A Parametric Framework for Modelling of Bioelectrical Signals
Springer | Biomedical Engineering | Jan. 5 2016 | ISBN-10: 9812879684 | 81 pages | pdf | 3.95 mb
Springer | Biomedical Engineering | Jan. 5 2016 | ISBN-10: 9812879684 | 81 pages | pdf | 3.95 mb
Authors: Mughal, Yar Muhammad
Presents non-invasive electrical-based methods for the diagnosis of the heart function modelling the measure signal
Offers a framework to guide the modelling of the impedance cardiography and impedance respirography signals
Gives freedom to the end-user to control the essential properties of the generated electrical bioimpedance signals depending on his/her needs
This 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).
Number of Illustrations and Tables
37 illus., 5 in colour
Topics
Biomedical Engineering
Cardiac Imaging (new)
Medical and Radiation Physics
Signal, Image and Speech Processing
Pneumology/Respiratory System
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