Stress Research Institute, Stockholm University, Stockholm, Sweden.
J Sleep Res. 2010 Jun;19(2):298-309. doi: 10.1111/j.1365-2869.2009.00796.x. Epub 2009 Dec 28.
Studies of driving and sleepiness indicators have mainly focused on prior sleep reduction. The present study sought to identify sleepiness indicators responsive to several potential regulators of sleepiness: sleep loss, time of day (TOD) and time on task (TOT) during simulator driving. Thirteen subjects drove a high-fidelity moving base simulator in six 1-h sessions across a 24-h period, after normal sleep duration (8 h) and after partial sleep deprivation (PSD; 4 h). The results showed clear main effects of TOD (night) and TOT but not for PSD, although the latter strongly interacted with TOD. The most sensitive variable was subjective sleepiness, the standard deviation of lateral position (SDLAT) and measures of eye closure [duration, speed (slow), amplitude (low)]. Measures of electroencephalography and line crossings (LCs) showed only modest responses. For most variables individual differences vastly exceeded those of the fixed effects, except for subjective sleepiness and SDLAT. In a multiple regression analysis, SDLAT, amplitude/peak eye-lid closing velocity and blink duration predicted subjective sleepiness bouts with a sensitivity and specificity of about 70%, but were mutually redundant. The prediction of LCs gave considerably weaker, but similar results. In summary, SDLAT and eye closure variables could be candidates for use in sleepiness-monitoring devices. However, individual differences are considerable and there is need for research on how to identify and predict individual differences in susceptibility to sleepiness.
研究驾驶和困倦指标主要集中在先前的睡眠减少上。本研究旨在确定对几种潜在的困倦调节因素敏感的困倦指标:睡眠剥夺、时间(TOD)和任务时间(TOT)在模拟器驾驶期间。13 名受试者在 24 小时内进行了 6 次 1 小时的高保真移动基础模拟器驾驶,分别在正常睡眠时间(8 小时)和部分睡眠剥夺(PSD;4 小时)后。结果表明,TOD(夜间)和 TOT 有明显的主要影响,但 PSD 没有,尽管后者与 TOD 强烈相互作用。最敏感的变量是主观困倦、侧向位置标准差(SDLAT)和闭眼测量[持续时间、速度(慢)、幅度(低)]。脑电图和线路交叉(LCs)测量仅显示出适度的反应。对于大多数变量,个体差异远远超过固定效应的差异,除了主观困倦和 SDLAT。在多元回归分析中,SDLAT、幅度/峰值眼睑闭合速度和眨眼持续时间预测主观困倦发作的敏感性和特异性约为 70%,但具有相互冗余性。LCs 的预测结果虽然较弱,但结果相似。总之,SDLAT 和闭眼变量可能是困倦监测设备中使用的候选者。然而,个体差异相当大,需要研究如何识别和预测对困倦易感性的个体差异。