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Performance of seven consumer sleep-tracking devices compared with polysomnography
Abstract Study Objectives Consumer sleep-tracking devices are widely used and becoming more technologically advanced, creating strong interest from researchers and clinicians for their possible use as alternatives to standard actigraphy. We, therefore, tested the performance of many of the latest co...
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Published in: | Sleep (New York, N.Y.) N.Y.), 2021-05, Vol.44 (5), p.1 |
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creator | Chinoy, Evan D Cuellar, Joseph A Huwa, Kirbie E Jameson, Jason T Watson, Catherine H Bessman, Sara C Hirsch, Dale A Cooper, Adam D Drummond, Sean P A Markwald, Rachel R |
description | Abstract
Study Objectives
Consumer sleep-tracking devices are widely used and becoming more technologically advanced, creating strong interest from researchers and clinicians for their possible use as alternatives to standard actigraphy. We, therefore, tested the performance of many of the latest consumer sleep-tracking devices, alongside actigraphy, versus the gold-standard sleep assessment technique, polysomnography (PSG).
Methods
In total, 34 healthy young adults (22 women; 28.1 ± 3.9 years, mean ± SD) were tested on three consecutive nights (including a disrupted sleep condition) in a sleep laboratory with PSG, along with actigraphy (Philips Respironics Actiwatch 2) and a subset of consumer sleep-tracking devices. Altogether, four wearable (Fatigue Science Readiband, Fitbit Alta HR, Garmin Fenix 5S, Garmin Vivosmart 3) and three nonwearable (EarlySense Live, ResMed S+, SleepScore Max) devices were tested. Sleep/wake summary and epoch-by-epoch agreement measures were compared with PSG.
Results
Most devices (Fatigue Science Readiband, Fitbit Alta HR, EarlySense Live, ResMed S+, SleepScore Max) performed as well as or better than actigraphy on sleep/wake performance measures, while the Garmin devices performed worse. Overall, epoch-by-epoch sensitivity was high (all ≥0.93), specificity was low-to-medium (0.18–0.54), sleep stage comparisons were mixed, and devices tended to perform worse on nights with poorer/disrupted sleep.
Conclusions
Consumer sleep-tracking devices exhibited high performance in detecting sleep, and most performed equivalent to (or better than) actigraphy in detecting wake. Device sleep stage assessments were inconsistent. Findings indicate that many newer sleep-tracking devices demonstrate promising performance for tracking sleep and wake. Devices should be tested in different populations and settings to further examine their wider validity and utility. |
doi_str_mv | 10.1093/sleep/zsaa291 |
format | article |
fullrecord | <record><control><sourceid>gale_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_8120339</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><galeid>A700260640</galeid><oup_id>10.1093/sleep/zsaa291</oup_id><sourcerecordid>A700260640</sourcerecordid><originalsourceid>FETCH-LOGICAL-c487t-a3e8fa632e9f6ca75686c7d1bb8ba0ade3342f9d8809fdc11dfa92224552a6b53</originalsourceid><addsrcrecordid>eNqFkUtv1DAUhS0EokNhyRZFYsMmrZ-JvUGqKl5SJRCCteXY1zMuiR3syVTDr8ftDOWxQV5Y9v3u0T33IPSc4DOCFTsvI8B8_qMYQxV5gFZECNyqWnqIVph0pJUEixP0pJRrXN9cscfohDHWS8HUCn3-BNmnPJlooUm-KbCD2NgUyzJBbu7U22029luI68bBLlgotT7NJoNrbsJ208xp3Jc0xbTOZt7sn6JH3owFnh3vU_T17Zsvl-_bq4_vPlxeXLWWy37bGgbSm45RUL6zphed7GzvyDDIwWDjgDFOvXJSYuWdJcR5oyilXAhqukGwU_T6oDsvwwTOQqxzjnrOYTJ5r5MJ-u9KDBu9TjstCcWMqSrw6iiQ0_cFylZPoVgYRxMhLUVT3nOupJC8oi__Qa_TkmO1p6lghCrMMa3U2YFamxF0iD7dbq4eB1OoOwUf6v9FjzHtcMdxbWgPDTanUjL4--kJ1rfx6rsA9DHeyr_40_I9_SvP35bSMv9H6yc3yrLD</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2531290402</pqid></control><display><type>article</type><title>Performance of seven consumer sleep-tracking devices compared with polysomnography</title><source>Oxford Journals Online</source><source>Alma/SFX Local Collection</source><creator>Chinoy, Evan D ; Cuellar, Joseph A ; Huwa, Kirbie E ; Jameson, Jason T ; Watson, Catherine H ; Bessman, Sara C ; Hirsch, Dale A ; Cooper, Adam D ; Drummond, Sean P A ; Markwald, Rachel R</creator><creatorcontrib>Chinoy, Evan D ; Cuellar, Joseph A ; Huwa, Kirbie E ; Jameson, Jason T ; Watson, Catherine H ; Bessman, Sara C ; Hirsch, Dale A ; Cooper, Adam D ; Drummond, Sean P A ; Markwald, Rachel R</creatorcontrib><description>Abstract
Study Objectives
Consumer sleep-tracking devices are widely used and becoming more technologically advanced, creating strong interest from researchers and clinicians for their possible use as alternatives to standard actigraphy. We, therefore, tested the performance of many of the latest consumer sleep-tracking devices, alongside actigraphy, versus the gold-standard sleep assessment technique, polysomnography (PSG).
