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Defining the rest interval associated with the main sleep period in actigraph scoring

Authors Chow CM, Wong SN, Shin M, Maddox RG, Feilds KL, Paxton K, Hawke C, Hazell P, Steinbeck K

Received 14 June 2016

Accepted for publication 8 September 2016

Published 21 November 2016 Volume 2016:8 Pages 321—328


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Professor Steven A Shea

Chin Moi Chow,1 Shi Ngar Wong,1 Mirim Shin,1 Rebecca G Maddox,2 Kristy-Lee Feilds,3 Karen Paxton,4 Catherine Hawke,4 Philip Hazell,3 Katharine Steinbeck5

1Discipline of Exercise and Sport Science, Faculty of Health Sciences, 2Sydney Medical School, 3Discipline of Psychiatry, 4School of Rural Health, 5Discipline of Paediatrics and Child Health, Sydney Medical School, The University of Sydney, Sydney, NSW, Australia

Abstract: Actigraphy is increasingly used for sleep monitoring. However, there is a lack of standardized methodology for data processing and analysis, which often makes between study comparisons difficult, if not impossible, and thus open to flawed interpretation. This study evaluated a manual method for detection of the rest interval in actigraph data collected with Actiwatch 2. The rest interval (time in bed), defined as the bedtime and rise time and set by proprietary software, is an essential requirement for the estimation of sleep indices. This study manually and systematically detected the rest interval of 187 nights of recording from seven healthy males and three females, aged 13.5±0.7 (mean ± standard deviation) years. Data were analyzed for agreement between software default algorithm and manual scoring. Inter-rater reliability in manual scoring was also tested between two scorers. Data showed consistency between default settings and manual scorers for bedtime and rise time, but only moderate agreement for the rest interval duration and poor agreement for activity level at bedtime and rise time. Manual detection of rest intervals between scorers showed a high degree of agreement for all parameters (intraclass correlations range 0.864 to 0.995). The findings demonstrate that the default algorithm on occasions was unable to detect rest intervals or set the exact interval. Participant issues and inter-scorer issues also made difficult the detection of rest intervals. These findings have led to a manual detection protocol to define bedtime and rise time, supplemented with an event diary.

Keywords: actigraph recording, activity level, light level

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