waveform can be acquired. Accelerometer The accelerometer was tested by supplying it with 3.3V and connecting its X, Y, Z pins to analog pins on a micro- controller. A simple program was written to display the raw voltages on a computer s c r e e n . F u n c t i o n a l i t y o f t h e accelerometer was then confirmed by orienting the accelerometer in various positions and seeing if there is a change in voltages in the the X, Y and Z directions. Next, a pedometer program was written and tested for accuracy. Results showed that the pedometer was able to keep track of every simulated step (a small shake of the board) taken. Further tests will involve testing the algorithms developed for calculating the energy expended and the distance traveled. Stretch Sensor T h e s t r e t c h r e s i s t o r w a s constructed out of the Silver coated Nylon fabric and tested for proper resistance values no less than 50 ohms when relaxed and no less than 90 ohms when stretched. Upon testing the fabric, of26 58
- 27. resistance values fellin this range when being stretched. The resistors were then tested individually and as a complete circuit, first on the breadboard and then on the compression shirt. Voltage readings were observed on the computer as the resistor was stretched to confirm proper function while breathing. Further testing will involve connecting the sensor to its respective low pass filter and making sure that high frequencies are removed from the system. Data Processing Sub-System Testing (WG) Algorithm Accuracy There are several tests that must be done to determine the degree of accuracy to which the algorithm computes various user data. The calculated data will be compared to experimental data and a degree of error will be established. For each output user data parameter, twenty ten minute trials will be conducted experimentally, and compared with twenty ten minute user sessions respectively. The user heart rate output by the algorithm will be tested through the use of a simulated ECG waveform. The calculated heart rate is expected to be within 5% of the actual BPM output by the simulated ECG. The user respiration rate output by the algorithm will be tested experimentally, by having an individual wear the device. The amount of breaths taken by the user will be recorded and compared with the computed value. The value the algorithm outputs is expected to be within 5% of the experimental value. The user steps taken, distance traversed, and energy expended will be tested experimentally. To test the user steps taken, an individual will wear the device, and the number of steps taken will be recorded, and compared to the computed value. The number of computed user steps taken is expected to be within 5% of the experimental value. In order to determine the distance traversed and energy expended experimentally, an individual will wear the device and run on a treadmill at several different cadences. The values calculated by the algorithm will then be compared to the experimental values. The algorithm is expected to output values of distance traveled, and energy e x p e n d e d w i t h i n 1 0 % o f t h e experimentally determined values. Battery Life The battery life of the device will be tested by leaving the device powered in active mode. The period of time until the LiPo battery dies during continuous use will be determined experimentally, and compared against the specifications and theoretically determined values. Also, the power consumption and current draw of the micro-controller will be tested in active mode experimentally, in order to improve the accuracy of the theoretical calculation of the battery life. Wireless Serial Data Transmission Tests were performed to verify that the processed data from the micro- controller can be transmitted wirelessly via Bluetooth. This was performed by printing the data to the serial monitor, while simultaneously outputting the data to a PC wirelessly using PuTTY, and of27 58
- 28. comparing these values.This test will be done again, but at several intervals of distances away from the PC, with the use of a measuring tape as a reference. This is done to meet the requirement of wireless transmission up to at least five meters. Wireless Transmission & User Interface Sub-System Testing (LP) Testing of an application comes with troubleshooting individual classes throughout the implementation of the code. Following the design of this sub- system, several tests are necessary in chronological order of the design. Starting with the initial Bluetooth connection, tests for each module have to be done throughout the design. The layout of each page and final design of the application are imperative as well and also go through multiple tests. Each of the following tests need to be done using the Android Studio and an Android smartphone. The final phase of testing will be done by 15 selected participants to download the app on their personal Android phones. These users will navigate through the app, using the capabilities and features throughout the design, while recording any bugs or feedback. The feedback will then be analyzed to repair all bugs and the participants will be surveyed to see what changes would make the app as intuitive as possible. Bluetooth Connectivity Bluetooth connectivity is tested by using the app to enable and connect the Android with another device. After compiling the source code, use Android Studio to upload the code to an Android smartphone. Following the structure of the app design, when launched, the app should enable and begin a search for Bluetooth devices. A list of all detected devices should display and one should be chosen. Following connection, the app should return to the main page. The Bluetooth logo in the top right of the Android phone will appear if the devices are paired successfully. To try with another connection, the user can go into settings and choose the Bluetooth option. Data Transmission Once the Bluetooth module of the app is working successfully, the data transmission can be tested. While paired t o t h e T e c h t i l e s d e v i c e , t h e BluetoothSocket should be opened and data should be being received. For this test, assure the accelerometer is functioning and the device is processing data. Do ensure this, open have the device plugged into a computer and open the Arduino Serial Monitor. If the accelerometer readings are appearing on the serial monitor, the data is ready to be received. For the initial part of this code the writemessage function will process and display any data received in string form. Before creating the store function, this test will simply display a log of the data being received. This data string will not appear as the proper form of data, however demonstrates a successful transmission of data. Compare the data from the serial monitor on the computer to the log of the app to see the similarity in numbers among the x, y, and z axis to assure the proper data is being received. of28 58
- 29. Data Storage The stepfollowing the successful implementation of both the bluetooth connection and data transmission is the storage. After implementing the storage m o d u l e , a n d c r e a t i n g t h e FileOutputStream, the data will now go directly into file form within the phone’s internal storage. To test the if the storage as accessible or not, go to the profile page and select history. The history page is designed to list every file of data that is recorded and received. When a file is selected, it should open the data that appears on the serial monitor connected to the Techtiles device. Furthermore for this test, disable bluetooth and try viewing the data within the app. This assures the data has accessed the internal storage. Data Display This is the final test of the data being received and processed correctly. When going through the My Profile page of the app, pressing Most Recent will offer the option of choosing which results to display. When choosing Respiratory, the graph of the respiratory output over time should be displayed. The image should replicate the image displayed on the serial monitor directly from the Techtiles device. For the Heart Rate Page, the data should be displayed in an ECG of beats per minute vs time. The time axis should be in minutes and intervals of 5. The Accelerometer page will display the figures for number of steps and distance traveled for that session. The graph should display peak acceleration vs. calories burnt. The layout of these 3 pages is imperative in the display, and the data must be accurate to the reading being directly output from the device. The numerical values from the serial monitor should be compared with the app’s display to ensure consistency over the transmission. Android Application Layout The final test of the sub-system is the layout and proper use of each function throughout the app design. Each page and button should be tested to verify the output is as expected and described in the table of functions. Each page should be tested for verification as well as design layout. While creating the view’s for each page in Android Studio, testing the app on an Android phone is how to test whether the layout of each button and page is accurate. To assure the app’s user-friendliness, 15 people will be asked to download and explore through the app. A survey will then be conducted to acquire the feedback and remarks regarding any bugs in the app, as well as recommendations. Economic Analysis (AH) Costs for each part needed for the prototype are listed in Table 6 of Appendix B. An extra $5.00 was charged for 3-D printing the housing and $10.00 was charged for stitching the sensors into the shirt. Additionally, a pass through fee of 5% of the total parts list was added to the final cost of the prototype. The resulting total value of the prototype came out to be $126.92. Labor positions were split into six jobs: project manager, design engineer, of29 58
- 30. hardware engineer, softwareengineer, test engineer and technical writer. The hours worked by each position was determined by the how long each process took in the project Gantt chart in Appendix C. Salaries and hours worked are shown in Table 7 in Appendix B. Along with the base salary value, a contract cost multiplier of 2.8 was factored into the salary, resulting in a total employee payment of $58,408. Large scale manufacturing costs are shown in Table 8 in Appendix B. The cost for producing 1000 units came out to be $82,370. To find the final price of a single unit, additional fees like manufacturing costs, software testing, a labor multiplier of 2, packaging, an overhead multiplier of 1.4, and a profit fee multiplier of 1.2 resulted in a total of $285.58 for a single unit. A multiplier of 1.2 was added to this cost to determine the wholesale price of $342.70. Finally, retail price was determined by adding a multiplier of 1.5 to the wholesale price, resulting in a final cost of $514.04 for one fully finished product. Detailed information on weekly expenditures for this system are given in Table 9 in Appendix B. A graph of the data can be seen in Figure 7 in Appendix B. The data of this economic analysis begins with ECE 3915 all the way to the first two months of ECE 4925. All costs and purchases made before the start of ECE 4920W are given as a lump sum in week 0. Actual values are shown in green and estimated expenses are shown in red. Implementation Plan Hardware (AH) There were many hardware implementations which were determined by factors other than the requirements of the device. A sleeveless shirt was chosen over one with sleeves simply because it was more cost effective and weighed less. Silver coated nylon was chosen over other conductive fabrics for its easy obtainability as well as its affordable cost. Resistor and capacitor values for the filters were determined using a computer program, and therefore will not be able to be perfectly repeatable in real life since certain resistor values do not exist. However to get as close to the simulated value as possible. resistors can be added in series or parallel. The housing was planned to be made out of plastic rather than metal or some other material. Using plastic keeps the device light, and it offers some circuit protection for the user when using the device. The Arduino Pro mini was chosen partly in fact because it was 39.87% of the cost of the Arduino Fio. The pro mini also occupies 31.82% of the volume, making implementing it into a smaller housing more feasible. Software (WG) In order to determine the heart rate, an algorithm was written to detect the occurrence of R-waves, and increment a counter accordingly. Then, over a set interval of time, using an internal clock, the heart rate could be determined by knowing the amount of R- waves that had been encountered, and the amount of time that had passed. The algorithm was implemented to count the R-waves because it is the most easily of30 58
- 31. differentiated from therest of the PQRST waveform due to its large amplitude. The occurrence of an R-wave can therefore be interpreted as a heartbeat. Another implementation decision was made in the decision to use a threshold to detect R-waves. In this manner, the algorithm compares the current value to the threshold value, will an R-wave defined as a reading above the threshold. Due to this fact, the coded also needed to be implemented so that the counter would not increment more than once for a single R-wave. In implementing the algorithm to determine a user’s respiration rate from the filtered stretch sensor data, a low pass filter was implemented to omit undesirable high frequencies. The first derivative of the filtered data is then taken, so that the instantaneous slope of the data can be determined. Two values were then declared, one to store the previous value of the slope, and one to store the instantaneous value. If the previous value is positive, and the current value is negative, this corresponds to the users inhaling. The opposite is true for exhalation. A counter is then incremented, for each time an inhalation is encountered, and then through the use of an internal clock, the respiration rate can be determined over a set interval of time. One problem in implementing the accelerometer algorithm is that one step was displayed as two peaks, as a result of the overall magnitude vector being utilized. In order to account for this, two other variables were declared. One of which, to count the number of encountered peaks, and another to determine if the current value is over the threshold. Using these two variables, a set of conditions are established that allow the step counter to be incremented only once two peaks are encountered, and the current value of the magnitude vector is under the threshold. In theory, if the sensors yielded perfectly accurate measurements, the first derivative of the calibrated accelerometer data would yield velocity, and the second derivative would yield position. This is not the case in reality, due to imperfect sensor readings, and the constant gravitational force experienced by the accelerometer. If one tries to account for this fact, and subtract the 1G acceleration due to gravity from the accelerometer readings then the data will be too noisy to be useful. As a result o this fact, other parameters are used to calculate the position of a user. Based upon the magnitude of the accelerometer data, and the rate of steps taken by the user, the user will be assumed to be resting, walking, jogging, or running. For each cadence, a different step length will be calculated based upon the input height of the user and the accelerometer data. Using these calculations, and the number of steps taken, a good approximation of the distance traversed by a user can be achieved. The calculated traversed distance will also be cross- referenced with the second derivative of the accelerometer data, in an attempt to improve accuracy. A Kalman filter was considered but ruled out due to its processing requirements. Energy expended by the user will be determined by user input data, including their height and weight, which will be calculated to yield a good approximation of their BMI. Based upon of31 58
- 32. the acceleration data,the number and frequency of user steps taken, the metabolic equivalent of the user’s current activity can be calculated at set intervals. Depending on the current m e t a b o l i c a c t i v i t y, t h e e n e r g y expenditure can be calculated in Calories per second as a constant, multiplied by the user’s weight in pounds, and the metabolic equivalent value. Summary and Conclusions (AH) The final design for the device did not deviate far from what was originally posed in ECE 3915. Beginning with textile-based sweat sensors, the project was simplified to include other sensors which determined heart rate, respiration rate and movement, as the former proposal would require much more research than actual design. More features like distance travelled and energy expended were added to the device to incorporate a more holistic view of the user’s physiological measurements. The team has been working well as a group and has been overall quite successful in implementing the design. We are currently working on making more accurate programs as well as analog filters for the sensors. Making the hardware components smaller is a constant goal that should be revisited frequently. Design is still being done on the app to make it as user-friendly and straightforward as possible, however this is probably the most difficult aspect of t h e p r o j e c t . I t i s r e l a t i v e l y straightforward to test sensor data and signal processing on a computer, but sending it through bluetooth to a mobile d e v i c e r e q u i r e s m o r e c o m p l e x programming. Applicable Standards (AH, WG: 50%) Given that the user will be directly in contact with this device, there are certain standards that must be met if this product were to be commercialized. Based off of the standards provided by the ANSI Search Engine for Standards (NSSN) and International Standards Organizations (ISO), the following is a list of standards which should be considered when producing this device on a larger scale. Document Number Title IEC 60601-2-47 Ed. 2.0 b: 2012 Medical electrical equipment - Part 2-47: Particular requirements for the basic safety and essential performance of ambulatory electrocardiographic systems Document Number of32 58
- 33. ISO/IEEE 11073-10406:2012 Health informatics -Personal health device communication - Part 10406: Device specialization - Basic electrocardiograph (ECG) (1- to 3-lead ECG) ASTM E2457-07(2013) Standard Terminology for Healthcare Informatics ISO 29.035.60 Varnished fabrics ISO 29.035.01 Insulating materials in general ISO 19.080 Electrical and electronic testing ISO 01.110 Technical product documentation Including rules for preparation of user guides, manuals, product specifications, etc. ISO 35.240.10 Computer-aided design (CAD) IEC 62209-2 Ed. 1.0 b: 2010 "Human exposure to radio frequency fields from hand-held and body- mounted wireless communication devices - Human models, instrumentation, and procedures - Part 2: Procedure to determine the specific absorption rate (SAR) for wireless communication devices used in close proximity to the human body (frequency range of 30 MHz to 6 GHz)" BNEPSpecification1 Bluetooth Network Encapsulation Protocol SAE AIR 5561-2013 (SAE AIR5561-2013) Lithium Battery Powered Portable Electronic Devices IEEE 1725-2011 IEEE Standard for Rechargeable Batteries for Cellular Telephones IEC 62281 Ed. 2.0 b:2012 Safety of primary and secondary lithium cells and batteries during transport TitleDocument Number of33 58
- 34. Table 5: ApplicableStandards IEC 60086-1 Ed. 11.0 b: 2011 Primary batteries - Part 1: General IEEE 1667-2009 Standard Protocol for Authentication in Host Attachments of Transient Storage Devices ISO/TS 17575-2:2010 Electronic fee collection - Application interface definition for autonomous systems ISO 6093:1985 Information processing - Representation of numerical values in character strings for information interchange ISO/IEC 14957:2010 Information technology - Representation of data element values - Notation of the format TitleDocument Number of34 58
