Published on

  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide


  1. 1. Wireless Portable Emergency Detection Device Param Vora Steven Garrett Collin Liu
  2. 2. 1. Introduction 1.1 Objectives We propose to build a device that will sense a potential emergency involving a subject either becoming unconscious or entering a state where he/she is unable to take action for rescue. Our device will:  Monitor Blood Oxygen Saturation  Monitor Heart Rate  Detect falls and non-movement  Make an emergency call when needed  Send GPS coordinates to facilitate rescue 2. Design 2.1 Block Diagram
  3. 3. 2.2 Block Descriptions Android® Mobile Phone Utilizing the Google open source development kit, an application will be created. This application will accept the serial data from the proposed integrated Bluetooth module to display heart rate, oxygen saturation, and motion information for the athlete wishing to utilize the data. The phone will also take care of the necessary communication link in the even of an emergency, along with providing authorities with exact location coordinates from the integrated GPS. Bluetooth Module This module will provide a serial link between the MSP430 and the Android phone for sending and receiving important data. Ideally the module will fall into the class II or III specification for bluetooth devices, which will allow for a communication range of 1 to 10 meters while minimizing power loss. MSP430 Microcontroller ® This ultra low power microcontroller from Texas Instruments will provide the platform for our algorithm which will monitor blood oxygen saturation, movement and temperature. The chip will ultimately be responsible for outputting real time biometric data. In addition to this, the microcontroller must control power to the LEDs in the pulse oximeter while reading the analog signals from the accelerometer and the pulse oximeter photodiode. Pulse Oximeter A Reflective pulse oximeter sensor placed on the forehead of the user will provide an analog signal to the MSP430 microcontroller for real time blood oxygen saturation data. LED Drive
  4. 4. This system will be controlled by the microcontroller and will allow for the two LEDs in the Sp02 probe to alternate function. This is necessary for a correct blood oxygen saturation measurement Analog Filter and Amplifier This small system will act as a basic noise filter and an amplifier for the signal coming from the photodiode on the Sp02 sensor. Accelerometer This integrated circuit module will detect movement and tilt and output a voltage proportional to the magnitude of acceleration. By processing the signal (one for each axis) with the MSP430, the motion of the user will be monitored. With this information, an impact can be sensed and analyzed to determine if the cause is a potential emergency. Digital Temperature Sensor This small sensor will communicate temperature data with the microcontroller. The sensor may be necessary to help calibrate the pulse oximeter to varying ambient or bodily temperatures. The temperature information could also prove vital for paramedics in the event of an emergency by monitoring falling or rising temperatures. Buzzer/ Button This combination of components will be vital to minimize the event of a false alarm. Upon detection of an emergency situation, the buzzer will emit a loud alarm. If the victim is conscious and alert, he/ she will press the button to dis- arm the alarm and avert transmission of an emergency call. Otherwise, if no response is provided via the button, the appropriate call will be made. Battery Module The proper battery must be selected which will provide the 3volt logic with
  5. 5. enough power to run for a long period of time. The battery must also be lightweight and easily replaceable. If the device is to be used in remote locations, the battery type must be common in a typical general store.
