A validation study of a commercial wearable device to automatically detect and estimate sleep
Journal article
Miller, Dean J., Roach, Gregory D., Lastella, Michelle, Scanlan, Aaron T., Bellenger, Clint R., Halson, Shona L. and Sargent, Charli. (2021). A validation study of a commercial wearable device to automatically detect and estimate sleep. Biosensors and Bioelectronics. 11(6), p. Article 185. https://doi.org/10.3390/bios11060185
Authors | Miller, Dean J., Roach, Gregory D., Lastella, Michelle, Scanlan, Aaron T., Bellenger, Clint R., Halson, Shona L. and Sargent, Charli |
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Abstract | 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. |
Keywords | consumer sleep technology; wearables; PSG; sleep staging; sleep monitoring; sleep quality |
Year | 2021 |
Journal | Biosensors and Bioelectronics |
Journal citation | 11 (6), p. Article 185 |
Publisher | Multidisciplinary Digital Publishing Institute (MDPI AG) |
ISSN | 2079-6374 |
Digital Object Identifier (DOI) | https://doi.org/10.3390/bios11060185 |
PubMed ID | 34201016 |
Scopus EID | 2-s2.0-85108272816 |
PubMed Central ID | PMC8226553 |
Open access | Published as ‘gold’ (paid) open access |
Research or scholarly | Research |
Page range | 1-14 |
Funder | Australian Research Council (ARC) |
Australian Institute of Sport (AIS) | |
Publisher's version | License File Access Level Open |
Output status | Published |
Publication dates | |
Online | 08 Jun 2021 |
Publication process dates | |
Accepted | 04 Jun 2021 |
Deposited | 25 Aug 2022 |
ARC Funded Research | This output has been funded, wholly or partially, under the Australian Research Council Act 2001 |
Grant ID | DP160104909 |
https://acuresearchbank.acu.edu.au/item/8y2yz/a-validation-study-of-a-commercial-wearable-device-to-automatically-detect-and-estimate-sleep
Download files
Publisher's version
OA_Miller_2021_A_validation_study_of_a_commercial.pdf | |
License: CC BY 4.0 | |
File access level: Open |
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