A generic environment for linear and nonlinear ECG processing

• Published in: Technology and health care Vol. 3; no. 2; p. 123
• Main Authors: Tombros, S, Tselikis, G, Marakas, S, Protonotarios, E, Koutsouris, D, Toutouzas, P
• Format: Journal Article
• Language: English
• Published: Netherlands 01.10.1995
• Subjects: Adult; Algorithms; Electrocardiography; Heart Diseases - diagnosis; Heart Diseases - physiopathology; Homeostasis; Humans; Linear Models; Nonlinear Dynamics; Prognosis; Signal Processing, Computer-Assisted
• ISSN: 0928-7329
• DOI: 10.3233/thc-1995-3207

Every aspect of cardiac function such as contractibility, depolarization and repolarization of cardiac cells, firing rate of pacemaker cells, is under a complex neurohumoral regulation. Especially the autonomic neuron system through the interplay of its two opposing components, sympathetic and parasympathetic (vagal), is controlling cardiac function on a beat to beat basis. Moreover, the interaction of sympathetic and parasympathetic systems is a non-linear function, with sympathetic tone modulating the response of vagal activation. It has been shown that the power of frequency components and especially the ratio of low to high frequency power spectra of heart rate variability are reliable indicators of sympathovagal balance (A. Malliani et al. 1991. Cardiovascular Neural regulation explored in the frequency domain. Circulation, 84 (2) 482-484. The most known algorithms of linear and non-linear signal processing have been applied to the ECG data recorded from healthy and high risk individuals. These methods together with the study and analysis of QRS frequency spectrum will lead to very useful conclusions with diagnostic and prognostic information. In this paper we will briefly describe the mathematical aspect of these algorithms presenting their results for normal and pathological ECG signals.