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Automated PCG signal delineation method for heart sound analysis

Publication Type : Conference Paper

Thematic Areas : Advanced Materials and Green Technologies

Publisher : Twentieth National Conference on Communications (NCC), 2014

Source : Twentieth National Conference on Communications (NCC), 2014 (2014)

Keywords : Acoustics, audio-visual stethoscope, automated PCG signal delineation method, background noises, candidate waveform, endpoint determination, filtering theory, hard-thresholding rule, Heart, Heart sound analysis, Hilbert transformation, Hilbert transforms, medical signal processing, Noise measurement, noisy pathological PCG signals, nonpathological PCG signals, peak-amplitude determination, Phonocardiography, real-time wireless cardiac health monitoring, Signal to noise ratio, smooth energy envelope computation, total variation filtering

Campus : Coimbatore

School : School of Engineering

Center : Center for Excellence in Advanced Materials and Green Technologies, Computational Engineering and Networking

Department : Civil, Mechanical Engineering

Verified : Yes

Year : 2014

Abstract : This paper presents an automated PCG signal delineation method for real-time wireless cardiac health monitoring and audio-visual stethoscope applications. The proposed method comprises the steps of: preprocessing, total variation filtering, smooth energy envelope computation, peak-amplitude determination and endpoint determination. The total variation filter is used to smooth out the background noises and preserves the heart sound components. The endpoints of heart sounds (S1, S2, S3, S4 and murmurs) are determined by using smooth energy envelope and hard-thresholding rule. The peaks of the heart sounds are determined by using candidate waveform obtained from Hilbert transformation of smooth envelope. The proposed delineation method is validated by using different clean and noisy pathological and non-pathological PCG signals. Experiments on a large PCG database show that the proposed method achieves an average sensitivity (Se) of 99.56% and positive predictivity (+P) of 96.97%, with the maximum average delineation error of 9.08-msec, 0.483-msec and 7.834-msec for endpoints of heart sounds, peak-locations and durations, respectively.

Cite this Research Publication : V. N. Varghees and Dr. K. I. Ramachandran, “Automated PCG signal delineation method for heart sound analysis”, in Twentieth National Conference on Communications (NCC), 2014 , 2014.

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