A methodology that reconstructs the inner structure of the heart using multichannel ECG.
Published in Chapter:
Spatial Heart Simulation and Analysis Using Unified Neural Network
Sándor Miklós Szilágyi (Hungarian Science University of Transylvania, Romania), László Szilágyi (Hungarian Science University of Transylvania, Romania), and Zoltán Benyó (Dept. of Control Engineering and Information Technology, Hungary)
Copyright: © 2008
|Pages: 8
DOI: 10.4018/978-1-59904-889-5.ch158
Abstract
The most important health problem affecting large groups of people is related to the malfunction of the heart, usually caused by heart attack, rhythm disturbances, and pathological degenerations. One of the main goals of health study is to predict these kinds of tragic events, and by identifying the patients situated in the most dangerous states, to make it possible to apply a preventing therapy. Creating a heart model is important (Thaker & Ferrero, 1998) as the computer, while applying traditional signal processing algorithms recognizes lots of waves, but it does not really “understand” what is happening. To overcome this, the computer needs to know the origin and the evolvement process of the ECG signal (MacLeod & Brooks, 1998). During signal processing, if the traditional algorithm finds an unrecognizable waveform, the model-based approach is activated, which tries to estimate the causes of the encountered phenomenon (e.g., quick recognition of ventricular fibrillation) (Szilágyi, 1998).