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Many studies had indicated that applying intelligent systems with physiology signal monitoring for e-health care is a current developing trend. A physiology signal monitoring system can help medical staffs to monitor and analyze humanpsilas physiology signal effectively, such that they can not only monitor the patientspsila physiology states immediately, but also reduce medical cost and save a lot of time of patients to visit hospitalpsilas doctors. Therefore, the study employed 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, which can be applied to monitor and analyze humanpsilas pulse signal in daily life. Meanwhile, the proposed system also developed a friendly web-based interface that is convenient to the observation of immediate human physiological signals. Moreover, this study also proposes an intelligent data analysis scheme based on the modified cosine similarity measure to diagnose abnormal human pulses for exploring potential chronic diseases. Therefore, the proposed system provides benefits in terms of aiding long-distance medical treatment, exploring trends of potential chronic diseases, and urgent situation informing for sudden diseases.