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Web-based remote human pulse monitoring system with intelligent data analysis for home health care
Authors:Chih-Ming Chen
Affiliation:1. IT Components and Materials Industry Technology Research Department, Electronics and Telecommunications Research Institute (ETRI), 218 Gajeongno, Yuseong-gu, Daejeon 305-700, Republic of Korea;2. Department of Solar & Energy Engineering, Cheongju University, 298 Daeseongro, Sangdang-gu, Cheongju, Chungbuk 360-764, Republic of Korea;3. Korea University of Science and Technology (UST), 217 Gajeongno, Yuseong-gu, Daejeon 305-350, Republic of Korea;1. Veratech for Health SL, Avenida del Puerto 237-1, Valencia 46011, Spain;2. Department of Computer Engineering and Science, Universitat Jaume I, Spain;3. Departamento de Informática y Sistemas, Universidad de Murcia, IMIB-Arrixaca, Spain;4. Fundación para la Formación e Investigación Sanitarias de la Región de Murcia, IMIB-Arrixaca, Spain
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.
Keywords:
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