A Time-Frequency Approach for Discrimination of Heart Murmurs  

作　　者：Sepideh Jabbari Hassan Ghassemian 

机构地区：[1]不详

出　　处：《Journal of Signal and Information Processing》2011年第3期232-237,共6页信号与信息处理（英文）

摘　　要：In this paper, a novel framework based on a time-frequency (TF) approach is proposed for detection of murmurs from heart sound signal. First, a high-resolution TF algorithm, matching pursuit, was used to decompose each heart beat into a series of TF atoms selected from a redundant dictionary. Next, representative components of murmurs were identified by clustering the selected atoms of all the beats into a finite number of clusters. Then, Wigner-Ville distribution of the representative components was used to generate a set of 8 features which were fed to a classifier. Experiments with a dataset consisting of heart sounds from 35 normal and 35 pathological subjects showed a classification accuracy of 95.71% in distinguishing murmurs from normal heart sounds.In this paper, a novel framework based on a time-frequency (TF) approach is proposed for detection of murmurs from heart sound signal. First, a high-resolution TF algorithm, matching pursuit, was used to decompose each heart beat into a series of TF atoms selected from a redundant dictionary. Next, representative components of murmurs were identified by clustering the selected atoms of all the beats into a finite number of clusters. Then, Wigner-Ville distribution of the representative components was used to generate a set of 8 features which were fed to a classifier. Experiments with a dataset consisting of heart sounds from 35 normal and 35 pathological subjects showed a classification accuracy of 95.71% in distinguishing murmurs from normal heart sounds.

关 键 词：PHONOCARDIOGRAM (PCG) MURMUR Matching PURSUIT (MP) TIME-FREQUENCY ATOM Clustering 

分 类 号：R73[医药卫生—肿瘤]