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Development and performance of a sleep estimation algorithm using a single accelerometer placed on the thigh: an evaluation against polysomnography

delete2022-09-27
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OA
AI
P
Peter Johansson *
P
Patrick Crowley *
J
John Axelsson
K
Karl A. Franklin
A
Anne Helene Garde
P
Pasan Hettiarachchi
A
Andreas Holtermann
G
Göran Kecklund
E
Eva Lindberg
M
Mirjam Ljunggren
E
Emmanuel Stamatakis
J
Jenny Theorell‐Haglöw
M
Magnus Svartengren
DOI:10.1111/jsr.13725delete
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Abstract

Abstract

En 中文
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.
Keywords:
actigraphy
activity tracker
wearables
physical activity
sedentary behaviour
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Journal of Sleep Research cover
Journal of Sleep Research
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Stockholm University
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uppsala university
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Karolinska Institutet
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