- 35. Qualifications of KeyPersonnel All members of the group are pursuing a degree in engineering from The George Washington University (Husain: Biomedical Engineering, Gottschalk: Biomedical Engineering, Parsons: Electrical Engineering). Each member has taken courses in computer programming, university physics, engineering electronics, data structures, algorithms, computer logic and circuit theory. To accompany these classes, all members are able to code, design structures using CAD programs and build electronic devices. Aamir Husain Qualifications (AH) Aamir has a strong background in hands on circuit circuit design and coding in C/C++. He also has extensive knowledge of CAD programs, specifically SolidWorks, from his internship at a spinal prosthetics company. Aamir has taken classes in Circuit Theory, Engineering Electronics and Digital Signal Processing, and he is planning on taking Mechatronics Design in the future. With these classes and previous knowledge learned from outside of school, including graphic design, Aamir has the necessary skills to properly design and implement his sub-system. William Gottschalk Qualifications (WG) W i l l i a m i s a B i o m e d i c a l Engineering major that has a strong background in the Natural Sciences, computer programming. William has taken Intro to C Programming, and Data Structures which allowed him to become proficient in using the Arduino IDE. He has also taken Circuit Theory, Circuits Signals and Systems, and Digital Signal Processing. These classes have given him the necessary skills to be successful in implementing his sub-system. Leo Parsons Qualifications (LP) Leo is an Electrical Engineering student with experience in and out of the classroom in computer engineering and software design. Leo has completed courses in Intro to C Programming, Data Structures, Data Communications, and Microprocessors: Software/Hardware. Outside of his studies, Leo has e x p e r i e n c e i n t e r n i n g a t a communications test design company, where he gained extensive experience in working with C/C++ as well as graphic user interface design. Through experiences in the field, and his current education in electrical and computer engineering, Leo has acquired the necessary skills to implement and design a successful sub-system. Intellectual Contributions Aamir Husain Intellectual Contributions (AH) Aamir is in charge of designing and integrating the ECG, respiration sensor and accelerometer into the compression shirt. Each sensor was chosen to minimize current draw and have a supply voltage of no more than 3.3V. He is responsible for purchasing the sensor and other hardware components as well except for the bluetooth module and micro-controller. of35 58
- 36. William Gottschalk Intellectual Contributions(WG) William is tasked with receiving and processing analog data from a 3-axis accelerometer, stretch sensor, and an electrocardiogram respectively. The data from each sensor must be quantized and processed. Using the Arduino IDE, algorithms were written to calibrate the device, and alert the user if incorrectly equipped. Additional algorithms were written to extrapolate heart rate, and respiration rate from physiological readings. Another algorithm was written to calculate the amount of steps taken, distance traveled, and energy expended based upon the accelerometer data, and user input information. Finally, a program was written to pair with, and form a wireless serial connection with a bluetooth enabled device, and to transmit the processed data to a bluetooth compatible device. William also was responsible for powering the device, and wireless module selection. Leo Parsons Intellectual Contributions (LP) Leo is charged with the wireless data transmission as well as graphic user interface design. The data being transmitted must be received, stored, and displayed within the GUI. Leo’s responsibilities consisted of deciding what platform the GUI will be designed on and what software will be used to implement the design. Choosing to create a GUI that would be a mobile application, Leo decided to create the app using the Android operating system. This app must display the data processed from the Techtiles device. It is Leo’s responsibility to create a professional looking application, which is intuitive for it’s user to navigate and work efficiently. Teaming Arrangements The project will be done in three sub-systems, by one group member respectively. Aamir Husain will handle the fabric design, and the integration of sensors and other necessary electronics. William Gottschalk will receive and process the analog signals from the sensors. The signals will be quantized, and formatted into usable data so that further analysis and calculations can be conducted. The processed data will then be transmitted wirelessly via bluetooth to a compatible personal device. Leo Parsons will conduct the analysis of the digital signals, and create the graphical user interface so the data can be displayed in a presentable manner. of36 58
- 37. Appendix A: ProductData Sheets Appendix A contains some necessary data sheets which were referenced throughout the report. More information on these products can be found on the companies’ respective websites. Data sheets are given for the following products: MedTex P-180 Conductive Fabric AD620 Differential Amplifier ADXL335 Triple Axis Accelerometer Class 2 Bluetooth Module of37 58
- 39. Low Cost LowPower Instrumentation Amplifier AD620 Rev. H Information furnished by Analog Devices is believed to be accurate and reliable. However, no responsibility is assumed by Analog Devices for its use, nor for any infringements of patents or other rights of third parties that may result from its use. Specifications subject to change without notice. No license is granted by implication or otherwise under any patent or patent rights of Analog Devices. Trademarks and registered trademarks are the property of their respective owners. One Technology Way, P.O. Box 9106, Norwood, MA 02062-9106, U.S.A. Tel: 781.329.4700 www.analog.com Fax: 781.326.8703© 2003–2011 Analog Devices, Inc. All rights reserved. FEATURES Easy to use Gain set with one external resistor (Gain range 1 to 10,000) Wide power supply range (±2.3 V to ±18 V) Higher performance than 3 op amp IA designs Available in 8-lead DIP and SOIC packaging Low power, 1.3 mA max supply current Excellent dc performance (B grade) 50 µV max, input offset voltage 0.6 µV/°C max, input offset drift 1.0 nA max, input bias current 100 dB min common-mode rejection ratio (G = 10) Low noise 9 nV/√Hz @ 1 kHz, input voltage noise 0.28 µV p-p noise (0.1 Hz to 10 Hz) Excellent ac specifications 120 kHz bandwidth (G = 100) 15 µs settling time to 0.01% APPLICATIONS Weigh scales ECG and medical instrumentation Transducer interface Data acquisition systems Industrial process controls Battery-powered and portable equipment CONNECTION DIAGRAM –IN RG –VS +IN RG +VS OUTPUT REF 1 2 3 4 8 7 6 5AD620 TOP VIEW 00775-0-001 Figure 1. 8-Lead PDIP (N), CERDIP (Q), and SOIC (R) Packages PRODUCT DESCRIPTION The AD620 is a low cost, high accuracy instrumentation amplifier that requires only one external resistor to set gains of 1 to 10,000. Furthermore, the AD620 features 8-lead SOIC and DIP packaging that is smaller than discrete designs and offers lower power (only 1.3 mA max supply current), making it a good fit for battery-powered, portable (or remote) applications. The AD620, with its high accuracy of 40 ppm maximum nonlinearity, low offset voltage of 50 µV max, and offset drift of 0.6 µV/°C max, is ideal for use in precision data acquisition systems, such as weigh scales and transducer interfaces. Furthermore, the low noise, low input bias current, and low power of the AD620 make it well suited for medical applications, such as ECG and noninvasive blood pressure monitors. The low input bias current of 1.0 nA max is made possible with the use of Superϐeta processing in the input stage. The AD620 works well as a preamplifier due to its low input voltage noise of 9 nV/√Hz at 1 kHz, 0.28 µV p-p in the 0.1 Hz to 10 Hz band, and 0.1 pA/√Hz input current noise. Also, the AD620 is well suited for multiplexed applications with its settling time of 15 µs to 0.01%, and its cost is low enough to enable designs with one in-amp per channel. Table 1. Next Generation Upgrades for AD620 Part Comment AD8221 Better specs at lower price AD8222 Dual channel or differential out AD8226 Low power, wide input range AD8220 JFET input AD8228 Best gain accuracy AD8295 +2 precision op amps or differential out AD8429 Ultra low noise 0 5 10 15 20 30,000 5,000 10,000 15,000 20,000 25,000 0 TOTALERROR,PPMOFFULLSCALE SUPPLY CURRENT (mA) AD620A RG 3 OP AMP IN-AMP (3 OP-07s) 00775-0-002 Figure 2. Three Op Amp IA Designs vs. AD620
- 40. IMPORTANT LINKS forthe AD620* Last content update 01/08/2014 09:49 am Looking for a high performance in-amp with lower noise, wider bandwidth, and fast settling time? Consider the AD8421 Looking for a high performance in-amp with lower power and a rail-to-rail output? Consider the AD8422. DOCUMENTATION AD620: Military Data Sheet AN-282: Fundamentals of Sampled Data Systems AN-244: A User's Guide to I.C. Instrumentation Amplifiers AN-245: Instrumentation Amplifiers Solve Unusual Design Problems AN-671: Reducing RFI Rectification Errors in In-Amp Circuits AN-589: Ways to Optimize the Performance of a Difference Amplifier A Designer's Guide to Instrumentation Amplifiers (3rd Edition) UG-261: Evaluation Boards for the AD62x, AD822x and AD842x Series ECG Front-End Design is Simplified with MicroConverter Low-Power, Low-Voltage IC Choices for ECG System Requirements Ask The Applications Engineer-10 Auto-Zero Amplifiers High-performance Adder Uses Instrumentation Amplifiers Protecting Instrumentation Amplifiers Input Filter Prevents Instrumentation-amp RF-Rectification Errors The AD8221 - Setting a New Industry Standard for Instrumentation Amplifiers ADI Warns Against Misuse of COTS Integrated Circuits Space Qualified Parts List Applying Instrumentation Amplifiers Effectively: The Importance of an Input Ground Return Leading Inside Advertorials: Applying Instrumentation Amplifiers Effectively–The Importance of an Input Ground Return DESIGN TOOLS, MODELS, DRIVERS & SOFTWARE In-Amp Error Calculator These tools will help estimate error contributions in your instrumentation amplifier circuit. It uses input parameters such as temperature, gain, voltage input, and source impedance to determine the errors that can contribute to your overall design. In-Amp Common Mode Calculator AD620 SPICE Macro-Model AD620A SPICE Macro-Model AD620B SPICE Macro-Model AD620S SPICE Macro-Model AD620 SABER Macro-Model Conv, 10/00 EVALUATION KITS & SYMBOLS & FOOTPRINTS View the Evaluation Boards and Kits page for documentation and purchasing Symbols and Footprints PRODUCT RECOMMENDATIONS & REFERENCE DESIGNS CN-0146: Low Cost Programmable Gain Instrumentation Amplifier Circuit Using the ADG1611 Quad SPST Switch and AD620 Instrumentation Amplifier DESIGN COLLABORATION COMMUNITY Collaborate Online with the ADI support team and other designers about select ADI products. Follow us on Twitter: www.twitter.com/ADI_News Like us on Facebook: www.facebook.com/AnalogDevicesInc DESIGN SUPPORT Submit your support request here: Linear and Data Converters Embedded Processing and DSP Telephone our Customer Interaction Centers toll free: Americas: 1-800-262-5643 Europe: 00800-266-822-82 China: 4006-100-006 India: 1800-419-0108 Russia: 8-800-555-45-90 Quality and Reliability Lead(Pb)-Free Data SAMPLE & BUY AD620 View Price & Packaging Request Evaluation Board Request Samples Check Inventory & Purchase Find Local Distributors * This page was dynamically generated by Analog Devices, Inc. and inserted into this data sheet. Note: Dynamic changes to the content on this page (labeled 'Important Links') does not constitute a change to the revision number of the product data sheet. This content may be frequently modified. Powered by TCPDF (www.tcpdf.org)
- 41. AD620 Rev. H |Page 2 of 20 TABLE OF CONTENTS Specifications .....................................................................................3 Absolute Maximum Ratings ............................................................5 ESD Caution ..................................................................................5 Typical Performance Characteristics..............................................6 Theory of Operation.......................................................................12 Gain Selection..............................................................................15 Input and Output Offset Voltage ..............................................15 Reference Terminal.....................................................................15 Input Protection ..........................................................................15 RF Interference............................................................................15 Common-Mode Rejection.........................................................16 Grounding....................................................................................16 Ground Returns for Input Bias Currents.................................17 AD620ACHIPS Information.........................................................18 Outline Dimensions........................................................................19 Ordering Guide...........................................................................20 REVISION HISTORY 7/11—Rev. G to Rev. H Deleted Figure 3.................................................................................1 Added Table 1 ....................................................................................1 Moved Figure 2..................................................................................1 Added ESD Input Diodes to Simplified Schematic ....................12 Changes to Input Protection Section............................................15 Added Figure 41; Renumbered Sequentially...............................15 Changes to AD620ACHIPS Information Section ......................18 Updated Ordering Guide ...............................................................20 12/04—Rev. F to Rev. G Updated Format..................................................................Universal Change to Features............................................................................1 Change to Product Description.......................................................1 Changes to Specifications.................................................................3 Added Metallization Photograph....................................................4 Replaced Figure 4-Figure 6 ..............................................................6 Replaced Figure 15............................................................................7 Replaced Figure 33..........................................................................10 Replaced Figure 34 and Figure 35.................................................10 Replaced Figure 37..........................................................................10 Changes to Table 3 ..........................................................................13 Changes to Figure 41 and Figure 42 .............................................14 Changes to Figure 43 ......................................................................15 Change to Figure 44........................................................................17 Changes to Input Protection section............................................15 Deleted Figure 9 ..............................................................................15 Changes to RF Interference section..............................................15 Edit to Ground Returns for Input Bias Currents section...........17 Added AD620CHIPS to Ordering Guide....................................19 7/03—Data Sheet Changed from Rev. E to Rev. F Edit to FEATURES............................................................................1 Changes to SPECIFICATIONS.......................................................2 Removed AD620CHIPS from ORDERING GUIDE ...................4 Removed METALLIZATION PHOTOGRAPH...........................4 Replaced TPCs 1–3...........................................................................5 Replaced TPC 12...............................................................................6 Replaced TPC 30...............................................................................9 Replaced TPCs 31 and 32...............................................................10 Replaced Figure 4............................................................................10 Changes to Table I...........................................................................11 Changes to Figures 6 and 7............................................................12 Changes to Figure 8 ........................................................................13 Edited INPUT PROTECTION section........................................13 Added new Figure 9........................................................................13 Changes to RF INTERFACE section............................................14 Edit to GROUND RETURNS FOR INPUT BIAS CURRENTS section...............................................................................................15 Updated OUTLINE DIMENSIONS.............................................16
- 42. AD620 Rev. H |Page 3 of 20 SPECIFICATIONS Typical @ 25°C, VS = ±15 V, and RL = 2 kΩ, unless otherwise noted. Table 2. Parameter Conditions AD620A AD620B AD620S1 Min Typ Max Min Typ Max Min Typ Max Unit GAIN G = 1 + (49.4 kΩ/RG) Gain Range 1 10,000 1 10,000 1 10,000 Gain Error2 VOUT = ±10 V G = 1 0.03 0.10 0.01 0.02 0.03 0.10 % G = 10 0.15 0.30 0.10 0.15 0.15 0.30 % G = 100 0.15 0.30 0.10 0.15 0.15 0.30 % G = 1000 0.40 0.70 0.35 0.50 0.40 0.70 % Nonlinearity VOUT = −10 V to +10 V G = 1–1000 RL = 10 kΩ 10 40 10 40 10 40 ppm G = 1–100 RL = 2 kΩ 10 95 10 95 10 95 ppm Gain vs. Temperature G = 1 10 10 10 ppm/°C Gain >12 −50 −50 −50 ppm/°C VOLTAGE OFFSET (Total RTI Error = VOSI + VOSO/G) Input Offset, VOSI VS = ±5 V to ± 15 V 30 125 15 50 30 125 µV Overtemperature VS = ±5 V to ± 15 V 185 85 225 µV Average TC VS = ±5 V to ± 15 V 0.3 1.0 0.1 0.6 0.3 1.0 µV/°C Output Offset, VOSO VS = ±15 V 400 1000 200 500 400 1000 µV VS = ± 5 V 1500 750 1500 µV Overtemperature VS = ±5 V to ± 15 V 2000 1000 2000 µV Average TC VS = ±5 V to ± 15 V 5.0 15 2.5 7.0 5.0 15 µV/°C Offset Referred to the Input vs. Supply (PSR) VS = ±2.3 V to ±18 V G = 1 80 100 80 100 80 100 dB G = 10 95 120 100 120 95 120 dB G = 100 110 140 120 140 110 140 dB G = 1000 110 140 120 140 110 140 dB INPUT CURRENT Input Bias Current 0.5 2.0 0.5 1.0 0.5 2 nA Overtemperature 2.5 1.5 4 nA Average TC 3.0 3.0 8.0 pA/°C Input Offset Current 0.3 1.0 0.3 0.5 0.3 1.0 nA Overtemperature 1.5 0.75 2.0 nA Average TC 1.5 1.5 8.0 pA/°C INPUT Input Impedance Differential 10||2 10||2 10||2 GΩ_pF Common-Mode 10||2 10||2 10||2 GΩ_pF Input Voltage Range3 VS = ±2.3 V to ±5 V −VS + 1.9 +VS − 1.2 −VS + 1.9 +VS − 1.2 −VS + 1.9 +VS − 1.2 V Overtemperature −VS + 2.1 +VS − 1.3 −VS + 2.1 +VS − 1.3 −VS + 2.1 +VS − 1.3 V VS = ± 5 V to ±18 V −VS + 1.9 +VS − 1.4 −VS + 1.9 +VS − 1.4 −VS + 1.9 +VS − 1.4 V Overtemperature −VS + 2.1 +VS − 1.4 −VS + 2.1 +VS + 2.1 −VS + 2.3 +VS − 1.4 V
- 43. AD620 Rev. H |Page 4 of 20 AD620A AD620B AD620S1 Parameter Conditions Min Typ Max Min Typ Max Min Typ Max Unit Common-Mode Rejection Ratio DC to 60 Hz with 1 kΩ Source Imbalance VCM = 0 V to ± 10 V G = 1 73 90 80 90 73 90 dB G = 10 93 110 100 110 93 110 dB G = 100 110 130 120 130 110 130 dB G = 1000 110 130 120 130 110 130 dB OUTPUT Output Swing RL = 10 kΩ VS = ±2.3 V to ± 5 V −VS + 1.1 +VS − 1.2 −VS + 1.1 +VS − 1.2 −VS + 1.1 +VS − 1.2 V Overtemperature −VS + 1.4 +VS − 1.3 −VS + 1.4 +VS − 1.3 −VS + 1.6 +VS − 1.3 V VS = ±5 V to ± 18 V −VS + 1.2 +VS − 1.4 −VS + 1.2 +VS − 1.4 −VS + 1.2 +VS − 1.4 V Overtemperature −VS + 1.6 +VS – 1.5 −VS + 1.6 +VS – 1.5 –VS + 2.3 +VS – 1.5 V Short Circuit Current ±18 ±18 ±18 mA DYNAMIC RESPONSE Small Signal –3 dB Bandwidth G = 1 1000 1000 1000 kHz G = 10 800 800 800 kHz G = 100 120 120 120 kHz G = 1000 12 12 12 kHz Slew Rate 0.75 1.2 0.75 1.2 0.75 1.2 V/µs Settling Time to 0.01% 10 V Step G = 1–100 15 15 15 µs G = 1000 150 150 150 µs NOISE Voltage Noise, 1 kHz 22 )/()( GeeNoiseRTITotal noni += Input, Voltage Noise, eni 9 13 9 13 9 13 nV/√Hz Output, Voltage Noise, eno 72 100 72 100 72 100 nV/√Hz RTI, 0.1 Hz to 10 Hz G = 1 3.0 3.0 6.0 3.0 6.0 µV p-p G = 10 0.55 0.55 0.8 0.55 0.8 µV p-p G = 100–1000 0.28 0.28 0.4 0.28 0.4 µV p-p Current Noise f = 1 kHz 100 100 100 fA/√Hz 0.1 Hz to 10 Hz 10 10 10 pA p-p REFERENCE INPUT RIN 20 20 20 kΩ IIN VIN+, VREF = 0 50 60 50 60 50 60 µA Voltage Range −VS + 1.6 +VS − 1.6 −VS + 1.6 +VS − 1.6 −VS + 1.6 +VS − 1.6 V Gain to Output 1 ± 0.0001 1 ± 0.0001 1 ± 0.0001 POWER SUPPLY Operating Range4 ±2.3 ±18 ±2.3 ±18 ±2.3 ±18 V Quiescent Current VS = ±2.3 V to ±18 V 0.9 1.3 0.9 1.3 0.9 1.3 mA Overtemperature 1.1 1.6 1.1 1.6 1.1 1.6 mA TEMPERATURE RANGE For Specified Performance −40 to +85 −40 to +85 −55 to +125 °C 1 See Analog Devices military data sheet for 883B tested specifications. 2 Does not include effects of external resistor RG. 3 One input grounded. G = 1. 4 This is defined as the same supply range that is used to specify PSR.
