Nardelli Mimma, Citi Luca, Barbieri Riccardo, Valenza Gaetano
Annu Int Conf IEEE Eng Med Biol Soc. 2020 Jul;2020:2577-2580. doi: 10.1109/EMBC44109.2020.9175587.
The analysis of complex heartbeat dynamics has been widely used to characterize heartbeat autonomic control in healthy and pathological conditions. However, underlying physiological correlates of complexity measurements from heart rate variability (HRV) series have not been identified yet. To this extent, we investigated intrinsic irregularity and complexity of cardiac sympathetic and vagal activity time series during postural changes. We exploited our recently proposed HRV-based, time-varying Sympathetic and Parasympathetic Activity Indices (SAI and PAI) and performed Sample Entropy, Fuzzy Entropy, and Distribution Entropy calculations on publicly-available heartbeat series gathered from 10 healthy subjects undergoing resting state and passive slow tilt sessions. Results show significantly higher entropy values during the upright position than resting state in both SAI and PAI series. We conclude that an increase in HRV complexity resulting from postural changes may derive from sympathetic and vagal activities with higher complex dynamics.
复杂心跳动力学分析已被广泛用于表征健康和病理状态下的心跳自主控制。然而，心率变异性（HRV）系列复杂性测量的潜在生理相关性尚未确定。在此范围内，我们研究了姿势变化期间心脏交感神经和迷走神经活动时间序列的内在不规则性和复杂性。我们利用了最近提出的基于HRV的时变交感神经和副交感神经活动指数（SAI和PAI），并对从10名健康受试者在静息状态和被动缓慢倾斜过程中收集的公开可用心跳系列进行了样本熵、模糊熵和分布熵计算。结果显示，在直立位时，SAI和PAI系列的熵值均显著高于静息状态。我们得出结论，姿势变化导致的HRV复杂性增加可能源于具有更高复杂动力学的交感神经和迷走神经活动。
