Identification Research Of Human Pulses Based On Lifting Wavelet And Clustering Algorithms

As a part of the biomedicalsignals, Pulse signals can reflect the pulse of human physiological and pathological information. Studying it can help us to deepen our understanding on our body, and it could play a great role in disease prevention and treatment. It is the main research purpose in this paper.Wavelet transform is developing very qucikly in a new areas at present, it is a good signal analytical method both in the time and the frequency domains, especially applicable for non-stationary signal processing. But wavelet tranform is not suitable for non-European space's application.In order to compensate for the shortcomings of the traditional wavelet,lifting wavelet generates.Lifting wavelet is not only common, flexible, but also it has effective lifting implementing algorithm. As the finite long filter's decomposition of the multiphase matrix is not unique,and lifting implementing algorithm is not necessarily the same between the same multiphase matrix. Thus, based on previous work, this paper applys lifting wavelet transform to the pulse signals proceeding feature extraction and identification, achieves in two different multiphase matrix decomposition formats and the corresponding lifting implementing algorithm. One of the decomposition formats and the corresponding lifting implementing algorithm is proposed by this paper,then performs lifting wavelet transfom individually to the 40 pulse signals (20 healthy normal persons and 20 heroin addicts), through the scale coefficients, performing feature extraction, the difference between the healthy persons and the heroin addicts can be found,and a primary criterion for measuring the healthy normal persons and the heroin addicts can be obtained.There are 18 cases of the healthy normal persons and 19 cases of the heroin addicts that are detected in the first lifting algorithm, the healthy normal person Z01 and Z10 are misjudged, and the heroin addict B13 is misjudged, too.Also there are 18 cases of the healthy normal persons and 20 cases of the heroin addicts that are detected in the second lifting algorithm, the healthy person Z01 and Z10 are misjudged. Then the two methords are compared between the advantages and disadvantages.This paper also gives the basic concepts and theorise of the fuzzy C-means clustering in detail, and expounds the fuzzy C-means clustering algorithm. Based on the feature extraction of the pulse signals, this paper uses the algorithm to identify the pulse signals between th 20 healthy persons and the 20 heroin addicts. And there is a general result at the beginning, then the misjudged samples are devided by the standard deviation and a good result is achieved.