Citation

Shin D, Sakai H, Uchiyama Y. J. Sleep Res. 2011; 20(3): 416-424.

Copyright

(Copyright © 2011, European Sleep Research Society, Publisher John Wiley and Sons)

DOI

10.1111/j.1365-2869.2010.00891.x

PMID

unavailable

Abstract

A delayed response caused by sleepiness can result in severe car accidents. Previous studies suggest that slow eye movement (SEM) is a sleep‐onset index related to delayed response. This study was undertaken to verify that SEM detection is effective for preventing sleep‐related accidents. We propose a real‐time detection algorithm of SEM based on feature‐extracted parameters of electrooculogram (EOG), i.e. amplitude and mean velocity of eye movement. In Experiment 1, 12 participants (33.5 ± 7.3 years) performed an auditory detection task with EOG measurement to determine the threshold parameters of the proposed algorithm. Consequently, the valid threshold parameters were determined, respectively, as >5° and <30° s⁻¹. In Experiment 2, 11 participants (32.8 ± 7.2 years) performed a simulated car‐following task to verify that the SEM detection is effective for preventing sleep‐related accidents. Accidents in the SEM condition were significantly more numerous than in the non‐SEM condition (P < 0.01, one‐way repeated‐measures anova followed by Scheffé's test). Furthermore, no accident occurred in the SEM condition with a warning generated using the proposed algorithm. Results also demonstrate clearly that the SEM detection can prevent sleep‐related accidents effectively in this simulated driving task.