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    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/57619


    Title: Web-based Remote Human Pulse Monitoring System with Intelligent Data Analysis for Home Healthcare
    Authors: Chen, Chih-Ming
    陳志銘
    Contributors: 政大圖檔所
    Keywords: Pulse physiology signal monitoring system;Embedded system;e-Health care;Sequence data analysis
    Date: 2011-03
    Issue Date: 2013-04-12 16:05:17 (UTC+8)
    Abstract: Many countries have already become aging societies, as evidenced by annually decreasing fertility rates. Elderly individuals often live independently because their families cannot look after them. Therefore, computer-assisted nursing has received increasing attention in modern society, explaining why intelligent systems with physiology signal monitoring for e-health care is an emerging area of development, owing to the urgent needs of homecare for elderly people suffering chronic or sudden diseases at home. Importantly, a physiology signal monitoring system can help medical staff to monitor and analyze physiology signal effectively, such that they can not only monitor the patients’ physiology states immediately, but also reduce medical cost and avoid having to visit doctors in hospital. Therefore, this study adopts system on chip (SOC) techniques to develop an embedded human pulse monitoring system with intelligent data analysis mechanism for disease detection and long-term health care. The proposed system can be applied to monitor and analyze pulse signal in daily life. The proposed system also has a friendly web-based interface for medical staff to observe immediate pulse signals for remote treatment. Hence, the proposed system provides aids long-distance medical treatment, exploring trends of potential chronic diseases, and urgent situations informing for sudden diseases. Moreover, this study also presents an intelligent data analysis scheme based on the modified cosine similarity measure to diagnose abnormal pulses for exploring potential chronic diseases.
    Relation: Expert Systems with Applications, 38(3), 2011-2019
    Data Type: article
    DOI 連結: http://dx.doi.org/10.1016/j.eswa.2010.07.136
    DOI: 10.1016/j.eswa.2010.07.136
    Appears in Collections:[圖書資訊與檔案學研究所] 期刊論文

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