Development and performance of a sleep estimation algorithm using a single accelerometer placed on the thigh: an evaluation against polysomnography
Autor: | Peter J. Johansson, Patrick Crowley, John Axelsson, Karl Franklin, Anne Helene Garde, Pasan Hettiarachchi, Andreas Holtermann, Göran Kecklund, Eva Lindberg, Mirjam Ljunggren, Emmanuel Stamatakis, Jenny Theorell Haglöw, Magnus Svartengren |
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Rok vydání: | 2022 |
Předmět: |
Arbetsmedicin och miljömedicin
Behavioral Neuroscience Folkhälsovetenskap global hälsa socialmedicin och epidemiologi wearables Cognitive Neuroscience sedentary behaviour activity tracker physical activity Public Health Global Health Social Medicine and Epidemiology Occupational Health and Environmental Health General Medicine actigraphy |
Zdroj: | Journal of sleep researchREFERENCES. |
ISSN: | 1365-2869 |
Popis: | 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. |
Databáze: | OpenAIRE |
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