Low-Cost Consumer-Based Trackers to Measure Physical Activity and Sleep Duration Among Adults in Free-Living Conditions: Validation Study.


Journal

JMIR mHealth and uHealth
ISSN: 2291-5222
Titre abrégé: JMIR Mhealth Uhealth
Pays: Canada
ID NLM: 101624439

Informations de publication

Date de publication:
19 05 2020
Historique:
received: 14 10 2019
accepted: 26 02 2020
revised: 24 02 2020
pubmed: 14 4 2020
medline: 28 4 2021
entrez: 14 4 2020
Statut: epublish

Résumé

Wearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are used not only by consumers to monitor their behavior but also by researchers to track the behavior of large samples and by health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high costs and accuracy concerns may be barriers to widespread adoption. This study aimed to investigate the concurrent validity of 6 low-cost activity trackers for measuring steps, moderate-to-vigorous physical activity (MVPA), and TST: Geonaut On Coach, iWown i5 Plus, MyKronoz ZeFit4, Nokia GO, VeryFit 2.0, and Xiaomi MiBand 2. A free-living protocol was used in which 20 adults engaged in their usual daily activities and sleep. For 3 days and 3 nights, they simultaneously wore a low-cost tracker and a high-cost tracker (Fitbit Charge HR) on the nondominant wrist. Participants wore an ActiGraph GT3X+ accelerometer on the hip at daytime and a BodyMedia SenseWear device on the nondominant upper arm at nighttime. Validity was assessed by comparing each tracker with the ActiGraph GT3X+ and BodyMedia SenseWear using mean absolute percentage error scores, correlations, and Bland-Altman plots in IBM SPSS 24.0. Large variations were shown between trackers. Low-cost trackers showed moderate-to-strong correlations (Spearman r=0.53-0.91) and low-to-good agreement (intraclass correlation coefficient [ICC]=0.51-0.90) for measuring steps. Weak-to-moderate correlations (Spearman r=0.24-0.56) and low agreement (ICC=0.18-0.56) were shown for measuring MVPA. For measuring TST, the low-cost trackers showed weak-to-strong correlations (Spearman r=0.04-0.73) and low agreement (ICC=0.05-0.52). The Bland-Altman plot revealed a variation between overcounting and undercounting for measuring steps, MVPA, and TST, depending on the used low-cost tracker. None of the trackers, including Fitbit (a high-cost tracker), showed high validity to measure MVPA. This study was the first to examine the concurrent validity of low-cost trackers. Validity was strongest for the measurement of steps; there was evidence of validity for measurement of sleep in some trackers, and validity for measurement of MVPA time was weak throughout all devices. Validity ranged between devices, with Xiaomi having the highest validity for measurement of steps and VeryFit performing relatively strong across both sleep and steps domains. Low-cost trackers hold promise for monitoring and measurement of movement and sleep behaviors, both for consumers and researchers.

Sections du résumé

BACKGROUND
Wearable trackers for monitoring physical activity (PA) and total sleep time (TST) are increasingly popular. These devices are used not only by consumers to monitor their behavior but also by researchers to track the behavior of large samples and by health professionals to implement interventions aimed at health promotion and to remotely monitor patients. However, high costs and accuracy concerns may be barriers to widespread adoption.
OBJECTIVE
This study aimed to investigate the concurrent validity of 6 low-cost activity trackers for measuring steps, moderate-to-vigorous physical activity (MVPA), and TST: Geonaut On Coach, iWown i5 Plus, MyKronoz ZeFit4, Nokia GO, VeryFit 2.0, and Xiaomi MiBand 2.
METHODS
A free-living protocol was used in which 20 adults engaged in their usual daily activities and sleep. For 3 days and 3 nights, they simultaneously wore a low-cost tracker and a high-cost tracker (Fitbit Charge HR) on the nondominant wrist. Participants wore an ActiGraph GT3X+ accelerometer on the hip at daytime and a BodyMedia SenseWear device on the nondominant upper arm at nighttime. Validity was assessed by comparing each tracker with the ActiGraph GT3X+ and BodyMedia SenseWear using mean absolute percentage error scores, correlations, and Bland-Altman plots in IBM SPSS 24.0.
RESULTS
Large variations were shown between trackers. Low-cost trackers showed moderate-to-strong correlations (Spearman r=0.53-0.91) and low-to-good agreement (intraclass correlation coefficient [ICC]=0.51-0.90) for measuring steps. Weak-to-moderate correlations (Spearman r=0.24-0.56) and low agreement (ICC=0.18-0.56) were shown for measuring MVPA. For measuring TST, the low-cost trackers showed weak-to-strong correlations (Spearman r=0.04-0.73) and low agreement (ICC=0.05-0.52). The Bland-Altman plot revealed a variation between overcounting and undercounting for measuring steps, MVPA, and TST, depending on the used low-cost tracker. None of the trackers, including Fitbit (a high-cost tracker), showed high validity to measure MVPA.
CONCLUSIONS
This study was the first to examine the concurrent validity of low-cost trackers. Validity was strongest for the measurement of steps; there was evidence of validity for measurement of sleep in some trackers, and validity for measurement of MVPA time was weak throughout all devices. Validity ranged between devices, with Xiaomi having the highest validity for measurement of steps and VeryFit performing relatively strong across both sleep and steps domains. Low-cost trackers hold promise for monitoring and measurement of movement and sleep behaviors, both for consumers and researchers.

