Heart Rate Variability Can Be Used to Estimate Sleepiness-related Decrements in Psychomotor Vigilance during Total Sleep Deprivation
Heart Rate Variability Can Be Used to Estimate Sleepiness-related Decrements in Psychomotor Vigilance during Total Sleep Deprivation
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DOI：
10.5665/sleep.1688
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发表时间：
2012-03-01
期刊：
影响因子：
5.6
通讯作者：
Gooley, Joshua J.
中科院分区：
文献类型：
--
作者：
Chua, Eric Chern-Pin;Tan, Wen-Qi;Gooley, Joshua J.
研究目的：评估心率变异性(HRV)能否评估睡眠剥夺期间精神运动警觉的变化。设计：比较心率变异性、眼电和脑电(EEG)测量对精神运动警戒任务(PVT)失误的预测能力。地点：新加坡杜克国立大学研究生院时间生物学和睡眠实验室。参与者：24名健康的中国男性(平均年龄+/-SD=25.9+/-2.8岁)。干预：受试者在恒定的环境条件下连续清醒40小时。每隔2小时，受试者完成10分钟的PVT，以评估他们维持视觉注意力的能力。测量和结果：在每个PVT期间，我们检查了心电图、EEG和闭眼时间百分比(PERCLOS)。与脑电功率密度和PERCLOS测量类似，在0.02-0.08赫兹范围内的心电图RR间期功率密度的时间进程与PVT的40小时曲线相关。根据接收器工作特性曲线，RR间期功率密度以及在识别嗜睡相关的PVT增加时的脑电功率密度均超过阈值。RR间期功率密度(0.02~0.08 Hz)对受试者表现的分类具有与PERCLOS相似的敏感性和特异性。因此，心率变异性测量可能被用来预测个体何时处于注意力失败的增加风险中。我们的结果表明，HRV监测，无论是单独的或结合其他生理措施，可以纳入安全装置，以警告昏昏欲睡的操作员时，他们的工作表现受损。
Study Objectives: To assess whether changes in psychomotor vigilance during sleep deprivation can be estimated using heart rate variability (HRV).Design: HRV, ocular, and electroencephalogram (EEG) measures were compared for their ability to predict lapses on the Psychomotor Vigilance Task (PVT).Setting: Chronobiology and Sleep Laboratory, Duke-NUS Graduate Medical School Singapore.Participants: Twenty-four healthy Chinese men (mean age +/- SD = 25.9 +/- 2.8 years).Interventions: Subjects were kept awake continuously for 40 hours under constant environmental conditions. Every 2 hours, subjects completed a 10-minute PVT to assess their ability to sustain visual attention.Measurements and Results: During each PVT, we examined the electrocardiogram (ECG), EEG, and percentage of time that the eyes were closed (PERCLOS). Similar to EEG power density and PERCLOS measures, the time course of ECG RR-interval power density in the 0.02-0.08Hz range correlated with the 40-hour profile of PVT lapses. Based on receiver operating characteristic curves, RR-interval power density performed as well as EEG power density at identifying a sleepiness-related increase in PVT lapses above threshold. RR-interval power density (0.02-0.08 Hz) also classified subject performance with sensitivity and specificity similar to that of PERCLOS.Conclusions: The ECG carries information about a person's vigilance state. Hence, HRV measures could potentially be used to predict when an individual is at increased risk of attentional failure. Our results suggest that HRV monitoring, either alone or in combination with other physiologic measures, could be incorporated into safety devices to warn drowsy operators when their performance is impaired.