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The accuracy of smart devices for measuring physical activity in daily life : validation study

Laurent Degroote (UGent) , Ilse De Bourdeaudhuij (UGent) , Maïté Verloigne (UGent) , Louise Poppe (UGent) and Geert Crombez (UGent)
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Abstract
Background: Wearables for monitoring physical activity (PA) are increasingly popular. These devices are not only used by consumers to monitor their own levels of PA but also by researchers to track the behavior of large samples. Consequently, it is important to explore how accurately PA can be tracked via these devices. Objectives: The aim of this study was, therefore, to investigate convergent validity of 3 Android Wear smartwatches-Polar M600 (Polar Electro Oy, Kempele, Finland), Huawei Watch (Huawei Technologies Co, Ltd, Shenzhen, Guangdong, China), Asus Zenwatch3 (AsusTek Computer Inc, Taipei, Taiwan)-and Fitbit Charge with an ActiGraph accelerometer for measuring steps and moderate to vigorous physical activity (MVPA) on both a day level and 15-min level. Methods: A free-living protocol was used in which 36 adults engaged in usual daily activities over 2 days while wearing 2 different wearables on the nondominant wrist and an ActiGraph GT3X+ accelerometer on the hip. Validity was evaluated on both levels by comparing each wearable with the ActiGraph GT3X+ accelerometer using correlations and Bland-Altman plots in IBM SPSS 24.0. Results: On a day level, all devices showed strong correlations (Spearman r=.757-.892) and good agreement (interclass correlation coefficient, ICC=.695-.885) for measuring steps, whereas moderate correlations (Spearman r=.557-.577) and low agreement (ICC=.377-.660) for measuring MVPA. Bland-Altman revealed a systematic overestimation of the wearables for measuring steps but a variation between over-and undercounting of MVPA. On a 15-min level, all devices showed strong correlations (Spearman r=.752-.917) and good agreement (ICC=.792-.887) for measuring steps, whereas weak correlations (Spearman r=.116-.208) and low agreement (ICC=.461-.577) for measuring MVPA. Bland-Altman revealed a systematic overestimation of the wearables for steps but under- or overestimation for MVPA depending on the device. Conclusions: In sum, all 4 consumer-level devices can be considered accurate step counters in free-living conditions. This study, however, provides evidence of systematic bias for all devices in measurement of MVPA. The results on a 15-min level also indicate that these devices are not sufficiently accurate to provide correct real-time feedback.
Keywords
physical activity, fitness trackes, accelerometry, ACTIVITY QUESTIONNAIRE, ACTIVITY MONITORS, SELF-EFFICACY, VALIDITY, HEALTH, FITNESS, ADULTS, RELIABILITY, CALIBRATION, PEDOMETER

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Chicago
Degroote, Laurent, Ilse De Bourdeaudhuij, Maïté Verloigne, Louise Poppe, and Geert Crombez. 2018. “The Accuracy of Smart Devices for Measuring Physical Activity in Daily Life : Validation Study.” Jmir Mhealth and Uhealth 6 (12).
APA
Degroote, L., De Bourdeaudhuij, I., Verloigne, M., Poppe, L., & Crombez, G. (2018). The accuracy of smart devices for measuring physical activity in daily life : validation study. JMIR MHEALTH AND UHEALTH, 6(12).
Vancouver
1.
Degroote L, De Bourdeaudhuij I, Verloigne M, Poppe L, Crombez G. The accuracy of smart devices for measuring physical activity in daily life : validation study. JMIR MHEALTH AND UHEALTH. 2018;6(12).
MLA
Degroote, Laurent et al. “The Accuracy of Smart Devices for Measuring Physical Activity in Daily Life : Validation Study.” JMIR MHEALTH AND UHEALTH 6.12 (2018): n. pag. Print.
@article{8585352,
  abstract     = {Background: Wearables for monitoring physical activity (PA) are increasingly popular. These devices are not only used by consumers to monitor their own levels of PA but also by researchers to track the behavior of large samples. Consequently, it is important to explore how accurately PA can be tracked via these devices. 
Objectives: The aim of this study was, therefore, to investigate convergent validity of 3 Android Wear smartwatches-Polar M600 (Polar Electro Oy, Kempele, Finland), Huawei Watch (Huawei Technologies Co, Ltd, Shenzhen, Guangdong, China), Asus Zenwatch3 (AsusTek Computer Inc, Taipei, Taiwan)-and Fitbit Charge with an ActiGraph accelerometer for measuring steps and moderate to vigorous physical activity (MVPA) on both a day level and 15-min level. 
Methods: A free-living protocol was used in which 36 adults engaged in usual daily activities over 2 days while wearing 2 different wearables on the nondominant wrist and an ActiGraph GT3X+ accelerometer on the hip. Validity was evaluated on both levels by comparing each wearable with the ActiGraph GT3X+ accelerometer using correlations and Bland-Altman plots in IBM SPSS 24.0. 
Results: On a day level, all devices showed strong correlations (Spearman r=.757-.892) and good agreement (interclass correlation coefficient, ICC=.695-.885) for measuring steps, whereas moderate correlations (Spearman r=.557-.577) and low agreement (ICC=.377-.660) for measuring MVPA. Bland-Altman revealed a systematic overestimation of the wearables for measuring steps but a variation between over-and undercounting of MVPA. On a 15-min level, all devices showed strong correlations (Spearman r=.752-.917) and good agreement (ICC=.792-.887) for measuring steps, whereas weak correlations (Spearman r=.116-.208) and low agreement (ICC=.461-.577) for measuring MVPA. Bland-Altman revealed a systematic overestimation of the wearables for steps but under- or overestimation for MVPA depending on the device. 
Conclusions: In sum, all 4 consumer-level devices can be considered accurate step counters in free-living conditions. This study, however, provides evidence of systematic bias for all devices in measurement of MVPA. The results on a 15-min level also indicate that these devices are not sufficiently accurate to provide correct real-time feedback.},
  articleno    = {e10972},
  author       = {Degroote, Laurent and De Bourdeaudhuij, Ilse and Verloigne, Maïté and Poppe, Louise and Crombez, Geert},
  issn         = {2291-5222},
  journal      = {JMIR MHEALTH AND UHEALTH},
  keywords     = {physical activity,fitness trackes,accelerometry,ACTIVITY QUESTIONNAIRE,ACTIVITY MONITORS,SELF-EFFICACY,VALIDITY,HEALTH,FITNESS,ADULTS,RELIABILITY,CALIBRATION,PEDOMETER},
  language     = {eng},
  number       = {12},
  pages        = {16},
  title        = {The accuracy of smart devices for measuring physical activity in daily life : validation study},
  url          = {http://dx.doi.org/10.2196/10972},
  volume       = {6},
  year         = {2018},
}

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