Development of an Indoor Positioning & Fall Detection System Based on Wearable Devices

碩士 === 國立臺灣大學 === 電子工程學研究所 === 104 === The elderly population in many developed countries are steadily growing, Taiwan has also entered the aging society. The change of population structure has made us gradually conscious of the aging problems. Therefore, there is no doubt that we need to pay more a...

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Bibliographic Details
Main Authors: Bo-Chen Huang, 黃柏琛
Other Authors: Tzi-Dar Chiueh
Format: Others
Language:zh-TW
Published: 2016
Online Access:http://ndltd.ncl.edu.tw/handle/90556324728483740485
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Summary:碩士 === 國立臺灣大學 === 電子工程學研究所 === 104 === The elderly population in many developed countries are steadily growing, Taiwan has also entered the aging society. The change of population structure has made us gradually conscious of the aging problems. Therefore, there is no doubt that we need to pay more attention to the home-care for the elderly. As far as home-care issue is concerned, falling is one of the major accidents at home for the elder people. It not only causes lots of physiological and psychological injuries, but it is also the main obstacle for elder people to live alone. In this thesis, we provide an ICT solution to home-care of elderly people. The user will wear a smart watch which can detect the wrist motion instantaneously. The sensor data are delivered to the server, which is able to detect the motion in real-time. If a falling accident is detected, the system will send a short message to the caregiver. Then indoor positioning function provides the location of the user to the caregiver so that they can assist the elder user immediately. In order to validate our system, we implemented two functions separately in different platforms. In the part of fall detection, we took advantage of Android wear smart watch to collect motion data, which will be sent to the Django web server. Then, the laptop could compute and determine the detection result by means of MATLAB simulation. In the part of indoor positioning, we built a real-time system. Besides using the National Instrument software-defined radio platform to receive the RF signal, we also implemented hardware acceleration with FPGA. In this way, we can track motion of the elderly people on the monitor screen in real time.