Study Of Recognition Based On Wavelet Analysis For The Manifestations Of The Pulse In Chinese Medicine

It has much significance of the Human Pulse(HP) objectification to success and develop the study of Pulse in Chinese Medicine. Signal processing and pattern recognition of Human Pulse are studied and discussed in this thesis on the basis of the research and development of A! recognition system for Human Pulse.Based on the characteristics of Human Pulse, Wavelet Transform(WT) is originally used to process and analysis it. Wavelet analysis has a good qualities both in time domain and frequency domain and is an ideal tool in analyzing unsteady signal, so it is used to detect the singularity of Human Pulse and extract the features of Human Pulse in time-domain. Human Pulse is characterized by a new feature which is the energy of its wavelet transform in different scales. BP Neural Network(NN) is used to classify the Human Pulse according to its spectra features and new features extracted by Wavelet Transform. The results show that different inputs of features will lead to different outcomes of pattern recognition. In spite of limited training samples, the method in this thesis is superior to traditional Pattern Recognition methods if choose suitable features to be input-cell such as features extracted by Wavelet Transform. The results also manifest that it is feasible to use Neural Network in Pulse processing.A data acquisition system base on serial communication is designed according to the characteristics of manifestations of Human Pulse.