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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2020
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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. |
format | Online Article Text |
id | pubmed-7732119 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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