Heart Sound Measurement and Analysis System with Digital Stethoscope

This paper is concerned with the cardiac sound measurement and analysis system for in-home use of heart abnormality monitoring. The heart sound acquiring system is consisted of a traditional chest-piece, earphone, microph- one, IC recorder. The recorded data is transmitted to a computer by USB interface for analysis based on cardiac sound characteristic waveform method (CSCW), which is extracted from an analytical model of single degree-of-freedom(SDOF). Furthermore, the characteristic parameters (T1, T2, T11, T12) are defined by the time intervals between the crossed points of the CSCW and a threshold value (THV), which are related to the first sound and the second sound and are used for discriminating normal and abnormal heart sounds. Also, an easy-understanding graphical representation for these parameters is considered, so that, even for an inexperienced user he or she is able to monitor his or her pathology progress easily. Finally, a case study on the abnormal/normal cardiac sounds is demonstrated to validate the usefulness and efficiency of this proposed system and the cardiac sound characteristic waveform method.

[1]  Yang Lei Short-time fourier transform analysis of the phonocardiogram signal , 2004 .

[2]  Zhongwei Jiang,et al.  A wearable cardiorespiratory sensor system for analyzing the sleep condition , 2008, Expert Syst. Appl..

[3]  Stefan Nilsson,et al.  The Circulatory System , 1983 .

[4]  Derek Abbott,et al.  Optimal wavelet denoising for phonocardiograms , 2001 .

[5]  Mariusz Kruk,et al.  Predictors of outcome and the lack of effect of percutaneous coronary intervention across the risk strata in patients with persistent total occlusion after myocardial infarction: Results from the OAT (Occluded Artery Trial) study. , 2008, JACC. Cardiovascular interventions.

[6]  M.N. Taib,et al.  Classification of heart sounds using a multilayer feed-forward neural network , 2005, 2005 Asian Conference on Sensors and the International Conference on New Techniques in Pharmaceutical and Biomedical Research.

[7]  Lisha Sun,et al.  A novel method of time-frequency representation and its application to biomedical signal processing , 2004, Proceedings 7th International Conference on Signal Processing, 2004. Proceedings. ICSP '04. 2004..

[8]  N BLOOM Practical cardiology. , 1957, Virginia medical monthly.

[9]  Chung-Hsien Wu,et al.  Computer-aided analysis and classification of heart sounds based on neural networks and time analysis , 1995, 1995 International Conference on Acoustics, Speech, and Signal Processing.

[10]  Metin Akay,et al.  Automated noninvasive detection of coronary artery disease using wavelet-based neural networks , 1994, Proceedings of 16th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[11]  Tamer Ölmez,et al.  Determination of features for heart sounds by using wavelet transforms , 2002, Proceedings of 15th IEEE Symposium on Computer-Based Medical Systems (CBMS 2002).

[12]  William Thornton,et al.  Auscultation of the Heart , 2002 .

[13]  Eugenio Cervesato,et al.  Hydroxymethylglutaryl coenzyme-a reductase inhibitors delay the progression of rheumatic aortic valve stenosis a long-term echocardiographic study. , 2009, Journal of the American College of Cardiology.

[14]  Karatza Ageliki,et al.  Diagnostic value of cardiac auscultation in the initial assessment of asymptomatic neonates with heart murmurs , 2008 .

[15]  M. Cheitlin,et al.  Hydroxymethylglutaryl Coenzyme-A Reductase Inhibitors Delay the Progression of Rheumatic Aortic Valve Stenosis: A Long-Term Echocardiographic Study , 2010 .

[16]  C R Thompson,et al.  Comparison of short-time Fourier, wavelet and time-domain analyses of intracardiac sounds. , 1993, Biomedical sciences instrumentation.

[17]  Zhongwei Jiang,et al.  A cardiac sound characteristic waveform method for in-home heart disorder monitoring with electric stethoscope , 2006, Expert Syst. Appl..

[18]  D. Barschdorff,et al.  Automatic phonocardiogram signal analysis in infants based on wavelet transforms and artificial neural networks , 1995, Computers in Cardiology 1995.