Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent.
Reproducibility of Heart Rate Variability Is Parameter and Sleep Stage Dependent.
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DOI：
10.3389/fphys.2017.01100
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发表时间：
2017
影响因子：
4
通讯作者：
Achermann P
中科院分区：
文献类型：
--
作者：
Herzig D;Eser P;Omlin X;Riener R;Wilhelm M;Achermann P
目的：睡眠期间心率变异性 (HRV) 的测量变得越来越流行，因为睡眠可以为 HRV 评估提供最佳状态。虽然据报道睡眠阶段会影响 HRV，但睡眠阶段对 HRV 参数方差的影响几乎没有研究。我们的目的是评估不同睡眠阶段 HRV 参数的变化。此外，我们还测试了使用 HRV 识别慢波睡眠（SWS，深度睡眠）中 5 分钟片段的算法的准确性。方法：对 15 名健康年轻男性 3 个晚上的多导睡眠图 (PSG) 睡眠记录进行了分析。根据常规标准对睡眠进行评分。分析不同睡眠阶段内连续 5 分钟片段的 HRV 参数。 HRV参数的总方差分为受试者间方差、夜间方差和段间方差，并在不同睡眠阶段之间进行比较。计算所有睡眠阶段的所有 HRV 参数的组内相关系数。根据 HRV、移动 5 分钟窗口（20 秒步长）的连续 R-R 间隔 (rRR) 的皮尔逊相关系数来识别 SWS 分段。从 rRR 时间序列中删除线性趋势，并确定 rRR 值低于平均 rRR 0.1 个单位并持续至少 10 分钟的第一段。在这样一个识别的片段的中间放置一个5分钟的片段，并使用相应的睡眠阶段来评估算法的准确性。结果：所有睡眠阶段的心率以及 SWS 中的高频 (HF) 功率在夜间和夜间均具有良好的再现性。在所有睡眠阶段，低频 (LF) 功率和 LF/HF 的再现性都很差。在根据 HRV 数据选择的所有 5 分钟片段中，87% 在 SWS 内准确定位。结论：SWS 是一种稳定状态，与清醒状态相比，不受内部和外部因素的影响，是一种可重复的状态，可以可靠地确定心率和高频功率，并且可以基于 R-R 间隔进行满意的检测，而不需要完整的 PSG。睡眠可能不是评估低频功率和低频/高频功率比的最佳条件。
Objective: Measurements of heart rate variability (HRV) during sleep have become increasingly popular as sleep could provide an optimal state for HRV assessments. While sleep stages have been reported to affect HRV, the effect of sleep stages on the variance of HRV parameters were hardly investigated. We aimed to assess the variance of HRV parameters during the different sleep stages. Further, we tested the accuracy of an algorithm using HRV to identify a 5-min segment within an episode of slow wave sleep (SWS, deep sleep). Methods: Polysomnographic (PSG) sleep recordings of 3 nights of 15 healthy young males were analyzed. Sleep was scored according to conventional criteria. HRV parameters of consecutive 5-min segments were analyzed within the different sleep stages. The total variance of HRV parameters was partitioned into between-subjects variance, between-nights variance, and between-segments variance and compared between the different sleep stages. Intra-class correlation coefficients of all HRV parameters were calculated for all sleep stages. To identify an SWS segment based on HRV, Pearson correlation coefficients of consecutive R-R intervals (rRR) of moving 5-min windows (20-s steps). The linear trend was removed from the rRR time series and the first segment with rRR values 0.1 units below the mean rRR for at least 10 min was identified. A 5-min segment was placed in the middle of such an identified segment and the corresponding sleep stage was used to assess the accuracy of the algorithm. Results: Good reproducibility within and across nights was found for heart rate in all sleep stages and for high frequency (HF) power in SWS. Reproducibility of low frequency (LF) power and of LF/HF was poor in all sleep stages. Of all the 5-min segments selected based on HRV data, 87% were accurately located within SWS. Conclusions: SWS, a stable state that, in contrast to waking, is unaffected by internal and external factors, is a reproducible state that allows reliable determination of heart rate, and HF power, and can satisfactorily be detected based on R-R intervals, without the need of full PSG. Sleep may not be an optimal condition to assess LF power and LF/HF power ratio.
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影响因子：
5.6
作者：
Elsenbruch, S;Harnish, MJ;Orr, WC
通讯作者：
Orr, WC
影响因子：
3.2
作者：
Fonseca, Pedro;Long, Xi;Rolink, Jerome
通讯作者：
Rolink, Jerome
影响因子：
4.7
作者：
Brandenberger, G;Ehrhart, J;Simon, C
通讯作者：
Simon, C
DOI：
10.1016/s0921-884x(96)96070-1
发表时间：
1997-05-01
期刊：
ELECTROENCEPHALOGRAPHY AND CLINICAL NEUROPHYSIOLOGY
影响因子：
--
作者：
Bonnet, MH;Arand, DL
通讯作者：
Arand, DL
影响因子：
5.6
作者：
Boudreau, Philippe;Yeh, Wei-Hsien;Boivin, Diane B.
通讯作者：
Boivin, Diane B.