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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/35744

Title: 基於雲端架構之生理訊號即時監控系統研製
The Investigation of the Physiological Signal Real-Time Monitoring System Based on Cloud Architecture
Authors: Shin-Cheng Liu
Contributors: NTOU:Department of Communications Navigation and Control Engineering
Keywords: 生理訊號;血氧飽和濃度;心電訊號;Lead Ⅰ;血壓;即時監控;嵌入式;雲端平台
Physiological signals;Blood oxygen saturation;ECG signals;Lead Ⅰ;Blood pressure;Real-time monitoring;Embedded;Cloud platforms
Date: 2013
Issue Date: 2013-10-07T02:58:28Z
Abstract: 由於科技的進步,人們生活水準逐漸提升,許多文明病因此產生,其中包括心臟、血壓、血糖與血氧異常等突發性病變。但人們卻往往忽略這些嚴重疾病發生的徵兆,其中以心臟病及高血壓為國人長期之病因,是以生理訊號的即時監控日益重要。但監控步驟往往繁瑣且監控設備體積過於龐大不易攜帶,甚至血糖濃度常以扎針方式量測而使受測者因感到疼痛而失去量測意願。為能長時間監控,量測系統體積小型化且技術非侵入化已是必然趨勢。本論文即擬研製建置於雲端服務平台之可攜式人體生理訊號量測裝置,將受測者資訊傳至雲端以作即時顯示生理訊號圖形與數值。主要研究方向在於利用心電圖、血氧及體溫感測電路運用微控制器擷取人體訊號,經由無線傳輸的方式傳送至雲端服務平台。接著將心電訊號繪製成心電圖並推估出舒張壓、收縮壓與心律;同時亦將血氧訊號轉換成血氧濃度。搭配體溫、血氧濃度與心律建構血糖濃度模型,並據此以發展出非侵入血糖偵測技術。
With the advancement of technology, people's living standards have been improved gradually and many diseases of civilization including heart abnormalities, dysarteriotony, glucose abnormalities and oxygen abnormalities, would therefore occur. Since people usually ignore these serious signs of diseases, in particular, for the cardiologists and hypertension, real-time monitoring of physiological signal is extremely important. However in addition to cumbersome monitoring procedure and bulky surveillance equipment reasons, the most important is the acupuncture treatments will cause subjects feel pain and thus lose willingness. In order to monitor the physiology signals for a long time, miniaturization of the measurement systems and development of the non-invasive techniques are already the trend at present. In this thesis, based on cloud services platform, portable devices for measuring the physiological signals will be developed such that the physiological information of subjects can be transmitted to the cloud platform for real-time display. The circuits for sensing electrocardiogram (ECG), oxygen and body temperature will be implemented to capture human signals which will be used to inference diastolic blood pressure, systolic blood pressure and heart rate. Finally, a non-invasive glucose detection technology can be developed by identifying the concentration model with body temperature, oxygen concentration and heart rate.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0010067015
Appears in Collections:[通訊與導航工程學系] 博碩士論文

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