Mahbuba Kaneez Hasna DOI: 10.1177/095624789500700210 The ...
Hasna
-
Upload
hasnaroshan -
Category
Documents
-
view
1.099 -
download
2
Transcript of Hasna
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 PaperA 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 SYSTEMIntelligent 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
Alarm
Alarm driver
Micro
controllerDecoder
Receiver
BLOCK DIAGRAM
BLOCK DIAGRAM
HEART BEAT
SENSOR
TEMPERATURE
SENSOR
FALL
DETECTOR
EMERGENCY
SWITCH
PC
LEVEL
CONTROLLER
ENCODER
TRANSMITTER
MICRO
CONTROLLER
SYSTEM CONTEXT DIAGRAM
AN INTELLIGENT
SYSTEM TO
ASSIST ELDERLY
EMBEDDED
SYSTEM
WEB CAMERA
PATIENT
SPECIALIST
COMPUTER
SYSTEM FLOW DIAGRAM
WEB CAMERA CAPTURE PATIENT
EMBEDDED SYSTEM
PC APPLICATION TEMPERATURE
SETTINGS
MAKE IN BIT MAP
HEART BEAT SIGNAL
COMPAREIMAGE CAPTURING
COMPARISSION
CONVERT GRAY SCALE
EDGE DETECTION
COMPARISION
ALARM SIGNAL
CROSSED
PLAY VOICE SMS
MESSAGES
RECEIVER
CONNECTED IN USB
ACTIVATE CAPTURE
CONNECTED
VIA SERIAL PORT
YES SEND
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