結合穿戴式裝置之室內定位與跌倒偵測系統開發

Abstract

由於老年人口比例穩定成長，使台灣邁向成為人口老化社會。然而這波社會結構改變，使銀髮族群問題逐漸受到重視。因此銀髮族群的居家照護時常被拿來討論。在居家照護議題中，跌倒是年長人在家最常遇到的危險意外，其會造成傷者龐大的身心靈創傷。也阻礙銀髮族獨自居住。 在本論文中，我們提出一完整的居家照護系統(Home Care System)。使用者穿戴一般智慧型手錶，即時偵測手腕資料。資料會傳輸至伺服器端，進行即時運算判斷。當伺服器偵測到跌倒意外時，會即時發出警訊，通知照護人員協助處理。此時照護系統中室內定位功能會通知照護人員跌倒傷者在的屋內精確位置，使其把握黃金搶救時間。 為驗證系統可行性，我們會將跌倒偵測以及室內定位功能個別實作成即時系統。跌倒偵測部分，以安卓穿戴系統之智慧型手錶蒐集動態資料，透過手機Wi-Fi傳輸到以Django架設之網頁伺服器，電腦再將這些收集到的資料交由MATALB運算，判斷是否跌倒。而室內定位部分，使用現有的室內定位驗算法，但其有計算量過大的問題。故我們除了軟體定義無線電之外，額外再使用FPGA進行硬體加速，使定位結果能即時呈現於螢幕上。

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.