title: In search of objective components for sleep quality indexing in normal sleep.
abstract: The main goal of this study was to investigate to what extent polysomnographic (PSG) recordings of nocturnal human sleep can provide information about sleep quality in terms of correlation with a set of daytime measures. These measures were designed with the aim of comprising selected quality of night sleep and consist of subjective sleep quality ratings, neuropsychological tests and physiological parameters. First, a factor analysis model was applied to the large number of daytime measures of sleep quality in order to detect their latent structure. Secondly, in addition to the gold standard sleep staging method to arrive at variables about sleep architecture from PSG, we applied a recently developed continuous sleep representation by considering the probabilistic sleep model (PSM) describing the microstructure of sleep. Significant correlations between sleep architecture and daytime variables of sleep quality were found. Both the factor analysis and the PSM helped maximize the information about this relationship.
authors.affiliation: Section for Artificial Intelligence, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University of Vienna, Austria. roman.rosipal@savba.sk
authors.forename: Roman
authors.initials: R
authors.lastname: Rosipal
authors.forename: Achim
authors.initials: A
authors.lastname: Lewandowski
authors.forename: Georg
authors.initials: G
authors.lastname: Dorffner
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D005163:Factor Analysis, Statistical; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D009483:Neuropsychological Tests; D017286:Polysomnography; D011336:Probability; D011930:Reaction Time / Q000502:physiology; D012106:Research; D012890:Sleep / Q000502:physiology*; D012894:Sleep Stages; D018709:Statistics, Nonparametric; D011795:Surveys and Questionnaires; D014851:Wakefulness; D055815:Young Adult
keywords: Continuous probabilistic sleep model; Factor analysis; Subjective and objective sleep indices