The Application Of Bayesian Arithmetic In Human Physiology Behavior Recognition

At present, with constant progress of scientist and technology, China's health care industry has been developed rapidly, which meets the growing demand of people for medical services. Meanwhile, the improvements of information technology and wireless information network caused a major change in the area of medical services. The concept of tele-medicine appears in this background. Tele-medicine can provide even more rapid and convenient medical services through the wireless network technology and the current level of advanced medical care for human beings. It is reported, currently, the custody of the elderly, chronically ill patients and patients after operation has become a major problem in the social health care industry.Some research on the tracking of human behavior of Tele-medicine has been done in this thesis, which includes real-time monitoring and recording of the conduct of human body's day-to-day state and warning when abnormal gait information is to be found. At the same time, to do a record of day-to-day information and physiological information and the preservation of individual proprietary database will provide a good basis for the diagnosis in the future of the medical treatment. It has made good identify results, which advanced intelligent Bayesian algorithm into the behavior and gait recognition in the above mentioned tele-monitoring process.In this thesis, the process of identification of human behavior includes collecting physiological signals through the wireless local area network firstly, and then classifying the collection of physiological signals, conversing victory signals into discrete ones, at last achieving some common recognition of the state of human behavior combined with a Bayesian algorithm. The experiments have proved that the method using Bayesian algorithm has been greatly improved recognition accuracy of human act. The algorithm is simple and reliable, asking with less original data signal but higher recognition rate. In addition, the method can be applied to other areas of BSN.