Frequency of diastolic third and fourth heart sounds with myocardial ischemia induced during percutaneous coronary intervention

Lee, Eun-Young; Michaels, Andrew D.; Selvester, Ronald H.; Drew, Barbara J.

doi:10.1016/j.jelectrocard.2008.07.009

Cited by 7 publications

(5 citation statements)

References 24 publications

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“…In the periods of S 1 and S 2 , there is no mutation and both the third and fourth sounds, S 3 and S 4 , are weak. If the observation time is reduced to a very short range, an approximately stable signal can be achieved, i.e., the heart sound signal is a time quasi-stable signal [8][9][10]. Therefore, a wavelet family of heart sound signals can be used to synthesize a set of simulated heart sounds.…”

Section: Model Of Heart Soundsmentioning

confidence: 99%

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Research on heart sound identification technology

Cheng

Liu

et al. 2011

Sci. China Inf. Sci.

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In this article, both the basic principles and the experimental methods of identity recognition technology based on heart sounds are addressed. First, the characteristics of heart sounds and the feasibility of heart sounds as a biometric were analyzed. A synthetic model of heart sounds was then developed based on a family of wavelets; Finally, the characteristic parameters of heart sounds were extracted by using the heart sounds linear band frequency cepstra (HS-LBFC) with a specified configuration, and the similarity distance was adopted for heart sound identification. To highlight the difference in two heart sound signals between the time and frequency domains, a construction method of the heart sound wavelet, a calculation method of the parameters of a synthetic model, selection of the characteristic parameters of heart sounds and the corresponding data processing technology were examined. The experimental results showed that the proposed method exhibited excellent performance and practicability.Keywords biometric, wavelet family of heart sounds, synthetic model of heart sounds, heart sounds linear band frequency cepstra (HS-LBFC)

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Section: Model Of Heart Soundsmentioning

confidence: 99%

“…According to the two-scale equation, and the construction of wavelet bases can be obtained by calculating low-pass filter coefficients. The scaling function φ(x) can also be constructed directly, and then wavelets are generated by the scaling function [10,12].…”

Section: Determination Of the Heart Sound Wavelet Family ψ(T)mentioning

confidence: 99%

Research on heart sound identification technology

Cheng

Liu

et al. 2011

Sci. China Inf. Sci.

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“…Some recent studies have also evaluated the relationship between the level of physician experience and accurate auscultation of heart sound [3]. These investigations mostly claimed that clearly heard S3 and S4 could be seen as markers with high specificity associated with left ventricular dysfunction and improve the detection rate for the patients who are nondiagnostic by standard ECG [1,2]. …”

Section: Discussionmentioning

confidence: 99%

“…Although some studies still demonstrated that the pathological influence of S3 and S4 was under estimation [27,28], heart sounds has already been encompassed in acoustic cardiography which combines ECG and sound information to diagnose myocardial ischemia [2,4,13]. The method we proposed is especially aimed for early detection and auto-alarm for some heart diseases, such as left ventricle dysfunction, congenital heart failure, or myocardial ischemia.…”

Section: Discussionmentioning

confidence: 99%

“…In 2009, E. Lee et al . has proved that patients without clinical ST criteria for ischemia developed new or increased-intensity S3 and S4 during percutaneous coronary intervention induced ischemia [2]. Therefore, the combination of using diastolic heart sounds with the standard ECG as a measurement of ventricular dysfunction may improve the noninvasive diagnosis of myocardial ischemia.…”

Section: Introductionmentioning

confidence: 99%

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Detection of the third and fourth heart sounds using Hilbert-Huang transform

Tseng

Jaw

2012

BioMed Eng OnLine

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BackgroundThe third and fourth heart sound (S3 and S4) are two abnormal heart sound components which are proved to be indicators of heart failure during diastolic period. The combination of using diastolic heart sounds with the standard ECG as a measurement of ventricular dysfunction may improve the noninvasive diagnosis and early detection of myocardial ischemia.MethodsIn this paper, an adaptive method based on time-frequency analysis is proposed to detect the presence of S3 and S4. Heart sound signals during diastolic periods were analyzed with Hilbert-Huang Transform (HHT). A discrete plot of maximal instantaneous frequency and its amplitude was generated and clustered. S3 and S4 were recognized by the clustered points, and performance of the method was further enhanced by period definition and iteration tracking.ResultsUsing the proposed method, S3 and S4 could be detected adaptively in a same method. 90.3% of heart sound cycles with S3 were detected using our method, 9.6% were missed, and 9.6% were false positive. 94% of S4 were detected using our method, 5.5% were missed, and 16% were false positive.ConclusionsThe proposed method is adaptive for detecting low-amplitude and low-frequency S3 and S4 simultaneously compared with previous detection methods, which would be practical in primary care.

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