VLSI DESIGN FOR HUMAN HEALTH MONITERING AND MEDICAL ALERT SYSTEM BASED ON FPGA, MEMS AND SPECIAL SENSOR NETWORK

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1 VLSI DESIGN FOR HUMAN HEALTH MONITERING AND MEDICAL ALERT SYSTEM BASED ON FPGA, MEMS AND SPECIAL SENSOR NETWORK 1 S.Hari Prasath Sharma, 2 P.Thamarai, 3 Dr. T.V.U Kiran Kumar, 1 PG Scholar, Department of Electronics and Communication Engineering, Bharath University-Chennai, India. hariprasath.segar@gmail.com 2 Assit.Professor, Department of Electronics and Communication Engineering, Bharath University- Chennai 3 Head of the Department, Department of Electronics and Communication Engineering, Bharath University-Chennai ABSTRACT: The main objective of this paper is used to monitor the physical health conditions of elderly people, patients. Where the system detects and informs the abnormal health condition (e.g. blood pressure, pulse rate and fall detection) by using the smart sensor network, MEMS module and GPS/GSM technology.here we using these special sensors units. Through user-friendly interface, it can be used to monitor the health conditions of the elderly people/patients. Also it will send information to the nearest nursing home and relative s if they fallen or sick. So we can take the appropriate action immediately. The main advantage of this system is compact and people can easily wearable device like necklace. And nursing home and relative can get the exact location of the person fall on the earth in the form of longitude and latitude. These systems provide monitoring of patient as long as the patient/elderly people are inside the house. When he/she wants to move out, someone has to accompany him to take care of any abnormal situations that can occur with him/her on the way. With our system, the patient/elderly people can be on the move without any companion and he is still being monitored. This gives them a feeling of being more independent. Our system takes care of informing any abnormal situation with the patients to nursing home along with their location information in case they are on move. Keywords: FPGA- Field-Programmable Gate Array, GPRS- General packet radio service, GPS-Global Positioning System, GSM- Global System for Mobile, MAC - Medium Access Control, MEMS-Micro Electro Mechanical Systems, Personal health, Heartbeat,Preasure. I. INTRODUCTION This paper is mainly used to monitor and intimate the physical health conditions of elderly people or patients. Here the system detects the abnormal health condition (e.g. blood pressure, pulse rate and fall detection) by using the smart sensor network, MEMS and GPS/GSM technology.the sensing devices can

2 be categorized as compact device. This can be easily attached to body such as heart beat sensor, pressure sensor, accelerometer and gyroscope. This device will observing the physical condition of elderly people or patients in personal environments such as home, workplace, and restroom has very importance because they might be unassisted in these locations. Generally elderly people or patients have limited physical abilities and are more vulnerable to serious physical damages even with minor accidents, e.g. fall. Mostly falls are unpredictable and inescapable. In that case the fall can be early detectable also we can prompt the notification to emergency services is essential for quick recovery. Here we propose a new fall detection system which can be easily wearable to the people. Also provide both the comfortable wearing and low computation overhead. This is look like a necklace-shaped device. This module includes tri-axial accelerometer and gyroscope and special sensors to classify the health condition and posture of the detection subject. with the help of GPS/GSM tracking system we can able to detect the exact location where the person has fallen to the ground and it used to alert relatives, nearest nursing home or other people who take care of the elderly People. Also it will send information to the nursing home and relative s if they fallen or sick. Then the appropriate action can be taken immediately so we are using these special sensors units. Through user-friendly interface. II.EXISTING APPROCAH The problem in our existing case is that there is no compact device to deduct detects the abnormal health condition (e.g. blood pressure, pulse rate and fall detection) of elderly peoples/patients accurately. That s why we propose a new system to find health conditions and fall deduction. 2.1PROBLEM STATEMENT Monitoring the people is to be manual operation Communication between nursing/relative is poor. III.PROPOSED METHODOLOGY Figure: 1 Proposed method

3 In this paper a fall detection and physical health monitoring system is proposed with a device consisting of tri-axial accelerometer, gyroscope and special sensor network (i.e. pressure sensor, heartbeat sensor and MEMS) which are fabricated in the form of a necklace.this is mainly used to monitoring the physical health conditions of elderly people or patients. Here the system detects the abnormal health condition (e.g. blood pressure, pulse rate and fall detection).it will send information to the nursing home and relative s if they fallen or sick. Then we can take appropriate action immediately. Also so the nursing home and relative can get the exact location of the person fall on the earth in the form of longitude and latitude. 3.1ADVANTAGES 1. Detect Abnormal Situation. 2. Patients/Elder s safety can be assured. 3. Easily find the location. 4. We can take immediate action. 5. Fast First aid or medical treatment can be guaranteed. 3.2 BLOCK DIAGRAM TRANSMITTER SECTION MEM S Heart beat sensor Encoder Circuit Sensing Unit Pressur e sensor GSM /GPS FPGA Figure: 2 Block diagram of Transmitter Section SERVAR SECTION

