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Evaluations of Commercial Sleep Technologies for Objective Monitoring During Routine Sleeping Conditions

PURPOSE: The commercial market is saturated with technologies that claim to collect proficient, free-living sleep measurements despite a severe lack of independent third-party evaluations. Therefore, the present study evaluated the accuracy of various commercial sleep technologies during in-home sle...

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Autores principales: Stone, Jason D, Rentz, Lauren E, Forsey, Jillian, Ramadan, Jad, Markwald, Rachel R, Finomore, Victor S, Galster, Scott M, Rezai, Ali, Hagen, Joshua A
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7603649/
https://www.ncbi.nlm.nih.gov/pubmed/33149712
http://dx.doi.org/10.2147/NSS.S270705
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author Stone, Jason D
Rentz, Lauren E
Forsey, Jillian
Ramadan, Jad
Markwald, Rachel R
Finomore, Victor S
Galster, Scott M
Rezai, Ali
Hagen, Joshua A
author_facet Stone, Jason D
Rentz, Lauren E
Forsey, Jillian
Ramadan, Jad
Markwald, Rachel R
Finomore, Victor S
Galster, Scott M
Rezai, Ali
Hagen, Joshua A
author_sort Stone, Jason D
collection PubMed
description PURPOSE: The commercial market is saturated with technologies that claim to collect proficient, free-living sleep measurements despite a severe lack of independent third-party evaluations. Therefore, the present study evaluated the accuracy of various commercial sleep technologies during in-home sleeping conditions. MATERIALS AND METHODS: Data collection spanned 98 separate nights of ad libitum sleep from five healthy adults. Prior to bedtime, participants utilized nine popular sleep devices while concurrently wearing a previously validated electroencephalography (EEG)-based device. Data collected from the commercial devices were extracted for later comparison against EEG to determine degrees of accuracy. Sleep and wake summary outcomes as well as sleep staging metrics were evaluated, where available, for each device. RESULTS: Total sleep time (TST), total wake time (TWT), and sleep efficiency (SE) were measured with greater accuracy (lower percent errors) and limited bias by Fitbit Ionic [mean absolute percent error, bias (95% confidence interval); TST: 9.90%, 0.25 (−0.11, 0.61); TWT: 25.64%, −0.17 (−0.28, −0.06); SE: 3.49%, 0.65 (−0.82, 2.12)] and Oura smart ring [TST: 7.39%, 0.19 (0.04, 0.35); TWT: 36.29%, −0.18 (−0.31, −0.04); SE: 5.42%, 1.66 (0.17, 3.15)], whereas all other devices demonstrated a propensity to over or underestimate at least one if not all of the aforementioned sleep metrics. No commercial sleep technology appeared to accurately quantify sleep stages. CONCLUSION: Generally speaking, commercial sleep technologies displayed lower error and bias values when quantifying sleep/wake states as compared to sleep staging durations. Still, these findings revealed that there is a remarkably high degree of variability in the accuracy of commercial sleep technologies, which further emphasizes that continuous evaluations of newly developed sleep technologies are vital. End-users may then be able to determine more accurately which sleep device is most suited for their desired application(s).
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spelling pubmed-76036492020-11-03 Evaluations of Commercial Sleep Technologies for Objective Monitoring During Routine Sleeping Conditions Stone, Jason D Rentz, Lauren E Forsey, Jillian Ramadan, Jad Markwald, Rachel R Finomore, Victor S Galster, Scott M Rezai, Ali Hagen, Joshua A Nat Sci Sleep Original Research PURPOSE: The commercial market is saturated with technologies that claim to collect proficient, free-living sleep measurements despite a severe lack of independent third-party evaluations. Therefore, the present study evaluated the accuracy of various commercial sleep technologies during in-home sleeping conditions. MATERIALS AND METHODS: Data collection spanned 98 separate nights of ad libitum sleep from five healthy adults. Prior to bedtime, participants utilized nine popular sleep devices while concurrently wearing a previously validated electroencephalography (EEG)-based device. Data collected from the commercial devices were extracted for later comparison against EEG to determine degrees of accuracy. Sleep and wake summary outcomes as well as sleep staging metrics were evaluated, where available, for each device. RESULTS: Total sleep time (TST), total wake time (TWT), and sleep efficiency (SE) were measured with greater accuracy (lower percent errors) and limited bias by Fitbit Ionic [mean absolute percent error, bias (95% confidence interval); TST: 9.90%, 0.25 (−0.11, 0.61); TWT: 25.64%, −0.17 (−0.28, −0.06); SE: 3.49%, 0.65 (−0.82, 2.12)] and Oura smart ring [TST: 7.39%, 0.19 (0.04, 0.35); TWT: 36.29%, −0.18 (−0.31, −0.04); SE: 5.42%, 1.66 (0.17, 3.15)], whereas all other devices demonstrated a propensity to over or underestimate at least one if not all of the aforementioned sleep metrics. No commercial sleep technology appeared to accurately quantify sleep stages. CONCLUSION: Generally speaking, commercial sleep technologies displayed lower error and bias values when quantifying sleep/wake states as compared to sleep staging durations. Still, these findings revealed that there is a remarkably high degree of variability in the accuracy of commercial sleep technologies, which further emphasizes that continuous evaluations of newly developed sleep technologies are vital. End-users may then be able to determine more accurately which sleep device is most suited for their desired application(s). Dove 2020-10-27 /pmc/articles/PMC7603649/ /pubmed/33149712 http://dx.doi.org/10.2147/NSS.S270705 Text en © 2020 Stone et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Stone, Jason D
Rentz, Lauren E
Forsey, Jillian
Ramadan, Jad
Markwald, Rachel R
Finomore, Victor S
Galster, Scott M
Rezai, Ali
Hagen, Joshua A
Evaluations of Commercial Sleep Technologies for Objective Monitoring During Routine Sleeping Conditions
title Evaluations of Commercial Sleep Technologies for Objective Monitoring During Routine Sleeping Conditions
title_full Evaluations of Commercial Sleep Technologies for Objective Monitoring During Routine Sleeping Conditions
title_fullStr Evaluations of Commercial Sleep Technologies for Objective Monitoring During Routine Sleeping Conditions
title_full_unstemmed Evaluations of Commercial Sleep Technologies for Objective Monitoring During Routine Sleeping Conditions
title_short Evaluations of Commercial Sleep Technologies for Objective Monitoring During Routine Sleeping Conditions
title_sort evaluations of commercial sleep technologies for objective monitoring during routine sleeping conditions
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7603649/
https://www.ncbi.nlm.nih.gov/pubmed/33149712
http://dx.doi.org/10.2147/NSS.S270705
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