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A Validation Study of a Commercial Wearable Device to Automatically Detect and Estimate Sleep

The aims of this study were to: (1) compare actigraphy (ACTICAL) and a commercially available sleep wearable (i.e., WHOOP) under two functionalities (i.e., sleep auto-detection (WHOOP-AUTO) and manual adjustment of sleep (WHOOP-MANUAL)) for two-stage categorisation of sleep (sleep or wake) against p...

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Autores principales: Miller, Dean J., Roach, Gregory D., Lastella, Michele, Scanlan, Aaron T., Bellenger, Clint R., Halson, Shona L., Sargent, Charli
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8226553/
https://www.ncbi.nlm.nih.gov/pubmed/34201016
http://dx.doi.org/10.3390/bios11060185
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author Miller, Dean J.
Roach, Gregory D.
Lastella, Michele
Scanlan, Aaron T.
Bellenger, Clint R.
Halson, Shona L.
Sargent, Charli
author_facet Miller, Dean J.
Roach, Gregory D.
Lastella, Michele
Scanlan, Aaron T.
Bellenger, Clint R.
Halson, Shona L.
Sargent, Charli
author_sort Miller, Dean J.
collection PubMed
description The aims of this study were to: (1) compare actigraphy (ACTICAL) and a commercially available sleep wearable (i.e., WHOOP) under two functionalities (i.e., sleep auto-detection (WHOOP-AUTO) and manual adjustment of sleep (WHOOP-MANUAL)) for two-stage categorisation of sleep (sleep or wake) against polysomnography, and; (2) compare WHOOP-AUTO and WHOOP-MANUAL for four-stage categorisation of sleep (wake, light sleep, slow wave sleep (SWS), or rapid eye movement sleep (REM)) against polysomnography. Six healthy adults (male: n = 3; female: n = 3; age: 23.0 ± 2.2 yr) participated in the nine-night protocol. Fifty-four sleeps assessed by ACTICAL, WHOOP-AUTO and WHOOP-MANUAL were compared to polysomnography using difference testing, Bland–Altman comparisons, and 30-s epoch-by-epoch comparisons. Compared to polysomnography, ACTICAL overestimated total sleep time (37.6 min) and underestimated wake (−37.6 min); WHOOP-AUTO underestimated SWS (−15.5 min); and WHOOP-MANUAL underestimated wake (−16.7 min). For ACTICAL, sensitivity for sleep, specificity for wake and overall agreement were 98%, 60% and 89%, respectively. For WHOOP-AUTO, sensitivity for sleep, wake, and agreement for two-stage and four-stage categorisation of sleep were 90%, 60%, 86% and 63%, respectively. For WHOOP-MANUAL, sensitivity for sleep, wake, and agreement for two-stage and four-stage categorisation of sleep were 97%, 45%, 90% and 62%, respectively. WHOOP-AUTO and WHOOP-MANUAL have a similar sensitivity and specificity to actigraphy for two-stage categorisation of sleep and can be used as a practical alternative to polysomnography for two-stage categorisation of sleep and four-stage categorisation of sleep.
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spelling pubmed-82265532021-06-26 A Validation Study of a Commercial Wearable Device to Automatically Detect and Estimate Sleep Miller, Dean J. Roach, Gregory D. Lastella, Michele Scanlan, Aaron T. Bellenger, Clint R. Halson, Shona L. Sargent, Charli Biosensors (Basel) Article The aims of this study were to: (1) compare actigraphy (ACTICAL) and a commercially available sleep wearable (i.e., WHOOP) under two functionalities (i.e., sleep auto-detection (WHOOP-AUTO) and manual adjustment of sleep (WHOOP-MANUAL)) for two-stage categorisation of sleep (sleep or wake) against polysomnography, and; (2) compare WHOOP-AUTO and WHOOP-MANUAL for four-stage categorisation of sleep (wake, light sleep, slow wave sleep (SWS), or rapid eye movement sleep (REM)) against polysomnography. Six healthy adults (male: n = 3; female: n = 3; age: 23.0 ± 2.2 yr) participated in the nine-night protocol. Fifty-four sleeps assessed by ACTICAL, WHOOP-AUTO and WHOOP-MANUAL were compared to polysomnography using difference testing, Bland–Altman comparisons, and 30-s epoch-by-epoch comparisons. Compared to polysomnography, ACTICAL overestimated total sleep time (37.6 min) and underestimated wake (−37.6 min); WHOOP-AUTO underestimated SWS (−15.5 min); and WHOOP-MANUAL underestimated wake (−16.7 min). For ACTICAL, sensitivity for sleep, specificity for wake and overall agreement were 98%, 60% and 89%, respectively. For WHOOP-AUTO, sensitivity for sleep, wake, and agreement for two-stage and four-stage categorisation of sleep were 90%, 60%, 86% and 63%, respectively. For WHOOP-MANUAL, sensitivity for sleep, wake, and agreement for two-stage and four-stage categorisation of sleep were 97%, 45%, 90% and 62%, respectively. WHOOP-AUTO and WHOOP-MANUAL have a similar sensitivity and specificity to actigraphy for two-stage categorisation of sleep and can be used as a practical alternative to polysomnography for two-stage categorisation of sleep and four-stage categorisation of sleep. MDPI 2021-06-08 /pmc/articles/PMC8226553/ /pubmed/34201016 http://dx.doi.org/10.3390/bios11060185 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Miller, Dean J.
Roach, Gregory D.
Lastella, Michele
Scanlan, Aaron T.
Bellenger, Clint R.
Halson, Shona L.
Sargent, Charli
A Validation Study of a Commercial Wearable Device to Automatically Detect and Estimate Sleep
title A Validation Study of a Commercial Wearable Device to Automatically Detect and Estimate Sleep
title_full A Validation Study of a Commercial Wearable Device to Automatically Detect and Estimate Sleep
title_fullStr A Validation Study of a Commercial Wearable Device to Automatically Detect and Estimate Sleep
title_full_unstemmed A Validation Study of a Commercial Wearable Device to Automatically Detect and Estimate Sleep
title_short A Validation Study of a Commercial Wearable Device to Automatically Detect and Estimate Sleep
title_sort validation study of a commercial wearable device to automatically detect and estimate sleep
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8226553/
https://www.ncbi.nlm.nih.gov/pubmed/34201016
http://dx.doi.org/10.3390/bios11060185
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