- 44. AD620 Rev. H |Page 5 of 20 ABSOLUTE MAXIMUM RATINGS Table 3. Parameter Rating Supply Voltage ±18 V Internal Power Dissipation1 650 mW Input Voltage (Common-Mode) ±VS Differential Input Voltage 25 V Output Short-Circuit Duration Indefinite Storage Temperature Range (Q) −65°C to +150°C Storage Temperature Range (N, R) −65°C to +125°C Operating Temperature Range AD620 (A, B) −40°C to +85°C AD620 (S) −55°C to +125°C Lead Temperature Range (Soldering 10 seconds) 300°C 1 Specification is for device in free air: 8-Lead Plastic Package: θJA = 95°C 8-Lead CERDIP Package: θJA = 110°C 8-Lead SOIC Package: θJA = 155°C Stresses above those listed under Absolute Maximum Ratings may cause permanent damage to the device. This is a stress rating only; functional operation of the device at these or any other condition s above those indicated in the operational section of this specification is not implied. Exposure to absolute maximum rating conditions for extended periods may affect device reliability. ESD CAUTION
- 45. AD620 Rev. H |Page 6 of 20 TYPICAL PERFORMANCE CHARACTERISTICS (@ 25°C, VS = ±15 V, RL = 2 kΩ, unless otherwise noted.) INPUT OFFSET VOLTAGE (μV) 20 30 40 50 –40 0 40 80 PERCENTAGEOFUNITS –80 SAMPLE SIZE = 360 10 0 00775-0-005 Figure 3. Typical Distribution of Input Offset Voltage INPUT BIAS CURRENT (pA) 0 10 20 30 40 50 –600 0 600 PERCENTAGEOFUNITS –1200 1200 SAMPLE SIZE = 850 00775-0-006 Figure 4. Typical Distribution of Input Bias Current 10 20 30 40 50 –200 0 200 400 INPUT OFFSET CURRENT (pA) PERCENTAGEOFUNITS –400 0 SAMPLE SIZE = 850 00775-0-007 Figure 5. Typical Distribution of Input Offset Current TEMPERATURE (°C) INPUTBIASCURRENT(nA) +IB –IB 2.0 –2.0 175 –1.0 –1.5 –75 –0.5 0 0.5 1.0 1.5 1257525–25 00775-0-008 Figure 6. Input Bias Current vs. Temperature CHANGEINOFFSETVOLTAGE(μV) 1.5 0.5 WARM-UP TIME (Minutes) 2.0 0 0 1 1.0 432 5 00775-0-009 Figure 7. Change in Input Offset Voltage vs. Warm-Up Time FREQUENCY (Hz) 1000 1 1 100k 100 10 10k1k100 VOLTAGENOISE(nV/Hz) GAIN = 1 GAIN = 10 10 GAIN = 100, 1,000 GAIN = 1000 BW LIMIT 00775-0-010 Figure 8. Voltage Noise Spectral Density vs. Frequency (G = 1−1000)
- 46. AD620 Rev. H |Page 7 of 20 FREQUENCY (Hz) 1000 100 10 1 10 1000100 CURRENTNOISE(fA/Hz) 00775-0-011 Figure 9. Current Noise Spectral Density vs. Frequency RTINOISE(2.0μV/DIV) TIME (1 SEC/DIV) 00775-0-012 Figure 10. 0.1 Hz to 10 Hz RTI Voltage Noise (G = 1) RTINOISE(0.1μV/DIV) TIME (1 SEC/DIV) 00775-0-013 Figure 11. 0.1 Hz to 10 Hz RTI Voltage Noise (G = 1000) 00775-0-014 Figure 12. 0.1 Hz to 10 Hz Current Noise, 5 pA/Div 100 1000 AD620A FET INPUT IN-AMP SOURCE RESISTANCE (Ω) TOTALDRIFTFROM25°CTO85°C,RTI(μV) 100,000 10 1k 10M 10,000 10k 1M100k 00775-0-015 Figure 13. Total Drift vs. Source Resistance FREQUENCY (Hz) CMR(dB) 160 0 1M 80 40 1 60 0.1 140 100 120 100k10k1k10010 G = 1000 G = 100 G = 10 G = 1 20 00775-0-016 Figure 14. Typical CMR vs. Frequency, RTI, Zero to 1 kΩ Source Imbalance
- 47. AD620 Rev. H |Page 8 of 20 FREQUENCY (Hz) PSR(dB) 160 1M 80 40 1 60 0.1 140 100 120 100k10k1k10010 20 G = 1000 G = 100 G = 10 G = 1 180 00775-0-017 Figure 15. Positive PSR vs. Frequency, RTI (G = 1−1000) FREQUENCY (Hz) PSR(dB) 160 1M 80 40 1 60 0.1 140 100 120 100k10k1k10010 20 180 G = 10 G = 100 G = 1 G = 1000 00775-0-018 Figure 16. Negative PSR vs. Frequency, RTI (G = 1−1000) 1000 100 10M 100 1 1k 10 100k 1M10k FREQUENCY (Hz) GAIN(V/V) 0.1 00775-0-019 Figure 17. Gain vs. Frequency OUTPUTVOLTAGE(Vp-p) FREQUENCY (Hz) 35 0 1M 15 5 10k 10 1k 30 20 25 100k G = 10, 100, 1000 G = 1 G = 1000 G = 100 BWLIMIT 00775-0-020 Figure 18. Large Signal Frequency Response INPUTVOLTAGELIMIT(V) (REFERREDTOSUPPLYVOLTAGES) 20 +1.0 +0.5 50 +1.5 –1.5 –1.0 –0.5 1510 SUPPLY VOLTAGE ± Volts +VS –0.0 –VS +0.0 00775-0-021 Figure 19. Input Voltage Range vs. Supply Voltage, G = 1 20 +1.0 +0.5 50 +1.5 –1.5 –1.0 –0.5 1510 SUPPLY VOLTAGE ± Volts RL = 10kΩ RL = 2kΩ RL = 10kΩ OUTPUTVOLTAGESWING(V) (REFERREDTOSUPPLYVOLTAGES) RL = 2kΩ +VS –VS 00775-0-022 –0.0 +0.0 Figure 20. Output Voltage Swing vs. Supply Voltage, G = 10
- 48. AD620 Rev. H |Page 9 of 20 OUTPUTVOLTAGESWING(Vp-p) LOAD RESISTANCE (Ω) 30 0 0 10k 20 10 100 1k VS = ±15V G = 10 00775-0-023 Figure 21. Output Voltage Swing vs. Load Resistance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00775-0-024 Figure 22. Large Signal Pulse Response and Settling Time G = 1 (0.5 mV = 0.01%) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00775-0-025 Figure 23. Small Signal Response, G = 1, RL = 2 kΩ, CL = 100 pF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00775-0-026 Figure 24. Large Signal Response and Settling Time, G = 10 (0.5 mV = 0.01%) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00775-0-027 Figure 25. Small Signal Response, G = 10, RL = 2 kΩ, CL = 100 pF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00775-0-030 Figure 26. Large Signal Response and Settling Time, G = 100 (0.5 mV = 0.01%)
- 49. AD620 Rev. H |Page 10 of 20 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00775-0-029 Figure 27. Small Signal Pulse Response, G = 100, RL = 2 kΩ, CL = 100 pF . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00775-0-030 Figure 28. Large Signal Response and Settling Time, G = 1000 (0.5 mV = 0.01% ) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00775-0-031 Figure 29. Small Signal Pulse Response, G = 1000, RL = 2 kΩ, CL = 100 pF OUTPUT STEP SIZE (V) SETTLINGTIME(μs) TO 0.01% TO 0.1% 20 0 0 2 15 5 5 10 10 015 00775-0-032 Figure 30. Settling Time vs. Step Size (G = 1) GAIN SETTLINGTIME(μs) 1000 1 1 1000 100 10 10 100 00775-0-033 Figure 31. Settling Time to 0.01% vs. Gain, for a 10 V Step . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00775-0-034 Figure 32. Gain Nonlinearity, G = 1, RL = 10 kΩ (10 µV = 1 ppm)
- 50. AD620 Rev. H |Page 11 of 20 . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00775-0-035 Figure 33. Gain Nonlinearity, G = 100, RL = 10 kΩ (100 µV = 10 ppm) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 00775-0-036 Figure 34. Gain Nonlinearity, G = 1000, RL = 10 kΩ (1 mV = 100 ppm) AD620 VOUT G = 1G = 1000 49.9Ω 10kΩ* 1kΩ 10T 10kΩ 499Ω G = 10G = 100 5.49kΩ +VS 11kΩ 1kΩ 100Ω 100kΩ INPUT 10V p-p –VS *ALL RESISTORS 1% TOLERANCE 71 2 3 8 6 4 5 00775-0-037 Figure 35. Settling Time Test Circuit
- 51. AD620 Rev. H |Page 12 of 20 THEORY OF OPERATION VB –VS A1 A2 A3 C2 RG R1 R2 GAIN SENSE GAIN SENSE 10kΩ 10kΩ I2I1 10kΩ REF 10kΩ +IN – IN R4 400Ω OUTPUT C1 Q2Q1 00775-0-038 R3 400Ω +VS +VS +VS 20µA20µA Figure 36. Simplified Schematic of AD620 The AD620 is a monolithic instrumentation amplifier based on a modification of the classic three op amp approach. Absolute value trimming allows the user to program gain accurately (to 0.15% at G = 100) with only one resistor. Monolithic construction and laser wafer trimming allow the tight matching and tracking of circuit components, thus ensuring the high level of performance inherent in this circuit. The input transistors Q1 and Q2 provide a single differential- pair bipolar input for high precision (Figure 36), yet offer 10× lower input bias current thanks to Superϐeta processing. Feedback through the Q1-A1-R1 loop and the Q2-A2-R2 loop maintains constant collector current of the input devices Q1 and Q2, thereby impressing the input voltage across the external gain setting resistor RG. This creates a differential gain from the inputs to the A1/A2 outputs given by G = (R1 + R2)/RG + 1. The unity-gain subtractor, A3, removes any common-mode signal, yielding a single-ended output referred to the REF pin potential. The value of RG also determines the transconductance of the preamp stage. As RG is reduced for larger gains, the transconductance increases asymptotically to that of the input transistors. This has three important advantages: (a) Open-loop gain is boosted for increasing programmed gain, thus reducing gain related errors. (b) The gain-bandwidth product (determined by C1 and C2 and the preamp transconductance) increases with programmed gain, thus optimizing frequency response. (c) The input voltage noise is reduced to a value of 9 nV/√Hz, determined mainly by the collector current and base resistance of the input devices. The internal gain resistors, R1 and R2, are trimmed to an absolute value of 24.7 kΩ, allowing the gain to be programmed accurately with a single external resistor. The gain equation is then 1 4.49 + Ω = GR k G 1 4.49 − Ω = G k RG Make vs. Buy: a Typical Bridge Application Error Budget The AD620 offers improved performance over “homebrew” three op amp IA designs, along with smaller size, fewer components, and 10× lower supply current. In the typical application, shown in Figure 37, a gain of 100 is required to amplify a bridge output of 20 mV full-scale over the industrial temperature range of −40°C to +85°C. Table 4 shows how to calculate the effect various error sources have on circuit accuracy.
