@article{ref1,
title="The accuracy of eyelid movement parameters for drowsiness detection",
journal="Journal of clinical sleep medicine",
year="2013",
author="Wilkinson, Vanessa E. and Jackson, Melinda L. and Westlake, Justine and Stevens, Bronwyn and Barnes, Maree and Swann, Philip and Rajaratnam, Shantha M. W. and Howard, Mark E.",
volume="9",
number="12",
pages="1315-1324",
abstract="STUDY OBJECTIVES: Drowsiness is a major risk factor for motor vehicle and occupational accidents. Real-time objective indicators of drowsiness could potentially identify drowsy individuals with the goal of intervening before an accident occurs. Several ocular measures are promising objective indicators of drowsiness; however, there is a lack of studies evaluating their accuracy for detecting behavioral impairment due to drowsiness in real time. METHODS: In this study, eye movement parameters were measured during vigilance tasks following restricted sleep and in a rested state (n = 33 participants) at three testing points (n = 71 data points) to compare ocular measures to a gold standard measure of drowsiness (OSLER). The utility of these parameters for detecting drowsiness-related errors was evaluated using receiver operating characteristic curves (ROC) (adjusted by clustering for participant) and identification of optimal cutoff levels for identifying frequent drowsiness-related errors (4 missed signals in a minute using OSLER). Their accuracy was tested for detecting increasing frequencies of behavioral lapses on a different task (psychomotor vigilance task [PVT]). RESULTS: Ocular variables which measured the average duration of eyelid closure (inter-event duration [IED]) and the ratio of the amplitude to velocity of eyelid closure were reliable indicators of frequent errors (area under the curve for ROC of 0.73 to 0.83, p < 0.05). IED produced a sensitivity and specificity of 71% and 88% for detecting ≥ 3 lapses (PVT) in a minute and 100% and 86% for ≥ 5 lapses. A composite measure of several eye movement characteristics (Johns Drowsiness Scale) provided sensitivities of 77% and 100% for detecting 3 and ≥ 5 lapses in a minute, with specificities of 85% and 83%, respectively. CONCLUSIONS: Ocular measures, particularly those measuring the average duration of episodes of eye closure are promising real-time indicators of drowsiness. CITATION: Wilkinson VE; Jackson ML; Westlake J; Stevens B; Barnes M; Swann P; Rajaratnam SMW; Howard ME. The accuracy of eyelid movement parameters for drowsiness detection. J Clin Sleep Med 2013;9(12):1315-1324.<p /> <p>Language: en</p>",
language="en",
issn="1550-9389",
doi="10.5664/jcsm.3278",
url="http://dx.doi.org/10.5664/jcsm.3278"
}