Phonocardiographic signal analysis method using a modified hidden Markovmodel
Abstract Auscultation is an important diagnostic indicator for cardiovascularanalysis. Heart sound classification and analysis play an important role in the auscultativediagnosis. This study uses a combination of Mel-frequency cepstral coefficient (MFCC) and hiddenMarkov model (HMM) to efficiently extract the features for pre-processed heart sound cycles for thepurpose of classification. A system was developed for the interpretation of heart sounds acquired byphonocardiography using pattern recognition. The task of feature extraction was performed usingthree methods: time-domain feature, short-time Fourier transforms (STFT) and MFCC. (more…)