Identifiants

pubmed: 32282332
pii: v8i5e16674
doi: 10.2196/16674
pmc: PMC7268004
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e16674

Informations de copyright

©Laurent Degroote, Gilles Hamerlinck, Karolien Poels, Carol Maher, Geert Crombez, Ilse De Bourdeaudhuij, Ann Vandendriessche, Rachel G Curtis, Ann DeSmet. Originally published in JMIR mHealth and uHealth (http://mhealth.jmir.org), 19.05.2020.

Références

JMIR Mhealth Uhealth. 2018 Apr 12;6(4):e94
pubmed: 29650506
J Sleep Res. 2011 Mar;20(1 Pt 2):183-200
pubmed: 20374444
BMJ Open. 2016 Jul 07;6(7):e011243
pubmed: 27388359
Health Psychol Open. 2016 Nov 29;3(2):2055102916679012
pubmed: 28815052
PeerJ. 2018 Jul 25;6:e5350
pubmed: 30065893
BMC Public Health. 2017 Nov 15;17(1):880
pubmed: 29141607
Int J Behav Nutr Phys Act. 2015 Mar 01;12:31
pubmed: 25889577
Am J Prev Med. 2016 Nov;51(5):843-851
pubmed: 27745684
JMIR Mhealth Uhealth. 2019 Feb 13;7(2):e11972
pubmed: 30758297
J Med Internet Res. 2016 Oct 04;18(10):e264
pubmed: 27702738
JMIR Mhealth Uhealth. 2019 Apr 05;7(4):e9832
pubmed: 30950807
Nutr Metab Cardiovasc Dis. 2007 Jun;17(5):338-43
pubmed: 17562571
J Strength Cond Res. 2017 Apr;31(4):1097-1106
pubmed: 27465631
J Appl Physiol (1985). 2005 Sep;99(3):1193-204
pubmed: 16103522
Diabetes Care. 2010 Feb;33(2):414-20
pubmed: 19910503
BMC Res Notes. 2016 Sep 21;9(1):448
pubmed: 27655477
Med Sci Sports Exerc. 2013 May;45(5):964-75
pubmed: 23247702
PLoS Med. 2016 Feb 02;13(2):e1001953
pubmed: 26836780
Prog Cardiovasc Dis. 2016 May-Jun;58(6):613-9
pubmed: 26943981
Sensors (Basel). 2016 May 05;16(5):
pubmed: 27164110
J Med Internet Res. 2016 Sep 07;18(9):e239
pubmed: 27604226
Public Health Nutr. 2013 Mar;16(3):440-52
pubmed: 22874087
Med Sci Sports Exerc. 2008 Jan;40(1):181-8
pubmed: 18091006
Prev Med. 2014 Oct;67:248-54
pubmed: 25138382
J Occup Environ Med. 2018 Oct;60(10):954-959
pubmed: 30001255
PLoS One. 2016 Mar 03;11(3):e0150534
pubmed: 26938240
JMIR Mhealth Uhealth. 2019 Apr 12;7(4):e11819
pubmed: 30977740
BMC Public Health. 2012 Jul 28;12:565
pubmed: 22839359
JMIR Mhealth Uhealth. 2017 Oct 30;5(10):e164
pubmed: 29084709
Int J Sports Med. 2013 Nov;34(11):975-82
pubmed: 23700330
Med Sci Sports Exerc. 2003 Aug;35(8):1381-95
pubmed: 12900694
J Med Internet Res. 2018 Dec 18;20(12):e11321
pubmed: 30563808
Med Sci Sports Exerc. 2007 Apr;39(4):716-27
pubmed: 17414811
Sleep Med Rev. 2012 Jun;16(3):231-41
pubmed: 21784678
PLoS One. 2016 Sep 02;11(9):e0161224
pubmed: 27589592
BMJ Open. 2016 Mar 15;6(3):e010038
pubmed: 27008686
Obesity (Silver Spring). 2013 Dec;21(12):E730-7
pubmed: 23512825
Med Sci Sports Exerc. 2003 May;35(5):867-71
pubmed: 12750599
J Med Internet Res. 2012 Jan 27;14(1):e19
pubmed: 22357448
Int J Behav Nutr Phys Act. 2012 Sep 19;9:116
pubmed: 22992350
Int J Behav Nutr Phys Act. 2015 Dec 18;12:159
pubmed: 26684758
Sleep Sci. 2015 Jan-Mar;8(1):9-15
pubmed: 26483937
