Research On The Identification Method For Pulse Signals Of Druggers

The pulse-diagnosis is a part of the motherland medical four sciences. It is indispensable objective basis of dialectical management. But the qualities and subjectivity of pulse-diagnosis very affected its accuracy and feasibility; this became the limitation factor for the pulse-diagnosis' application, development and communication. Thus, impersonal research of the pulse-diagnosis has important meaning for inheriting and expanding of our country medicine. This paper research the pulse analysis and identified on the base of research and exploitation of the pulse identified system. First designing the system for collecting the pulse signal is introduced. The signal collection system procedure is established by VB in this paper, and the VB has the stronger advantage in the sketch customer interface development.This paper deduced the theorems and formulas of the wavelet transform, and discussed the physics meaning of them, applied and proved them in the processing of the pulse signals, compared to analysis of experiment result by extracting the different characteristic parameter.At the same time, applying the wavelet analysis theory in the processing and analysis, as it is used to extract the abnormal information from the pulse signals of heroin druggers and to obtain the primary judgment criterion which can be used to identify druggers from healthy persons. After the pulse signals of 15 heroin druggers and 15 healthy persons are decomposed into 3 levels, using the wavelet packet transform, the following three identify methods are used to distinguish: (1), the scale spectrum and the total signal energy of every signal are extracted.It is found that the ratio between the sum (i.e., scale-wavelet energy) of the scale spectrum in a specific scale-time region and the total signal energy for heroin druggers is generally higher than that of healthy persons. This method has all 1 subject drugger and healthy person is misjudged. (2), tthe wavelet packet coefficients at level 3 scales are extracted, counting their means as characteristic parameters. Two druggers are judged to healthy persons and one healthy person is judged to drugger. The experiment results of classification show that the method presented in this paper is feasible and effective for detecting the pulse abnormalities of heroin druggers. Meanwhile, the pulse wave of the new 7 normal people applied in the two methods also had got better effect.This paper also deduced the theorems and formulas of the BP neural networks, and gave especial research on algorithm of the BP neural network, which is much helpful for the model recognition. At the basis of using wavelet packet transformation, this paper also uses the BP neural network to identify the 37 pulse signals. (15 heroin druggers, 22 normal healthy people) the 15 pulse signals from the heroin druggers are well picked up, with excellent results to the end.