Pattern Classification for Doppler Ultrasonic Wrist Pulse Signals
Wrist pulse signal contains important information about the health status of a person and it has been used in Traditional Chinese Medicine for a long time. In this work, digitalized wrist pulse signals from patients with different diseases as well as healthy persons are collected by a Doppler ultrasonic device. Two methods, namely, the wavelet method and the auto regressive prediction error (ARPE) method, are proposed to analyze the pulse signals and distinguish patients from healthy persons. Distinctive features are first extracted from the pulse signals and then the support vector machine (SVM) is used for classification. The applicability of the methods is investigated using wrist pulse signals collected from 50 healthy persons and 74 patients. The results illustrate a great promise of the proposed methods for computerized pulse signal analysis.
Traditional Chinese pulse diagnosis wavelet transform auto regressive model SVM
Yinghui Chen Lei Zhang David Zhang Dongyu Zhang
Dept.of Computing,The Hong Kong Polytechnic University,Kowloon,Hong Kong,China
国际会议
北京
英文
1-4
2009-06-11（万方平台首次上网日期，不代表论文的发表时间）