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Tracking intermediate performance of vigilant attention using multiple eye metrics.
Abe, Takashi; Mishima, Kazuo; Kitamura, Shingo; Hida, Akiko; Inoue, Yuichi; Mizuno, Koh; Kaida, Kosuke; Nakazaki, Kyoko; Motomura, Yuki; Maruo, Kazushi; Ohta, Toshiko; Furukawa, Satoshi; Dinges, David F; Ogata, Katsuhiko.
Afiliação
  • Abe T; Astronaut and Operation Control Unit, Human Spaceflight Technology Directorate, Japan Aerospace Exploration Agency, Tsukuba, Ibaraki, Japan.
  • Mishima K; International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Ibaraki, Japan.
  • Kitamura S; Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.
  • Hida A; International Institute for Integrative Sleep Medicine (WPI-IIIS), University of Tsukuba, Tsukuba, Ibaraki, Japan.
  • Inoue Y; Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.
  • Mizuno K; Department of Neuropsychiatry, Akita University Graduate School of Medicine, Akita-city, Akita, Japan.
  • Kaida K; Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.
  • Nakazaki K; Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.
  • Motomura Y; Department of Somnology, Tokyo Medical University, Shinjuku-Ku, Tokyo, Japan.
  • Maruo K; Astronaut and Operation Control Unit, Human Spaceflight Technology Directorate, Japan Aerospace Exploration Agency, Tsukuba, Ibaraki, Japan.
  • Ohta T; Faculty of Education, Tohoku Fukushi University, Sendai, Miyagi, Japan.
  • Furukawa S; Automotive Human Factors Research Center, Department of Information Technology and Human Factors, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki, Japan.
  • Dinges DF; Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.
  • Ogata K; Department of Sleep-Wake Disorders, National Institute of Mental Health, National Center of Neurology and Psychiatry, Kodaira, Tokyo, Japan.
Sleep ; 43(3)2020 03 12.
Article em En | MEDLINE | ID: mdl-32040590
ABSTRACT
Vigilance deficits account for a substantial number of accidents and errors. Current techniques to detect vigilance impairment measure only the most severe level evident in eyelid closure and falling asleep, which is often too late to avoid an accident or error. The present study sought to identify ocular biometrics of intermediate impairment of vigilance and develop a new technique that could detect a range of deficits in vigilant attention (VA). Sixteen healthy adults performed well-validated Psychomotor Vigilance Test (PVT) for tracking vigilance attention while undergoing simultaneous recording of eye metrics every 2 hours during 38 hours of continuous wakefulness. A novel marker was found that measured VA when the eyes were open-the prevalence of microsaccades. Notably, the prevalence of microsaccades decreased in response to sleep deprivation and time-on-task. In addition, a novel algorithm for detecting multilevel VA was developed, which estimated performance on the PVT by integrating the novel marker with other eye-related indices. The novel algorithm also tracked changes in intermediate level of VA (specific reaction times in the PVT, i.e. 300-500 ms) during prolonged time-on-task and sleep deprivation, which had not been tracked previously by conventional techniques. The implication of the findings is that this novel algorithm, named "eye-metrical estimation version of the PVT PVT-E," can be used to reduce human-error-related accidents caused by vigilance impairment even when its level is intermediate.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Vigília / Benchmarking Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Vigília / Benchmarking Idioma: En Ano de publicação: 2020 Tipo de documento: Article