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AN INTELLIGENT
SYSTEM TO ASSIST
PATIENTS
   BY:
   HASNA HASSAN ANNACOT(72105205013)

        KARTHIKEYAN.S(72105205018)

        NAREN PRASATH(72105205301)
AIM OF THE PROJECT

To save an ill person with low cost equipment
  using wireless applications.
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.
   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.
MODULES

   Three main modules:
           The user badge module
           The receiver module
           The system module
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.
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
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.
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.
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.
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.
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.
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.
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.
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.
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.
AUTHENTICATION MODULE
UPDATE MODULE
MONITOR MODULE
FALL DETECTION MODULE

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

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

   The magnitude of the gradient is then
    calculated using the formula:

   An approximate magnitude can be calculated
    using: |G| = |Gx| + |Gy|
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).
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.
EDGE DETECTION MODULE
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.
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.
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.
FALL DETECTION MODULE
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
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.
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.
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.
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.
   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.
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.
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.
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 .
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
SYSTEM CONFIGRATION

   SOFTWARE SPECIFICATION

•   Operating System - Windows 98 and above
•   Front End – C# and .NET 2005
BLOCK DIAGRAM

   Alarm




Alarm driver             Receiver




   Micro
               Decoder
 controller
BLOCK DIAGRAM




  HEART BEAT
                                PC
    SENSOR

 TEMPERATURE                   LEVEL
    SENSOR                  CONTROLLER
                 MICRO
               CONTROLLER
    FALL
                             ENCODER
  DETECTOR

  EMERGENCY
                            TRANSMITTER
    SWITCH
SYSTEM CONTEXT DIAGRAM




  EMBEDDED
   SYSTEM                       PATIENT
              AN INTELLIGENT
                SYSTEM TO
              ASSIST ELDERLY




                               SPECIALIST
 WEB CAMERA
                               COMPUTER
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
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.
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.
REFERENCES
      . Figueroa, W. Solano, C. Thurman, and J. Schmalzel, “A future vision of data
       acquisition: Distributed sensing, processing, and health monitoring,” in Proc. IMTC
       Budapest, Hungary, May 2001
      E. J. Hogenbirk, H.-J. Verhoeven, and J. H. Huijsing, “An integrated smart sensor
       for flow and temperature with I2C bus interface: FTS2,” in Proc. Int. Sym. Circuits
       Systems, 1995
      IEEE Standard for Information Technology—Part 3: Carrier Sense Multiple Access
       with Collision Detection (CSMA/CD) Access Method and Physical Layer
       Specifications Amendment: Data Terminal Equipment (DTE) Power via Media
       Dependent Interface (MDI)
      S. Hong and G. May, “Neural network modeling of reactive ion etching using
       principal component analysis of optical emission spectroscopy data,” in Proc.
       Advanced Semiconductor Manufacturing Conf. Boston, MA, Apr. 2002
   J.S. Lim, Two-Dimensional Signal and Image Processing, Prentice Hall, Upper Saddle
    River, N.J., 1990.

   W.K. Pratt, Digital Image Processing, John Wiley & Sons, New York, 1978.
   Ollero et al., "Techniques for Reducing False Alarms in Infrared Forest-Fire Automatic
    Detection Systems," Control Engineering Practice, Vol. 7, No. 1, 1999,
   R.C. Gonzalez and R.E. Woods, Digital Image Processing, Addison-Wesley, New
    York, 1993.
   Ollero, J.R. Martínez-de Dios and B.C. Arrúe, "Integrated Systems for Early
    Forest-Fire Detection," Proc. Third Int"l Conf. Forest Fire Research, SPIE Press,
    Bellingham, Wash., 1998
   Y. Rauste, "Forest Fire Detection with Satellites for Forest Fire Control," Int"l
    Archives of Photogrammetry and Remote Sensing, Vol.31, Part B7, Proc. XVIII
    Congress of ISPRS, Int"l Soc. for Photogrammetry and Remote Sensing,
    ISPRSVienna, 1996
   G. Bovio and A. Nosenzo, "Comparison between Methods of Forecasting Danger
    of Forest Fires," Proc. Second Int"l Conf. Forest Fire Research, SPIE Int"l
    Symposium,Orlando, Fla., 1994
   Ollero et al., "Techniques for Reducing False Alarms in Infrared Forest-Fire
    Automatic Detection Systems," Control Engineering Practice, Vol. 7, No. 1, 1999

