Signal and noise separation in medical diagnostic system based on independent component analysis

The possibility to study graphic recording (PCG -Phonocardiography) of auscultator findings is a helpful diagnostic tool for the clinician and forms the basis of early detection of the heart problems. Due to its dispersed nature and overlapping with breathing sounds Heart Sound Signals (HSS) is difficult to detect and comprehend in conventional PCG. We present a Hardware system utilizing Frequency-Domain Independent Component Analysis (ICA) deploying Direction of Arrival (DOA) and Beamforming (BF) techniques for the suppression of noise which will enhance the quality of HSS and aid the physicians. Such techniques of HSS extraction have been rarely studied in the past. By putting microphone probes at appropriate places on the body we can extract signals of our interest that are S1 and S2 beats produced due to beginning and ending of ventricular contraction respectively. Since the two valves are physically separated, yet close to each other, they can be treated as independent sources and we can treat their beat sequences as independent components. The algorithm was applied to actual mixtures of HSS, extracted from a healthy human subject, in a real environment, with possible signal conditions of saturation, reverberation and noise. The algorithm effectiveness and performance is discussed below.