Methods
In total, 34 healthy young adults (22 women; 28.1 ± 3.9 years, mean ± SD) were tested on three consecutive nights (including a disrupted sleep condition) in a sleep laboratory with PSG, along with actigraphy (Philips Respironics Actiwatch 2) and a subset of consumer sleep-tracking devices. Altogether, four wearable (Fatigue Science Readiband, Fitbit Alta HR, Garmin Fenix 5S, Garmin Vivosmart 3) and three nonwearable (EarlySense Live, ResMed S+, SleepScore Max) devices were tested. Sleep/wake summary and epoch-by-epoch agreement measures were compared with PSG.
Results
Most devices (Fatigue Science Readiband, Fitbit Alta HR, EarlySense Live, ResMed S+, SleepScore Max) performed as well as or better than actigraphy on sleep/wake performance measures, while the Garmin devices performed worse. Overall, epoch-by-epoch sensitivity was high (all ≥0.93), specificity was low-to-medium (0.18–0.54), sleep stage comparisons were mixed, and devices tended to perform worse on nights with poorer/disrupted sleep.
Conclusions
Consumer sleep-tracking devices exhibited high performance in detecting sleep, and most performed equivalent to (or better than) actigraphy in detecting wake. Device sleep stage assessments were inconsistent. Findings indicate that many newer sleep-tracking devices demonstrate promising performance for tracking sleep and wake. Devices should be tested in different populations and settings to further examine their wider validity and utility.</description><identifier>ISSN: 0161-8105</identifier><identifier>EISSN: 1550-9109</identifier><identifier>DOI: 10.1093/sleep/zsaa291</identifier><identifier>PMID: 33378539</identifier><language>eng</language><publisher>US: Oxford University Press</publisher><subject>Actigraphy ; Adult ; Basic Science of Sleep and Circadian Rhythms ; Comparative analysis ; Consumer behavior ; Editor's Choice ; Female ; Humans ; Marketing research ; Polysomnography ; Reproducibility of Results ; Sleep ; Sleep Stages ; Young Adult</subject><ispartof>Sleep (New York, N.Y.), 2021-05, Vol.44 (5), p.1</ispartof><rights>Sleep Research Society 2020. Published by Oxford University Press on behalf of the Sleep Research Society. 2020</rights><rights>Sleep Research Society 2020. Published by Oxford University Press on behalf of the Sleep Research Society.</rights><rights>COPYRIGHT 2021 Oxford University Press</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c487t-a3e8fa632e9f6ca75686c7d1bb8ba0ade3342f9d8809fdc11dfa92224552a6b53</citedby><cites>FETCH-LOGICAL-c487t-a3e8fa632e9f6ca75686c7d1bb8ba0ade3342f9d8809fdc11dfa92224552a6b53</cites><orcidid>0000-0002-3670-1189 ; 0000-0001-6613-6654 ; 0000-0002-0432-3937 ; 0000-0002-9815-626X</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33378539$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Chinoy, Evan D</creatorcontrib><creatorcontrib>Cuellar, Joseph A</creatorcontrib><creatorcontrib>Huwa, Kirbie E</creatorcontrib><creatorcontrib>Jameson, Jason T</creatorcontrib><creatorcontrib>Watson, Catherine H</creatorcontrib><creatorcontrib>Bessman, Sara C</creatorcontrib><creatorcontrib>Hirsch, Dale A</creatorcontrib><creatorcontrib>Cooper, Adam D</creatorcontrib><creatorcontrib>Drummond, Sean P A</creatorcontrib><creatorcontrib>Markwald, Rachel R</creatorcontrib><title>Performance of seven consumer sleep-tracking devices compared with polysomnography</title><title>Sleep (New York, N.Y.)</title><addtitle>Sleep</addtitle><description>Abstract
Study Objectives
Consumer sleep-tracking devices are widely used and becoming more technologically advanced, creating strong interest from researchers and clinicians for their possible use as alternatives to standard actigraphy. We, therefore, tested the performance of many of the latest consumer sleep-tracking devices, alongside actigraphy, versus the gold-standard sleep assessment technique, polysomnography (PSG).