  6. 6. 2.3 Performance Requirement  Distance of Cell phone from receiver – Within 33 feet (Bluetooth specification)  Due to the design of the sensor, extreme motion and temperatures may cause slight inaccuracies in the readings from the sensor. The following are the minimum and maximum operating temperatures for each device: Operating Temperature Name Min Max Texas Instruments -40°C 85°C MSP430 DSP BlueSMiRF -40°C 70°C Bluetooth Modem Triple Axis -20°C 85°C Accelerometer Digital Temperature -25°C 85°C Sensor Nonin Reusable 0°C 40°C Reflective Sensor  The Nonin sensor is accurate within ±3% oxygen saturation  The temperature sensor is accurate within ±0.5°C  The accelerometer’s sensitivity is temperature based and is 0.6%/°C
  7. 7.  The current ratings are as follows: Voltage Current Usage Name Range Sleep/Standby Active Texas Instruments 1.8V - 3.6V 1.1uA 300uA MSP430 DSP BlueSMiRF 3.3V – 6.0V <10mA 30mA Bluetooth Modem Triple Axis 2.2V – 3.6V 3uA 500uA Accelerometer
  8. 8. Digital 1.4V – 3.6V 1uA 10uA Temperature Sensor Typical Operation Nonin Reusable +3.3VDC 8.78mA Reflective Sensor +5.0VDC 9mA 3. Verification 3.1 Testing Procedures Android Cell Phone  Communication with Bluetooth The communication between the Bluetooth modules in the manufactured device must be thoroughly tested with the android phone. It must be ensured
  9. 9. that a reliable connection between the two devices is made in a variety of situations. Different situations will be tested, such as having the phone in a backpack or having the phone in a pocket. Accelerometer The accelerometer output voltages will be monitored on lab-view while the device is dropped, vibrated and generally worn around. Knowing what type of signals are present in a variety of different situations will help in developing an algorithm for detecting a harmful or emergency inducing fall. Following this analysis, the accelerometer must be interfaced with the MSP430 and the appropriate algorithms must be programmed onto the microprocessor. Pulse Oximeter Testing The pulse oximeter signal outputs must be analyzed with lab-view in a variety of situations to determine how and when to get an accurate reading of blood oxygen saturation. Often times motion will impact the accuracy of the pulse oximeter reading. Using the accelerometer, the motion artifacts in the signal may be filtered out to provide an all around accurate reading. Also, a threshold must be determined for dangerously low blood oxygen and heart rate levels. This can be tested by having the user hold their breath or enter a period of rest to slow their heart rate. The accuracy of the Sp02 reading from the oximeter must be calibrated to empirical data determined in clinical studies. This data must be found and utilized to allow calibration of our pulse oximeter. Local Alarm Check The local alarm will be tested to ensure it is audible by the user in a variety of situations and noise levels. This test will also allow testing of a variety of disarming methods. The method of disarming of the alarm must be tested to
  10. 10. ensure that the alarm is never accidentally disarmed by the user. Emergency Calling Check The emergency calling capability will be tested by dialing a personal cell phone or texting the emergency message. The final design will simply involve replacing the personal phone number with that of emergency services. Overall Device Setup The finalized device must be tested thoroughly with a variety of activity levels to determine that the device minimizes false alarms and correctly determines an emergency situation. Also, the finished device should be tested for battery life using a variety of batteries. This way the run-time for the device can be well known by the user to ensure that the device does not turn off before an emergency is encountered. 3.2 Tolerance Analysis Due to many possible factors affecting the signal acquisition stage of the heart rate and oxygen saturation, the performance of our system is heavily dependent on the accuracy of the pulse oximeter sensor. Important noise contributors include, an increase in body heat, a significant drop in blood oxygen saturation, and interference due to ambient light. Because our product is targeted toward active individuals such as athletes or military personnel, noise generated by motion may create artifacts that greatly decrease the accuracy of our pulse oximeter. Any transient motion of the sensor relative to the skin could distort the output of the sensor by “mimicking” a heartbeat. In this project we are implementing the Nonin® 8000R reusable reflectance SpO2 sensor. According to the data for this device, the accuracy of oxygen saturation measurement falls within +/-3% range under normal (hospital) operation. No data is provided on the
  11. 11. pulse rate accuracy while the subject is moving [1]. One method, which could resolve motion artifact, includes averaging the oxygen saturation level and heart rate over several time periods before determining either value [2]. However, this method may be limited by the frequency of the movement of the sensor against the skin. Another major source of noise that may contribute to a false reading may be due to the photodiode picking up ambient along with the light from the integrated diodes. Because photodiodes are extremely sensitive to light, strong ambient light such as that from fluorescent lamps will saturate the diode, impeding our ability to detect the light that passed through the pulsating arterial vessel. One of the basic approaches to minimize this effect is by placing opaque material around the photodiode. In addition, by having two active filters feed into both (plus and minus) terminals of another operational amplifier, ambient light errors, which appear in both primary operational amplifiers, can be subtracted, eliminating the error [3]. An increase in body heat due to strenuous exercise may also contribute to a decrease in sensor’s accuracy. Since the wavelength of any LED is known to be temperature dependent, an increase in temperature may shift the wavelength of the LED, ultimately causing a false reading and computation of oxygen saturation. For example, an increase in temperature from 0 – 50 degrees can create a 5.5nm increase in wavelength in a given 660nm LED, and a shift of 7.8nm in a 950nm LED [2]. To correct this problem, compensation needs to be made. First, the signal amplitude from each LED has to be normalized so that the intensity of the signal for each LED is about the same. In addition, a different calibration curve may need to be generated to create accurate readings in a given temperature range. So while the Nonin® 800R sensor operates between 0⁰C - 40⁰C [2], different correction factors may need to be implemented at different ranges. Finally, error in the reading of oxygen saturation increases as the level of
  12. 12. arterial oxygen saturation decreases. For blood oxygen saturation in the range of 70%-100%, the expected error is less than 1% [1]. However, once blood oxygen saturation falls below 70% the percentage error is expected to increase drastically. The error induced by low oxygen saturation, however, is not a significant problem for our device simply due to the fact that we are using this device to detect for low oxygen saturation as an indication of possible emergency, not for diagnostic purposes.
