穿戴式生理量測於 行動裝置與雲端伺服器平台之實現;A Biological Signal Acquisition Platform for Wearable and Mobile Devices with Cloud Computing

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Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/74628

Title:	穿戴式生理量測於行動裝置與雲端伺服器平台之實現;A Biological Signal Acquisition Platform for Wearable and Mobile Devices with Cloud Computing
Authors:	許子亮;HSU, TZU-LIANG
Contributors:	資訊工程學系
Keywords:	穿戴式裝置;行動裝置;雲端運算;生理訊號處理;Wearable devices;Mobile devices;Cloud computing;Biomedical signal processing
Date:	2017-07-06
Issue Date:	2017-10-27 14:34:22 (UTC+8)
Publisher:	國立中央大學
Abstract:	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.
Appears in Collections:	[Graduate Institute of Computer Science and Information Engineering] Electronic Thesis & Dissertation

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