Yuanyang Li

Detection of the First and Second Heart Sound Using Heart Sound Energy

Detection of the primary sound components in heart sound signal is the first step in automated diagnosis of cardiac abnormality. Although most existing heart sound detection algorithms perform well in normal signals, they usually have no effect on signals with heart murmurs. In this paper, an algorithm based on energy is proposed for robust detection of the first and second heart sound. It improved preprocessing and energy formula in envelope-based algorithm to overcome the interference of noises, which include heart murmurs and background noises, and can detect the accurate boundaries of the first and second heart sounds by constructing time gates. The algorithm has been tested using normal and abnormal clinical data and compared with the normalized average Shannon energy algorithm. The results show that the algorithm has over 96 percent correct ratio. That is superior to the normalized average Shannon energy algorithm.

Identifying Heart Sound Sources through Multi-Channel Acquisition and a 3-D Model

A method of identifying heart sound sources is proposed through a multi-channel synchronous acquisition method and a 3-D model. Many kinds of sound localization methods were used to discover a method suitable for heart sounds. Electronic heart sound sensors were used to record real signals from subjects who were healthy under normal environment. A multi-channel synchronous acquisition method is proposed to remove the error of time delay between the heart sound sensors which are used to record heart sound signals. It is emphasized that the same components of the heart sound should be identified correctly through the physiological characters and reference signals such as ECG. A 3-D model is established to improve the previous models, most of which were used in a 2-D plane. Heart sound sources are identified in a 3-D right-angle reference frame using the coordinates (x, y, z) that can be computed from the equations.