Related Experiment Video
Updated: May 28, 2026

The Rodent Psychomotor Vigilance Test (rPVT): A Method for Assessing Neurobehavioral Performance in Rats and Mice
Published on: December 29, 2016
Detecting deteriorated vigilance using percentage of eyelid closure time during behavioral maintenance of wakefulness
Takashi Abe1, Tomohide Nonomura, Yoko Komada
1Japan Somnology Center, Neuropsychiatric Research Institute, Tokyo, Japan. abe@somnology.com
Abstract:
Several researchers have investigated the relation between vigilance and ocular variables such as saccade, slow eye movement, pupil, blink, or eyelid closure. This study was undertaken to find the most effective indicator among these ocular variables for evaluating short-term (1 min) fluctuation of vigilance, and to investigate the ability of the most effective ocular variable for predicting deteriorated vigilance during behavioral maintenance of the wakefulness test (Oxford sleep resistance test: OSLER test). Nine healthy volunteers (two women, 19-30 years old, 23.4±3.9 years old) participated in this study. Ocular variables were recorded during the OSLER test at 10 A.M. and 2 P.M. before and after partial sleep deprivation (4h sleep). The periods during the OSLER test were divided into 1 min epochs. Each epoch was classified according to the number of consecutive missed responses. Decreased blink frequency and pupil diameter as well as increased percentage of eyelid closure time (PERCLOS) and slow eye movement were observed as the consecutive missed responses increased. Among these variables, PERCLOS showed the highest ability to detect occurrence of any missed response and three or more consecutive missed responses. Moreover, a missed response seldom occurred (0.2±0.2/20 trial/min) when PERCLOS was less than 11.5% per minute. Results suggest that, among the ocular variables, PERCLOS can prevent error or accident caused by low vigilance most effectively.
More Related Videos
07:26Characterizing the Relationship Between Eye Movement Parameters and Cognitive Functions in Non-demented Parkinson's Disease Patients with Eye Tracking
Published on: September 26, 2019
08:36Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
Published on: August 8, 2019