The document proposes an intelligent system to assist patients using wireless applications and low-cost equipment. The system has three main modules: a user badge module worn by the patient with sensors to detect vital signs, a receiver module at the patient's location, and a system module on a central computer. The system monitors the patient's heartbeat and temperature from the user badge and can detect falls using a web camera. If vital signs go outside normal ranges or a fall is detected, an alert is triggered to help patients in critical conditions.

1. AN INTELLIGENT
SYSTEM TO ASSIST
PATIENTS
BY:
HASNA HASSAN ANNACOT(72105205013)
KARTHIKEYAN.S(72105205018)
NAREN PRASATH(72105205301)

2. AIM OF THE PROJECT
To save an ill person with low cost equipment
using wireless applications.

3. OVERVIEW OF THE PROJECT
 System has heart beat sensor to detect the persons
heart beat,when the person in critical position, the
sensor intimates to the applications.
 The application rings the alarm and warn about their
illness.
 The system has another advantage to watch the
person through web camera,when the person falls
down,it will invoke the application.

4.  Suppose the person cannot get up within a
particular duration, the application calls the
helpers.
 Using embedded system the person can talk with
some one.
 Required electronics components available in
the market with reasonable prizes.
 The new image-processing algorithm named “
FALL DETECTION” using edge detection
methods is introduced here.
 Through this application we can view the
persons present body condition from any
remote locations.
 The RFID reveals the present position when the
patient is out, and offers the navigation
information.

5. MODULES
 Three main modules:
The user badge module
The receiver module
The system module

6. MODULE BRIEFING
 The user badge has a heart beat sensor,
temperature sensor, microphone and emergency
button. It is a surface mountable device that is fixed
to the body of the person.
 The receiver module is a static mode with a alarm
interface and is installed in the room where the
person stays most of the time. The interface, when
enabled due to a fall or rise in the pulse,
automatically rings the alarm to inform the hospital
staff.

7. MODULE BRIEFING
 The system module is the computer that is kept at
a central place that validates the events from the
patient. The system module has 6 sub-modules:
• Authentication module
• Update module
• Monitor module
• Fall detection module
• RFID module

8. USER BADGE MODULE
 It consists of a 555 IC which is used as a heart beat
sensor. An astable multivibrator is a timing circuit
whose 'low' and 'high' states are both unstable. As
such, the output of an a stable multivibrator toggles
between 'low' and 'high' continuously, in effect
generating a train of pulses. This circuit is therefore
also known as a 'pulse generator' circuit.
 The 555 timer possesses a high degree of accuracy
and stability. The initial monostable timing accuracy is
typically is typically within 1% of its calculated value,
and exhibits negligible (0.1%/v) drift with the supply
voltage.

9. USER BADGE MODULE
 It consists of LM35 used as a temperature sensor.
The LM35 is a precision temperature sensor, whose
output voltage is linearly proportional to the
temperature in degrees Celsius.
 The LM35 thus has an advantage over linear
temperature sensors calibrated in ° Kelvin, as the
user is not required to subtract a large constant
voltage from its output to obtain convenient
Centigrade scaling. The LM35 does not require any
external calibration or trimming to provide typical
accuracies of ±0.25°C at room temperature. The
LM35 is rated to operate over a −55° to +150°C
temperature range.

10. USER BADGE MODULE
 It consists of TYPE 60 TACT SWITCH which is
used as an emergency key. Professional grade
Tact Switches are used in Audio, Video and
Electronic applications. Various knob heights in
attractive colors and different operating forces are
available.
 These switches are generally dust proof, water proof
and has a long life.
 In case there is an emergency automatically the
application is invoked and transmitter sends a
message to the receiver module.

11. USER BADGE MODULE
 It consists of 212 encoders. The 212 encoders are a
series of CMOS LSIs for remote control system
applications. They are capable of encoding
information which consists of N address bits and 12N
data bits. Each address/data input can be set to one
of the two logic states.