- 52. AD620 Rev. H |Page 13 of 20 Regardless of the system in which it is being used, the AD620 provides greater accuracy at low power and price. In simple systems, absolute accuracy and drift errors are by far the most significant contributors to error. In more complex systems with an intelligent processor, an autogain/autozero cycle removes all absolute accuracy and drift errors, leaving only the resolution errors of gain, nonlinearity, and noise, thus allowing full 14-bit accuracy. Note that for the homebrew circuit, the OP07 specifications for input voltage offset and noise have been multiplied by √2. This is because a three op amp type in-amp has two op amps at its inputs, both contributing to the overall input error. R = 350Ω 10V PRECISION BRIDGE TRANSDUCER R = 350Ω R = 350Ω R = 350Ω 00775-0-039 AD620A MONOLITHIC INSTRUMENTATION AMPLIFIER, G = 100 SUPPLY CURRENT = 1.3mA MAX AD620A RG 499Ω REFERENCE 00775-0-040 Figure 37. Make vs. Buy "HOMEBREW" IN-AMP, G = 100 *0.02% RESISTOR MATCH, 3ppm/°C TRACKING **DISCRETE 1% RESISTOR, 100ppm/°C TRACKING SUPPLY CURRENT = 15mA MAX 100Ω** 10kΩ* 10kΩ** 10kΩ* 10kΩ* 10kΩ** 10kΩ* OP07D OP07D OP07D 00775-0-041 Table 4. Make vs. Buy Error Budget Error, ppm of Full Scale Error Source AD620 Circuit Calculation “Homebrew” Circuit Calculation AD620 Homebrew ABSOLUTE ACCURACY at TA = 25°C Input Offset Voltage, µV 125 µV/20 mV (150 µV × √2)/20 mV 6,250 10,607 Output Offset Voltage, µV 1000 µV/100 mV/20 mV ((150 µV × 2)/100)/20 mV 500 150 Input Offset Current, nA 2 nA ×350 Ω/20 mV (6 nA ×350 Ω)/20 mV 18 53 CMR, dB 110 dB(3.16 ppm) ×5 V/20 mV (0.02% Match × 5 V)/20 mV/100 791 500 Total Absolute Error 7,559 11,310 DRIFT TO 85°C Gain Drift, ppm/°C (50 ppm + 10 ppm) ×60°C 100 ppm/°C Track × 60°C 3,600 6,000 Input Offset Voltage Drift, µV/°C 1 µV/°C × 60°C/20 mV (2.5 µV/°C × √2 × 60°C)/20 mV 3,000 10,607 Output Offset Voltage Drift, µV/°C 15 µV/°C × 60°C/100 mV/20 mV (2.5 µV/°C × 2 × 60°C)/100 mV/20 mV 450 150 Total Drift Error 7,050 16,757 RESOLUTION Gain Nonlinearity, ppm of Full Scale 40 ppm 40 ppm 40 40 Typ 0.1 Hz to 10 Hz Voltage Noise, µV p-p 0.28 µV p-p/20 mV (0.38 µV p-p × √2)/20 mV 14 27 Total Resolution Error 54 67 Grand Total Error 14,663 28,134 G = 100, VS = ±15 V. (All errors are min/max and referred to input.)
- 53. AD620 Rev. H |Page 14 of 20 3kΩ 5V DIGITAL DATA OUTPUT ADC REF IN AGND 20kΩ 10kΩ 20kΩ AD620BG = 100 1.7mA 0.10mA 0.6mA MAX 499Ω 3kΩ 3kΩ3kΩ 2 1 8 3 7 6 5 4 1.3mA MAX AD705 00775-0-042 Figure 38. A Pressure Monitor Circuit that Operates on a 5 V Single Supply Pressure Measurement Although useful in many bridge applications, such as weigh scales, the AD620 is especially suitable for higher resistance pressure sensors powered at lower voltages where small size and low power become more significant. Figure 38 shows a 3 kΩ pressure transducer bridge powered from 5 V. In such a circuit, the bridge consumes only 1.7 mA. Adding the AD620 and a buffered voltage divider allows the signal to be conditioned for only 3.8 mA of total supply current. Small size and low cost make the AD620 especially attractive for voltage output pressure transducers. Since it delivers low noise and drift, it also serves applications such as diagnostic noninvasive blood pressure measurement. Medical ECG The low current noise of the AD620 allows its use in ECG monitors (Figure 39) where high source resistances of 1 MΩ or higher are not uncommon. The AD620’s low power, low supply voltage requirements, and space-saving 8-lead mini-DIP and SOIC package offerings make it an excellent choice for battery- powered data recorders. Furthermore, the low bias currents and low current noise, coupled with the low voltage noise of the AD620, improve the dynamic range for better performance. The value of capacitor C1 is chosen to maintain stability of the right leg drive loop. Proper safeguards, such as isolation, must be added to this circuit to protect the patient from possible harm. G = 7 AD620A 0.03Hz HIGH- PASS FILTER OUTPUT 1V/mV +3V –3V RG 8.25kΩ 24.9kΩ 24.9kΩ AD705J G = 143 C1 1MΩ R4 10kΩ R1 R3 R2 OUTPUT AMPLIFIER PATIENT/CIRCUIT PROTECTION/ISOLATION 00775-0-043 Figure 39. A Medical ECG Monitor Circuit
- 54. AD620 Rev. H |Page 15 of 20 Precision V-I Converter The AD620, along with another op amp and two resistors, makes a precision current source (Figure 40). The op amp buffers the reference terminal to maintain good CMR. The output voltage, VX, of the AD620 appears across R1, which converts it to a current. This current, less only the input bias current of the op amp, then flows out to the load. AD620RG –VS VIN+ VIN– LOAD R1 IL Vx I =L R1 = IN+[(V ) – (V )] GIN– R1 6 5 + V –X 42 1 8 3 7 +VS AD705 00775-0-044 Figure 40. Precision Voltage-to-Current Converter (Operates on 1.8 mA, ±3 V) GAIN SELECTION The AD620 gain is resistor-programmed by RG, or more precisely, by whatever impedance appears between Pins 1 and 8. The AD620 is designed to offer accurate gains using 0.1% to 1% resistors. Table 5 shows required values of RG for various gains. Note that for G = 1, the RG pins are unconnected (RG = ∞). For any arbitrary gain, RG can be calculated by using the formula: 1 4.49 − Ω = G k RG To minimize gain error, avoid high parasitic resistance in series with RG; to minimize gain drift, RG should have a low TC—less than 10 ppm/°C—for the best performance. Table 5. Required Values of Gain Resistors 1% Std Table Value of RG(Ω) Calculated Gain 0.1% Std Table Value of RG(Ω ) Calculated Gain 49.9 k 1.990 49.3 k 2.002 12.4 k 4.984 12.4 k 4.984 5.49 k 9.998 5.49 k 9.998 2.61 k 19.93 2.61 k 19.93 1.00 k 50.40 1.01 k 49.91 499 100.0 499 100.0 249 199.4 249 199.4 100 495.0 98.8 501.0 49.9 991.0 49.3 1,003.0 INPUT AND OUTPUT OFFSET VOLTAGE The low errors of the AD620 are attributed to two sources, input and output errors. The output error is divided by G when referred to the input. In practice, the input errors dominate at high gains, and the output errors dominate at low gains. The total VOS for a given gain is calculated as Total Error RTI = input error + (output error/G) Total Error RTO = (input error × G) + output error REFERENCE TERMINAL The reference terminal potential defines the zero output voltage and is especially useful when the load does not share a precise ground with the rest of the system. It provides a direct means of injecting a precise offset to the output, with an allowable range of 2 V within the supply voltages. Parasitic resistance should be kept to a minimum for optimum CMR. INPUT PROTECTION The AD620 safely withstands an input current of ±60 mA for several hours at room temperature. This is true for all gains and power on and off, which is useful if the signal source and amplifier are powered separately. For longer time periods, the input current should not exceed 6 mA. For input voltages beyond the supplies, a protection resistor should be placed in series with each input to limit the current to 6 mA. These can be the same resistors as those used in the RFI filter. High values of resistance can impact the noise and AC CMRR performance of the system. Low leakage diodes (such as the BAV199) can be placed at the inputs to reduce the required protection resistance. AD620 R REF R +SUPPLY –SUPPLY VOUT +IN –IN 00775-0-052 Figure 41. Diode Protection for Voltages Beyond Supply RF INTERFERENCE All instrumentation amplifiers rectify small out of band signals. The disturbance may appear as a small dc voltage offset. High frequency signals can be filtered with a low pass R-C network placed at the input of the instrumentation amplifier. Figure 42 demonstrates such a configuration. The filter limits the input
- 55. AD620 Rev. H |Page 16 of 20 signal according to the following relationship: )2(2 1 CD DIFF CCR FilterFreq +π = C CM RC FilterFreq π = 2 1 where CD ≥10CC. CD affects the difference signal. CC affects the common-mode signal. Any mismatch in R × CC degrades the AD620 CMRR. To avoid inadvertently reducing CMRR-bandwidth performance, make sure that CC is at least one magnitude smaller than CD. The effect of mismatched CCs is reduced with a larger CD:CC ratio. 499Ω AD620 + – VOUT R R CC CD CC +IN –IN REF –15V 0.1μ F 1 μ F0 +15V 0.1μ F 1 μ F0 00775-0-045 Figure 42. Circuit to Attenuate RF Interference COMMON-MODE REJECTION Instrumentation amplifiers, such as the AD620, offer high CMR, which is a measure of the change in output voltage when both inputs are changed by equal amounts. These specifications are usually given for a full-range input voltage change and a specified source imbalance. For optimal CMR, the reference terminal should be tied to a low impedance point, and differences in capacitance and resistance should be kept to a minimum between the two inputs. In many applications, shielded cables are used to minimize noise; for best CMR over frequency, the shield should be properly driven. Figure 43 and Figure 44 show active data guards that are configured to improve ac common-mode rejections by “bootstrapping” the capacitances of input cable shields, thus minimizing the capacitance mismatch between the inputs. REFERENCE VOUT AD620 100Ω 100Ω – INPUT + INPUT AD648 RG –VS +VS –VS 00775-0-046 Figure 43. Differential Shield Driver 100Ω – INPUT + INPUT REFERENCE VOUT AD620 –VS +VS 2 RG 2 RG AD548 00775-0-047 Figure 44. Common-Mode Shield Driver GROUNDING Since the AD620 output voltage is developed with respect to the potential on the reference terminal, it can solve many grounding problems by simply tying the REF pin to the appropriate “local ground.” To isolate low level analog signals from a noisy digital environment, many data-acquisition components have separate analog and digital ground pins (Figure 45). It would be convenient to use a single ground line; however, current through ground wires and PC runs of the circuit card can cause hundreds of millivolts of error. Therefore, separate ground returns should be provided to minimize the current flow from the sensitive points to the system ground. These ground returns must be tied together at some point, usually best at the ADC package shown in Figure 45. DIGITAL P.S. +5VC ANALOG P.S. +15V C –15V AD574A DIGITAL DATA OUTPUT + 1μF AD620 0.1μF AD585 S/H ADC 0.1μF 1μF 1μF 00775-0-048 Figure 45. Basic Grounding Practice
- 56. AD620 Rev. H |Page 17 of 20 GROUND RETURNS FOR INPUT BIAS CURRENTS VOUT – INPUT + INPUT RG LOAD TO POWER SUPPLY GROUND REFERENCE +VS –VS AD620 00775-0-050 Input bias currents are those currents necessary to bias the input transistors of an amplifier. There must be a direct return path for these currents. Therefore, when amplifying “floating” input sources, such as transformers or ac-coupled sources, there must be a dc path from each input to ground, as shown in Figure 46, Figure 47, and Figure 48. Refer to A Designer’s Guide to Instrumentation Amplifiers (free from Analog Devices) for more information regarding in-amp applications. VOUTAD620 – INPUT RG TO POWER SUPPLY GROUND REFERENCE+ INPUT +VS –VS LOAD 00775-0-049 Figure 47. Ground Returns for Bias Currents with Thermocouple Inputs 100kΩ VOUTAD620 – INPUT + INPUT RG LOAD TO POWER SUPPLY GROUND REFERENCE 100kΩ –VS +VS 00775-0-051 Figure 46. Ground Returns for Bias Currents with Transformer-Coupled Inputs Figure 48. Ground Returns for Bias Currents with AC-Coupled Inputs
- 57. AD620 Rev. H |Page 18 of 20 AD620ACHIPS INFORMATION Die size: 1803 µm × 3175 µm Die thickness: 483 µm Bond Pad Metal: 1% Copper Doped Aluminum To minimize gain errors introduced by the bond wires, use Kelvin connections between the chip and the gain resistor, RG, by connecting Pad 1A and Pad 1B in parallel to one end of RG and Pad 8A and Pad 8B in parallel to the other end of RG. For unity gain applications where RG is not required, Pad 1A and Pad 1B must be bonded together as well as the Pad 8A and Pad 8B. 1A 1B 2 3 4 5 6 7 8A 8B LOGO 00775-0-053 Figure 49. Bond Pad Diagram Table 6. Bond Pad Information Pad Coordinates1 Pad No. Mnemonic X (µm) Y (µm) 1A RG −623 +1424 1B RG −789 +628 2 −IN −790 +453 3 +IN −790 −294 4 −VS −788 −1419 5 REF +570 −1429 6 OUTPUT +693 −1254 7 +VS +693 +139 8A RG +505 +1423 8B RG +693 +372 1 The pad coordinates indicate the center of each pad, referenced to the center of the die. The die orientation is indicated by the logo, as shown in Figure 49.
