Detection of the first heart sound using a time-delay neural network

A method for detecting the first heart sound (SI) using a time-delay neural network (TDNN) is reported The network consists of a single hidden layer, with time-delay links connecting the hidden units to the time-frequency energy coefficients of a Morlet wavelet decomposition of the input phonocardiogram (PCG) signal. The neural network operates on a 200 msec sliding window with each time-delay hidden unit spanning 100 msec of wavelet data. Heart sounds were recorded from 30 subjects for 20 seconds at each of four standard auscultatory sites using a commercially available electronic stethoscope. A training set comprised of half of the heartbeats from 20 randomly selected subjects was created The network was trained on this set and tested on the full data set. The average performance is 1.6% deletion error and 2.2% insertion error. This level of S1 detection is considered satisfactory for analysis of the phonocardiogram signal.