Recurrence quantification analysis base on wavelet packets for wrist pulse

As the traditional diagnosis in traditional Chinese medicine, wrist pulses reflect the condition of the cardiovascular system which contains much nonlinearity. The linear analysis might not provide the enough useful information for the wrist pulse signals any more, so it is proposed the combination of wavelet packet and recurrence quantification plot analysis to analyze the wrist pulses in this paper. In this paper, 5 kinds of wrist pulse signals, which are the slippery pulses, the normal pulses, the thread pulses, the taut pulses and the slippery and taut pulses, are analyzed by using the recurrence quantification analysis which based on wavelet packets transform, and some results are obtained finally. From recurrence plot and recurrence quantification plot analysis based on wavelet packets transform, the differences can be observed among those 5 kinds of wrist pulses, which mean that the recurrence quantification plot analysis measures are the useful features to distinguish different kinds of traditional Chinese medicine (TCM) wrist pulses for the further classification.