Separation of heart sound signal from noise in joint cycle frequency-time-frequency domains based on fuzzy detection.
Noise is generally unavoidable during recordings of heart sound signal. Therefore, noise reduction is one of the important preprocesses in the analysis of heart sound signal. This was achieved in joint cycle frequency-time-frequency domains in this study. Heart sound signal was decomposed into components (called atoms) characterized by time delay, frequency, amplitude, time width, and phase. It was discovered that atoms of heart sound signal congregate in the joint domains. On the other hand, atoms of noise were dispersed. The atoms of heart sound signal could, therefore, be separated from the atoms of noise based on fuzzy detection. In a practical experiment, heart sound signal was successfully separated from lung sounds and disturbances due to chest motion. Computer simulations for various clinical heart sound signals were also used to evaluate the performance of the proposed noise reduction. It was shown that heart sound signal can be reconstructed from simulated complex noise (perhaps non-Gaussian, nonstationary, and colored). The proposed noise reduction can recover variations in the both waveform and time delay of heart sound signal during the reconstruction. Correlation coefficient and normalized residue were used to indicate the closeness of the reconstructed and noise-free heart sound signal. Correlation coefficient may exceed 0.90 and normalized residue may be around 0.10 in 0-dB noise environment, even if the phonocardiogram signal covers only ten cardiac cycles.
Tang
Hong
H
Department of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China. tanghong@dlut.edu.cn
Li
Ting
T
Park
Yongwan
Y
Qiu
Tianshuang
T
D000328:Adult; D001024:Aortic Valve Stenosis / Q000503:physiopathology; D003198:Computer Simulation; D004562:Electrocardiography / Q000379:methods*; D017143:Fuzzy Logic; D006347:Heart Sounds / Q000502:physiology*; D006801:Humans; D008297:Male; D010701:Phonocardiography / Q000379:methods*; D012815:Signal Processing, Computer-Assisted