Lung sounds an advanced signal processing perspective /

Lung sounds auscultation is often the first noninvasive resource for detection and discrimination of respiratory pathologies available to the physician through the use of the stethoscope. Hearing interpretation, though, was the only means of appreciation of the lung sounds diagnostic information for...

Full description

Bibliographic Details
Main Author: Hadjileontiadis, Leontios J.
Format: Electronic
Language:English
Published: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool Publishers, c2009.
Series:Synthesis lectures on biomedical engineering (Online) ; # 9.
Subjects:
Online Access:Abstract with links to full text
LEADER 06639nam a2200601 a 4500
001 3393
005 20090109171545.0
006 m e d
007 cr cn |||m|||a
008 090108s2009 caua fsab 000 0 eng d
020 # # |a 9781598297119 (electronic bk.) 
020 # # |a 9781598297102 (pbk.) 
024 7 # |a 10.2200/S00127ED1V01Y200811BME009  |2 doi 
035 # # |a (CaBNvSL)gtp00532334 
040 # # |a CaBNvSL  |c CaBNvSL  |d CaBNvSL 
050 # 4 |a RC76.3  |b .H235 2009 
082 0 4 |a 616.1207544  |2 22 
100 1 # |a Hadjileontiadis, Leontios J. 
245 1 0 |a Lung sounds  |b an advanced signal processing perspective /  |c Leontios J. Hadjileontiadis.  |h [electronic resource] : 
260 # # |a San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) :  |b Morgan & Claypool Publishers,  |c c2009. 
300 # # |a 1 electronic text (vii, 99 p. : ill.) :  |b digital file. 
490 1 # |a Synthesis lectures on biomedical engineering,  |v # 9  |x 1930-0336 ; 
500 # # |a Part of: Synthesis digital library of engineering and computer science. 
500 # # |a Title from PDF t.p. (viewed on January 8, 2009). 
500 # # |a Series from website. 
504 # # |a Includes bibliographical references (p. 87-98b). 
505 0 # |a The nature of lung sound signals -- Historical overview -- Main characteristics and categorization -- Recording issues -- Standards -- Procedures and considerations -- Trends in LS analysis -- New domains in LS representation -- Overview -- Higher-order statistics (spectra) -- Epitomized rationale -- HOS definitions: higher-order statistics -- HOS definitions: higher-order spectra -- The parametric approach -- LS quadratic phase coupling detection -- Autoregressive-HOS modeling of LS source and transmission -- Lower-order statistics -- Epitomized rationale -- LOS definitions: a-stable distribution -- LOS definitions: fractional lower-order moments and covariation coefficient -- LOS analysis tools: converging variance test -- LOS analysis tools: parameter estimates for SAS distributions -- LOS analysis tools: AR modeling of SAS distributions -- LOS analysis of discontinuous adventitious sounds -- Wavelet analysis -- Epitomized rationale -- Continuous wavelet transform -- Discrete WT and multiresolution representation -- Wavelet-based analysis of LS -- Wavelet-HOS -- Epitomized rationale -- CWT-HOS definitions -- Wheeze analysis with CWT-HOS -- Higher-order crossings -- Epitomized rationale -- HOC definitions -- HOC discrimination tools -- HOC analysis of DAS -- Empirical mode decomposition -- Epitomized rationale -- EMD description -- EMD considerations and extensions -- EMD crackles analysis -- Fractal dimension-lacunarity analysis -- Epitomized rationale -- FD estimation -- Lacunarity estimation -- FD analysis of LS -- Lacunarity analysis of DAS -- Denoising techniques -- Overview -- Wavelet-based denoising -- CWT-WED -- WTST-NST filter -- Kurtosis-based extractor -- Fractal dimension-based detector -- Wavelet-fractal dimension-based denoising -- Empirical mode decomposition-fractal dimension-based denoising -- Heart sound cancellation -- HOS-based HSC -- WT-based HSC -- Recursive least squares-based HSC -- Time-frequency-based HSC -- Recurrent time statistics and nonlinear prediction-based HSC -- Other denoising approaches -- Fuzzy logic-based denoising -- Independent component analysis-based HSC -- Variance fractal dimension-based heart sound localization -- Entropy-based heart sound localization -- Reflective implications -- From an engineer's viewpoint -- From a physician's viewpoint. 
506 # # |a Abstract freely available; full-text restricted to subscribers or individual document purchasers. 
510 0 # |a Compendex 
510 0 # |a INSPEC 
510 0 # |a Google scholar 
510 0 # |a Google book search 
520 # # |a Lung sounds auscultation is often the first noninvasive resource for detection and discrimination of respiratory pathologies available to the physician through the use of the stethoscope. Hearing interpretation, though, was the only means of appreciation of the lung sounds diagnostic information for many decades. Nevertheless, in recent years, computerized auscultation combined with signal processing techniques has boosted the diagnostic capabilities of lung sounds. The latter were traditionally analyzed and characterized by morphological changes in the time domain using statistical measures, by spectral properties in the frequency domain using simple spectral analysis, or by nonstationary properties in a joint time-frequency domain using short-time Fourier transform. Advanced signal processing techniques, however, have emerged in the last decade, broadening the perspective in lung sounds analysis. The scope of this book is to present up-to-date signal processing techniques that have been applied to the area of lung sound analysis. It starts with a description of the nature of lung sounds and continues with the introduction of new domains in their representation, new denoising techniques, and concludes with some reflective implications, both from engineers' and physicians' perspective. Issues of nonstationarity, nonlinearity, non-Gaussianity, modeling, and classification of lung sounds are addressed with new methodologies, revealing a more realistic approach to their pragmatic nature. Advanced denoising techniques that effectively circumvent the noise presence (e.g., heart sound interference, background noise) in lung sound recordings are described, providing the physician with high-quality auscultative data. The book offers useful information both to engineers and physicians interested in bioacoustics, clearly demonstrating the current trends in lung sound analysis. 
530 # # |a Also available in print. 
538 # # |a Mode of access: World Wide Web. 
538 # # |a System requirements: Adobe Acrobat reader. 
650 # 0 |a Auscultation  |x Data processing. 
650 # 0 |a Lungs  |x Sounds  |x Data processing. 
650 # 0 |a Lungs  |x Diseases  |x Diagnosis  |x Data processing. 
650 # 0 |a Signal processing  |x Digital techniques. 
690 # # |a Lung sounds. 
690 # # |a Advanced signal processing. 
690 # # |a Nonstationarity. 
690 # # |a Nonlinearity. 
690 # # |a Non-Gaussianity. 
690 # # |a Modeling. 
690 # # |a Classification. 
690 # # |a Denoising. 
690 # # |a Heart sound cancellation. 
730 0 # |a Synthesis digital library of engineering and computer science. 
830 # 0 |a Synthesis lectures on biomedical engineering (Online) ;  |v # 9. 
856 4 2 |u https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.2200/S00127ED1V01Y200811BME009  |3 Abstract with links to full text