Alvaro Pasquale K, Jackson Melinda L, Berlowitz David J, Swann Philip, Howard Mark E
Institute for Breathing and Sleep, Department of Respiratory and Sleep Medicine, Austin Health, Melbourne, Australia.
School of Psychological Sciences Monash University, Melbourne, Australia.
J Clin Sleep Med. 2016 Aug 15;12(8):1099-103. doi: 10.5664/jcsm.6044.
Real life ocular measures of drowsiness use average blink duration, amplitude and velocity of eyelid movements to reflect drowsiness in drivers. However, averaged data may conceal the variability in duration of eyelid closure episodes, and more prolonged episodes that indicate higher levels of drowsiness. The current study aimed to describe the frequency and duration of prolonged eyelid closure episodes during acute sleep deprivation.
Twenty male professional drivers (mean age ± standard deviation = 41.9 ± 8.3 years) were recruited from the Transport Workers Union newsletter and newspaper advertisements in Melbourne, Australia. Each participant underwent 24 hours of sleep deprivation and completed a simulated driving task (AusEd), the Psychomotor Vigilance Task, and the Karolinska Sleepiness Scale. Eyelid closure episodes during the driving task were recorded and analyzed manually from digital video recordings.
Eyelid closure episodes increased in frequency and duration with a median of zero s/h of eyelid closure after 3 h increasing to 34 s/h after 23 h awake. Eyelid closure episodes were short and infrequent from 3 to 14 h of wakefulness. After 17 h of sleep deprivation, longer and more frequent eyelid closure episodes began to occur. Episodes lasting from 7 seconds up to 18 seconds developed after 20 h of wakefulness. Length of eyelid closure episodes was moderately to highly correlated with the standard deviation of lateral lane position, braking reaction time, crashes, impaired vigilance, and subjective sleepiness.
The frequency and duration of episodes of prolonged eyelid closure increases during acute sleep deprivation, with very prolonged episodes after 17 hours awake. Automated devices that assess drowsiness using averaged measures of eyelid closure episodes need to be able to detect prolonged eyelid closure episodes that occur during more severe sleep deprivation.
现实生活中用于测量驾驶员嗜睡程度的眼部指标,是通过平均眨眼持续时间、幅度和眼睑运动速度来反映嗜睡情况。然而,平均数据可能会掩盖眼睑闭合时长的变异性,以及更长时间的闭合情况,而更长时间的闭合表明更高程度的嗜睡。本研究旨在描述急性睡眠剥夺期间长时间眼睑闭合事件的频率和持续时间。
从澳大利亚墨尔本运输工人工会通讯和报纸广告中招募了20名男性职业驾驶员(平均年龄±标准差=41.9±8.3岁)。每位参与者经历24小时睡眠剥夺,并完成模拟驾驶任务(AusEd)、心理运动警觉任务和卡罗林斯卡嗜睡量表。驾驶任务期间的眼睑闭合事件通过数字视频记录进行手动记录和分析。
眼睑闭合事件的频率和持续时间增加,在清醒3小时后眼睑闭合中位数为0秒/小时,在清醒23小时后增加到34秒/小时。在清醒3至14小时期间,眼睑闭合事件短暂且不频繁。在睡眠剥夺17小时后,开始出现更长且更频繁的眼睑闭合事件。在清醒20小时后,出现了持续7秒至18秒的事件。眼睑闭合事件的时长与横向车道位置的标准差、制动反应时间、碰撞、警觉性受损和主观嗜睡程度呈中度至高度相关。
在急性睡眠剥夺期间,长时间眼睑闭合事件的频率和持续时间会增加,在清醒17小时后会出现非常长时间的事件。使用眼睑闭合事件平均测量值来评估嗜睡程度的自动化设备,需要能够检测出在更严重睡眠剥夺期间发生的长时间眼睑闭合事件。