Literature DB >> 32053169

Actigraphy-Based Assessment of Sleep Parameters.

Desta Fekedulegn1,2, Michael E Andrew1, Mingming Shi1, John M Violanti3, Sarah Knox2, Kim E Innes2.   

Abstract

Actigraphy, a method for inferring sleep/wake patterns based on movement data gathered using actigraphs, is increasingly used in population-based epidemiologic studies because of its ability to monitor activity in natural settings. Using special software, actigraphic data are analyzed to estimate a range of sleep parameters. To date, despite extensive application of actigraphs in sleep research, published literature specifically detailing the methodology for derivation of sleep parameters is lacking; such information is critical for the appropriate analysis and interpretation of actigraphy data. Reporting of sleep parameters has also been inconsistent across studies, likely reflecting the lack of consensus regarding the definition of sleep onset and offset. In addition, actigraphy data are generally underutilized, with only a fraction of the sleep parameters generated through actigraphy routinely used in current sleep research. The objectives of this paper are to review existing algorithms used to estimate sleep/wake cycles from movement data, demonstrate the rules/methods used for estimating sleep parameters, provide clear technical definitions of the parameters, and suggest potential new measures that reflect intraindividual variability. Utilizing original data collected using Motionlogger Sleep Watch (Ambulatory Monitoring Inc., Ardsley, NY), we detail the methodology and derivation of 29 nocturnal sleep parameters, including those both widely and rarely utilized in research. By improving understanding of the actigraphy process, the information provided in this paper may help: ensure appropriate use and interpretation of sleep parameters in future studies; enable the recalibration of sleep parameters to address specific goals; inform the development of new measures; and increase the breadth of sleep parameters used. Published by Oxford University Press on behalf of The British Occupational Hygiene Society 2020.

Entities:  

Keywords:  Motionlogger Sleep Watch; actigraphy; sleep parameters; sleep/wake algorithms

Mesh:

Year:  2020        PMID: 32053169      PMCID: PMC7191872          DOI: 10.1093/annweh/wxaa007

Source DB:  PubMed          Journal:  Ann Work Expo Health        ISSN: 2398-7308            Impact factor:   2.179


  43 in total

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