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The diagnosis of cardie arrhythmias using heart rate variability analysis by the EMD

机译:EMD使用心率变异性分析诊断心律失常

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In this study, we analyzed Heart Rate Variability (HRV) in different situations with the aim of obtaining indices reflecting the activity of the autonomic function plays an important role in the pathophysiology of arrhythmias. The data are values of RR intervals presented as a time series, called tachogram, like a random signal, subject to significant fluctuations. The tachogram of HRV represents the beat to beat variability of heart rate as a plot of RR intervals according to time. The analysis of the variability of the heart rate by spectral methods used to estimate the modulation of the Autonomic Nervous System (ANS) in different contexts involving a modification of the sympatho-vagal balance, as well to the healthy subject as to the carrier pathology subject. In this article we propose the analysis of the variability of the frequency by an adaptive and non-stationary method such as the Empirical Modal Decomposition (EMD) and a frequency analysis by the calculation of the Power Spectral Density (PSD). The proposed strategy can provide valuable information on mechanisms of certain cardiac arrhythmia for early diagnosis.
机译:在这项研究中,我们分析了不同情况下的心率变异性(HRV),目的是获得反映自主功能活动的指标,在​​心律不齐的病理生理中起重要作用。数据是表示为时间序列的RR间隔值,称为轮速图,就像随机信号一样,会受到很大的波动。 HRV的转速表表示心率的心跳到心跳变异性,作为根据时间的RR间隔图。通过频谱方法对心率变异性进行分析,该方法可用于估计在不同情境下涉及自主神经系统平衡(ANS)调节的自主神经系统(ANS)的调制,对于健康受试者以及携带者病理受试者而言。在本文中,我们提出通过自适应和非平稳方法(如经验模态分解(EMD))对频率的可变性进行分析,并通过计算功率谱密度(PSD)进行频率分析。所提出的策略可以为早期诊断某些心律不齐的机制提供有价值的信息。

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