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研究生:許子亮
研究生(外文):HSU, TZU-LIANG
論文名稱:穿戴式生理量測於 行動裝置與雲端伺服器平台之實現
論文名稱(外文):A Biological Signal Acquisition Platform for Wearable and Mobile Devices with Cloud Computing
指導教授:蘇柏齊李柏磊
指導教授(外文):Po-Chyi Su
學位類別:碩士
校院名稱:國立中央大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2017
畢業學年度:105
語文別:中文
論文頁數:65
中文關鍵詞:穿戴式裝置行動裝置雲端運算生理訊號處理
外文關鍵詞:Wearable devicesMobile devicesCloud computingBiomedical signal processing
相關次數:
  • 被引用被引用:0
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  • 下載下載:47
  • 收藏至我的研究室書目清單書目收藏:0
本研究提出利用雲端監控之生理訊號偵測機制,此機制藉由自行開發的軟體架構,結合實驗室所研製的生理訊號採集樣本硬體MSP430F5438A完成整體研究實作。生理訊號由MSP430F5438A以頻率500Hz採樣,採樣內容包含腦波、眼動圖、血氧飽和指數、心電圖等訊號,並通過藍牙無線介面傳輸至移動式裝置。移動式裝置採用Android系統,生理訊號在此裝置經過初步前處理後,再同步上傳至雲端伺服器記錄結果,我們亦在移動裝置上提供使用者生理訊號即時查看功能。雲端伺服器包含一個網頁伺服器,以及一個檔案傳輸伺服器,並建立背景服務實現生理訊號即時濾波與分析,提供即時瀏覽網頁功能讓遠端監測者觀看,完成服務多人之訊號偵測系統架構實作。
本機制利用多平台溝通與分散運算資源,降低高採樣率所造成的硬體負擔與建置成本,也提供了一個生理訊號監測即時平台,可將其應用於任一生理訊號即時回報環境,如醫學或生理訊號教學評估系統,解決生理訊號蒐集者無法獲得即時資訊的困難。
This research presents a biomedical signal collecting scheme, which consists of a self-developed software architecture and a MSP430F5438A biomedical signal collecting hardware. Biomedical signals will be collected by MSP430F5438A with a 500Hz sampling rate. The collected signals in the proposed scheme include Electroencephalography, Electrooculography, Electrocardiography, and Photoplethysmography. The hardware will acquire these signals and transfer the data to a mobile device running an Android system through the Bluetooth interface. The signals will be preprocessed and the data will be transferred to a cloud-computing server. The mobile device also provides a real-time signal viewing interface for users to check. A web service, a file transfer service, and a signal processing service are running on this cloud-computing server to support multiple users.
This proposed scheme relies on communications between multiple platforms to redistribute the computing resources. The biomedical signals often have a large volume of data, especially when we collect them with a high frequency and from multiple signal sources. Therefore, the major research objectives are to reduce the cost of signal collection and to solve the problem that healthcare professionals cannot acquire real-time data. The demo shows the feasibility of the proposed scheme.
目錄
論文摘要 i
Abstract ii
目錄 iv
附圖目錄 vii
附表目錄 ix
第一章 緒論 1
1.1研究背景與動機 1
1.2 研究貢獻 3
1.3 論文架構 5
第二章 生理訊號分析系統原理與建置 6
2.1 訊號分析簡介 6
2.1.1 雜訊濾除 7
2.1.2 R波間距計算(RR-Interval,RRI) 7
2.1.3 心率變異度(Heart Rate Variability,HRV) 分析 9
2.2生理訊號分析實作 13
2.2.1 生理訊號時域分析 13
2.2.2生理訊號頻域分析 14
第三章Android APP原理與建置 16
3.1 Android系統簡介 16
3.2 Android系統實作方法 17
3.2.1 Android平台選用 17
3.2.2 Android 藍牙訊號解析 18
3.2.3 Android生理訊號轉發 20
3.2.4 Android 背景通訊服務 23
3.2.5 Android自定浮動式網頁Activity 24
第四章 伺服器系統設計與原理 27
4.1 伺服器作業系統 28
4.2 Apache網頁伺服器系統簡介與搭建 30
4.2.1 HTML 與 PHP簡介 30
4.2.2 JavaScript與D3.js 31
4.2.3 Apache伺服器搭建 32
4.3 FTP 伺服器原理與搭建 32
4.3.1 FTP伺服器建置 33
4.4 JAVA生理訊號編解伺服器程式 34
4.5 即時網頁顯示頁面實作 34
第五章 實作展示與討論 36
5.1 實驗設備 36
5.2 操作流程展示 38
5.3 FTP 檔案存取展示 45
第六章 結論與未來展望 46
6.1 結論 46
6.2 未來展望 46
參考文獻 48
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