Research On High-efficiency Sensing Of Physical Sign Information

The technology of wireless sensor network has permeated into a new generation of the biomedical application field gradually. With the rapid growing of the wireless communication, biological and physiological sensor, digital medical-tech, computer science and low power integrated circuit technique, WSN presents a diversified trend. The wireless sensor network is more applicable to the different range of applications, for example, the remote health monitoring of human body vital signs, the management of growing status of agriculture plants, monitoring of the forest tire and etc. However, as the special nature of medical health care, the transmission delay, quality of service and power consumption of the special wireless communication has more certain requirements, especially in the long time continuous monitoring application.This thesis will focus on the one brench of the wireless sensor network, physiological status monitoring system or the BAN(Body Area Network), which is a cross-disciplinary area and a revolutionary work of medical health monitoring system. Physiological status monitoring system combines the real-time updating biomedical data with the continuous and dynamic health care closely through wireless communication technique. A great deal of intelligent biomedical sensors can be integrated to a wireless physiological status monitoring system, and the system can be used for prevention, diagnosis and instantaneous caring of sufferer’s condition.This thesis presents a solution for the high-efficiency problem of physiological status monitoring system based on biomedical signals. The algorithm this thesis raises is based on biomedical signals. It balances measurements and reconstruction accuracy. The simulation results show that the algorithm can reduce sample rate, thus reduce power consumption on sampling, compression, transferring and storing biomedical datas.Based on the special nature of biomedical signals, a kind of wireless physiological monitoring system was firstly designed, which could acquire and process multiple physiological signals. For reducing the total power consumption, a low-power scheduling scheme is further proposed so as to provide long-term continuous sensing for wearer’s health and safety and extend the operational lifetime of the physiological status monitoring system.