Tombros S, Tselikis G, Marakas S, Protonotarios E, Koutsouris D, Toutouzas P
National Technical University of Athens, Department of Electrical and Computer Engineering, Greece.
Technol Health Care. 1995 Oct;3(2):123-30.
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.
心脏功能的各个方面，如心肌收缩性、心肌细胞的去极化和复极化、起搏细胞的发放频率等，都受到复杂的神经体液调节。特别是自主神经系统通过其两个相互对立的组成部分，即交感神经和副交感神经（迷走神经）的相互作用，逐搏控制心脏功能。此外，交感神经系统和副交感神经系统的相互作用是一种非线性函数，交感神经张力调节迷走神经激活的反应。研究表明，心率变异性的频率成分功率，尤其是低频与高频功率谱的比值，是交感迷走神经平衡的可靠指标（A. 马利亚尼等人，1991年。在频域中探索心血管神经调节。《循环》，84(2) 482 - 484）。最著名的线性和非线性信号处理算法已应用于从健康人和高危个体记录的心电图数据。这些方法连同对QRS频谱的研究和分析，将得出具有诊断和预后信息的非常有用的结论。在本文中，我们将简要描述这些算法的数学方面，并展示它们对正常和病理性心电图信号的分析结果。
