Point Process Heart Rate Variability Assessment during Sleep Deprivation.

Computing in cardiology Pub Date : 2010-12-31
L Citi, Eb Klerman, En Brown, R Barbieri
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引用次数: 0

Abstract

To investigate the potential relationships between Heart rate variability (HRV) and objective performance-subjective alertness measures during sleep deprivation, a novel point process algorithm was applied to ECG data from healthy young subjects in a 52-hour Constant Routine protocol, which includes sleep deprivation. Our algorithm is able to estimate the time-varying behavior of the HRV spectral indexes in an on-line instantaneous fashion. Results demonstrate the ability of our framework to provide high time-resolution sympatho-vagal dynamics as measured by spectral low frequency (LF) and high frequency (HF) power. Correlation analysis on individual subjects reveals a relevant correspondence between LF/HF and subjective alertness during the initial hours of sleep deprivation. At longer times awake, high correlation levels between LF/HF and objective performance indicate an increasing sympathetic drive as performance measures worsen. These results suggest that our point-process based HRV assessment could aid in real-time prediction of performance-alertness.

睡眠剥夺期间的点过程心率变异性评估。
为了研究睡眠剥夺期间心率变异性(HRV)与客观表现(主观警觉性)之间的潜在关系,采用一种新颖的点处理算法对健康年轻受试者的52小时恒定常规(包括睡眠剥夺)心电图数据进行处理。我们的算法能够在线瞬时估计HRV光谱指标的时变行为。结果表明,我们的框架能够通过频谱低频(LF)和高频(HF)功率提供高时间分辨率的交感神经迷走神经动力学。对个体受试者的相关分析显示,在剥夺睡眠的最初几个小时内,低频/高频与主观警觉性之间存在相关的对应关系。在清醒时间较长的情况下,LF/HF与客观表现之间的高相关性表明,随着表现指标的恶化,交感神经驱动会增加。这些结果表明,我们基于点过程的HRV评估可以帮助实时预测性能警觉性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.10
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0.00%
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