Heart sound localization in chest sound using temporal fuzzy c-means classification

Most of heart sound cancellation algorithms to improve the quality of lung sound use information about heart sound locations. Therefore, a reliable estimation of heart sound localizations within chest sound is a key issue to enhance the performance of heart sound cancellation algorithms. In this paper, we present a new technique to estimate locations of heart sound segments in chest sound using the temporal fuzzy c-means (TFCM) algorithm. In applying the method, chest sound is first divided into frames and then for each frame, the entropy feature is calculated. Next, by means of these features, the TFCM algorithm is applied to classify a chest sound into two classes: heart sound (heart sound containing lung sound) and non-heart sound (only lung sound). The proposed method was tested on the database used in the liteature and experimetal results are compared with the baseline which is a well-known method in the literature. The experimental results show that the proposed method outperforms the baseline method interms of false negative rate (FNR), false positive rate (FPR) and accuracy (ACC).