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Über dieses Buch

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).



Chapter 1. Introduction and Motivation

Healthcare is becoming an important challenge around the world. Many developed countries are facing socio-economic problems such as increasing healthcare costs. For example, in 2010, the USA alone spent about US $2.5 trillion (17 % of its GDP) on healthcare, and this number is expected to grow in the future due to emerging new requirements in healthcare. In response to these growing concerns, developed countries such as the USA, EU, and Japan are advancing a new healthcare model called “Personalized Healthcare” to control the healthcare costs while improving the medical quality by use of Information Communication Technology (ICT) (Wu 2011).
Yar M. Mughal (Yar Muhammad)

Chapter 2. State of the Art of Modelling and Simulation of the Physiological Systems

This chapter reviews the physiology of the cardiovascular system in order to understand its main mechanisms and parameters, which are of interest in this work. This chapter also describes other researchers’ approaches to developing cardiovascular system models as well as three simulation examples, namely (a) a cardiovascular simulator (“CVSim”), (b) a software tool for analysing breathing-related errors in transthoracic electrical bio-impedance spectroscopy measurements, and (c) simulation of lung edema in impedance cardiography.
Yar M. Mughal (Yar Muhammad)

Chapter 3. Proposed Novel Generic Framework for Modelling the Bioelectrical Information

In this chapter, a generic framework is proposed to guide the modelling of signals and to develop a simulator for the bioelectrical information. The framework is a pathway to develop bioelectrical applications; first, the bioelectrical information must be modelled based on template signals and then a corresponding simulator must be developed.
Yar M. Mughal (Yar Muhammad)

Chapter 4. Implementation of the Framework and Experimental Results

As the basis for the implementation, the EBI measurement method was selected to measure the impedance cardiography (ICG) and impedance respirogram (IRG) signals in order to develop the corresponding signal models; for this purpose, different curve-fitting methods are discussed.
Yar M. Mughal (Yar Muhammad)

Chapter 5. Conclusions

At the beginning of my research studies, my research was focused on developing an efficient and robust algorithm to separate the cardiac and respiratory signals from an electrical bio-impedance signal. The separated signals could then be analysed by cardiologists to understand the conditions of the heart and lungs.
Yar M. Mughal (Yar Muhammad)


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