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Human Heart Oscillatory Behavior during Atrial Fibrillation Based on Second Order System

机译:基于二阶系统的心房颤动期间人心脏振荡行为

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In this paper, the viability of a second order system to characterize the oscillatory behavior of human heart of atrial fibrillation patient was monitored and analysed. Sampling were patients who experienced atrial fibrillation. This study used the MIT-BIH Atrial Fibrillation dataset (MIT-afdb) from the Physiobank ECG database. ECG recordings of normal sinus rhythm (N) and atrial fibrillation (AF) which occurred sequentially, were analyzed for both ECG's Lead I and Lead II. From here, the oscillatory behavior of human heart was characterized in accordance to the extracted parameters for each rhythm, i.e. natural frequency, damping coefficient and forcing input from the second order system. Results show that there were significant differences in mean value of natural frequency (ω), ratios of natural frequency to damping coefficient (ω/ζ), derivative of the natural frequency with respect to time (dω/dt) and derivative of the forcing input with respect to time (dμ/dt), between N and AF from Lead I (P < 0.01). Each parameter provides more than 95 % accuracy using artificial neural networks.
机译:在本文中,监测了第二阶系统的可行性,以表征心房颤动患者人心脏振荡行为的表征和分析。抽样是经历心房颤动的患者。本研究使用了来自Physiobank ECG数据库的MIT-BIH心房颤动数据集(MIT-AFDB)。对于依次发生的正常窦性节律(n)和心房颤动(AF)的ECG记录被分析,用于ECG的铅I和铅II。从这里,人体的振荡行为是根据每个节奏的提取参数表征,即自然频率,阻尼系数和从二阶系统的输入输入。结果表明,固有频率(ω)的平均值,自然频率比对阻尼系数(ω/∞)的比例,相对于时间(dω/ dt)的衍生物的衍生物的差异存在显着差异,以及迫使输入的衍生物关于时间(dμ/ dt),来自铅i的n和af(p <0.01)。每个参数使用人工神经网络提供超过95%的精度。

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