- 58. AD620 Rev. H |Page 19 of 20 OUTLINE DIMENSIONS COMPLIANT TO JEDEC STANDARDS MS-001 CONTROLLING DIMENSIONS ARE IN INCHES; MILLIMETER DIMENSIONS (IN PARENTHESES) ARE ROUNDED-OFF INCH EQUIVALENTS FOR REFERENCE ONLY AND ARE NOT APPROPRIATE FOR USE IN DESIGN. CORNER LEADS MAY BE CONFIGURED AS WHOLE OR HALF LEADS. 070606-A 0.022 (0.56) 0.018 (0.46) 0.014 (0.36) SEATING PLANE 0.015 (0.38) MIN 0.210 (5.33) MAX 0.150 (3.81) 0.130 (3.30) 0.115 (2.92) 0.070 (1.78) 0.060 (1.52) 0.045 (1.14) 8 1 4 5 0.280 (7.11) 0.250 (6.35) 0.240 (6.10) 0.100 (2.54) BSC 0.400 (10.16) 0.365 (9.27) 0.355 (9.02) 0.060 (1.52) MAX 0.430 (10.92) MAX 0.014 (0.36) 0.010 (0.25) 0.008 (0.20) 0.325 (8.26) 0.310 (7.87) 0.300 (7.62) 0.195 (4.95) 0.130 (3.30) 0.115 (2.92) 0.015 (0.38) GAUGE PLANE 0.005 (0.13) MIN Figure 50. 8-Lead Plastic Dual In-Line Package [PDIP] Narrow Body (N-8). Dimensions shown in inches and (millimeters) CONTROLLING DIMENSIONS ARE IN INCHES; MILLIMETER DIMENSIONS (IN PARENTHESES) ARE ROUNDED-OFF INCH EQUIVALENTS FOR REFERENCE ONLY AND ARE NOT APPROPRIATE FOR USE IN DESIGN. 0.310 (7.87) 0.220 (5.59) 0.005 (0.13) MIN 0.055 (1.40) MAX 0.100 (2.54) BSC 15° 0° 0.320 (8.13) 0.290 (7.37) 0.015 (0.38) 0.008 (0.20) SEATING PLANE 0.200 (5.08) MAX 0.405 (10.29) MAX 0.150 (3.81) MIN 0.200 (5.08) 0.125 (3.18) 0.023 (0.58) 0.014 (0.36) 0.070 (1.78) 0.030 (0.76) 0.060 (1.52) 0.015 (0.38) 1 4 58 Figure 51. 8-Lead Ceramic Dual In-Line Package [CERDIP] (Q-8) Dimensions shown in inches and (millimeters) CONTROLLING DIMENSIONS ARE IN MILLIMETERS; INCH DIMENSIONS (IN PARENTHESES) ARE ROUNDED-OFF MILLIMETER EQUIVALENTS FOR REFERENCE ONLY AND ARE NOT APPROPRIATE FOR USE IN DESIGN. COMPLIANT TO JEDEC STANDARDS MS-012-AA 012407-A 0.25 (0.0098) 0.17 (0.0067) 1.27 (0.0500) 0.40 (0.0157) 0.50 (0.0196) 0.25 (0.0099) 45° 8° 0° 1.75 (0.0688) 1.35 (0.0532) SEATING PLANE 0.25 (0.0098) 0.10 (0.0040) 4 1 8 5 5.00 (0.1968) 4.80 (0.1890) 4.00 (0.1574) 3.80 (0.1497) 1.27 (0.0500) BSC 6.20 (0.2441) 5.80 (0.2284) 0.51 (0.0201) 0.31 (0.0122) COPLANARITY 0.10 Figure 52. 8-Lead Standard Small Outline Package [SOIC_N] Narrow Body (R-8) Dimensions shown in millimeters and (inches)
- 59. AD620 Rev. H |Page 20 of 20 ORDERING GUIDE Model1 Temperature Range Package Description Package Option AD620AN −40°C to +85°C 8-Lead PDIP N-8 AD620ANZ −40°C to +85°C 8-Lead PDIP N-8 AD620BN −40°C to +85°C 8-Lead PDIP N-8 AD620BNZ −40°C to +85°C 8-Lead PDIP N-8 AD620AR −40°C to +85°C 8-Lead SOIC_N R-8 AD620ARZ −40°C to +85°C 8-Lead SOIC_N R-8 AD620AR-REEL −40°C to +85°C 8-Lead SOIC_N, 13" Tape and Reel R-8 AD620ARZ-REEL −40°C to +85°C 8-Lead SOIC_N, 13" Tape and Reel R-8 AD620AR-REEL7 −40°C to +85°C 8-Lead SOIC_N, 7" Tape and Reel R-8 AD620ARZ-REEL7 −40°C to +85°C 8-Lead SOIC_N, 7" Tape and Reel R-8 AD620BR −40°C to +85°C 8-Lead SOIC_N R-8 AD620BRZ −40°C to +85°C 8-Lead SOIC_N R-8 AD620BR-REEL −40°C to +85°C 8-Lead SOIC_N, 13" Tape and Reel R-8 AD620BRZ-RL −40°C to +85°C 8-Lead SOIC_N, 13" Tape and Reel R-8 AD620BR-REEL7 −40°C to +85°C 8-Lead SOIC_N, 7" Tape and Reel R-8 AD620BRZ-R7 −40°C to +85°C 8-Lead SOIC_N, 7" Tape and Reel R-8 AD620ACHIPS −40°C to +85°C Die Form AD620SQ/883B −55°C to +125°C 8-Lead CERDIP Q-8 1 Z = RoHS Compliant Part. © 2003–2011 Analog Devices, Inc. All rights reserved. Trademarks and registered trademarks are the property of their respective owners. C00775–0–7/11(H)
- 60. Small, Low Power,3-Axis ±3 g Accelerometer ADXL335 Rev. 0 Information furnished by Analog Devices is believed to be accurate and reliable. However, no responsibilityisassumedbyAnalogDevicesforitsuse,norforanyinfringementsofpatentsorother rightsofthirdpartiesthatmayresultfromitsuse.Specificationssubjecttochangewithoutnotice.No licenseisgrantedbyimplicationorotherwiseunderanypatentorpatentrightsofAnalogDevices. Trademarksandregisteredtrademarksarethepropertyoftheirrespectiveowners. One Technology Way, P.O. Box 9106, Norwood, MA 02062-9106, U.S.A. Tel: 781.329.4700 www.analog.com Fax: 781.461.3113 ©2009 Analog Devices, Inc. All rights reserved. FEATURES 3-axis sensing Small, low profile package 4 mm × 4 mm × 1.45 mm LFCSP Low power : 350 µA (typical) Single-supply operation: 1.8 V to 3.6 V 10,000 g shock survival Excellent temperature stability BW adjustment with a single capacitor per axis RoHS/WEEE lead-free compliant APPLICATIONS Cost sensitive, low power, motion- and tilt-sensing applications Mobile devices Gaming systems Disk drive protection Image stabilization Sports and health devices GENERAL DESCRIPTION The ADXL335 is a small, thin, low power, complete 3-axis accel- erometer with signal conditioned voltage outputs. The product measures acceleration with a minimum full-scale range of ±3 g. It can measure the static acceleration of gravity in tilt-sensing applications, as well as dynamic acceleration resulting from motion, shock, or vibration. The user selects the bandwidth of the accelerometer using the CX, CY, and CZ capacitors at the XOUT, YOUT, and ZOUT pins. Bandwidths can be selected to suit the application, with a range of 0.5 Hz to 1600 Hz for the X and Y axes, and a range of 0.5 Hz to 550 Hz for the Z axis. The ADXL335 is available in a small, low profile, 4 mm × 4 mm × 1.45 mm, 16-lead, plastic lead frame chip scale package (LFCSP_LQ). FUNCTIONAL BLOCK DIAGRAM 07808-001 3-AXIS SENSOR AC AMP DEMOD OUTPUT AMP OUTPUT AMP OUTPUT AMP VS COM ST XOUT YOUT ZOUT +3V CX CY CZ ADXL335 ~32kΩ ~32kΩ ~32kΩ CDC Figure 1.
- 61. ADXL335 Rev. 0 |Page 2 of 16 TABLE OF CONTENTS Features .............................................................................................. 1 Applications....................................................................................... 1 General Description......................................................................... 1 Functional Block Diagram .............................................................. 1 Revision History ............................................................................... 2 Specifications..................................................................................... 3 Absolute Maximum Ratings............................................................ 4 ESD Caution.................................................................................. 4 Pin Configuration and Function Descriptions............................. 5 Typical Performance Characteristics ............................................. 6 Theory of Operation ...................................................................... 10 Mechanical Sensor...................................................................... 10 Performance................................................................................ 10 Applications Information.............................................................. 11 Power Supply Decoupling......................................................... 11 Setting the Bandwidth Using CX, CY, and CZ.......................... 11 Self Test........................................................................................ 11 Design Trade-Offs for Selecting Filter Characteristics: The Noise/BW Trade-Off.......................................................... 11 Use with Operating Voltages Other than 3 V............................. 11 Axes of Acceleration Sensitivity ............................................... 12 Layout and Design Recommendations ................................... 13 Outline Dimensions....................................................................... 14 Ordering Guide .......................................................................... 14 REVISION HISTORY 1/09—Revision 0: Initial Version
- 62. ADXL335 Rev. 0 |Page 3 of 16 SPECIFICATIONS TA = 25°C, VS = 3 V, CX = CY = CZ = 0.1 µF, acceleration = 0 g, unless otherwise noted. All minimum and maximum specifications are guaranteed. Typical specifications are not guaranteed. Table 1. Parameter Conditions Min Typ Max Unit SENSOR INPUT Each axis Measurement Range ±3 ±3.6 g Nonlinearity % of full scale ±0.3 % Package Alignment Error ±1 Degrees Interaxis Alignment Error ±0.1 Degrees Cross-Axis Sensitivity1 ±1 % SENSITIVITY (RATIOMETRIC)2 Each axis Sensitivity at XOUT, YOUT, ZOUT VS = 3 V 270 300 330 mV/g Sensitivity Change Due to Temperature3 VS = 3 V ±0.01 %/°C ZERO g BIAS LEVEL (RATIOMETRIC) 0 g Voltage at XOUT, YOUT VS = 3 V 1.35 1.5 1.65 V 0 g Voltage at ZOUT VS = 3 V 1.2 1.5 1.8 V 0 g Offset vs. Temperature ±1 mg/°C NOISE PERFORMANCE Noise Density XOUT, YOUT 150 µg/√Hz rms Noise Density ZOUT 300 µg/√Hz rms FREQUENCY RESPONSE4 Bandwidth XOUT, YOUT 5 No external filter 1600 Hz Bandwidth ZOUT 5 No external filter 550 Hz RFILT Tolerance 32 ± 15% kΩ Sensor Resonant Frequency 5.5 kHz SELF-TEST6 Logic Input Low +0.6 V Logic Input High +2.4 V ST Actuation Current +60 μA Output Change at XOUT Self-Test 0 to Self-Test 1 −150 −325 −600 mV Output Change at YOUT Self-Test 0 to Self-Test 1 +150 +325 +600 mV Output Change at ZOUT Self-Test 0 to Self-Test 1 +150 +550 +1000 mV OUTPUT AMPLIFIER Output Swing Low No load 0.1 V Output Swing High No load 2.8 V POWER SUPPLY Operating Voltage Range 1.8 3.6 V Supply Current VS = 3 V 350 μA Turn-On Time7 No external filter 1 ms TEMPERATURE Operating Temperature Range −40 +85 °C 1 Defined as coupling between any two axes. 2 Sensitivity is essentially ratiometric to VS. 3 Defined as the output change from ambient-to-maximum temperature or ambient-to-minimum temperature. 4 Actual frequency response controlled by user-supplied external filter capacitors (CX, CY, CZ). 5 Bandwidth with external capacitors = 1/(2 × π × 32 kΩ × C). For CX, CY = 0.003 µF, bandwidth = 1.6 kHz. For CZ = 0.01 µF, bandwidth = 500 Hz. For CX, CY, CZ = 10 µF, bandwidth = 0.5 Hz. 6 Self-test response changes cubically with VS. 7 Turn-on time is dependent on CX, CY, CZ and is approximately 160 × CX or CY or CZ + 1 ms, where CX, CY, CZ are in microfarads (µF).
- 63. ADXL335 Rev. 0 |Page 4 of 16 ABSOLUTE MAXIMUM RATINGS Table 2. Parameter Rating Acceleration (Any Axis, Unpowered) 10,000 g Acceleration (Any Axis, Powered) 10,000 g VS −0.3 V to +3.6 V All Other Pins (COM − 0.3V) to (VS + 0.3V) Output Short-Circuit Duration (Any Pin to Common) Indefinite Temperature Range (Powered) −55°C to +125°C Temperature Range (Storage) −65°C to +150°C Stresses above those listed under Absolute Maximum Ratings may cause permanent damage to the device. This is a stress rating only; functional operation of the device at these or any other conditions above those indicated in the operational section of this specification is not implied. Exposure to absolute maximum rating conditions for extended periods may affect device reliability. ESD CAUTION
- 64. ADXL335 Rev. 0 |Page 5 of 16 PIN CONFIGURATION AND FUNCTION DESCRIPTIONS 07808-003 NOTES 1. EXPOSED PAD IS NOT INTERNALLY CONNECTED BUT SHOULD BE SOLDERED FOR MECHANICAL INTEGRITY. NC = NO CONNECT NC 1 ST 2 COM 3 NC 4 XOUT12 NC11 YOUT10 NC9 COM COM COM ZOUT 5 6 7 8 16 NC 15 VS 14 VS 13 NC ADXL335 TOP VIEW (Not to Scale) +Z +X +Y Figure 2. Pin Configuration Table 3. Pin Function Descriptions Pin No. Mnemonic Description 1 NC No Connect1 . 2 ST Self-Test. 3 COM Common. 4 NC No Connect1 . 5 COM Common. 6 COM Common. 7 COM Common. 8 ZOUT Z Channel Output. 9 NC No Connect1 . 10 YOUT Y Channel Output. 11 NC No Connect1 . 12 XOUT X Channel Output. 13 NC No Connect1 . 14 VS Supply Voltage (1.8 V to 3.6 V). 15 VS Supply Voltage (1.8 V to 3.6 V). 16 NC No Connect1 . EP Exposed Pad Not internally connected. Solder for mechanical integrity. 1 NC pins are not internally connected and can be tied to COM pins, unless otherwise noted.
- 65. ADXL335 Rev. 0 |Page 6 of 16 TYPICAL PERFORMANCE CHARACTERISTICS N > 1000 for all typical performance plots, unless otherwise noted. 50 0 10 20 30 40 1.42 1.44 1.46 1.48 1.50 1.52 1.54 1.56 1.58 %OFPOPULATION OUTPUT (V) 07808-005 Figure 3. X-Axis Zero g Bias at 25°C, VS = 3 V 50 0 10 20 30 40 1.42 1.44 1.46 1.48 1.50 1.52 1.54 1.56 1.58 %OFPOPULATION OUTPUT (V) 07808-006 Figure 4. Y-Axis Zero g Bias at 25°C, VS = 3 V 1.42 1.44 1.46 1.48 1.50 1.52 1.54 1.56 1.58 %OFPOPULATION OUTPUT (V) 07808-007 0 5 10 15 20 25 Figure 5. Z-Axis Zero g Bias at 25°C, VS = 3 V %OFPOPULATION VOLTS (V) 07808-008 0 10 20 30 40 –0.40 –0.38 –0.36 –0.34 –0.32 –0.30 –0.28 –0.26 Figure 6. X-Axis Self-Test Response at 25°C, VS = 3 V %OFPOPULATION VOLTS (V) 07808-009 0 10 20 30 50 40 0.26 0.28 0.30 0.32 0.34 0.36 0.38 0.40 Figure 7. Y-Axis Self-Test Response at 25°C, VS = 3 V %OFPOPULATION VOLTS (V) 07808-010 0 10 20 30 40 0.48 0.50 0.52 0.54 0.56 0.58 0.60 0.62 Figure 8. Z-Axis Self-Test Response at 25°C, VS = 3 V
- 66. ADXL335 Rev. 0 |Page 7 of 16 %OFPOPULATION TEMPERATURE COEFFICIENT (mg/°C) 0 5 10 15 20 25 30 –3.0 –2.5 –2.0 –1.5 –1.0 –0.5 0 0.5 1.0 1.5 2.0 2.5 3.0 07808-011 Figure 9. X-Axis Zero g Bias Temperature Coefficient, VS = 3 V %OFPOPULATION TEMPERATURE COEFFICIENT (mg/°C) 0 10 20 40 30 –3.0 –2.5 –2.0 –1.5 –1.0 –0.5 0 0.5 1.0 1.5 2.0 2.5 3.0 07808-012 Figure 10. Y-Axis Zero g Bias Temperature Coefficient, VS = 3 V %OFPOPULATION TEMPERATURE COEFFICIENT (mg/°C) 0 5 10 15 20 –7 –6 –5 –4 –3 –2 –1 0 1 2 3 4 5 6 7 07808-013 Figure 11. Z-Axis Zero g Bias Temperature Coefficient, VS = 3 V 1.45 1.46 1.47 1.48 1.49 1.50 1.51 1.52 1.53 1.54 1.55 –40 –30 –20 –10 0 10 20 30 40 50 60 70 80 90 100 N = 8 TEMPERATURE (°C) OUTPUT(V) 07808-014 Figure 12. X-Axis Zero g Bias vs. Temperature— Eight Parts Soldered to PCB 1.45 1.46 1.47 1.48 1.49 1.50 1.51 1.52 1.53 1.54 1.55 –40 –30 –20 –10 0 10 20 30 40 50 60 70 80 90 100 N = 8 TEMPERATURE (°C) OUTPUT(V) 07808-015 Figure 13. Y-Axis Zero g Bias vs. Temperature— Eight Parts Soldered to PCB 1.30 1.32 1.34 1.36 1.38 1.40 1.42 1.44 1.46 1.48 1.50 –40 –30 –20 –10 0 10 20 30 40 50 60 70 80 90 100 N = 8 TEMPERATURE (°C) OUTPUT(V) 07808-016 Figure 14. Z-Axis Zero g Bias vs. Temperature— Eight Parts Soldered to PCB
- 67. ADXL335 Rev. 0 |Page 8 of 16 %OFPOPULATION SENSITIVITY (V/g) 0 5 10 15 20 0.285 0.288 0.291 0.294 0.297 0.300 0.303 0.306 0.309 0.312 0.315 07808-017 Figure 15. X-Axis Sensitivity at 25°C, VS = 3 V %OFPOPULATION SENSITIVITY (V/g) 0 5 10 15 20 0.285 0.288 0.291 0.294 0.297 0.300 0.303 0.306 0.309 0.312 0.315 25 07808-018 Figure 16. Y-Axis Sensitivity at 25°C, VS = 3 V %OFPOPULATION SENSITIVITY (V/g) 0 5 10 15 20 0.285 0.288 0.291 0.294 0.297 0.300 0.303 0.306 0.309 0.312 0.315 25 07808-019 Figure 17. Z-Axis Sensitivity at 25°C, VS = 3 V 0.280 0.285 0.290 0.295 0.300 0.305 0.310 0.315 0.320 –40 –30 –20 –10 0 10 20 30 40 50 60 70 80 90 100 N = 8 TEMPERATURE (°C) SENSITIVITY(V/g) 07808-020 Figure 18.X-AxisSensitivityvs.Temperature— Eight PartsSolderedtoPCB,VS =3V 0.280 0.285 0.290 0.295 0.300 0.305 0.310 0.315 0.320 –40 –30 –20 –10 0 10 20 30 40 50 60 70 80 90 100 TEMPERATURE (°C) SENSITIVITY(V/g) N = 8 07808-021 Figure 19. Y-AxisSensitivityvs.Temperature— EightPartsSolderedtoPCB,VS =3V 0.280 0.285 0.290 0.295 0.300 0.305 0.310 0.315 0.320 –40 –30 –20 –10 0 10 20 30 40 50 60 70 80 90 100 TEMPERATURE (°C) SENSITIVITY(V/g) N = 8 07808-022 Figure 20. Z-Axis Sensitivity vs. Temperature— Eight Parts Soldered to PCB, VS = 3 V
- 68. ADXL335 Rev. 0 |Page 9 of 16 SUPPLY (V) CURRENT(µA) 0 100 200 300 400 500 600 1.5 2.0 2.5 3.0 3.5 4.0 07808-023 Figure 21. Typical Current Consumption vs. Supply Voltage TIME (1ms/DIV) CH4: ZOUT, 500mV/DIV CH3: YOUT, 500mV/DIV CH1: POWER, 1V/DIV CH2: XOUT, 500mV/DIV OUTPUTS ARE OFFSET FOR CLARITY 07808-024 Figure 22. Typical Turn-On Time, VS = 3 V
- 69. ADXL335 Rev. 0 |Page 10 of 16 THEORY OF OPERATION The ADXL335 is a complete 3-axis acceleration measurement system. The ADXL335 has a measurement range of ±3 g mini- mum. It contains a polysilicon surface-micromachined sensor and signal conditioning circuitry to implement an open-loop acceleration measurement architecture. The output signals are analog voltages that are proportional to acceleration. The accelerometer can measure the static acceleration of gravity in tilt-sensing applications as well as dynamic acceleration resulting from motion, shock, or vibration. The sensor is a polysilicon surface-micromachined structure built on top of a silicon wafer. Polysilicon springs suspend the structure over the surface of the wafer and provide a resistance against acceleration forces. Deflection of the structure is meas- ured using a differential capacitor that consists of independent fixed plates and plates attached to the moving mass. The fixed plates are driven by 180° out-of-phase square waves. Acceleration deflects the moving mass and unbalances the differential capacitor resulting in a sensor output whose amplitude is proportional to acceleration. Phase-sensitive demodulation techniques are then used to determine the magnitude and direction of the acceleration. The demodulator output is amplified and brought off-chip through a 32 kΩ resistor. The user then sets the signal bandwidth of the device by adding a capacitor. This filtering improves measurement resolution and helps prevent aliasing. MECHANICAL SENSOR The ADXL335 uses a single structure for sensing the X, Y, and Z axes. As a result, the three axes’ sense directions are highly orthogonal and have little cross-axis sensitivity. Mechanical misalignment of the sensor die to the package is the chief source of cross-axis sensitivity. Mechanical misalignment can, of course, be calibrated out at the system level. PERFORMANCE Rather than using additional temperature compensation circui- try, innovative design techniques ensure that high performance is built in to the ADXL335. As a result, there is no quantization error or nonmonotonic behavior, and temperature hysteresis is very low (typically less than 3 mg over the −25°C to +70°C temperature range).
