000			06656nam a2200625 i 4500
001			6812512
003			IEEE
005			20200413152853.0
006			m eo d
007			cr cn |||m|||a
008			090108s2009 caua foab 000 0 eng d
020			_a9781598297119 (electronic bk.)
020			_a9781598297102 (pbk.)
024	7		_a10.2200/S00127ED1V01Y200811BME009 _2doi
035			_a(CaBNVSL)gtp00532334
035			_a(OCoLC)299803419
040			_aCaBNVSL _cCaBNVSL _dCaBNVSL
050		4	_aRC76.3 _b.H235 2009
082	0	4	_a616.1207544 _222
100	1		_aHadjileontiadis, Leontios J.
245	1	0	_aLung sounds _h[electronic resource] : _ban advanced signal processing perspective / _cLeontios J. Hadjileontiadis.
260			_aSan Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : _bMorgan & Claypool Publishers, _cc2009.
300			_a1 electronic text (vii, 99 p. : ill.) : _bdigital file.
490	1		_aSynthesis lectures on biomedical engineering, _x1930-0336 ; _v# 9
538			_aMode of access: World Wide Web.
538			_aSystem requirements: Adobe Acrobat reader.
500			_aPart of: Synthesis digital library of engineering and computer science.
500			_aSeries from website.
504			_aIncludes bibliographical references (p. 87-98b).
505	0		_aThe 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	1		_aAbstract freely available; full-text restricted to subscribers or individual document purchasers.
510	0		_aCompendex
510	0		_aINSPEC
510	0		_aGoogle scholar
510	0		_aGoogle book search
520			_aLung 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			_aAlso available in print.
588			_aTitle from PDF t.p. (viewed on January 8, 2009).
650		0	_aAuscultation _xData processing.
650		0	_aLungs _xSounds _xData processing.
650		0	_aLungs _xDiseases _xDiagnosis _xData processing.
650		0	_aSignal processing _xDigital techniques.
690			_aLung sounds.
690			_aAdvanced signal processing.
690			_aNonstationarity.
690			_aNonlinearity.
690			_aNon-Gaussianity.
690			_aModeling.
690			_aClassification.
690			_aDenoising.
690			_aHeart sound cancellation.
730	0		_aSynthesis digital library of engineering and computer science.
830		0	_aSynthesis lectures on biomedical engineering ; _v# 9.
856	4	2	_3Abstract with links to resource _uhttp://ieeexplore.ieee.org/servlet/opac?bknumber=6812512
999			_c561659 _d561659