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Assessing the performance of a commercial multisensory sleep tracker

Wearable sleep technology allows for a less intruding sleep assessment than PSG, especially in long-term sleep monitoring. Though such devices are less accurate than PSG, sleep trackers may still provide valuable information. This study aimed to validate a commercial sleep tracker, Garmin Vivosmart...

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Autores principales: Mouritzen, Nanna J., Larsen, Lisbeth H., Lauritzen, Maja H., Kjær, Troels W.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732119/
https://www.ncbi.nlm.nih.gov/pubmed/33306678
http://dx.doi.org/10.1371/journal.pone.0243214
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author Mouritzen, Nanna J.
Larsen, Lisbeth H.
Lauritzen, Maja H.
Kjær, Troels W.
author_facet Mouritzen, Nanna J.
Larsen, Lisbeth H.
Lauritzen, Maja H.
Kjær, Troels W.
author_sort Mouritzen, Nanna J.
collection PubMed
description Wearable sleep technology allows for a less intruding sleep assessment than PSG, especially in long-term sleep monitoring. Though such devices are less accurate than PSG, sleep trackers may still provide valuable information. This study aimed to validate a commercial sleep tracker, Garmin Vivosmart 4 (GV4), against polysomnography (PSG) and to evaluate intra-device reliability (GV4 vs. GV4). Eighteen able-bodied adults (13 females, M = 56.1 ± 12.0 years) with no self-reported sleep disorders were simultaneously sleep monitored by GV4 and PSG for one night while intra-device reliability was monitored in one participant for 23 consecutive nights. Intra-device agreement was considered sufficient (observed agreement = 0.85 ± 0.13, Cohen’s kappa = 0.68 ± 0.24). GV4 detected sleep with high accuracy (0.90) and sensitivity (0.98) but low specificity (0.28). Cohen’s kappa was calculated for sleep/wake detection (0.33) and sleep stage detection (0.20). GV4 significantly underestimated time awake (p = 0.001) including wake after sleep onset (WASO) (p = 0.001), and overestimated light sleep (p = 0.045) and total sleep time (TST) (p = 0.001) (paired t-test). Sleep onset and sleep end differed insignificantly from PSG values. Our results suggest that GV4 is not able to reliably describe sleep architecture but may allow for detection of changes in sleep onset, sleep end, and TST (ICC ≥ 0.825) in longitudinally followed groups. Still, generalizations are difficult due to our sample limitations.
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spelling pubmed-77321192020-12-18 Assessing the performance of a commercial multisensory sleep tracker Mouritzen, Nanna J. Larsen, Lisbeth H. Lauritzen, Maja H. Kjær, Troels W. PLoS One Research Article Wearable sleep technology allows for a less intruding sleep assessment than PSG, especially in long-term sleep monitoring. Though such devices are less accurate than PSG, sleep trackers may still provide valuable information. This study aimed to validate a commercial sleep tracker, Garmin Vivosmart 4 (GV4), against polysomnography (PSG) and to evaluate intra-device reliability (GV4 vs. GV4). Eighteen able-bodied adults (13 females, M = 56.1 ± 12.0 years) with no self-reported sleep disorders were simultaneously sleep monitored by GV4 and PSG for one night while intra-device reliability was monitored in one participant for 23 consecutive nights. Intra-device agreement was considered sufficient (observed agreement = 0.85 ± 0.13, Cohen’s kappa = 0.68 ± 0.24). GV4 detected sleep with high accuracy (0.90) and sensitivity (0.98) but low specificity (0.28). Cohen’s kappa was calculated for sleep/wake detection (0.33) and sleep stage detection (0.20). GV4 significantly underestimated time awake (p = 0.001) including wake after sleep onset (WASO) (p = 0.001), and overestimated light sleep (p = 0.045) and total sleep time (TST) (p = 0.001) (paired t-test). Sleep onset and sleep end differed insignificantly from PSG values. Our results suggest that GV4 is not able to reliably describe sleep architecture but may allow for detection of changes in sleep onset, sleep end, and TST (ICC ≥ 0.825) in longitudinally followed groups. Still, generalizations are difficult due to our sample limitations. Public Library of Science 2020-12-11 /pmc/articles/PMC7732119/ /pubmed/33306678 http://dx.doi.org/10.1371/journal.pone.0243214 Text en © 2020 Mouritzen et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Mouritzen, Nanna J.
Larsen, Lisbeth H.
Lauritzen, Maja H.
Kjær, Troels W.
Assessing the performance of a commercial multisensory sleep tracker
title Assessing the performance of a commercial multisensory sleep tracker
title_full Assessing the performance of a commercial multisensory sleep tracker
title_fullStr Assessing the performance of a commercial multisensory sleep tracker
title_full_unstemmed Assessing the performance of a commercial multisensory sleep tracker
title_short Assessing the performance of a commercial multisensory sleep tracker
title_sort assessing the performance of a commercial multisensory sleep tracker
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732119/
https://www.ncbi.nlm.nih.gov/pubmed/33306678
http://dx.doi.org/10.1371/journal.pone.0243214
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