12. USER BADGE MODULE
 The TWS-434 is extremely small, and are excellent
for applications requiring short-range RF remote
controls. The transmitter module is only 1/3 the
size of a standard postage stamp, and can easily be
placed inside a small plastic enclosure.
 TWS-434: The transmitter output is up to 8mW at
433.92MHz with a range of approximately 400 foot
(open area) outdoors. Indoors, the range is
approximately 200 foot, and will go through most
walls.

13. RECEIVER MODULE
 It consists of RWS-434 receiver.RWS-434 are
extremely small, and are excellent for applications
requiring short-range RF remote controls.
 RWS-434: The receiver also operates at
433.92MHz, and has a sensitivity of 3uV. The
RWS-434 receiver operates from 4.5 to 5.5 volts-
DC, and has both linear and digital outputs.

14. RECEIVER MODULE
 It consists of a 212 decoder. The 212 decoders are a
series of CMOS LSIs for remote control system
applications. They are paired with Holteks 212 series
of encoders. For proper operation, a pair of encoder/
decoder with the same number of addresses and
data format should be chosen.
 The decoders receive serial addresses and data
from a programmed 212 series of encoders that are
transmitted by a carrier using an RF or an IR
transmission medium. They compare the serial input
data three times continuously with their local
addresses. If no error or unmatched codes are
found, the input data codes are decoded and then
transferred to the output pins.

15. RECEIVER MODULE
 It consists of ATMEL 89S51 microcontroller. The
micro controller, which we are going to use, is
89S51 it is manufactured by Atmel, MC, USA. This
is advanced version of 8031. This Micro controller
have inbuilt 4K bytes of flash ROM, 256 bytes of
RAM, 32 I/O lines (4 bit ports) and 6 vectored
interrupts.
 There are four I/O ports available in AT89S51. They
are port 0, port 1, port 2, and port 3. All these ports
are eight bit ports. All these ports can be controlled
as eight-bit port or it can be controlled individually.

16. SYSTEM MODULE
 Authentication module: this module is to
authenticate the specialist computer user with an id
and password and to keep the data secure.
 Update module: this is to keep an update of the
normal heart beat rate and temperature of the
patient.
 Monitor module: this is used to keep a watch over
the variations in the patients heartbeat rate
temperature and falls detected using a web camera.

17. AUTHENTICATION MODULE

18. UPDATE MODULE

19. MONITOR MODULE

20. FALL DETECTION MODULE
 There are two algorithms used for fall
detection:
Edge Detection Algorithm
Motion Detection Algorithm

21. EDGE DETECTION MODULE
 This module deals with image processing and edge
detection algorithms.
 Edges characterize boundaries and are therefore a
problem of fundamental importance in image
processing. Edges in images are areas with strong
intensity contrasts – a jump in intensity from one
pixel to the next.
 Edge detecting an image significantly reduces the
amount of data and filters out useless
information, while preserving the important
structural properties in an image.
 There are many ways to perform edge detection.
However, the majority of different methods may be
grouped into two categories, gradient and Laplacian.

22. EDGE DETECTION MODULE
 Sobel Algorithm:The Sobel operator performs a 2-
D spatial gradient measurement on an image.
Typically it is used to find the approximate absolute
gradient magnitude at each point in an input
grayscale image.
 The Sobel edge detector uses a pair of 3x3
convolution masks, one estimating the gradient in
the x-direction (columns) and the other estimating
the gradient in the y-direction (rows).
 A convolution mask is usually much smaller than the
actual image. As a result, the mask is slid over the
image, manipulating a square of pixels at a time.

