Performance prediction by sleepiness-related subjective symptoms during 26-hour sleep deprivation

Sleepiness is a major cause of lower productivity and higher risk of accidents in various work situations. Developing sleepiness monitoring techniques is important to improve work efficiency and to reduce accident risk, so that people can take a rest/break in appropriate timing before an accident or a mistake occurs. The aims of the present study are (1) to explain subjective sleepiness using sleep-related symptoms, and (2) to examine which symptoms are useful to predict performance errors. Participants were healthy paid volunteers (six males, six females; mean ± SD, 31.5 ± 10.74 years). Participants took part in 26-h sleep deprivation. During sleep deprivation, they carried out several performance tasks every 3 h and an hourly rating of questionnaires to evaluate subjective symptoms including two types of Karolinska sleepiness scale (KSS). The present study confirmed that performance errors can be predicted by subjective symptoms. While mental fatigue was correlated to KSS scores linearly, eye-related subjective symptoms showed quadratic correlations to KSS. By taking into consideration this noteworthy relationship between subjective symptoms and sleepiness, more accurate introspection of sleepiness and performance errors prediction (detection) may be possible.