title: Bioradiolocation-based sleep stage classification.
abstract: This paper presents a method for classifying wakefulness, REM, light and deep sleep based on the analysis of respiratory activity and body motions acquired by a bioradar. The method was validated using data of 32 subjects without sleep-disordered breathing, who underwent a polysomnography study in a sleep laboratory. We achieved Cohen's kappa of 0.49 in the wake-REM-light-deep sleep classification, 0.55 for the wake-REM-NREM classification and 0.57 for the sleep/wakefulness determination. The results might be useful for the development of unobtrusive sleep monitoring systems for diagnostics, prevention, and management of sleep disorders.
authors.forename: Alexander
authors.initials: A
authors.lastname: Tataraidze
authors.forename: Lyudmila
authors.initials: L
authors.lastname: Korostovtseva
authors.forename: Lesya
authors.initials: L
authors.lastname: Anishchenko
authors.forename: Mikhail
authors.initials: M
authors.lastname: Bochkarev
authors.forename: Yurii
authors.initials: Y
authors.lastname: Sviryaev
authors.forename: Sergey
authors.initials: S
authors.lastname: Ivashov
mesh_terms: D000328:Adult; D000368:Aged; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000379:methods*; D009068:Movement; D012119:Respiration; D012894:Sleep Stages / Q000502:physiology*; D012893:Sleep Wake Disorders / Q000175:diagnosis / Q000503:physiopathology; D012895:Sleep, REM / Q000502:physiology; D014851:Wakefulness / Q000502:physiology; D055815:Young Adult