23. EDGE DETECTION MODULE
 The actual Sobel masks are shown below:

24. EDGE DETECTION MODULE
 The magnitude of the gradient is then
calculated using the formula:
 An approximate magnitude can be calculated
using: |G| = |Gx| + |Gy|

25. EDGE DETECTION MODULE
 Sobel Explanation: The mask is slid over an area of
the input image, changes that pixel's value and then
shifts one pixel to the right and continues to the right
until it reaches the end of a row. It then starts at the
beginning of the next row.
 The example below shows the mask being slid over
the top left portion of the input image represented by
the green outline. The formula shows how a particular
pixel in the output image would be calculated.
 The center of the mask is placed over the pixel you
are manipulating in the image. And the I & J values
are used to move the file pointer so you can multiply,
for example, pixel (a22) by the corresponding mask
value (m22).

26. EDGE DETECTION MODULE
 It is important to notice that pixels in the first and last
rows, as well as the first and last columns cannot be
manipulated by a 3x3 mask. This is because when
placing the center of the mask over a pixel in the
first row (for example), the mask will be outside the
image boundaries.
 The GX mask highlights the edges in the horizontal
direction while the GY mask highlights the edges in
the vertical direction. After taking the magnitude of
both, the resulting output detects edges in both
directions.

27. EDGE DETECTION MODULE

28. MOTION DETECTION
 There are many approaches for motion detection in
a continuous video stream. All of them are based on
comparing of the current video frame with one from
the previous frames or with something that we'll call
background.
 One of the most common approaches is to compare
the current frame with the previous one. It's useful in
video compression when you need to estimate
changes and to write only the changes, not the
whole frame. But it is not the best one for motion
detection applications. So, let me describe the idea
more closely.

29. MOTION DETECTION
 The most efficient algorithms are based on building
the so called background of the scene and
comparing each current frame with the background.
There are many approaches to build the scene, but
most of them are too complex.
 Let's assume that we have an original 24 bpp RGB
image called current frame (image), a grayscale
copy of it (currentFrame) and a background frame
also gray scaled (backgroundFrame). At the
beginning, we get the first frame of the video
sequence as the background frame. And then we'll
always compare the current frame with the
background one.

30. MOTION DETECTION
 Our approach is to "move" the background frame to
the current frame on the specified amount. We
move the background frame slightly in the direction
of the current frame - we are changing colors of
pixels in the background by one level per frame.

31. FALL DETECTION MODULE

32. RFID MODULE
 A radio frequency identifier consists of a tiny
silicon computer chip and an antenna.
 It has a remote reader which can scan and send to
a database.
 Each RFID chip has a unique number for every
product.
 Its antenna helps remote scanner to read RFID tags
 They can read them through materials like fabric
and plastic
 Accurate information

33. RFID MODULE
 There are 2 kinds of tags :hidden tag and a much
large battery tag (active tag)
 Hidden tag can be just 4 inches away while active
tags can be 300 feet away
 It has a device (a receiver device connected to an
antenna and reads the tag)
 With the RFID, personal information (such as age
and health history) can be adopted to customize the
detection sensitivity for each individual in order to
reduce the probability of false alarms for less likely
events and put more attention on more likely events.

34. RFID MODULE
 The proposed system achieves about 91%
successful fall detection rate according to the
experimental results, where various walking paths
and falling directions are tested.
 This can be used when the patient is within the
hospital compound.
 RFID is less expensive and can be used to locate
the exact position of the patient.

35. GPS MODULE
 This module of GPS can be used when remote
assistance is required for patients at home.
 In case of remote assistance for patients at home
we also need to change the alarm interface into
telephonic interface.
 In this case if there is any emergency need an
automatic call goes to the nearby hospitals and they
can locate where the patient is using GPS.
 In case of using a GPS the expenses are higher
than that of using RFID which can be limited only to
the hospital vicinity.

36. EXISTING SYSTEM
 A patient is any person who receives medical
attention, care, or treatment. The person is most
often ill or injured and in need of treatment by a
physician or other medical professional, although
one who is visiting a physician for a routine check-
up may also be viewed as a patient. Caring is a
must in all type of hospitals. Manual check up may
give only approximate results.

