Use of the fast fourier transform for frequency analysis of the first heart sound in normal man

Yoganathan, Ajit P.; Gupta, Ramesh K.; Udwadia, Firdaus E.; Miller, Jonathan; Corcoran, W. H.; Sarma, Radha J.; Johnson, Jeff; Bing, Richard J.

doi:10.1007/bf02477093

Cited by 62 publications

(16 citation statements)

References 10 publications

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“…Ajit et al [37] used simple FFT for localization and classification without any further processing as frequency contents of different heart sounds have different spectrum contents. Authors in [29] used both frequency-and energy-based features for classification while Mandeep and Cheema [30] used time, frequency, cepstrum, and statistical features for localization as well as for classification.…”

Section: Mel(fmentioning

confidence: 99%

Localization and classification of heart beats in phonocardiography signals —a comprehensive review

Ismail

Siddiqi

Akram

2018

EURASIP J. Adv. Signal Process.

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Phonocardiogram (PCG) signal represents recording of sounds and murmurs resulting from heart auscultation. Analysis of these PCG signals is critical in diagnosis of different heart diseases. Over the years, a variety of methods have been proposed for automatic analysis of PCG signals in time, frequency, and time-frequency domains. This paper presents a comprehensive survey of different methods proposed for automatic analysis of PCG signals with the objective to evaluate the current state-of-the-art and to determine the potential domains of effective analysis. An important aspect of our contribution is that the review is carried out as a function of domains of analysis rather than simply discussing different methods. Our method further splits analysis into pre-processing, localization, and classification, and details are presented in terms of techniques and classifiers used during these phases. Finally, results are summarized for normal heart beat, noisy heart beat, and different pathologies using metrices like accuracy and detection rate. In addition to time and frequency domain, time-frequency based methods including wavelet, empirical mode decomposition (EMD) and time-frequency representation (TFR) are selected for detailed analysis. The review concludes that the time-frequency representations like EMD and wavelets represent areas of exploration in future along with perspective of using different time-frequency techniques together.

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Section: Mel(fmentioning

confidence: 99%

Localization and classification of heart beats in phonocardiography signals —a comprehensive review

Ismail

Siddiqi

Akram

2018

EURASIP J. Adv. Signal Process.

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“…Beyond the presented time-domain analysis, examining the spectrum of this periodic signal can be instructive for students, and it can be easily calculated in the LabVIEW environment by built-in functions. Furthermore, spectral analysis of the heart sounds are widely used in diagnostics too, which can also be implemented in undergraduate projects as well [33].…”

Section: Further Analysis Of the Processed Datamentioning

confidence: 99%

Digital phonocardiographic experiments and signal processing in multidisciplinary fields of university education

Nagy¹,

Vadai²,

Gingl³

2017

Eur. J. Phys.

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During the embargo period (the 12 month period from the publication of the Version of Record of this article), the Accepted Manuscript is fully protected by copyright and cannot be reused or reposted elsewhere. As the Version of Record of this article is going to be / has been published on a subscription basis, this Accepted Manuscript is available for reuse under a CC BY-NC-ND 3.0 licence after the 12 month embargo period.

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“…Alternative approaches, based on measurement of myocardial vibrations during isovolumic systole, recently have been developed. These vibrations generate audible and inaudible components, which can be measured by an accelerometer 3–5 . Preliminary studies performed with an implantable micromass tip‐mounted accelerometer incorporated in a pacing lead connected to a pacemaker (Sorin Biomedica, Salugia, Italy) have shown that changes in the peak of these myocardial vibrations (peak endocardial acceleration [PEA]) are closely related to changes in max d P /d t 6–11 .…”

Section: Introductionmentioning

confidence: 99%

Validation of a New Noninvasive Device for the Monitoring of Peak Endocardial Acceleration in Pigs: Implications for Optimization of Pacing Site and Configuration

Bordachar

Labrousse

Ploux

et al. 2008

Cardiovasc electrophysiol

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Use of the fast fourier transform for frequency analysis of the first heart sound in normal man

Cited by 62 publications

References 10 publications

Localization and classification of heart beats in phonocardiography signals —a comprehensive review

Localization and classification of heart beats in phonocardiography signals —a comprehensive review

Digital phonocardiographic experiments and signal processing in multidisciplinary fields of university education

Validation of a New Noninvasive Device for the Monitoring of Peak Endocardial Acceleration in Pigs: Implications for Optimization of Pacing Site and Configuration

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