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Development and performance of a sleep estimation algorithm using a single accelerometer placed on the thigh: an evaluation against polysomnography
Department of Medical Sciences, Occupational and Environmental Medicine, Uppsala University, Uppsala University Hospital, Uppsala, Sweden.
The National Research Centre for the Working Environment, Copenhagen, Denmark.
Department of Psychology, Department of Clinical Neuroscience, Stress Research Institute, Karolinska Institutet, Stockholm University, Stockholm, Sweden.
Umeå University, Faculty of Medicine, Department of Surgical and Perioperative Sciences.ORCID iD: 0000-0002-5306-1697
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2023 (English)In: Journal of Sleep Research, ISSN 0962-1105, E-ISSN 1365-2869, Vol. 32, no 2, article id e13725Article in journal (Refereed) Published
Abstract [en]

Accelerometers placed on the thigh provide accurate measures of daily physical activity types, postures and sedentary behaviours, over 24 h and across consecutive days. However, the ability to estimate sleep duration or quality from thigh-worn accelerometers is uncertain and has not been evaluated in comparison with the ‘gold-standard’ measurement of sleep polysomnography. This study aimed to develop an algorithm for sleep estimation using the raw data from a thigh-worn accelerometer and to evaluate it in comparison with polysomnography. The algorithm was developed and optimised on a dataset consisting of 23 single-night polysomnography recordings, collected in a laboratory, from 15 asymptomatic adults. This optimised algorithm was then applied to a separate evaluation dataset, in which, 71 adult males (mean [SD] age 57 [11] years, height 181 [6] cm, weight 82 [13] kg) wore ambulatory polysomnography equipment and a thigh-worn accelerometer, simultaneously, whilst sleeping at home. Compared with polysomnography, the algorithm had a sensitivity of 0.84 and a specificity of 0.55 when estimating sleep periods. Sleep intervals were underestimated by 21 min (130 min, Limits of Agreement Range [LoAR]). Total sleep time was underestimated by 32 min (233 min LoAR). Our results evaluate the performance of a new algorithm for estimating sleep and outline the limitations. Based on these results, we conclude that a single device can provide estimates of the sleep interval and total sleep time with sufficient accuracy for the measurement of daily physical activity, sedentary behaviour, and sleep, on a group level in free-living settings.

Place, publisher, year, edition, pages
John Wiley & Sons, 2023. Vol. 32, no 2, article id e13725
Keywords [en]
actigraphy, activity tracker, wearables, physical activity, sedentary behaviour
National Category
Public Health, Global Health, Social Medicine and Epidemiology
Identifiers
URN: urn:nbn:se:umu:diva-200237DOI: 10.1111/jsr.13725ISI: 000860314300001PubMedID: 36167935Scopus ID: 2-s2.0-85139070466OAI: oai:DiVA.org:umu-200237DiVA, id: diva2:1703564
Funder
AFA Insurance, 150159Forte, Swedish Research Council for Health, Working Life and Welfare, 2021-01561Swedish Heart Lung Foundation, 20160343Available from: 2022-10-13 Created: 2022-10-13 Last updated: 2024-02-08Bibliographically approved

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Franklin, Karl

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