  13. 13. 4. Cost and Schedule 4.1 Cost Analysis 4.1.1 Labor  Average starting salary for Electrical Engineering major - $60,125 [4]  Average starting hourly wage (assuming 40 hr work weeks) - $28.90/hour  $28.90 x 2.5 x 100 hours = $7,225.00 4.1.2 Parts Name Part Number Price (per unit) Production Device Texas Instruments MSP430FG437 $5.15 MSP430 DSP BlueSMiRF Bluetooth RP-SMA $64.95 Modem Triple Axis MMA7260Q $19.95 Accelerometer Digital Temperature TMP102 $5.95 Sensor Texas Instruments OPA2340 $3.10 OpAmp Nonin Reusable 8000R $160.00 Reflective Sensor Helmet --- $19.99
  14. 14. Development Expenditure TI 80-pin target board/ MSP-FET430U80 $149.99 Programmer Design of Pulse ISBN: 0750304677 $127.96 Oximeters textbook Google Nexus One --- $562.06 Cell phone Google Android SDK --- Free 4.1.3 Total Total Parts: $1,119.10 Total Labor: $7225 x 3 = $21,675 Total: $22,794 4.2 Schedule Week Team Member: Tasks 15-Feb Steven Continue Research, Program the MSP430/ Android Phone Param Continue Research, Program the MSP430/ Android Phone Collin Develop Sensor powering circuit All Order Parts and Develop Circuitry for Design Review 22-Feb All Work on Design review, Prepare to Present 1-Mar Steven Test Accelerometer and fall detection algorithm Param Work with processing algorithm for SP02 measurement
  15. 15. Collin Determine Temp. and Motion effects on the Oximeter All Integrate Parts with the MSP430 8-Mar Steven Interface Fall algorithm with Sp02 Measurement Param Interface Fall algorithm with Sp02 Measurement Collin Calibrate Sp02 Sensor to Temperature Effects All Integrate Parts with the MSP430 15-Mar Steven Test and Develop Integration of Components Param Test and Develop Integration of Components Collin Test and Develop Integration of Components All Work on Android Development/ Ind. Progress Reports 22-Mar All Spring Break 29-Mar All Mock-up Demo, Sign up for Mock-up Presentation 5-Apr All Mock-up Presentations 12-Apr All Test and Prepare for Presentations 19-Apr All Final Ind. Progress Reports, Signup for Presentations 26-Apr All Demos and Presentations 3-May All Final Paper Due, Checkout
  16. 16. [1] OEM III Module Specification and Technical Information, Nonin® Medical, Inc., Plymouth, Minnesota, 2007. [2] J.G. Webster, Design of Pulse Oximeters, New York: Taylor and Francis Group, LLC, 1997. [3] Diagnostic, Patient Monitoring and Therapy, Texas Instruments., Dallas, Texas, 2009 [4] Source: CNN Money, “Most lucrative college degrees”, 7/24/2009