A novel heart sound activity detection framework for automated heart sound analysis
Publication Type:Journal Article
Source:Biomedical Signal Processing and Control, Elsevier Ltd, Volume 13, Number 1, p.174-188 (2014)
Keywords:algorithm, aorta valve regurgitation, article, Audio-visual, automated robust heart sound activity detection, Automation, Cardiac signals, Cardiology, carotid artery pulse, data base, entropy, heart murmur, heart sound, Heart sound analysis, Heart sounds, noise reduction, Phonocardiograms, Phonocardiography, priority journal, QRS complex, RR interval, sensitivity analysis, signal noise ratio, Signal processing, T wave
In automated heart sound analysis and diagnosis, a set of clinically valued parameters including sound intensity, frequency content, timing, duration, shape, systolic and diastolic intervals, the ratio of the first heart sound amplitude to second heart sound amplitude (S1/S2), and the ratio of diastolic to systolic duration (D/S) is measured from the PCG signal. The quality of the clinical feature parameters highly rely on accurate determination of boundaries of the acoustic events (heart sounds S1, S2, S3, S4 and murmurs) and the systolic/diastolic pause period in the PCG signal. Therefore, in this paper, we propose a new automated robust heart sound activity detection (HSAD) method based on the total variation filtering, Shannon entropy envelope computation, instantaneous phase based boundary determination, and boundary location adjustment. The proposed HSAD method is validated using different clean and noisy pathological and non-pathological PCG signals. Experiments on a large PCG database show that the HSAD method achieves an average sensitivity (Se) of 99.43% and positive predictivity (+P) of 93.56%. The HSAD method accurately determines boundaries of major acoustic events of the PCG signal with signal-to-noise ratio of 5 dB. Unlike other existing methods, the proposed HSAD method does not use any search-back algorithms. The proposed HSAD method is a quite straightforward and thus it is suitable for real-time wireless cardiac health monitoring and electronic stethoscope devices. © 2014 Elsevier Ltd.
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Cite this Research Publication
V. N. Varghees and Dr. K. I. Ramachandran, “A novel heart sound activity detection framework for automated heart sound analysis”, Biomedical Signal Processing and Control, vol. 13, pp. 174-188, 2014.