| Author |
Abbas, Abbas K. (Abbas Khudair)
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| Title |
Phonocardiography signal processing / Abbas K. Abbas, Rasha Bassam. |
| OCLC |
200904BME031 |
| ISBN |
9781598299762 (electronic bk.) |
|
9781598299755 (pbk.) |
| ISBN/ISSN |
10.2200/S00187ED1V01Y200904BME031 doi |
| Publisher |
San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool Publishers, [2009] |
|
©2009 |
| Description |
1 electronic text (xxi, 194 pages : illustrations\.) : digital file. |
| LC Subject heading/s |
Phonocardiography.
|
|
Signal processing.
|
| SUBJECT |
Phonocardiography.
|
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Auscultation technique.
|
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Signal processing.
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Signal filtering.
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Heart sounds.
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Stethoscope microphone.
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Cardiac acoustic modeling.
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Wavelets analysis.
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Data classification.
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Spectral estimation and analysis.
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PCG classification.
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Phonocardiography calibration.
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Intracardiac phonocardiography.
|
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Cardiac acoustic imaging.
|
| System details note |
Mode of access: World Wide Web. |
|
System requirements: Adobe Acrobat reader. |
| Bibliography |
Includes bibliographical references (pages 181-189). |
| Contents |
Introduction to phonocardiography signal processing -- Introduction -- Signal processing -- Overview of signal processing -- Application of signal processing in biomedical engineering -- Cardiovascular physiology -- Cardiac cycle -- Cardiac pressure profile -- Ventricular pressure-volume loops -- Cardiac electrical conduction system -- Physiology of the heart sound -- Abnormal heart sound pattern -- Heart sound as hemodynamic index -- Auscultation technique -- Summary -- Phonocardiography acoustics measurement -- Dynamics of phonocardiography -- Vibratory PCG signal spectrum -- Band-pass filter versus high-pass filter -- Phonocardiography calibration -- Investigation of normal cardiac cycle in multi-frequency band -- High-frequency vibrations bands (500-1000 Hz and 1000-2000 Hz) -- Ultra-low frequency tracing (linear frequency band) -- Medium-low frequency tracing (60-120 Hz) -- Medium-high frequency band (120-240 Hz and 240-480 Hz) -- The heart tones production mechanism -- Stethoscope transducer modeling -- Microphone transducer -- Acoustic coupling -- Summary -- PCG signal processing framework -- Phonocardiography signal presentation -- Denoising and signal filtering techniques -- PCG signal presentation -- Cardiac sound modeling and identification -- S1 cardiac sound modeling -- S2 cardiac sound modeling -- Modeling abnormal heart sound S3 and S4 -- Model-based phonocardiography acoustic signal processing -- Future perspectives -- Pacemaker heart sound acoustic detection -- Physiological monitoring of blood pressure with phonocardiography -- Automated blood pressure-PCG based measurement -- Transit times extraction and estimation -- Hemodynamics and transit intervals modulation -- Summary -- Phonocardiography wavelets analysis -- Wavelets -- Historical perspective -- Fourier analysis -- Wavelets versus fourier analysis -- Haar wavelet -- Debauchies (Db) wavelet -- Subband coding -- Wavelets decomposition -- Continuous wavelet transform -- Discrete wavelet transform -- Pattern detection based on adaptive wavelets analysis -- Summary -- Phonocardiography spectral analysis -- PCG signal spectral analysis -- Energy spectral density of deterministic signals -- PCG spectral estimation -- Nonparametric method for phonocardiography spectral estimation -- Effect of signal sampling -- Windowing, periodic extension, and extrapolation -- Periodogram method -- Modified periodogram method -- Parametric method for phonocardiography spectral estimation -- PCG ARMA spectral estimation -- ARMA modeling approach -- Phonocardiography ESPRIT method -- Spectral-window method for PCG-signal processing -- Digital stethoscope system (DS) -- Visual electronic stethoscope -- Summary -- PCG pattern classification -- Introduction -- PCG pattern classification methods -- K-means clustering method -- Fuzzy c-means classification algorithm -- Principal component analysis (PCA) -- Higher-order statistics PCG classification PCG-HOS -- Independent component analysis (ICA) method -- PCG classification based on artificial neural network (ANN) -- General concept of ANN -- Neural network topologies -- PCG diagnosis with self-organizing mapping (SOM) -- Self-organization principle -- Bayes classifier -- PCG signal Bayesian parameter estimation -- Phonocardiography hemodynamic identification -- PCG pattern classification application example -- Delimitation of systoles and diastoles Assessment -- Time and frequency decomposition of systoles and diastoles -- Extraction of PCG power and frequency feature vectors -- Correction of feature vectors for S1/S2 remnants -- Future trends in phonocardiography pattern classification -- Summary -- Special application of phonocardiography -- Introduction -- Fetal phonocardiography signal processing -- Fetal sound detection medical sensors -- Challenges and motivation -- Intracardiac phonocardiography (ICP) signal processing -- ICP measurement device -- ICP signal processing -- ICP acoustic transmission properties -- Separation of phonocardiography from phonospirography signal -- Phonocardiogram cardiac pacemaker driven system -- Basis of cardiac supportive device -- Summary -- Phonocardiography acoustic imaging and mapping -- Introduction -- Motivation and problem formulation -- PATI-experimental setup and system prototyping -- Acoustic array signal processing -- Adaptive beam-forming in cardiac acoustic imaging -- Adaptive beam former with minimum-variance distortionless response -- Heart sounds physiological modeling based on PATI method -- Summary. |
| Restrictions |
Abstract freely available; full-text restricted to subscribers or individual document purchasers. |
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Access may be restricted to authorized users only. |
|
Unlimited user license access |
| NOTE |
Compendex. |
|
INSPEC. |
|
Google book search. |
| Abstract |
The auscultation method is an important diagnostic indicator for hemodynamic anomalies. Heart sound classification and analysis play an important role in the auscultative diagnosis. The term phonocardiography refers to the tracing technique of heart sounds and the recording of cardiac acoustics vibration by means of a microphone-transducer. Therefore, understanding the nature and source of this signal is important to give us a tendency for developing a competent tool for further analysis and processing, in order to enhance and optimize cardiac clinical diagnostic approach. This book gives the reader an inclusive view of the main aspects in phonocardiography signal processing. |
| NOTE |
Google scholar. |
| Additional physical form available note |
Also available in print. |
| General note |
Part of: Synthesis digital library of engineering and computer science. |
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Title from PDF t.p. (viewed on May 8, 2009). |
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Series from website. |
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