Article

Subjective sleepiness, simulated driving performance and blink duration: Examining individual differences. J Sleep Res 15: 47-53

Department of Psychology, Stockholm University, Tukholma, Stockholm, Sweden
Journal of Sleep Research (Impact Factor: 3.35). 03/2006; 15(1):47-53. DOI: 10.1111/j.1365-2869.2006.00504.x
Source: PubMed

ABSTRACT

The present study aimed to provide subject-specific estimates of the relation between subjective sleepiness measured with the Karolinska Sleepiness Scale (KSS) and blink duration (BLINKD) and lane drifting calculated as the standard deviation of the lateral position (SDLAT) in a high-fidelity moving base driving simulator. Five male and five female shift workers were recruited to participate in a 2-h drive (08:00-10:00 hours) after a normal night sleep and after working a night shift. Subjective sleepiness was rated on the KSS in 5-min intervals during the drive, electro-occulogram (EOG) was measured continuously to calculate BLINKD, and SDLAT was collected from the simulator. A mixed model anova showed a significant (P < 0.001) effect of the KSS for both dependent variables. A test for a quadratic trend suggests a curvilinear effect with a steeper increase at high KSS levels for both SDLAT (P < 0.001) and BLINKD (P = 0.003). Large individual differences were observed for the intercept (P < 0.001), suggesting that subjects differed in their overall driving performance and blink duration independent of sleepiness levels. The results have implications for any application that needs prediction at the subject level (e.g. driver fatigue warning systems) as well as for research design and the interpretation of group average data.

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    • "It is currently unknown whether different drowsiness detection devices have different sensitivities, and whether differential effectiveness is evident between these measures. Large and random individual differences in response to sleep loss are often observed in assessments of drowsiness/sleepiness (Van Dongen et al., 2004), performance of attentional tasks and within ocular measures designed to assess drowsiness, such as blink parameters (Ingre et al., 2006). Therefore , it is necessary to assess and compare individual variations in automated ocular measures during sleep loss. "

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