The Research of Heart Sound Signal Energy Detection System

Article Preview

Abstract:

Aimed to enhance the efficiency of heart sound signal energy detection, a kind of heart sound signal energy detection system based on LabVIEW 8.5 is developed in this paper. The system makes use of saddlebag of signal processing and analysis tool of LabVIEW to detect and analyze energy of the heart sound signal. The system can detect, display, record and analyze the energy of heart sound signal. From the results of experiments, the detection and analysis of heart sound signal energy have importance clinical value to the earlier period diagnosis of coronary artery disease (CAD).

You might also be interested in these eBooks

Info:

Periodical:

Pages:

3003-3007

Citation:

Online since:

October 2011

Authors:

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2012 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] Akay A M, Semmlow J L, Welkowitz W, et al. Detection of coronary occlusions using autoregressive modeling diastolic heart sound[J] . IEEE trans. BME, 1990, 37 : 366-373.

DOI: 10.1109/10.52343

Google Scholar

[2] Yasemin Akay, et al. Noninvasive Acoustical Detection of Coronary Artery Disease: A Comparative Study of Signal Processing Methods[J] . IEEE trans. BME, 1993, 40 : 571-578.

DOI: 10.1109/10.237677

Google Scholar

[3] Z. Gau, et al. Time-frequency distributions of non-stationary signals based on a Bessel kernel [J]. IEEE Trans. SP, 1994, 42(2) : 1700-1707.

DOI: 10.1109/78.298277

Google Scholar

[4] Wood JC, Daniel TB. Time - frequency analysis of the first heart sound [J]. IEEE Eng Med Biol, 1995, 14(2): 144-151.

DOI: 10.1109/51.376751

Google Scholar

[5] Durand LG, Pibarot P. Digital signal processing of the phonocardiogram: Review of the most recent advancements [J]. Crit Rev Biomed Eng, 1995, 23(3/4): 163-219.

DOI: 10.1615/critrevbiomedeng.v23.i3-4.10

Google Scholar

[6] Sava H, Pibarot P, Durand LG. Application of the matching pursuit method for structural decomposition and averaging of phonocardiographic signals [J]. Med Biol Eng Comput, 1998, 36 : 302-308.

DOI: 10.1007/bf02522475

Google Scholar

[7] Xu JP, Durand LG, Pibaro P. Extraction of the aortic and pulmonary components of the second heart sound using a nonlinear transient chirp signal model [J]. IEEE Trans Biomed Eng, 2001, 48(3) : 277-283.

DOI: 10.1109/10.914790

Google Scholar

[8] Tong S, Bezerianos A, Paul J, et al. Removal of ECG interference from the EEG recordings in small animals using independent component analysis [J]. Journal of Neuroscience Methods, 2001, 108 : 11-17.

DOI: 10.1016/s0165-0270(01)00366-1

Google Scholar

[9] WU Kai,LIN Shao-jie, WU Xiao-ming, ZHANG Li-li. Design of virtual instrument for measuring phonocardiogram based on LabVIEW [J]. Chinese Medical Equipment Journal, 2007, (03): 19-21.

Google Scholar

[10] WU Xiao-ming, WU Kai, CEN Ren-jing, ZENG Wei-jie, ZHI Xiao-xing. Development of a multiparametric remote monitoring system for heart function [J]. Chinese Medical Equipment Journal, 2004, (04): 17-18.

Google Scholar

[11] Kang Feng, Ye Xue-song, Wang Ping, Chen Yu-quan. Research on signal processing of heart sounds to diagnose coronary artery disease [J]. Journal of ZheJiang University (Engineering Science). 2004, (01): 99-103.

Google Scholar