Brandenberger Gabrielle, Buchheit Martin, Ehrhart Jean, Simon Chantal, Piquard François
Laboratoire des Régulations Physiologiques et des Rythmes Biologiques chez l'Homme, Faculté de Médecine, 4, rue Kirschleger, 67085 Strasbourg Cedex, France.
Auton Neurosci. 2005 Aug 31;121(1-2):81-6. doi: 10.1016/j.autneu.2005.06.002.
Heart rate variability (HRV) analysis holds increasing interest but electrocardiographic (ECG) recordings are strongly disturbed by body movements, changes in environment and respiration. Here we give arguments for the use of slow wave sleep (SWS) as an appropriate recording condition. Sixteen healthy subjects aged 21-31 years (10 males, 6 females) underwent polygraphic sleep, ECG, and respiratory recordings during one experimental night. HRV was analyzed in 5-min SWS segments and compared to data collected during quiet wake in the morning with controlled breathing, using for each individual the same respiratory frequency as that recorded during SWS. SWS has two major advantages. First, it is a quiet sleep period, free of any external confounding events and is characterized by fewer body movements or arousals that cause abrupt heart rate (HR) increases which disrupt the ECG signal. Second, SWS avoids the deleterious effect of controlled breathing on HRV. Respiratory cycles were spontaneously more regular during SWS than during generally used wake (Standard deviation (SD) of the respiratory cycles was 0.27+/-0.02 s during SWS vs 0.42+/-0.07 s during wake under controlled breathing; p<0.01). Compared to quiet wake, the SD of normal R-R intervals reflecting global variability was significantly lower during SWS (54.3+/-4.7 vs 78.8+/-6.1 ms; p<0.001) and the normalized high frequency power was increased (0.57+/-0.04 vs 0.51+/-0.03; p<0.05), suggesting a higher parasympathetic control of the heart. Thus, SWS offers a "self-controlled" and undisturbed moment of observation for assessing time and frequency domain HRV indexes. Its relevance as an optimal ECG recording condition has to be confirmed in various experimental conditions.
心率变异性（HRV）分析越来越受到关注，但心电图（ECG）记录会受到身体运动、环境变化和呼吸的强烈干扰。在此，我们阐述了将慢波睡眠（SWS）作为合适记录条件的依据。16名年龄在21 - 31岁的健康受试者（10名男性，6名女性）在一个实验夜间接受了多导睡眠图、心电图和呼吸记录。在5分钟的慢波睡眠时段分析HRV，并与早晨安静觉醒且呼吸受控时收集的数据进行比较，每个个体使用与慢波睡眠期间记录的相同呼吸频率。慢波睡眠有两个主要优点。首先，它是一个安静的睡眠时段，没有任何外部干扰事件，其特点是身体运动或觉醒较少，这些会导致心率（HR）突然增加，从而干扰心电图信号。其次，慢波睡眠避免了受控呼吸对HRV的有害影响。慢波睡眠期间呼吸周期比一般使用的觉醒期间自发更规律（慢波睡眠期间呼吸周期的标准差（SD）为0.27±0.02秒，而在受控呼吸的觉醒期间为0.42±0.07秒；p<0.01）。与安静觉醒相比，反映整体变异性的正常R - R间期标准差在慢波睡眠期间显著更低（54.3±4.7对78.8±6.1毫秒；p<0.001），且归一化高频功率增加（0.57±0.04对0.51±0.03；p<0.05），表明心脏的副交感神经控制更高。因此，慢波睡眠为评估时域和频域HRV指标提供了一个“自我控制”且不受干扰的观察时刻。其作为最佳心电图记录条件的相关性必须在各种实验条件下得到证实。
