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Frequency modulation between low- and high-frequency components of the heart rate variability spectrum

机译:心率变异性频谱的低频和高频成分之间的频率调制

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Interactions among physiological mechanisms are abundant in biomedical signals, and they may exist to maintain efficient homeostasis. For example, sympathetic and parasympathetic neural activities interact to either elevate or depress the heart rate to maintain homeostasis. There has been considerable effort devoted to developing algorithms that can detect interactions between various physiological mechanisms. However, methods used to detect the presence of interactions between the sympathetic and parasympathetic nervous systems, to take one example, have had limited success. This may be because interactions in physiological systems are nonlinear and non-stationary. The goal of this work was to identify non-linear interactions between the sympathetic and parasympathetic nervous systems in the form of frequency and amplitude modulations in human heart-rate data (n = 6). To this end, wavelet analysis was performed, followed by frequency analysis of the resultant wavelet decomposed signals in several frequency brackets we define as: very low frequency (f < 0.04 Hz), low frequency (0.04-0.15 Hz) and high frequency (0.15-0.4 Hz). Our analysis suggests that the high-frequency bracket is modulated by the low-frequency bracket in the heart rate data obtained in both upright and sitting positions. However, there was no evidence of amplitude modulation among these frequencies.
机译:生理机制之间的相互作用在生物医学信号中非常丰富,它们可能存在以维持有效的体内平衡。例如,交感神经和副交感神经活动相互作用,以升高或降低心率以维持体内平衡。已经投入了大量的精力来开发可以检测各种生理机制之间的相互作用的算法。然而,举一个例子,用来检测交感神经系统和副交感神经系统之间相互作用的方法的成功有限。这可能是因为生理系统中的相互作用是非线性且不稳定的。这项工作的目的是以人类心率数据中的频率和幅度调制的形式识别交感神经系统和副交感神经系统之间的非线性相互作用(n = 6)。为此,进行了小波分析,然后对在几个频率范围内得到的小波分解信号进行频率分析,我们将它们定义为:极低频(f <0.04 Hz),低频(0.04-0.15 Hz)和高频(0.15 -0.4 Hz)。我们的分析表明,在垂直位置和就座位置获得的心率数据中,高频范围受低频范围的调制。但是,没有证据表明这些频率之间存在幅度调制。

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