4 3.3 BLOCK DIAGRAM DISCRIPTION Figure: 3 Block diagram of server section Figure.2 shows the proposed system of this project consist of special sensor network (i.e. Pressure sensor, Heart beat sensor, MEMS and GPS/GSM Modules) connected to the FPGA (Field Programmable Gate Array).In this system the Pressure sensor is used to measure the blood pressure, Heart beat sensor is used to calculate the heart beat values and MEMS (Micro Electro Mechanical System) is used to find the Fall detection of the People. Using these special sensor network and MEMS we can find the abnormal health condition of the people. And we can easily find the location using GPS in the form of latitude and longitude. Once the device detects the fall or poor health condition of the people. FPGA will get the latitude and longitude from the GPS module and also send the information to the server section in the form of latitude and longitude values. By using GSM Technology. Figure.3 server section consists of GSM (Global System for Mobile) module and Data base unit. In data base unit we have to maintain the personal detail of the people who having our health monitoring device. Here the GSM is connected to the PC (Personal computer) here we can find the global location by getting the latitude, longitude values from GPS.And it will send information to the nursing home and relative s if they fallen or sick After finding the exact location, we can give the information to relatives or other people who take care of the patients/elderly People. Then we can take appropriate action immediately. IV.PROCESS FLOW DIAGRAM

5 Fall or sick detection Figure: 4 Overall Flow Diagrams V.RELATED RESULTS 5.1Simulation Results Figure.5 Model sim Output waveform

6 Figure.6 Model sim Output waveform VI.APPLICATIONS Automatic health monitoring and fall detection Easily Detect the person who is in Abnormal Situation Monitor if the elder/patients moves away from the place of residence using GPS tracking. Easily find the location Patients/Elder s safety can be assured. Reliability, Easy usage Immediate Action -Fast First aid or medical treatment can be guaranteed. VII.CONCLUSIONS In this paper, we proposed a user friendly interface sensor network consisting of heart beat, pressure sensor, accelerometer and gyroscope. Here we used simple algorithm to find fall detection and abnormal health condition. Our proposed fall detection system can be regarded as alternative device to the existing detection approaches, since the device provides the comfortable wearing and fast detection response. These advantage features are obtained by sacrificing the sensitivity of the falls/health condition using special sensor network. VIII.FUTURE ENHANCEMENT For the future work, we plan to implement an energy efficient medium access control (MAC) protocol into our smaller sized sensor network for the data reliability and to develop a new type of handheld device.

7 IX.AUTHER PROFILE S.Hari Prasath Sharma He has obtained Bachelors of Engineering Degree in Electronics and Communication Engineering from Anna University Chennai, Tamil Nadu. Who was worked as (R&D Engineer) in Signals and System India Pvt.Ltd- Chennai After that he worked as (Sr.Project Engineer) in Pantech Solutions Pvt.ltd- Chennai. Now He is the Director at APPKEE Solutions Pvt.ltd-Coimbatore, Tamil Nadu and also pursuing M.Tech. (VLSI Design) from Bharat University- Chennai, Tamil Nadu, India. His research interest contributes to the development of VLSI- FPGA Design, Implementation and Low power VLSI Design. X.REFERENCES [I] D. N. Kanten, C. D. Mulrow, M. B. Gerety, M. J. Lichtenstein, C. Aquilar and J. E. Cornell, "Falls : an examination of three reporting methods in nursing homes," Journal of Am Geriatr Soc., vol. 41, pp , [2] Y. G. Lee, D. 1. Cheon and G. W. Yoon, "Telemonitoring System of Fall Detection for the Elderly," Journal of Sensor Science and Technology., vol. 20, no. 6, pp , [3] C. W. Lin, Z. H. Ling, Y. C. Chang and C. J. Kuo, "Compresseddomain Fall Incident Detection for Intelligent Homecare," Journal of VLSI Signal Processing., vol. 49, pp , [4] A. Sixsmith and N. Johnson, "A Smart Sensor to Detect the Falls of the Elderly," Journals & Magazines., vol. 3, no. 2, pp , [5] Q. Li, J. A. Stankovic, M. Hanson, A. Barth and J. Lach, "Accurate, Fast Fall Detection Using Gyroscopes and Accelerometer-Derived Posture Information," in 2009 Sixth International Workshop on Wearable and Implantable BSN., pp , Jun [6] A. K. Bourke, J. V. O'Brien and G. M. Lyons, "Evaluation of a threshold-based tri-axial accelerometer fall detection algorithm," in Gait & Posture., vol. 26, pp ,2007. [7] N. S. Kim, "Development of an Emergency Monitoring Device in a Wrist Watch," The Journal of Korea Institute of Information Technology., vol. 8, no 4, pp. 9-18, Apr [8] M. Quwaider and S. Biswas, "Physical Context Detection using Wearable Wireless Sensor Networks," Journal of Communications Software and Systems., vol. 4, no. 3, pp , Sep [9]Som A. E S esign for reliability mechanical failure modes and testing in Proc. th nt. onf. Percept. Technol. Methods in MEMS design, Polyana, Ukraine, May, 2011, pp [10]van Spengen W. M., "MEMS reliability from a failure mechanisms perspective," Microelectron. Reliab., vol. 43, no. 7, 2003,pp [11] T. Penzel and R. Conradt, "Computer based sleep recording and analysis", Sleep Med. Rev., vol.4, 2000, pp [12]. Y. Nishida, T. Mori, H. Mizoguchi, and T. Sato, "Sleep apnea syndrome diagnosis based on image processing", Journal of the Robotics Society of Japan, vol.16, 1998, pp (in Japanese) [13]. N. A. Fox, C. Heneghan, M. Gonzalez, R. B. Shouldiece, P. de Chazal, "An Evaluation of a Noncontact Biomotion Sensor with Actimetry," Engineering in Medicine and Biology Society, pp , Aug