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000753305 019__ $$a934770712
000753305 020__ $$a9789812879691$$q(electronic book)
000753305 020__ $$a9812879692$$q(electronic book)
000753305 020__ $$z9789812879684
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000753305 0247_ $$a10.1007/978-981-287-969-1$$2doi
000753305 035__ $$aSP(OCoLC)ocn934608010
000753305 035__ $$aSP(OCoLC)934608010$$z(OCoLC)934770712
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000753305 049__ $$aISEA
000753305 050_4 $$aQP341
000753305 08204 $$a612/.01427$$223
000753305 1001_ $$aMughal, Yar M.,$$eauthor.
000753305 24512 $$aA parametric framework for modelling of bioelectrical signals$$h[electronic resource] /$$cYar M. Mughal (Yar Muhammad).
000753305 264_1 $$aSingapore :$$bSpringer,$$c2016.
000753305 300__ $$a1 online resource (xv, 81 pages) :$$billustrations.
000753305 336__ $$atext$$btxt$$2rdacontent
000753305 337__ $$acomputer$$bc$$2rdamedia
000753305 338__ $$aonline resource$$bcr$$2rdacarrier
000753305 4901_ $$aSeries in BioEngineering,$$x2196-8861
000753305 504__ $$aIncludes bibliographical references.
000753305 5050_ $$aIntroduction and Motivation -- State of the Art of Modelling and Simulation of the Physiological Systems -- Proposed Novel Generic Framework for Modelling the Bioelectrical Information -- Implementation of the Framework and the Experimental Results -- Conclusions.
000753305 506__ $$aAccess limited to authorized users.
000753305 520__ $$aThis book examines non-invasive, electrical-based methods for disease diagnosis and assessment of heart function. In particular, a formalized signal model is proposed since this offers several advantages over methods that rely on measured data alone. By using a formalized representation, the parameters of the signal model can be easily manipulated and/or modified, thus providing mechanisms that allow researchers to reproduce and control such signals. In addition, having such a formalized signal model makes it possible to develop computer tools that can be used for manipulating and understanding how signal changes result from various heart conditions, as well as for generating input signals for experimenting with and evaluating the performance of e.g. signal extraction methods. The work focuses on bioelectrical information, particularly electrical bio-impedance (EBI). Once the EBI has been measured, the corresponding signals have to be modelled for analysis. This requires a structured approach in order to move from real measured data to the model of the corresponding signals. This book proposes a generic framework for this procedure. It can be used as a guide for modelling impedance cardiography (ICG) and impedance respirography (IRG) signals, as well as for developing the corresponding bio-impedance signal simulator (BISS).
000753305 588__ $$aOnline resource; title from PDF title page (SpringerLink, viewed January 14, 2016).
000753305 650_0 $$aImpedance, Bioelectric$$xMathematical models.
000753305 77608 $$iPrint version:$$z9812879684$$z9789812879684$$w(OCoLC)920447188
000753305 830_0 $$aSeries in bioengineering.
000753305 852__ $$bebk
000753305 85640 $$3SpringerLink$$uhttps://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-981-287-969-1$$zOnline Access$$91397441.1
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000753305 980__ $$aEBOOK
000753305 980__ $$aBIB
000753305 982__ $$aEbook
000753305 983__ $$aOnline
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