   R. S. Habib Istepanian, "Modeling of GSM-based mobile telemedical system,"
    Hong Kong, China, 1998,
   W. D. Yu and A. Ramani, "Design and implementation of a personal mobile
    medical assistant," Busan, South Korea, 2005,
   M. Ogawa and T. Tamura, "Monitoring of heart and respiratory signals with PPG
    in bathing,"Atlanta, GA, USA, 1999
   2007 IEEE/ICME International Conference on Complex Medical Engineering. A
    CDMA-based Mobile Embedded Telemedical System for Healthcare

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Hasna

  • 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.
  • 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.
  • 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.
  • 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.
  • 49. REFERENCES  . Figueroa, W. Solano, C. Thurman, and J. Schmalzel, “A future vision of data acquisition: Distributed sensing, processing, and health monitoring,” in Proc. IMTC Budapest, Hungary, May 2001  E. J. Hogenbirk, H.-J. Verhoeven, and J. H. Huijsing, “An integrated smart sensor for flow and temperature with I2C bus interface: FTS2,” in Proc. Int. Sym. Circuits Systems, 1995  IEEE Standard for Information Technology—Part 3: Carrier Sense Multiple Access with Collision Detection (CSMA/CD) Access Method and Physical Layer Specifications Amendment: Data Terminal Equipment (DTE) Power via Media Dependent Interface (MDI)  S. Hong and G. May, “Neural network modeling of reactive ion etching using principal component analysis of optical emission spectroscopy data,” in Proc. Advanced Semiconductor Manufacturing Conf. Boston, MA, Apr. 2002  J.S. Lim, Two-Dimensional Signal and Image Processing, Prentice Hall, Upper Saddle River, N.J., 1990.  W.K. Pratt, Digital Image Processing, John Wiley & Sons, New York, 1978.  Ollero et al., "Techniques for Reducing False Alarms in Infrared Forest-Fire Automatic Detection Systems," Control Engineering Practice, Vol. 7, No. 1, 1999,  R.C. Gonzalez and R.E. Woods, Digital Image Processing, Addison-Wesley, New York, 1993.
  • 50. Ollero, J.R. Martínez-de Dios and B.C. Arrúe, "Integrated Systems for Early Forest-Fire Detection," Proc. Third Int"l Conf. Forest Fire Research, SPIE Press, Bellingham, Wash., 1998  Y. Rauste, "Forest Fire Detection with Satellites for Forest Fire Control," Int"l Archives of Photogrammetry and Remote Sensing, Vol.31, Part B7, Proc. XVIII Congress of ISPRS, Int"l Soc. for Photogrammetry and Remote Sensing, ISPRSVienna, 1996  G. Bovio and A. Nosenzo, "Comparison between Methods of Forecasting Danger of Forest Fires," Proc. Second Int"l Conf. Forest Fire Research, SPIE Int"l Symposium,Orlando, Fla., 1994  Ollero et al., "Techniques for Reducing False Alarms in Infrared Forest-Fire Automatic Detection Systems," Control Engineering Practice, Vol. 7, No. 1, 1999  R. S. Habib Istepanian, "Modeling of GSM-based mobile telemedical system," Hong Kong, China, 1998,  W. D. Yu and A. Ramani, "Design and implementation of a personal mobile medical assistant," Busan, South Korea, 2005,  M. Ogawa and T. Tamura, "Monitoring of heart and respiratory signals with PPG in bathing,"Atlanta, GA, USA, 1999  2007 IEEE/ICME International Conference on Complex Medical Engineering. A CDMA-based Mobile Embedded Telemedical System for Healthcare