Methods
In total, 34 healthy young adults (22 women; 28.1 ± 3.9 years, mean ± SD) were tested on three consecutive nights (including a disrupted sleep condition) in a sleep laboratory with PSG, along with actigraphy (Philips Respironics Actiwatch 2) and a subset of consumer sleep-tracking devices. Altogether, four wearable (Fatigue Science Readiband, Fitbit Alta HR, Garmin Fenix 5S, Garmin Vivosmart 3) and three nonwearable (EarlySense Live, ResMed S+, SleepScore Max) devices were tested. Sleep/wake summary and epoch-by-epoch agreement measures were compared with PSG.
Results
Most devices (Fatigue Science Readiband, Fitbit Alta HR, EarlySense Live, ResMed S+, SleepScore Max) performed as well as or better than actigraphy on sleep/wake performance measures, while the Garmin devices performed worse. Overall, epoch-by-epoch sensitivity was high (all ≥0.93), specificity was low-to-medium (0.18–0.54), sleep stage comparisons were mixed, and devices tended to perform worse on nights with poorer/disrupted sleep.
Conclusions
Consumer sleep-tracking devices exhibited high performance in detecting sleep, and most performed equivalent to (or better than) actigraphy in detecting wake. Device sleep stage assessments were inconsistent. Findings indicate that many newer sleep-tracking devices demonstrate promising performance for tracking sleep and wake. Devices should be tested in different populations and settings to further examine their wider validity and utility.</description><subject>Actigraphy</subject><subject>Adult</subject><subject>Basic Science of Sleep and Circadian Rhythms</subject><subject>Comparative analysis</subject><subject>Consumer behavior</subject><subject>Editor's Choice</subject><subject>Female</subject><subject>Humans</subject><subject>Marketing research</subject><subject>Polysomnography</subject><subject>Reproducibility of Results</subject><subject>Sleep</subject><subject>Sleep Stages</subject><subject>Young Adult</subject><issn>0161-8105</issn><issn>1550-9109</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>TOX</sourceid><recordid>eNqFkUtv1DAUhS0EokNhyRZFYsMmrZ-JvUGqKl5SJRCCteXY1zMuiR3syVTDr8ftDOWxQV5Y9v3u0T33IPSc4DOCFTsvI8B8_qMYQxV5gFZECNyqWnqIVph0pJUEixP0pJRrXN9cscfohDHWS8HUCn3-BNmnPJlooUm-KbCD2NgUyzJBbu7U22029luI68bBLlgotT7NJoNrbsJ208xp3Jc0xbTOZt7sn6JH3owFnh3vU_T17Zsvl-_bq4_vPlxeXLWWy37bGgbSm45RUL6zphed7GzvyDDIwWDjgDFOvXJSYuWdJcR5oyilXAhqukGwU_T6oDsvwwTOQqxzjnrOYTJ5r5MJ-u9KDBu9TjstCcWMqSrw6iiQ0_cFylZPoVgYRxMhLUVT3nOupJC8oi__Qa_TkmO1p6lghCrMMa3U2YFamxF0iD7dbq4eB1OoOwUf6v9FjzHtcMdxbWgPDTanUjL4--kJ1rfx6rsA9DHeyr_40_I9_SvP35bSMv9H6yc3yrLD</recordid><startdate>20210501</startdate><enddate>20210501</enddate><creator>Chinoy, Evan D</creator><creator>Cuellar, Joseph A</creator><creator>Huwa, Kirbie E</creator><creator>Jameson, Jason T</creator><creator>Watson, Catherine H</creator><creator>Bessman, Sara C</creator><creator>Hirsch, Dale A</creator><creator>Cooper, Adam D</creator><creator>Drummond, Sean P A</creator><creator>Markwald, Rachel R</creator><general>Oxford University Press</general><scope>TOX</scope><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>88G</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>M2M</scope><scope>M2O</scope><scope>MBDVC</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>PSYQQ</scope><scope>Q9U</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-3670-1189</orcidid><orcidid>https://orcid.org/0000-0001-6613-6654</orcidid><orcidid>https://orcid.org/0000-0002-0432-3937</orcidid><orcidid>https://orcid.org/0000-0002-9815-626X</orcidid></search><sort><creationdate>20210501</creationdate><title>Performance of seven consumer sleep-tracking devices compared with polysomnography</title><author>Chinoy, Evan D ; Cuellar, Joseph A ; Huwa, Kirbie E ; Jameson, Jason T ; Watson, Catherine H ; Bessman, Sara C ; Hirsch, Dale A ; Cooper, Adam D ; Drummond, Sean P A ; Markwald, Rachel R</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c487t-a3e8fa632e9f6ca75686c7d1bb8ba0ade3342f9d8809fdc11dfa92224552a6b53</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Actigraphy</topic><topic>Adult</topic><topic>Basic Science of Sleep and Circadian Rhythms</topic><topic>Comparative analysis</topic><topic>Consumer behavior</topic><topic>Editor's Choice</topic><topic>Female</topic><topic>Humans</topic><topic>Marketing research</topic><topic>Polysomnography</topic><topic>Reproducibility of