000 | 03382nam a22005415i 4500 | ||
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001 | 978-981-287-969-1 | ||
003 | DE-He213 | ||
005 | 20200420220222.0 | ||
007 | cr nn 008mamaa | ||
008 | 160105s2016 si | s |||| 0|eng d | ||
020 |
_a9789812879691 _9978-981-287-969-1 |
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024 | 7 |
_a10.1007/978-981-287-969-1 _2doi |
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050 | 4 | _aR856-857 | |
072 | 7 |
_aMQW _2bicssc |
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072 | 7 |
_aTEC009000 _2bisacsh |
|
082 | 0 | 4 |
_a610.28 _223 |
100 | 1 |
_aMughal, Yar M. _eauthor. |
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245 | 1 | 2 |
_aA Parametric Framework for Modelling of Bioelectrical Signals _h[electronic resource] / _cby Yar M. Mughal. |
264 | 1 |
_aSingapore : _bSpringer Singapore : _bImprint: Springer, _c2016. |
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300 |
_aXV, 81 p. 42 illus., 5 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSeries in BioEngineering, _x2196-8861 |
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505 | 0 | _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. | |
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). | ||
650 | 0 | _aEngineering. | |
650 | 0 | _aCardiac imaging. | |
650 | 0 |
_aRespiratory organs _xDiseases. |
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650 | 0 | _aMedical physics. | |
650 | 0 | _aRadiation. | |
650 | 0 | _aBiomedical engineering. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aBiomedical Engineering. |
650 | 2 | 4 | _aCardiac Imaging. |
650 | 2 | 4 | _aMedical and Radiation Physics. |
650 | 2 | 4 | _aSignal, Image and Speech Processing. |
650 | 2 | 4 | _aPneumology/Respiratory System. |
710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9789812879684 |
830 | 0 |
_aSeries in BioEngineering, _x2196-8861 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-981-287-969-1 |
912 | _aZDB-2-ENG | ||
942 | _cEBK | ||
999 |
_c51967 _d51967 |