- 70. ADXL335 Page 11 of16 APPLICATIONS INFORMATION POWER SUPPLY DECOUPLING For most applications, a single 0.1 µF capacitor, CDC, placed close to the ADXL335 supply pins adequately decouples the accelerometer from noise on the power supply. However, in applications where noise is present at the 50 kHz internal clock frequency (or any harmonic thereof), additional care in power supply bypassing is required because this noise can cause errors in acceleration measurement. If additional decoupling is needed, a 100 Ω (or smaller) resistor or ferrite bead can be inserted in the supply line. Additionally, a larger bulk bypass capacitor (1 µF or greater) can be added in parallel to CDC. Ensure that the connection from the ADXL335 ground to the power supply ground is low impedance because noise transmitted through ground has a similar effect to noise transmitted through VS. SETTING THE BANDWIDTH USING CX, CY, AND CZ The ADXL335 has provisions for band limiting the XOUT, YOUT, and ZOUT pins. Capacitors must be added at these pins to imple- ment low-pass filtering for antialiasing and noise reduction. The equation for the 3 dB bandwidth is F−3 dB = 1/(2π(32 kΩ) × C(X, Y, Z)) or more simply F–3 dB = 5 μF/C(X, Y, Z) The tolerance of the internal resistor (RFILT) typically varies as much as ±15% of its nominal value (32 kΩ), and the bandwidth varies accordingly. A minimum capacitance of 0.0047 μF for CX, CY, and CZ is recommended in all cases. Table 4. Filter Capacitor Selection, CX, CY, and CZ Bandwidth (Hz) Capacitor (µF) 1 4.7 10 0.47 50 0.10 100 0.05 200 0.027 500 0.01 SELF-TEST The ST pin controls the self-test feature. When this pin is set to VS, an electrostatic force is exerted on the accelerometer beam. The resulting movement of the beam allows the user to test if the accelerometer is functional. The typical change in output is −1.08 g (corresponding to −325 mV) in the X-axis, +1.08 g (or +325 mV) on the Y-axis, and +1.83 g (or +550 mV) on the Z-axis. This ST pin can be left open-circuit or connected to common (COM) in normal use. Never expose the ST pin to voltages greater than VS + 0.3 V. If this cannot be guaranteed due to the system design (for instance, if there are multiple supply voltages), then a low VF clamping diode between ST and VS is recommended. DESIGN TRADE-OFFS FOR SELECTING FILTER CHARACTERISTICS: THE NOISE/BW TRADE-OFF The selected accelerometer bandwidth ultimately determines the measurement resolution (smallest detectable acceleration). Filtering can be used to lower the noise floor to improve the resolution of the accelerometer. Resolution is dependent on the analog filter bandwidth at XOUT, YOUT, and ZOUT. The output of the ADXL335 has a typical bandwidth of greater than 500 Hz. The user must filter the signal at this point to limit aliasing errors. The analog bandwidth must be no more than half the analog-to-digital sampling frequency to minimize aliasing. The analog bandwidth can be further decreased to reduce noise and improve resolution. The ADXL335 noise has the characteristics of white Gaussian noise, which contributes equally at all frequencies and is described in terms of μg/√Hz (the noise is proportional to the square root of the accelerometer bandwidth). The user should limit bandwidth to the lowest frequency needed by the applica- tion to maximize the resolution and dynamic range of the accelerometer. With the single-pole, roll-off characteristic, the typical noise of the ADXL335 is determined by )1.6( ××= BWDensityNoiseNoiserms It is often useful to know the peak value of the noise. Peak-to- peak noise can only be estimated by statistical methods. Table 5 is useful for estimating the probabilities of exceeding various peak values, given the rms value. Table 5. Estimation of Peak-to-Peak Noise Peak-to-Peak Value % of Time That Noise Exceeds Nominal Peak-to-Peak Value 2 × rms 32 4 × rms 4.6 6 × rms 0.27 8 × rms 0.006 USE WITH OPERATING VOLTAGES OTHER THAN 3 V The ADXL335 is tested and specified at VS = 3 V; however, it can be powered with VS as low as 1.8 V or as high as 3.6 V. Note that some performance parameters change as the supply voltage is varied.
- 71. ADXL335 Rev. 0 |Page 12 of 16 The ADXL335 output is ratiometric, therefore, the output sensitivity (or scale factor) varies proportionally to the supply voltage. At VS = 3.6 V, the output sensitivity is typi- cally 360 mV/g. At VS = 2 V, the output sensitivity is typically 195 mV/g. The zero g bias output is also ratiometric, thus the zero g output is nominally equal to VS/2 at all supply voltages. The output noise is not ratiometric but is absolute in volts; therefore, the noise density decreases as the supply voltage increases. This is because the scale factor (mV/g) increases while the noise voltage remains constant. At VS = 3.6 V, the X-axis and Y-axis noise density is typically 120 µg/√Hz, whereas at VS = 2 V, the X-axis and Y-axis noise density is typically 270 μg/√Hz. Self-test response in g is roughly proportional to the square of the supply voltage. However, when ratiometricity of sensitivity is factored in with supply voltage, the self-test response in volts is roughly proportional to the cube of the supply voltage. For example, at VS = 3.6 V, the self-test response for the ADXL335 is approximately −560 mV for the X-axis, +560 mV for the Y-axis, and +950 mV for the Z-axis. At VS = 2 V, the self-test response is approximately −96 mV for the X-axis, +96 mV for the Y-axis, and −163 mV for the Z-axis. The supply current decreases as the supply voltage decreases. Typical current consumption at VS = 3.6 V is 375 µA, and typi- cal current consumption at VS = 2 V is 200 µA. AXES OF ACCELERATION SENSITIVITY AZ AY AX 07808-025 Figure 23. Axes of Acceleration Sensitivity; Corresponding Output Voltage Increases When Accelerated Along the Sensitive Axis. XOUT = –1g YOUT = 0g ZOUT = 0g GRAVITY XOUT = 0g YOUT = 1g ZOUT = 0g XOUT = 0g YOUT = –1g ZOUT = 0g XOUT = 1g YOUT = 0g ZOUT = 0g XOUT = 0g YOUT = 0g ZOUT = 1g XOUT = 0g YOUT = 0g ZOUT = –1g TOP TOP TOP TOP 07808-026 Figure 24. Output Response vs. Orientation to Gravity
- 72. ADXL335 Page 13 of16 LAYOUT AND DESIGN RECOMMENDATIONS The recommended soldering profile is shown in Figure 25 followed by a description of the profile features in Table 6. The recommended PCB layout or solder land drawing is shown in Figure 26. 07808-002 tP tL t25°C TO PEAK tS PREHEAT CRITICAL ZONE TL TO TP TEMPERATURE TIME RAMP-DOWN RAMP-UP TSMIN TSMAX TP TL Figure 25. Recommended Soldering Profile Table 6. Recommended Soldering Profile Profile Feature Sn63/Pb37 Pb-Free Average Ramp Rate (TL to TP) 3°C/sec max 3°C/sec max Preheat Minimum Temperature (TSMIN) 100°C 150°C Maximum Temperature (TSMAX) 150°C 200°C Time (TSMIN to TSMAX)(tS) 60 sec to 120 sec 60 sec to 180 sec TSMAX to TL Ramp-Up Rate 3°C/sec max 3°C/sec max Time Maintained Above Liquidous (TL) Liquidous Temperature (TL) 183°C 217°C Time (tL) 60 sec to 150 sec 60 sec to 150 sec Peak Temperature (TP) 240°C + 0°C/−5°C 260°C + 0°C/−5°C Time Within 5°C of Actual Peak Temperature (tP) 10 sec to 30 sec 20 sec to 40 sec Ramp-Down Rate 6°C/sec max 6°C/sec max Time 25°C to Peak Temperature 6 minutes max 8 minutes max EXPOSED PAD IS NOT INTERNALLY CONNECTED BUT SHOULD BE SOLDERED FOR MECHANICAL INTEGRITY. 0.50 MAX 0.65 0.325 1.95 0.65 0.325 4 4 0.35 MAX 1.95 DIMENSIONS SHOWN IN MILLIMETERS 07808-004 Figure 26. Recommended PCB Layout
- 73. ADXL335 Rev. 0 |Page 14 of 16 OUTLINE DIMENSIONS 111808-A 1 0.65 BSC BOTTOM VIEWTOP VIEW 16 58 9 12 13 4 EXPOSED PAD PIN 1 INDICATOR 2.55 2.40 SQ 2.25 0.55 0.50 0.45 SEATING PLANE 1.50 1.45 1.40 0.05 MAX 0.02 NOM 0.15 REF COPLANARITY 0.08 0.15 MAX PIN 1 INDICATOR 4.15 4.00 SQ 3.85 0.35 0.30 0.25 FOR PROPER CONNECTION OF THE EXPOSED PAD, REFER TO THE PIN CONFIGURATION AND FUNCTION DESCRIPTIONS SECTION OF THIS DATA SHEET. Figure 27. 16-Lead Lead Frame Chip Scale Package [LFCSP_LQ] 4 mm × 4 mm Body, 1.45 mm Thick Quad (CP-16-14) Dimensions shown in millimeters ORDERING GUIDE Model Measurement Range Specified Voltage Temperature Range Package Description Package Option ADXL335BCPZ1 ±3 g 3 V −40°C to +85°C 16-Lead LFCSP_LQ CP-16-14 ADXL335BCPZ–RL1 ±3 g 3 V −40°C to +85°C 16-Lead LFCSP_LQ CP-16-14 ADXL335BCPZ–RL71 ±3 g 3 V −40°C to +85°C 16-Lead LFCSP_LQ CP-16-14 EVAL-ADXL335Z1 Evaluation Board 1 Z = RoHS Compliant Part.
- 74. ADXL335 Page 15 of16 NOTES
- 75. ADXL335 Rev. 0 |Page 16 of 16 NOTES ©2009 Analog Devices, Inc. All rights reserved. Trademarks and registered trademarks are the property of their respective owners. D07808-0-1/09(0)
- 76. RN-42/RN-42-N Data Sheet www.rovingnetworks.comDS-RN42-V1.0 6/21/2011 809 University Avenue • Los Gatos, CA 95032 • Tel (408) 395-6539 • info@RovingNetworks.com ~ 1 ~ Class 2 Bluetooth® Module Features Fully qualified Bluetooth 2.1/2.0/1.2/1.1 module Bluetooth v2.0+EDR support Available with on board chip antenna (RN- 42) and without antenna (RN-42-N) Postage stamp sized form factor, 13.4mm x 25.8 mm x 2mm (RN-42) and 13.4mm x 20 mm x 2 mm (RN-42-N) Low power (26uA sleep, 3mA connected, 30mA transmit) UART (SPP or HCI) and USB (HCI only) data connection interfaces. Sustained SPP data rates - 240Kbps (slave), 300Kbps (master) HCI data rates - 1.5Mbps sustained, 3.0Mbps burst in HCI mode Embedded Bluetooth stack profiles included (requires no host stack): GAP, SDP, RFCOMM and L2CAP protocols, with SPP and DUN profile support. Bluetooth SIG certified Castellated SMT pads for easy and reliable PCB mounting Certifications: FCC, ICS, CE Environmentally friendly, RoHS compliant Applications Cable replacement Barcode scanners Measurement and monitoring systems Industrial sensors and controls Medical devices Barcode readers Computer accessories Description The RN42 is a small form factor, low power, highly economic Bluetooth radio for OEM’s adding wireless capability to their products. The RN42 supports multiple interface protocols, is simple to design in and fully certified, making it a complete embedded Bluetooth solution. The RN 42 is functionally compatible with RN 41. With its high performance on chip antenna and support for Bluetooth® Enhanced Data Rate (EDR), the RN42 delivers up to 3 Mbps data rate for distances to 20M. The RN-42 also comes in a package with no antenna (RN-42-N). Useful when the application requires an external antenna, the RN-42-N is shorter in length and has RF pads to route the antenna signal. Block Diagram CSR BlueCore-04 External BALUNPA RF Switch Crystal Flash Memory GND VCC USB UART PCM PIO6 PIO5 PIO4
- 77. RN-42/RN-42-N Data Sheet www.rovingnetworks.comDS-RN42-V3.2 6/21/2011 809 University Avenue • Los Gatos, CA 95032 • Tel (408) 395-6539 • info@RovingNetworks.com ~ 2 ~ Overview Baud rate speeds: 1200bps up to 921Kbps, non-standard baud rates can be programmed. Class 2 radio, 60 feet (20meters) distance, 4dBm output transmitter, -80dBm typical receive sensitivity Frequency 2402 ~ 2480MHz, FHSS/GFSK modulation, 79 channels at 1MHz intervals Secure communications, 128 bit encryption Error correction for guaranteed packet delivery UART local and over-the-air RF configuration Auto-discovery/pairing requires no software configuration (instant cable replacement). Auto-connect master, IO pin (DTR) and character based trigger modes Digital I/O Characteristics 2.7V ≤ VDD ≤ 3.0V Min Typ. Max. Unit Input logic level LOW -0.4 - +0.8 V Input logic level HIGH 0.7VDD - VDD+0.4 V Output logc level LOW - - 0.2 V Output logic level HIGH VDD-0.2 - - V All I/O’s (except reset) default to weakpull down +0.2 +1.0 +5.0 uA Environmental Conditions Parameter Value Temperature Range (Operating) -40 o C ~ 85 o C Temperature Range (Storage) -40 o C ~ 85 o C Relative Humidity (Operating) 90% Relative Humidity (Storage) 90% Electrical Characteristics Parameter Min Typ. Max. Unit Supply Voltage (DC) 3.0 3.3 3.6 V Average power consumption Radio ON* (Discovery or Inquiry window time) 40 mA Connected Idle (No Sniff) 25 mA Connected Idle (Sniff 100 milli secs) 12 mA Connected with data transfer 40 45 50 mA Deep Sleep Idle mode 26 uA * If in SLAVE mode there are bursts of radio ON time which vary with the windows. Depending on how you set the windows that determines your average current.
