Stefan Lüdtke1, Wiebke Hermann2, Thomas Kirste3, Heike Beneš4, Stefan Teipel5. 1. Institute of Visual & Analytic Computing, University of Rostock, Rostock, Germany. Electronic address: stefan.luedtke2@uni-rostock.de. 2. German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany; Department of Neurology, University of Rostock, Rostock, Germany. 3. Institute of Visual & Analytic Computing, University of Rostock, Rostock, Germany. 4. Department of Neurology, University of Rostock, Rostock, Germany; Somni Bene Institute for Medical Research and Sleep Medicine, Schwerin, Germany. 5. German Center for Neurodegenerative Diseases (DZNE), Rostock, Germany; Department of Psychosomatic and Psychotherapeutic Medicine, University of Rostock, Rostock, Germany.
Abstract
OBJECTIVE: To evaluate the accuracy of actigraphy against polysomnography (PSG) as gold standard using a newly developed algorithm for sleep/wake discrimination that explicitly models the temporal structure of sleep. METHODS: PSG was recorded in 11 men and 9 women (age 71.1±5.0) to evaluate suspected neuropsychiatric sleep disturbances. Simultaneously, wrist actigraphy was recorded, from which 37 features were computed for each 1-min epoch. We compared prediction of PSG-derived sleep/wake states for each of these features between our newly developed algorithm, and four state-of-the-art algorithms. The algorithms were evaluated using a leave-one-subject out cross validation. RESULTS: The new algorithm classified 84.9% of sleep epochs (sensitivity) and 74.2% of wake epochs correctly (specificity), leading to a sleep/wake scoring accuracy of 79.0%. Four out of five sleep parameters were estimated more accurately by the new algorithm than by state-of-the-art algorithms. CONCLUSION: The proposed algorithm achieved a significantly higher specificity than state-of-the-art algorithm, with only minor decrease in sensitivity for patients with sleep disorders. We assume this reflects the capability of the algorithm to explicitly model sleep architecture. SIGNIFICANCE: The unobtrusive assessment of sleep/wake cycles is particularly relevant for patients with neuropsychiatric diseases that are associated with sleep disturbances, such as depression or dementia.
OBJECTIVE: To evaluate the accuracy of actigraphy against polysomnography (PSG) as gold standard using a newly developed algorithm for sleep/wake discrimination that explicitly models the temporal structure of sleep. METHODS: PSG was recorded in 11 men and 9 women (age 71.1±5.0) to evaluate suspected neuropsychiatric sleep disturbances. Simultaneously, wrist actigraphy was recorded, from which 37 features were computed for each 1-min epoch. We compared prediction of PSG-derived sleep/wake states for each of these features between our newly developed algorithm, and four state-of-the-art algorithms. The algorithms were evaluated using a leave-one-subject out cross validation. RESULTS: The new algorithm classified 84.9% of sleep epochs (sensitivity) and 74.2% of wake epochs correctly (specificity), leading to a sleep/wake scoring accuracy of 79.0%. Four out of five sleep parameters were estimated more accurately by the new algorithm than by state-of-the-art algorithms. CONCLUSION: The proposed algorithm achieved a significantly higher specificity than state-of-the-art algorithm, with only minor decrease in sensitivity for patients with sleep disorders. We assume this reflects the capability of the algorithm to explicitly model sleep architecture. SIGNIFICANCE: The unobtrusive assessment of sleep/wake cycles is particularly relevant for patients with neuropsychiatric diseases that are associated with sleep disturbances, such as depression or dementia.
Authors: Dagfinn Matre; Per Anton Sirnes; Elisabeth Goffeng; Øivind Skare; Marit Skogstad Journal: Int J Environ Res Public Health Date: 2022-02-10 Impact factor: 3.390