Wilhelm B, Wilhelm H, Lüdtke H, Streicher P, Adler M
Department of Pathophysiology of Vision and Neuro-ophthalmology, University Eye Hospital Tübingen.
Sleep. 1998 May 1;21(3):258-65.
Spontaneous pupillary-behavior in darkness provides information about a subject's level of sleepiness. In the present work, pupil measurements in complete darkness and quiet have been recorded continuously over 11-minute period with infrared video pupillography at 25 Hz. The data have been analyzed to yield three parameters describing pupil behavior; the power of diameter variation at frequencies below 0.8 Hz (slow changes in pupil size), the pupillary unrest index, and the average pupil size. To investigate the changes of these parameters in sleep deprivation, spontaneous pupillary behavior in darkness was recorded every 2 hours in 13 healthy subjects from 19:00 to 07:00 during forced wakefulness. On each occasion, comparative subjective sleepiness was assessed with a self-rating scale (Stanford Sleepiness Scale, SSS). The power of slow pupillary oscillations (< or = 0.8 Hz) increased significantly and so did the values of SSS, while basic pupil diameter decreased significantly. Slow pupillary oscillations and SSS did not correlate well in general but high values of pupil parameters were always associated with high values in subjective rating. Our results demonstrate a strong relationship between ongoing sleep deprivation and typical changes in the frequency profiles of spontaneous pupillary oscillations and the tendency to instability in pupil size in normals. These findings suggest that the results of pupil data analysis permit an objective measurement of sleepiness.
黑暗环境下的自发性瞳孔行为可提供有关受试者困倦程度的信息。在本研究中,使用红外视频瞳孔测量法以25赫兹的频率,在完全黑暗且安静的环境中持续记录了11分钟的瞳孔测量数据。对这些数据进行分析后得出了三个描述瞳孔行为的参数:低于0.8赫兹频率下直径变化的功率(瞳孔大小的缓慢变化)、瞳孔不安指数以及平均瞳孔大小。为了研究睡眠剥夺时这些参数的变化,在强制清醒期间,于19:00至07:00每隔2小时记录13名健康受试者在黑暗环境下的自发性瞳孔行为。每次记录时,使用自评量表(斯坦福嗜睡量表,SSS)评估相对主观困倦程度。缓慢瞳孔振荡(≤0.8赫兹)的功率显著增加,SSS值也显著增加,而基础瞳孔直径则显著减小。总体而言,缓慢瞳孔振荡与SSS的相关性不佳,但瞳孔参数的高值总是与主观评分的高值相关。我们的结果表明,持续的睡眠剥夺与正常受试者自发性瞳孔振荡频率分布的典型变化以及瞳孔大小不稳定的趋势之间存在密切关系。这些发现表明,瞳孔数据分析结果可实现对困倦程度的客观测量。