title: Two auto-detection methods for eye movements during eyes closed.
abstract: Eye movements during closed eyes closely reflect changes of the arousal level during transition from wakefulness to sleep. Because they contain both rapid and slow eye movements (REM and SEM), it has been difficult to detect them automatically. Hiroshige recently developed the method of linear regression analysis for automatic detection of the two types of eye movements, and we have developed a template matching method for autodetection. The aim of the present study was to compare both auto-detection methods and visual scoring for REM and SEM. The results revealed high agreement between the two quantitative methods and the visual scoring, indicating that auto-detection of eye movements is useful for quantitative evaluation of arousal level.
authors: Department of Neuropsychiatry, Nihon University School of Medicine, Tokyo, Japan. hiroyuki@kk.catv.ne.jp
authors: H
authors: H
authors: Suzuki
authors: M
authors: M
authors: Matsuura
authors: K
authors: K
authors: Moriguchi
authors: T
authors: T
authors: Kojima
authors: Y
authors: Y
authors: Hiroshige
authors: T
authors: T
authors: Matsuda
authors: Y
authors: Y
authors: Noda
mesh_terms: D001143:Arousal / Q000502:physiology; D004585:Electrooculography / Q000379:methods; D005123:Eye; D005133:Eye Movements / Q000502:physiology*; D006801:Humans; D017286:Polysomnography / Q000379:methods*; D012044:Regression Analysis; D012894:Sleep Stages / Q000502:physiology*; D012895:Sleep, REM / Q000502:physiology; D013997:Time Factors; D014851:Wakefulness / Q000502:physiology