文献类型：期刊文献

英文题名：Feature extraction and recognition for pulse waveform in traditional chinese medicine based on hemodynamics principle

作者：Yan, Hai Xia[1]; Wang, Yi Qin[1]; Guo, Rui[1]; Liu, Zhao Rong[2]; Li, Fu Feng[1]; Run, Feng Ying[1]; Hong, Yu Jian[1]; Yan, Jian Jun[3]

机构：[1] Faculty of Basic Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China; [2] Biomechanics Laboratory, Fudan University, Shanghai 201203, China; [3] Center for Mechatronics Engineering, East China University of Science and Technology, Shanghai 200237, China

年份：2010

起止页码：972

外文期刊名：2010 8th IEEE International Conference on Control and Automation, ICCA 2010

收录：EI(收录号：20104213298163)

语种：英文

外文关键词：Diagnosis - Extraction - Classification (of information) - Feature extraction - Nearest neighbor search

摘要：Pulse diagnosis is one of important diagnosis methods in Traditional Chinese Medicine (TCM). Recognition of TCM pulse has received more and more attention in recent years. Extracting proper features is crucial for satisfactory classification. While most of previous methods for feature extraction of TCM pulse have no specific correlation with the mechanism of TCM pulse, a hemodynamics method is used to calculate the pulse waveform velocity (PWV) and pulse reflection factor(R), which reflects the principle of TCM pulse diagnosis. Then K-Nearest Neighbor (KNN) algorithm is employed to classify the data and double cross-validation method is used for accuracy assessment. An average accuracy rate of more than 97.8 % is achieved. It is concluded that the PWV and R may be used as the features for the classification of TCM pulses. ? 2010 IEEE.