Results</topic><topic>Sleep</topic><topic>Sleep Stages</topic><topic>Young Adult</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Chinoy, Evan D</creatorcontrib><creatorcontrib>Cuellar, Joseph A</creatorcontrib><creatorcontrib>Huwa, Kirbie E</creatorcontrib><creatorcontrib>Jameson, Jason T</creatorcontrib><creatorcontrib>Watson, Catherine H</creatorcontrib><creatorcontrib>Bessman, Sara C</creatorcontrib><creatorcontrib>Hirsch, Dale A</creatorcontrib><creatorcontrib>Cooper, Adam D</creatorcontrib><creatorcontrib>Drummond, Sean P A</creatorcontrib><creatorcontrib>Markwald, Rachel R</creatorcontrib><collection>Open Access: Oxford University Press Open Journals</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Psychology Database (Alumni)</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Psychology Database</collection><collection>ProQuest research library</collection><collection>Research Library (Corporate)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest One Psychology</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Sleep (New York, N.Y.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Chinoy, Evan D</au><au>Cuellar, Joseph A</au><au>Huwa, Kirbie E</au><au>Jameson, Jason T</au><au>Watson, Catherine H</au><au>Bessman, Sara C</au><au>Hirsch, Dale A</au><au>Cooper, Adam D</au><au>Drummond, Sean P A</au><au>Markwald, Rachel R</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Performance of seven consumer sleep-tracking devices compared with polysomnography</atitle><jtitle>Sleep (New York, N.Y.)</jtitle><addtitle>Sleep</addtitle><date>2021-05-01</date><risdate>2021</risdate><volume>44</volume><issue>5</issue><spage>1</spage><pages>1-</pages><issn>0161-8105</issn><eissn>1550-9109</eissn><abstract>Abstract
Study Objectives
Consumer sleep-tracking devices are widely used and becoming more technologically advanced, creating strong interest from researchers and clinicians for their possible use as alternatives to standard actigraphy. We, therefore, tested the performance of many of the latest consumer sleep-tracking devices, alongside actigraphy, versus the gold-standard sleep assessment technique, polysomnography (PSG).
Methods
In total, 34 healthy young adults (22 women; 28.1 ± 3.9 years, mean ± SD) were tested on three consecutive nights (including a disrupted sleep condition) in a sleep laboratory with PSG, along with actigraphy (Philips Respironics Actiwatch 2) and a subset of consumer sleep-tracking devices. Altogether, four wearable (Fatigue Science Readiband, Fitbit Alta HR, Garmin Fenix 5S, Garmin Vivosmart 3) and three nonwearable (EarlySense Live, ResMed S+, SleepScore Max) devices were tested. Sleep/wake summary and epoch-by-epoch agreement measures were compared with PSG.
Results
Most devices (Fatigue Science Readiband, Fitbit Alta HR, EarlySense Live, ResMed S+, SleepScore Max) performed as well as or better than actigraphy on sleep/wake performance measures, while the Garmin devices performed worse. Overall, epoch-by-epoch sensitivity was high (all ≥0.93), specificity was low-to-medium (0.18–0.54), sleep stage comparisons were mixed, and devices tended to perform worse on nights with poorer/disrupted sleep.
Conclusions
Consumer sleep-tracking devices exhibited high performance in detecting sleep, and most performed equivalent to (or better than) actigraphy in detecting wake. Device sleep stage assessments were inconsistent. Findings indicate that many newer sleep-tracking devices demonstrate promising performance for tracking sleep and wake. Devices should be tested in different populations and settings to further examine their wider validity and utility.</abstract><cop>US</cop><pub>Oxford University Press</pub><pmid>33378539</pmid><doi>10.1093/sleep/zsaa291</doi><orcidid>https://orcid.org/0000-0002-3670-1189</orcidid><orcidid>https://orcid.org/0000-0001-6613-6654</orcidid><orcidid>https://orcid.org/0000-0002-0432-3937</orcidid><orcidid>https://orcid.org/0000-0002-9815-626X</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Actigraphy Adult Basic Science of Sleep and Circadian Rhythms Comparative analysis Consumer behavior Editor's Choice Female Humans Marketing research Polysomnography Reproducibility of Results Sleep Sleep Stages Young Adult |
title | Performance of seven consumer sleep-tracking devices compared with polysomnography |
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