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Integrated Central-Autonomic Multifractal Complexity in the Heart Rate Variability of Healthy Humans

机译:健康人心率变异性的综合中央自主多重分形复杂性

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摘要

Purpose of Study: The aim of this study was to characterize the central-autonomic interaction underlying the multifractality in heart rate variability (HRV) of healthy humans. Materials and Methods: Eleven young healthy subjects participated in two separate ~40 min experimental sessions, one in supine (SUP) and one in, head-up-tilt (HUT), upright (UPR) body positions. Surface scalp electroencephalography (EEG) and electrocardiogram (ECG) were collected and fractal correlation of brain and heart rate data was analyzed based on the idea of relative multifractality. The fractal correlation was further examined with the EEG, HRV spectral measures using linear regression of two variables and principal component analysis (PCA) to find clues for the physiological processing underlying the central influence in fractal HRV. Results: We report evidence of a central-autonomic fractal correlation (CAFC) where the HRV multifractal complexity varies significantly with the fractal correlation between the heart rate and brain data (P = 0.003). The linear regression shows significant correlation between CAFC measure and EEG Beta band spectral component (P = 0.01 for SUP and P = 0.002 for UPR positions). There is significant correlation between CAFC measure and HRV LF component in the SUP position (P = 0.04), whereas the correlation with the HRV HF component approaches significance (P = 0.07). The correlation between CAFC measure and HRV spectral measures in the UPR position is weak. The PCA results confirm these findings and further imply multiple physiological processes underlying CAFC, highlighting the importance of the EEG Alpha, Beta band, and the HRV LF, HF spectral measures in the supine position. Discussion and Conclusion: The findings of this work can be summarized into three points: (i) Similar fractal characteristics exist in the brain and heart rate fluctuation and the change toward stronger fractal correlation implies the change toward more complex HRV multifractality. (ii) CAFC is likely contributed by multiple physiological mechanisms, with its central elements mainly derived from the EEG Alpha, Beta band dynamics. (iii) The CAFC in SUP and UPR positions is qualitatively different, with a more predominant central influence in the fractal HRV of the UPR position.
机译:研究目的:本研究的目的是表征健康人心率变异性(HRV)多重分形背后的中枢-自主相互作用。资料和方法:11名年轻健康受试者参加了两个独立的〜40分钟的实验,一次为仰卧(SUP),另一次为平头(HUT),直立(UPR)体位。收集表面头皮脑电图(EEG)和心电图(ECG),并基于相对多重分形的思想分析脑和心率数据的分形相关性。使用两个变量的线性回归和主成分分析(PCA),通过脑电图,HRV频谱测量进一步检查了分形相关性,以找到有关分形HRV核心影响的生理处理线索。结果:我们报告了中枢自主分形相关性(CAFC)的证据,其中HRV多重分形复杂度随心率和大脑数据之间的分形相关性而显着变化(P = 0.003)。线性回归显示CAFC度量与EEG Beta谱带频谱分量之间存在显着相关性(SUP的P = 0.01,UPR位置的P = 0.002)。 CAFC量度与SUP位置的HRV LF分量之间存在显着相关性(P = 0.04),而与HRV HF分量的相关性接近显着性(P = 0.07)。 UPR位置的CAFC量度和HRV频谱量度之间的相关性较弱。 PCA结果证实了这些发现,并进一步暗示了CAFC潜在的多种生理过程,突出了仰卧位EEG Alpha,Beta频段和HRV LF,HF频谱测量的重要性。讨论与结论:这项工作的发现可以归纳为三点:(i)脑和心率波动中存在类似的分形特征,分形相关性向更强的变化意味着HRV多重分形向更复杂的方向变化。 (ii)CAFC可能是由多种生理机制贡献的,其主要成分主要来源于脑电图的Alpha,Beta谱带动力学。 (iii)SUP和UPR职位的CAFC在质量上有所不同,UPR职位的分形HRV的中心影响更为主要。

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  • 作者

    Lin, D. C.; Sharif, A.;

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  • 年度 2012
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  • 原文格式 PDF
  • 正文语种 {"code":"en","name":"English","id":9}
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