Health Psychol. 2008 May;27(3):379-87
pubmed: 18624603
JMIR Mhealth Uhealth. 2019 Dec 20;7(12):e15707
pubmed: 31859680
Med Sci Sports Exerc. 1998 May;30(5):777-81
pubmed: 9588623
PLoS One. 2015 Oct 13;10(10):e0139984
pubmed: 26461112
Epidemiology. 2008 Nov;19(6):838-45
pubmed: 18854708
Int J Behav Nutr Phys Act. 2015 Mar 27;12:42
pubmed: 25890168
Front Physiol. 2017 Sep 22;8:725
pubmed: 29018355
Br J Sports Med. 2006 Aug;40(8):714-6
pubmed: 16790485
Cancer. 2019 Aug 15;125(16):2846-2855
pubmed: 31012970
Arch Phys Med Rehabil. 2013 Jun;94(6):1161-70
pubmed: 23201318
Health Psychol Rev. 2016 Sep;10(3):297-312
pubmed: 26262912
BMC Res Notes. 2014 Dec 23;7:952
pubmed: 25539733
PLoS One. 2013 Jun 24;8(6):e67206
pubmed: 23826236
Eur Heart J. 2011 Jun;32(12):1484-92
pubmed: 21300732
J Med Internet Res. 2018 Mar 22;20(3):e110
pubmed: 29567635
Health Psychol. 2009 Nov;28(6):690-701
pubmed: 19916637
Physiol Behav. 2016 May 1;158:143-9
pubmed: 26969518
J Phys Act Health. 2015 Feb;12(2):149-54
pubmed: 24770438
J Med Internet Res. 2017 Jan 24;19(1):e27
pubmed: 28119275
Med Sci Sports Exerc. 2004 May;36(5):905-10
pubmed: 15126728
JMIR Mhealth Uhealth. 2016 Sep 19;4(3):e110
pubmed: 27644334
Biometrics. 1977 Mar;33(1):159-74
pubmed: 843571
Med Sci Sports Exerc. 2016 Aug;48(8):1619-28
pubmed: 27015387
Int J Exerc Sci. 2017 Jan 1;10(1):146-153
pubmed: 28479955
BMC Public Health. 2012 Jan 25;12:80
pubmed: 22276600
J Appl Physiol (1985). 2004 Jan;96(1):343-51
pubmed: 12972441
BMC Sports Sci Med Rehabil. 2015 Oct 12;7:24
pubmed: 26464801
JMIR Mhealth Uhealth. 2016 Jan 27;4(1):e7
pubmed: 26818775
Med Sci Sports Exerc. 2016 Mar;48(3):457-65
pubmed: 26484953

Auteurs

Laurent Degroote (L)

Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.
Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium.
Research Foundation Flanders, Brussels, Belgium.

Gilles Hamerlinck (G)

Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.

Karolien Poels (K)

Department of Communication Studies, University of Antwerp, Antwerp, Belgium.

Carol Maher (C)

School of Health Sciences, University of South Australia, Adelaide, Australia.

Geert Crombez (G)

Department of Experimental Clinical and Health Psychology, Ghent University, Ghent, Belgium.

Ilse De Bourdeaudhuij (I)

Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.

Ann Vandendriessche (A)

Department of Public Health and Primary Care, Ghent University, Ghent, Belgium.

Rachel G Curtis (RG)

School of Health Sciences, University of South Australia, Adelaide, Australia.

Ann DeSmet (A)

Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium.
Research Foundation Flanders, Brussels, Belgium.
Department of Communication Studies, University of Antwerp, Antwerp, Belgium.
Department of Clinical and Health Psychology, Université Libre de Bruxelles, Brussels, Belgium.

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