The Key Technology Of Body Sensor Networks And Accomplishment

The key technology of the body area network is one of the popular researching in modern medical technology, one of the key technologies of the body area network is data processing technology. It is to study data processing in the body area network in our mainly work. Body Area Network is mainly to detect and extract the body physiological signals, and the heart sounds is one of the most important the body physiological signal. With the rapidly development of computer technology and digital information processing technology, there is the mature theory for physiological signal processing. In this paper, it is based on wavelet multi-resolution analysis to process the heart sound signals in the Body Area Network. Experimental results show that the algorithm is not complexity and requirements of hardware is low. It can identify the heart sound in a good way. The main content of this paper is as follows:(1) By the characteristics of the heart sound signal frequency and lesion characteristics frequency, heart sound signal can be decomposition by the way of wavelet multi-resolution.It can be determined by the approximate coefficients that the first heart sound and second heart sounds that its frequency characteristics seen, and it can distinguish the frequency characteristics of the lesions.(2) Characteristics of heart sound signal energy. Based on wavelet multire solution analysis, it can extract the energy characteristics of heart sound signals in different frequency ranges within the eigenvectors of the heart sound signal that frequency and energy distribution for each level different.(3) Identification of heart sound signals. It is based on supporting vector machine classifier designing, supporting vector machine can identify signal classification in the small sample library. There were a library by learning and training some samples, experiments results shows that can be successful heart sound signal recognition in our researching.