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Pulse diagnosis with finger pulse-taking is popular in Chinese culture. Wrist pulse waveform analysis has becoming common in Traditional Chinese Medicine (TCM) engineering and diagnosis modernization. An improved two-step classification method is proposed in this paper to differentiate seven common TCM pulse conditions, include four mono and three concurrent pulses. For both time-domain and frequency-domain...
In this paper, wavelet packet energy entropy (WPEE) and support vector machine (SVM) were utilized to detect and classify auscultation signals in Traditional Chinese Medicine (TCM). The auscultation signals of health and qi-vacuity and yin-vacuity subjects were collected from the outpatient by Shanghai University of TCM. And the wavelet packet decomposition (WPD) at level 6 was employed to split more...
This study aims at utilizing mutual information algorithm to make an objective and quantitative research for the pulses in Traditional Chinese Medicine (TCM) diagnosis. The normal pulse signals, slippery pulse signals and taut pulse signals were collected from the outpatients by Shanghai University of TCM. Some typical pulse signals from all these classes were selected as the templates to be matched...
Syndrome is a unique TCM concept, which is an abstractive collection of symptoms and signs. Several modern algorithms have been applied to classify syndromes, but no satisfied results have been obtained because of the complexity of diagnosis procedure. Support vector machine (SVM) has been found to be very efficient to solve the classification problems, especially for binary classification with good...
The cardiovascular system is complex system containing many nonlinearities. Pulse signals are nonlinear reflecting the status of the heart and the vascular system. Sample entropy analysis can quantify signal regularity or the system complexity generating the signal. In this paper the wrist pulse signals of healthy group and coronary heart disease group are analyzed and studied with sample entropy...
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