- 78. RN-42/RN-42-N Data Sheet www.rovingnetworks.comDS-RN42-V3.2 6/21/2011 809 University Avenue • Los Gatos, CA 95032 • Tel (408) 395-6539 • info@RovingNetworks.com ~ 3 ~ Radio Characteristics Parameter Freq. (GHz) Min Typ Max Bluetooth Specification Units Sensitivity @ 0.1%BER 2.402 - -80 -86 ≤ -70 dBm 2.441 - -80 -86 dBm 2.480 - -80 -86 dBm RF Transmit Power 2.402 0 2 4 ≤ 4 dBm 2.441 0 2 4 dBm 2.480 0 2 4 dBm Initial Carrier Frequency Tolerance 2.402 - 5 75 75 kHz 2.441 - 5 75 kHz 2.480 - 5 75 kHz 20dB bandwidth for modulated carrier - 900 1000 ≤ 1000 kHz Drift (Five slots packet) - 15 - 40 kHz Drift Rate - 13 - 20 kHz ∆f1avg Max Modulation 2.402 140 165 175 >140 kHz 2.441 140 165 175 kHz 2.480 140 165 175 kHz ∆f2avg Min Modulation 2.402 140 190 - 115 kHz 2.441 140 190 - kHz 2.480 140 190 - kHz Range Characteristics (Approximate range in office environment) Range RN-42 After One Wall 55 feet After Two Walls 60 feet After Three Walls 36 feet The above readings are approximate and may vary depending upon the RF environment. Bluetooth hops in a pseudo-random fashion over the 79 frequencies in the ISM band to adapt to the interference. Data throughput and range vary depending on the RF interference environment.
- 79. RN-42/RN-42-N Data Sheet www.rovingnetworks.comDS-RN42-V3.2 6/21/2011 809 University Avenue • Los Gatos, CA 95032 • Tel (408) 395-6539 • info@RovingNetworks.com ~ 4 ~ Pin Description Pin Name Description Default Voltage 1 GND 0V 2 SPI MOSI Programming only No Connect 3V 3 PIO6 Set BT master (HIGH=auto-master mode) Input to RN42with weak pulldown 0V-3.3V 4 PIO7 Set Baud rate (HIGH = force 9600, LOW = 115K or firmware setting) Input to RN42 with weak pulldown 0V-3.3V 5 RESET Active LOW reset Input to RN42 with 1K pullup 6 SPI_CLK Programming only No Connect 7 PCM_CLK PCM interface No Connect 8 PCM_SYNC PCM interface No Connect 9 PCM_IN PCM interface No Connect 10 PCM_OUT PCM interface No Connect 11 VDD 3.3V regulated power input 12 GND 13 UART_RX UART receive Input Input to RN42 0V-3.3V 14 UART_TX UART transmit output High level output from RN42 0V-3.3V 15 UART_RTS UART RTS, goes HIGH to disable host transmitter Low level output from RN42 0V-3.3V 16 UART_CTS UART CTS, if set HIGH, disables transmitter Low level input to RN42 0V-3.3V 17 USB_D+ USB port Pull up 1.5K when active 0V-3.3V 18 USB_D- USB port 0V-3.3V 19 PIO2 Status, HIGH when connected, LOW otherwise Output from RN42 0V-3.3V 20 PIO3 Auto discovery = HIGH Input to RN42 with weak pulldown 0V-3.3V 21 PIO5 Status, toggles based on state, LOW on connect Output from RN42 0V-3.3V 22 PIO4 Set factory defaults Input to RN42 with weak pulldown 0V-3.3V 23 SPI_CSB Programming only No Connect 24 SPI_MISO Programming only No Connect 25 GND GND for RN42-N 26 RF Pad RF Pad for RN42-N 27 GND GND for RN42-N 30 AIO0 Optional analog input Not Used 31 PIO8 Status (RF data rx/tx) Output from RN42 0V-3.3V 32 PIO9 IO Input to RN42 with weak pulldown 0V-3.3V 33 PIO10 IO (remote DTR signal) Input to RN42 with weak pulldown 0V-3.3V 34 PIO11 IO (remote RTS signal ) Input to RN42 with weak pulldown 0V-3.3V 35 AIO1 Optional analog input Not Used 1 2 3 4 5 6 7 8 9 10 11 12 GND SPIMOSI PIO6 PIO7 RESET SPI_CLOCK PCM_CLK PCM_SYNC PCM_IN PCM_OUT VDD GND 24 23 22 21 20 19 18 17 16 15 14 13 SPI_MOSI SPI_CSB PIO4 PIO5 PIO3 PIO2 USB_D- USB_D+ UART_CTS UART_RST UART_TX UART_RX RN-42 AIO1 GND PIO11 PIO10 PIO9 PIO8 GND AIO0 35 29 34 33 32 31 28 30 SPI_MISO UART_RTS 1 2 3 4 5 6 7 8 9 10 11 12 GND SPIMOSI PIO6 PIO7 RESET SPI_CLOCK PCM_CLK PCM_SYNC PCM_IN PCM_OUT VDD GND 24 23 22 21 20 19 18 17 16 15 14 13 SPI_MOSI SPI_CSB PIO4 PIO5 PIO3 PIO2 USB_D- USB_D+ UART_CTS UART_RST UART_TX UART_RX RN-42-N AIO1 GND PIO11 PIO10 PIO9 PIO8 GND AIO0 35 29 34 33 32 31 28 30 GND RFPAD GND 27 26 25 SPI_MISO UART_RTS
- 80. RN-42/RN-42-N Data Sheet www.rovingnetworks.comDS-RN42-V3.2 6/21/2011 809 University Avenue • Los Gatos, CA 95032 • Tel (408) 395-6539 • info@RovingNetworks.com ~ 5 ~ Typical Application Circuit Since the RN 41 and RN 42 are functionally compatible, this application diagram applies to RN 41 and RN 42.
- 81. RN-42/RN-42-N Data Sheet www.rovingnetworks.comDS-RN42-V3.2 6/21/2011 809 University Avenue • Los Gatos, CA 95032 • Tel (408) 395-6539 • info@RovingNetworks.com ~ 6 ~ RN-42 Module Dimensions NOTE: All dimensions are in mm
- 82. RN-42/RN-42-N Data Sheet www.rovingnetworks.comDS-RN42-V3.2 6/21/2011 809 University Avenue • Los Gatos, CA 95032 • Tel (408) 395-6539 • info@RovingNetworks.com ~ 7 ~ RN-42-N Module Dimensions NOTE: All dimensions are in mm
- 83. RN-42/RN-42-N Data Sheet www.rovingnetworks.comDS-RN42-V3.2 6/21/2011 809 University Avenue • Los Gatos, CA 95032 • Tel (408) 395-6539 • info@RovingNetworks.com ~ 8 ~ Design Concerns 1.Reset circuit. RN-42 contains a weak pullup to VCC, the polarity of reset on the RN42 is ACTIVE LOW. A power on reset circuit with delay is OPTIONAL on the reset pin of the module. It should only be required if the input power supply has a very slow ramp, or tends to bounce or have instability on power up. Often a microcontroller or embedded CPU IO is available to generate reset once power is stable. If not, there are many low cost power supervisor chips available, such as MCP809, MCP102/121, and Torex XC61F. 2.Factory reset PIO4. It is a good idea to connect this pin to a switch, or jumper, or resistor, so it can be accessed. This pin can be used to reset the module to FACTORY DEFAULTS and is often critical in situations where the module has been mis-configured. To set Factory defaults start HIGH, then toggle two times. 3.Connection status. PIO5 is available to drive an LED, and blinks at various speeds to indicate status. PIO2 is an output which directly reflects the connection state, it goes HIGH when connected, and LOW otherwise. 4.HCI mode. The RN42 module must be loaded with special firmware to run in HCI mode. When in HCI mode the standard SPP/DUN applications are disabled. 5.Using SPI bus for flash upgrade. While not required, this bus is very useful for configuring advanced parameters of the Bluetooth modules, and is required for upgrading the firmware on modules. The suggested ref-design shows a 6pin header which can be implemented to gain access to this bus. A minimum-mode version could just use the SPI signals (4pins) and pickup ground and VCC from elsewhere on the design. 6.Minimizing Radio interference. When laying out the carrier board for the RN42 module the areas under the antenna and shielding connections should not have surface traces, GND planes, or exposed vias. (See diagram to right) For optimal radio performance the antenna end of RN42 module should protrude 5mm past any metal enclosure.
- 84. RN-42/RN-42-N Data Sheet www.rovingnetworks.comDS-RN42-V3.2 6/21/2011 809 University Avenue • Los Gatos, CA 95032 • Tel (408) 395-6539 • info@RovingNetworks.com ~ 9 ~ 7.Antenna Design. The pattern from the rf_out terminal pad should be designed with 50ohms impedance and traced with straight lines. (see diagram to the right) The rf_out signal line should not run under of near the RN21 module. The GND plane should be on the side of the PCB which the module is mounted. The GND should be reinforced with through-hole connections and other means to stabilize the electric potential. 8.Soldering Reflow Profile. Lead-Free Solder Reflow Temp: 230 degree C, 30-40 seconds, Peak 250 degree C maximum. Preheat temp: 165 +- 15 degree C, 90 to 120 seconds. Time: Single Pass, One Time Compliance Information Category Country Standard Radio USA FCC Part 15 Subpart B: 2008 Class B FCC CRF Title 47 Part 15 Subpart C FCC ID: T9J-RN42 EUROPE ETSI EN 301 489-1 V1.8.1 ETSI EN 301 489-17 V2.1.1 ETSI EN 300 328 V1.7.1 CANADA IC RSS-210 low power comm. device Certification Number: 6514A-RN42 EMC USA FCC CFR47 Part 15 subclass B EUROPE EN 55022 Class B radiated EN61000-4-2 ESD immunity EN61000-4-3 radiated field EN61000-4-6 RF immunity EN61000-4-8 power magnetic immunity Bluetooth BQB LISTED B014867- SPP and DUN profiles Environmental RoHS RoHS compliant Ordering Information Part Number Description RN-42 Standard Application firmware (SPP/DUN Master and Slave) RN-42-H HCI firmware (HCI over H4 UART) RN-42-U USB firmware (HCI over USB port, slave device at 12Mbps rate) RN-42-N No Antenna, Standard Application firmware (SPP/DUN Master and Slave) For other configurations, contact Roving Networks directly. Visit http://www.rovingnetworks.com/buynow.php for current pricing and a list of distributors carrying our products. RN21 Module GND RF_OUT GND RN21 Module GND RF_OUT GND
- 85. RN-42/RN-42-N Data Sheet www.rovingnetworks.comDS-RN42-V3.2 6/21/2011 809 University Avenue • Los Gatos, CA 95032 • Tel (408) 395-6539 • info@RovingNetworks.com ~ 10 ~ Copyright © 2011 Roving Networks. All rights reserved. The Bluetooth trademark and logo are registered trademarks and are owned by the Bluetooth SIG, Inc. All other trademarks are property of their respective owners. Roving Networks reserves the right to make corrections, modifications, and other changes to its products, documentation and services at any time. Customers should obtain the latest relevant information before placing orders and should verify that such information is current and complete. Roving Networks assumes no liability for applications assistance or customer product design. Customers are responsible for their products and applications using Roving Networks components. To minimize the risks associated with customer products and applications, customers should provide adequate design and operating safeguards. Roving Networks products are not authorized for use in safety-critical applications (such as life support) where a failure of the Roving Networks product would reasonably be expected to cause severe personal injury or death, unless officers of the parties have executed an agreement specifically governing such use.