37.  Even a seconds delay can cause severe problems
for a patient. The Doctor and the nurse cannot
have a constant watch on the patient’s heart beat
and temperature unless the patient is in ICU.
Every second is precious when the patient is in
hospital for their treatment . The existing system
brings the drawbacks due to Fully Manual Process
and Patients are affected by the delays.

38. Brief Description On The Base Paper
A CDMA-based Mobile Embedded Telemedical
System for Healthcare
 The mobile telemedical system based on CDMA
networks includes the following four parts: Medical
information nods (MIN), WDL, Medical information
center, and specialist computer system
 Its modules are: CDMA module, GPS module, Heart
Rate module, Electrocardiogram module and
Photopkthysmograph module.
 The application of CDMA has made it portable and
facile to realize remote care, remote diagnostic
consultation and emergency treatment.

39. PROPOSED SYSTEM
Intelligent System to Assist Patients
 The intelligent system includes the following four
parts: Embedded system, Web camera, Specialist
computer system and User badge.
 Its modules are: user badge module, receiver
module, system module and GPS module.
 This application helps to keep a constant watch on
the patients and the hospital authority can find the
exact position of the patient in case of danger.

40. ADVANTAGES OF THE PROPOSED
SYSTEM
 Assist the doctors and patients
 Help the patients in critical condition
 Get good names to Hospital
 Avoid manual checks
 Can use this option in Home also .

41. SYSTEM CONFIGRATION
 HARDWARE SPECIFICATION
• Microcontroller – ATMEL 89S51
• Heartbeat Sensor – IC555
• Temperature Sensor – LM35
• Emergency Key – TYPE 60 TAT SWITCH
• Transmitter – TWS-434
• Receiver – RWS-434
• Web Camera
• PC

42. SYSTEM CONFIGRATION
 SOFTWARE SPECIFICATION
• Operating System - Windows 98 and above
• Front End – C# and .NET 2005

43. BLOCK DIAGRAM
Alarm
Alarm driver Receiver
Micro
Decoder
controller

44. BLOCK DIAGRAM
HEART BEAT
PC
SENSOR
TEMPERATURE LEVEL
SENSOR CONTROLLER
MICRO
CONTROLLER
FALL
ENCODER
DETECTOR
EMERGENCY
TRANSMITTER
SWITCH

45. SYSTEM CONTEXT DIAGRAM
EMBEDDED
SYSTEM PATIENT
AN INTELLIGENT
SYSTEM TO
ASSIST ELDERLY
SPECIALIST
WEB CAMERA
COMPUTER

46. SYSTEM FLOW DIAGRAM
RECEIVER
WEB CAMERA CAPTURE PATIENT
ACTIVATE CAPTURE
CONNECTED IN USB SETTINGS
CONNECTED
EMBEDDED PC APPLICATION TEMPERATURE
SYSTEM VIA SERIAL
PORT
IMAGE CAPTURING HEART BEAT COMPARE
SIGNAL
MAKE IN BIT MAP COMPARISSION
CONVERT GRAY SCALE
CROSSED
EDGE DETECTION
PLAY VOICE
COMPARISION
SMS
YES
SEND MESSAGES
ALARM SIGNAL

47. CONCLUSION
 The system can be used in hospitals, senior
citizens’ homes, Prisons and asylums, using
a common server to monitor the movements
of its inhabitants.
 This system keeps a constant watch on the
patients activities and keep monitoring their
health condition.

48. PROJECT REPORT
 In the month of January we collected information
and reference related to our project.
 In the month of February we started the work on fall
detection algorithm such as Sobel algorithm and
tried to implement it in the project for our primary
module that includes fall detection after capturing
images, processing them converting them to gray
scale, detect the edges and do motion detection.
 At present we are working on the hardware part that
includes the user badge module and the receiver
module and programming of the microcontroller
accordingly.

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