Title :
A wavelet packet based pulse waveform analysis for cholecystitis and nephrotic syndrome diagnosis
Author :
Guo, Qing-li ; Wang, Kuan-Quan ; Zhang, Dong-yu ; Li, Nai-min
Author_Institution :
Sch. of Comput. Sci. & Technol., Harbin Inst. of Technol., Harbin
Abstract :
Traditional Chinese Pulse Diagnosis (TCPD), one of the four diagnostic methods of Traditional Chinese Medicine (TCM), had been proved to be clinically valid in Chinese Medicine history. Different from most previous work which focused on the diagnosis of cardiovascular diseases, this paper further investigated the possibility of diagnosing cholecystitis and nephrotic syndrome using the pulse waveform data. After the pre-processing, the pulse waveform signals were decomposed into a given level by Wavelet Packet Transform and the best basis was picked out by Shannon entropy criterion. Then, subband energies contained in the best basis were extracted as features and the support vector machine classifiers were trained. Experimental results indicated that the proposed method can effectively discriminate these two kinds of diseases.
Keywords :
diseases; entropy; feature extraction; kidney; medical diagnostic computing; medical signal processing; signal classification; support vector machines; waveform analysis; wavelet transforms; Chinese medicine history; Shannon entropy; cholecystitis syndrome diagnosis; disease; feature extraction; nephrotic syndrome diagnosis; pulse waveform analysis; subband energy; support vector machine classifier; traditional Chinese pulse diagnosis; wavelet packet transform; Cardiovascular diseases; Data mining; Entropy; Feature extraction; History; Medical diagnostic imaging; Support vector machines; Wavelet analysis; Wavelet packets; Wavelet transforms; Pulse waveform; SVM; wavelet packet transform;
Conference_Titel :
Wavelet Analysis and Pattern Recognition, 2008. ICWAPR '08. International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-2238-8
Electronic_ISBN :
978-1-4244-2239-5
DOI :
10.1109/ICWAPR.2008.4635834