- 86. Appendix B: EconomicAnalysis Table 6: Cost Analysis for Prototype Design Table 7: Estimated Labor Hours Cost for One Prototype Parts & Manufacturing Processes Individual Cost Quantity Total Conductive Thread (Thin) (1 foot) 0.21 10 2.1 Conductive Fabric - 12"x13" MedTex180 16.96 1 16.96 Triple Axis Accelerometer Breakout - ADXL335 14.95 1 14.95 Arduino Pro Mini 328 - 3.3V 8Mhz 9.96 1 9.96 Polymer Lithim Ion Battery - 1000mAh 8.96 1 8.96 SparkFun Bluetooth Mate Gold 34.95 1 34.95 Single Row Flat Header Socket Connector (400 ct) 0.01 22 0.22 Sleeveless Compression Shirt 12.90 1 12.9 AD620 Differential Amplifier 4.82 1 4.82 Various Resistors 0.02 3 0.06 3-D Printing 5.00 Stitching 10.00 Pass Through Fee x 1.05 Total 126.924 Labor Hours Position Hours Salary ($/hr) Additional Costs Total Income Project Manager 60 66 3960 Design Engineer 60 57 3420 Hardware Engineer 80 48 3840 Software Engineer 160 40 6400 Test Engineer 10 36 360 Technical Writer 96 30 2880 Sub-Total 20860 Contract Cost x 2.8 Total 58408 of38 58
- 87. Table 8: LargeScale Manufacturing Costs Large Scale Manufacturing Costs Parts & Manufacturing Individual Cost ($) Quantity Total Conductive Thread (Thin) (1 foot) 0.17 10 1.7 Conductive Fabric - 12"x13" MedTex180 15.96 1 15.96 Triple Axis Accelerometer Breakout - ADXL335 11.96 1 11.96 Arduino Pro Mini 328 - 3.3V 8Mhz 7.96 1 7.96 Polymer Lithim Ion Battery - 1000mAh 8.95 1 8.95 SparkFun Bluetooth Mate Gold 19.96 1 19.96 Single Row Flat Header Socket Connector (400 ct) 0.08 22 1.76 Sleeveless Compression Shirt 10.00 1 10 AD620 Differential Amplifier 4.09 1 4.09 Various Resistors 0.01 3 0.03 Sub-Total (x1000) 82370 Manufacturing Costs 20 per hour 65 1300 Software Testing 15 per hour 30 450 Labor Multiplier x 2 Packaging 1.75 1000 1750 Overhead Costs x 1.4 Profit (fee) x 1.2 Total 285583.2 Cost Per Product 285.5832 of39 58
- 88. Table 9: Actualand Estimated Weekly Burn Rate Economic Analysis Week Labor Cost (per week in $) Project Manager Labor Cost (per week in $) Design Engineer Labor Cost (per week in $) Hardware Engineer Labor Cost (per week in $) Software Engineer Labor Cost (per week in $) Test Engineer Labor Cost (per week in $) Technical Writer Lump Sum Expenditures Total Weekly Burn Rate Cumulative Expenditures 0 396 0 0 0 0 900 0 1296 1296 1 396 855 0 0 0 0 51.63 1302.63 2598.63 2 396 855 480 400 180 0 72.33 2383.33 4981.96 3 396 342 0 320 360 0 57.49 1475.49 6457.45 4 396 342 0 400 360 900 0 2398 8855.45 5 396 171 96 80 180 0 79.02 1002.02 9857.47 6 396 342 96 120 180 0 0 1134 10991.47 7 396 855 480 80 180 0 12.90 2003.9 12995.37 8 396 855 480 80 180 0 5.28 1996.28 14991.65 9 396 912 240 360 180 0 21.70 2109.7 17101.35 10 396 171 96 360 108 0 0 1131 18232.35 11 396 171 96 40 108 1080 0 1891 20123.35 12 396 171 96 40 0 0 0 703 20826.35 13 396 171 480 40 0 0 0 1087 21913.35 14 396 855 480 120 0 1080 50.00 2981 24894.35 15 396 171 240 400 180 180 0 1567 26461.35 16 396 342 0 400 180 180 0 1498 27959.35 17 396 0 0 400 360 180 0 1336 29295.35 18 396 171 240 360 360 180 0 1707 31002.35 19 396 855 480 0 108 180 60.00 2079 33081.35 20 396 342 480 0 108 180 50.00 1556 34637.35 21 396 171 240 400 0 180 0 1387 36024.35 22 396 171 240 400 0 180 15.00 1402 37426.35 23 396 171 0 360 360 180 100.00 1567 38993.35 24 396 0 0 360 360 900 0 2016 41009.35 25 396 0 0 0 360 900 0 1656 42665.35 of40 58
- 89. Figure 7: Actualand Estimated Weekly Burn Rate of41 58
- 90. Part Number Descriptio n Manufactu rer Manufactu rer’s Part Number Supplier Name Supplier’s Catalog Number Cost LMC7101 LowPower Single Supply Op Amp Texas Instruments LMC7101BI M5 Texas Instruments SNOS719F $0.36 per unit AD620 Low Power Differential Amplifier Analog Devices AD620 Analog Devices C00775–0– 7/11(H) $4.09 per unit MedTex 180 Conductive Fabric Shieldex 1101301180 Sparkfun DEV-10055 $15.96 per unit for 1000+ units TM-V05- WS_S Sleeveless Compressio n Shirt Tesla Gears TM-V05- WS_S Amazon B00HYDUN SK $12.9 per unit a11090900u x0280 10 Pcs Single Row Flat Header 40 Pins Socket Connector Smart Fly a11090900u x0280 Amazon B007Q84C4 O $3.45 per unit ADXL335 3-Axis Acceleromet er Analog Devices D07808-0-1/ 09(0) Sparkfun SEN-09269 $14.95 per unit VN 14/2X90/175 S/316L Conductive Thread Bexinox VN 14/2X90/175 S/316L Sparkfun DEV-10118 $7.16 per unit for 100+ units ERJ-6ENF30 11V 3.01 kΩ Resistor Panasonic ERJ-6ENF30 11V Texas Instruments ERJ-6ENF30 11V $0.01 per unit ERJ-6ENF10 71V 1.07 kΩ Resistor Panasonic ERJ-6ENF10 71V Texas Instruments ERJ-6ENF10 71V $0.01 per unit ERJ-6ENF12 11V 1.21 kΩ Resistor Panasonic ERJ-6ENF12 11V Texas Instruments ERJ-6ENF12 11V $0.01 per unit TAP105K025 SCS-VP 1 uF Capacitor Tantalum TAP105K025 SCS-VP Jameco TAP105K025 SCS-VP $0.17 per unit for 1000+ units 027-326 2.7 µF Capacitor Dayton Audio 844632018114Parts Express 844632018114$0.24 per unit for 1000+ units PRT-00339 Polymer Lithium Ion Battery - 1000mAh Great Power Battery Co, Ltd P-1S5045BC Sparkfun PRT-00339 $7.61 per unit Part Number of42 58
- 91. Table 10: Billof Materials PRT-00339 Bluetooth Mate Silver Roving Networks RN-42 Sparkfun PRT-00339 $24.95 per unit WRL-09434 Bluetooth USB Module Mini Konig CMP- BLUEKEY31 Sparkfun WRL-09434 $10.95 per unit DEV-11114 Arduino Pro Mini 328 - 3.3V/8MHz Sparkfun DEV-11114 Sparkfun DEV-11114 $9.95 per unit DEV-10116 Arduino Fio Sparkfun DEV-10116 Sparkfun DEV-10116 $24.95 per unit Descriptio n Manufactu rer Manufactu rer’s Part Number Supplier Name Supplier’s Catalog Number CostPart Number Module Function Call to Module Calls From Modules Estimated Lines of Code Estimated Time To Code and test Estimated cost to design, test, and code ECG Algorithm Determine User Heart Rate N/A N/A 70 Acceleromet er Algorithm Determine User Acceleration and Steps Taken N/A N/A 50 Distance Traveled Algorithm Determine User Distance Traveled GUI Subsystem Module N/A 80 Energy Expended Algorithm Determine User Energy Expended GUI Subsystem Module N/A 100 Module of43 58
- 92. Table 11: SoftwareParts List Wireless Connectivity Algorithm Form a wireless serial connection with a Bluetooth compatible device GUI Subsystem Module GUI Subsystem Module 20 Function Call to Module Calls From Modules Estimated Lines of Code Estimated Time To Code and test Estimated cost to design, test, and code Module of44 58
- 93. Appendix C: ProjectTimeline & Milestones (AH) Figure 8: Gantt Chart Part 1 Figure 9: Gantt Chart Part 2 of45 58
- 94. Figure 10: GanttChart Part 3 Figure 11: Gantt Chart Part 4 of46 58
- 95. Appendix D: ModuleMatrices Table 12: Module Matrix for Sensor Integration Sub-System Table 13: Module Matrix for Data Processing Sub-System Table 14: Module Matrix for GUI Design Sub-System Module Estimated Hours Total Hours Completion Research 14.25 15 95% Design 18 20 90% Implementation 20 25 80% Testing 12.5 25 50% Documentation 9 10 90% Module Estimated Hours Total Hours Completion Research 15 20 75% Design 8.4 12 70% Implementation 12 30 40% Testing 8 20 40% Documentation 8 10 80% Module Estimated Hours Total Hours Completion Research 12.75 15 85% Design 8.25 15 55% Implementation 15 25 60% Testing 15 30 50% Documentation 8.5 10 85% of47 58
- 96. Appendix D: SystemDiagrams " Figure 12: Overall System Design Figure 12 shows the integration of all three subsystems in one diagram. Analog signals from the body are detected by three sensors. The ECG and respiration sensor go through analog low pass filters and then all three sensors send their signals to a micro- controller for processing. After the signals have been digitized and analyzed, the output data is sent to a Bluetooth transmitter which sends the signal wirelessly to the user’s mobile device. Vcc is a regulated 3.3 V power supply which is supplied by the 3.7 V Li-Po battery plugged into the micro-controller. of48 58
- 97. Figure 13: ArduinoPro Mini Schematic of49 58
- 98. Appendix E: MechanicalDrawings (AH) Figure 14: Housing 3-D Model Figure 15: Housing Schematic (Bottom Piece) 2.00 R2.15 R.40TOP 3.49 .35 R.10 .20 .15 RIGHT R.01 .04 R.10 R.06 .35 DETAIL A RIGHT SCALE 4 : 1 .35 2.00 .20 .15 R.10 FRONT LEFT DO NOT SCALE DRAWING Bottom Drawing SHEET 1 OF 1 UNLESS OTHERWISE SPECIFIED: SCALE: 1:1 WEIGHT: REVDWG. NO. A SIZE TITLE: NAME DATE COMMENTS: Q.A. MFG APPR. ENG APPR. CHECKED DRAWN FINISH MATERIAL INTERPRET GEOMETRIC TOLERANCING PER: DIMENSIONS ARE IN INCHES TOLERANCES: FRACTIONAL ANGULAR: MACH BEND TWO PLACE DECIMAL THREE PLACE DECIMAL APPLICATION USED ONNEXT ASSY PROPRIETARY AND CONFIDENTIAL THE INFORMATION CONTAINED IN THIS DRAWING IS THE SOLE PROPERTY OF <INSERT COMPANY NAME HERE>. ANY REPRODUCTION IN PART OR AS A WHOLE WITHOUT THE WRITTEN PERMISSION OF <INSERT COMPANY NAME HERE> IS PROHIBITED. 5 4 3 2 1 of50 58
- 99. Figure 16: HousingSchematic (Top Piece) of51 58 2.00 R2.05 2.34 R.50 1.80 TOP 3.39 .10 R.10 2.82 2.34 2.00 R.10 1.80 A R.01 R.06 .04 R.10 DETAIL A LEFT SCALE 8 : 1 FRONT DO NOT SCALE DRAWING Top Drawing SHEET 1 OF 1 UNLESS OTHERWISE SPECIFIED: SCALE: 1:1 WEIGHT: REVDWG. NO. A SIZE TITLE: NAME DATE COMMENTS: Q.A. MFG APPR. ENG APPR. CHECKED DRAWN FINISH MATERIAL INTERPRET GEOMETRIC TOLERANCING PER: DIMENSIONS ARE IN INCHES TOLERANCES: FRACTIONAL ANGULAR: MACH BEND TWO PLACE DECIMAL THREE PLACE DECIMAL APPLICATION USED ONNEXT ASSY PROPRIETARY AND CONFIDENTIAL THE INFORMATION CONTAINED IN THIS DRAWING IS THE SOLE PROPERTY OF <INSERT COMPANY NAME HERE>. ANY REPRODUCTION IN PART OR AS A WHOLE WITHOUT THE WRITTEN PERMISSION OF <INSERT COMPANY NAME HERE> IS PROHIBITED. 5 4 3 2 1
- 100. Appendix F: ProgramFlow Diagrams (WG: 75%, LP: 25%) " Figure 17: Mobile Device Flow Diagram of52 58
- 101. Figure 18: OverallMicro-ControllerSoftware Flow Diagram The micro-controller will digitize all of the analog data from the sensors. It will then filter data, and ensure calibration has been completed. Finally, the micro- controller processes the data, and analyzes it. Two modes of operation have been programmed into the micro-controller. In sleep mode, the micro-controller will wait for the user to begin a new session. Once the user begins a new session, the device enters active mode, in which it constantly transmits the processed data wirelessly to a compatible bluetooth device. of53 58
- 102. Figure 19: ECGSoftware Flowchart An algorithm was written to determine a user’s heart rate based upon their filtered ECG waveform. The program works through the utilization of an internal clock, and the incrementing of a counter every time the algorithm encounters an R-wave. The R-wave was utilized because it is the most easily differentiated from the rest of the PQRST waveform, due to it’s large amplitude. The occurrence of an R-wave is interpreted to be a heartbeat. The filtered ECG signal is first digitized through the use of an analog to digital converter. Then, the algorithm checks to see if calibration has been completed. If uncalibrated, the amplitude of an R-wave is taken by using the max function, and then set to be equal to a floating variable. A threshold is then set a standardized value below the max. Once the calibration condition has been met, the algorithm compares current value to the threshold value. If the current value is equal to or greater than the threshold, a temporary variable is set to a value of one. In the other case, if the current value is less than the threshold, and second temporary variable is set equal to one, a counter is incremented and the first temporary variable is set back to zero. Every six seconds, a variable storing the calculated value of BPM is set equal to the count*10. Count is then set back to zero, along with the internal clock. The value of BPM is constantly printed wirelessly via a bluetooth serial connection in active mode. of54 58
- 103. Figure 20: AccelerometerSoftware Flow Diagram First, the algorithm digitizes the analog accelerometer data, through the use of an analog to digital converter. The magnitude of the acceleration vector is then determined. The algorithm then checks to see if the calibration condition has been met. If uncalibrated, based upon the max amplitude of the overall acceleration vector, a threshold is set a standardized integer below the max value. Two other variables are declared; one to count the encountered peaks, and one to check if the current value is over the threshold. The step counter is only incremented when two peaks have been encountered, and the current value is under the threshold. The two variables are then reinitialized to zero after each cycle. In active mode, the number of steps taken is transmitted wirelessly to a bluetooth compatible device. of55 58
- 104. Figure 21: RespirationRateSoftware Flowchart First, the algorithm digitizes the stretch sensor output. Then, a low pass filter is applied to filter out unwanted high frequencies. The first derivative of the data is then taken. The previous value of the derivative is stored as a variable called previous, and the current value of the derivative is stored as a variable called current. If the previous value is positive, and the current value is negative, that corresponds to an inhalation, and therefore the inhalation counter is incremented. The value of inhalation counter is recorded over a set interval of time. Through the use an internal clock, the user’s respiration rate can be determined. In active mode, the processed data is continually transmitted to a bluetooth compatible device. of56 58
- 105. Appendix G: ComponentComparisons and Other Useful Tables Table 15: Energy Expenditure Relations Table 16: Battery Selection Table 17: Wireless Modem Selection Metabolic Equivalent (MET) Activity Description Theoretical Steps Per Second 1 Sitting Resting Metabolic Rate 0 1.2 Standing Standing Quietly 0.2 2.5 - 3 Walking Slowly 2-2.5 mph 1-1.3 3.5 - 4 Walking Moderately 3-3.5 mph 1.4-1.7 4 - 6 Walking Fast 4-5 mph 1.7-2 7 - 8 Jogging 4-5 mph 1.8-2.2 9 - 11 Running Slowly 5.2-6.7 mph 2.5-2.8 11 - 14 Running Moderately 7-8.6 mph 2.8-3.3 15 - 18 Sprinting 9-11 mph 3.5-4 Battery Lithium Polymer Ion Coin Cell Nickel Hydride Volume (in3) 0.6 0.061 0.6 Capacity (mAh) 1000 250 2500 Nominal Cell Voltage (V) 3.7 3 1.2 Price ($) $8.96 $1.95 $2.95 Modem Bluetooth Mate Gold Bluetooth Mate Silver XBee PCB Antenna - Series 2 Range (m) 100 10 125 Dimensions (in) 1.75 x .65 1.75 x .65 0.960 x 1.087 Current Consumption (mA) 25 25 40 Operating Voltage (V) 3.3-6 3.3-6 3.3 Price ($) 34.95 24.95 25.95 of57 58
- 106. References 1 Wasik, Bill."Why Wearable Tech Will Be as Big as the Smartphone | WIRED." Wired.com. Conde Nast Digital, 15 Dec. 0013. Web. 15 Nov. 2014. Narwal, Lally. "Moto 360: Choose a Watch That Fits Your Style." Web log post. The Official2 Motorola Blog. N.p., 6 Nov. 2014. Web. 17 Nov. 2014. "Mobihealthnews." Mobihealthnews RSS. N.p., n.d. Web.3 "Health-Monitoring Devices Market Outpaces Telehealth." InformationWeek. N.p., n.d. Web.4 "School of Health Sciences." Role of the ECG Machine. N.p., n.d. Web.5 Pandian, P. S., K. Mohanavelu, and K. P. Safeer. "Smart Vest: Wearable Multi-parameter6 Remote Physiological Monitoring System."ResearchGate. N.p., n.d. Web. "How to Choose the Best Fitness Fabric for Workout Clothing American Fitness Couture."7 American Fitness Couture. N.p., n.d. Web. 29 Sept. 2014. Madias, JE. "Result Filters." National Center for Biotechnology Information. U.S. National8 Library of Medicine, Dec. 2003. Web. 17 Nov. 2014. Saritha,, C. "ECG Signal Analysis Using Wavelet Transforms."Http://www.bjp-bg.com/papers/9 bjp2008_1_68-77.pdf. Department of Physics and Electronics, S.S.B.N. COLLEGE, 16 Feb. 2008. Web. 17 Nov. 2014. "Design and Development of Embroidered Textile Electrodes for Continuous Measurement of10 Electrocardiogram Signals." Design and Development of Embroidered Textile Electrodes for Continuous Measurement of Electrocardiogram Signals. N.p., n.d. Web. 29 Sept. 2014. Graydon. "Fun with Physics, Part 2: Foot Impact Forces." Web log post. Fun with Physics,11 Part 2: Foot Impact Forces. N.p., 9 Sept. 2012. Web. 17 Nov. 2014. "Stretch Sensors (Resistors)." Chipkin Automation Systems, n.d. Web. 17 Nov. 2014.12 "Burning Calories with Exercise: Calculating Estimated Energy Expenditure." Hospital for13 Special Surgery. N.p., n.d. Web. of58 58