scholarly journals Validity of Wrist-Wearable Activity Devices for Estimating Physical Activity in Adolescents: Comparative Study

10.2196/18320 ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. e18320
Author(s):  
Yingying Hao ◽  
Xiao-Kai Ma ◽  
Zheng Zhu ◽  
Zhen-Bo Cao
Keyword(s):  
Physical Activity ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Activity Cycle ◽  
Living Conditions ◽  
Free Living ◽  
Self Monitoring ◽  
Metabolic Chamber ◽  
Absolute Percent Error ◽  
Free Living Conditions

Background The rapid advancements in science and technology of wrist-wearable activity devices offer considerable potential for clinical applications. Self-monitoring of physical activity (PA) with activity devices is helpful to improve the PA levels of adolescents. However, knowing the accuracy of activity devices in adolescents is necessary to identify current levels of PA and assess the effectiveness of intervention programs designed to increase PA. Objective The study aimed to determine the validity of the 11 commercially available wrist-wearable activity devices for monitoring total steps and total 24-hour total energy expenditure (TEE) in healthy adolescents under simulated free-living conditions. Methods Nineteen (10 male and 9 female) participants aged 14 to 18 years performed a 24-hour activity cycle in a metabolic chamber. Each participant simultaneously wore 11 commercial wrist-wearable activity devices (Mi Band 2 [XiaoMi], B2 [Huawei], Bong 2s [Meizu], Amazfit [Huamei], Flex [Fitbit], UP3 [Jawbone], Shine 2 [Misfit], GOLiFE Care-X [GoYourLife], Pulse O2 [Withings], Vivofit [Garmin], and Loop [Polar Electro]) and one research-based triaxial accelerometer (GT3X+ [ActiGraph]). Criterion measures were total EE from the metabolic chamber (mcTEE) and total steps from the GT3X+ (AGsteps). Results Pearson correlation coefficients r for 24-hour TEE ranged from .78 (Shine 2, Amazfit) to .96 (Loop) and for steps ranged from 0.20 (GOLiFE) to 0.57 (Vivofit). Mean absolute percent error (MAPE) for TEE ranged from 5.7% (Mi Band 2) to 26.4% (Amazfit) and for steps ranged from 14.2% (Bong 2s) to 27.6% (Loop). TEE estimates from the Mi Band 2, UP3, Vivofit, and Bong 2s were equivalent to mcTEE. Total steps from the Bong 2s were equivalent to AGsteps. Conclusions Overall, the Bong 2s had the best accuracy for estimating TEE and total steps under simulated free-living conditions. Further research is needed to examine the validity of these devices in different types of physical activities under real-world conditions.

scholarly journals Validity of Wrist-Wearable Activity Devices for Estimating Physical Activity in Adolescents: Comparative Study (Preprint)

2020 ◽  
Author(s):  
Yingying Hao ◽  
Xiao-Kai Ma ◽  
Zheng Zhu ◽  
Zhen-Bo Cao
Keyword(s):  
Physical Activity ◽  
Pearson Correlation ◽  
Correlation Coefficients ◽  
Activity Cycle ◽  
Living Conditions ◽  
Free Living ◽  
Self Monitoring ◽  
Metabolic Chamber ◽  
Absolute Percent Error ◽  
Free Living Conditions

BACKGROUND The rapid advancements in science and technology of wrist-wearable activity devices offer considerable potential for clinical applications. Self-monitoring of physical activity (PA) with activity devices is helpful to improve the PA levels of adolescents. However, knowing the accuracy of activity devices in adolescents is necessary to identify current levels of PA and assess the effectiveness of intervention programs designed to increase PA. OBJECTIVE The study aimed to determine the validity of the 11 commercially available wrist-wearable activity devices for monitoring total steps and total 24-hour total energy expenditure (TEE) in healthy adolescents under simulated free-living conditions. METHODS Nineteen (10 male and 9 female) participants aged 14 to 18 years performed a 24-hour activity cycle in a metabolic chamber. Each participant simultaneously wore 11 commercial wrist-wearable activity devices (Mi Band 2 [XiaoMi], B2 [Huawei], Bong 2s [Meizu], Amazfit [Huamei], Flex [Fitbit], UP3 [Jawbone], Shine 2 [Misfit], GOLiFE Care-X [GoYourLife], Pulse O2 [Withings], Vivofit [Garmin], and Loop [Polar Electro]) and one research-based triaxial accelerometer (GT3X+ [ActiGraph]). Criterion measures were total EE from the metabolic chamber (mcTEE) and total steps from the GT3X+ (AGsteps). RESULTS Pearson correlation coefficients r for 24-hour TEE ranged from .78 (Shine 2, Amazfit) to .96 (Loop) and for steps ranged from 0.20 (GOLiFE) to 0.57 (Vivofit). Mean absolute percent error (MAPE) for TEE ranged from 5.7% (Mi Band 2) to 26.4% (Amazfit) and for steps ranged from 14.2% (Bong 2s) to 27.6% (Loop). TEE estimates from the Mi Band 2, UP3, Vivofit, and Bong 2s were equivalent to mcTEE. Total steps from the Bong 2s were equivalent to AGsteps. CONCLUSIONS Overall, the Bong 2s had the best accuracy for estimating TEE and total steps under simulated free-living conditions. Further research is needed to examine the validity of these devices in different types of physical activities under real-world conditions.

scholarly journals Accuracy of 12 Wearable Devices for Estimating Physical Activity Energy Expenditure Using a Metabolic Chamber and the Doubly Labeled Water Method: Validation Study

10.2196/13938 ◽  
2019 ◽  
Vol 7 (8) ◽  
pp. e13938 ◽  
Author(s):  
Haruka Murakami ◽  
Ryoko Kawakami ◽  
Satoshi Nakae ◽  
Yosuke Yamada ◽  
Yoshio Nakata ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Correlation Coefficients ◽  
Wearable Devices ◽  
Doubly Labeled Water ◽  
Free Living ◽  
Daily Lives ◽  
Self Monitoring ◽  
Metabolic Chamber ◽  
Positive Correlations

Background Self-monitoring using certain types of pedometers and accelerometers has been reported to be effective for promoting and maintaining physical activity (PA). However, the validity of estimating the level of PA or PA energy expenditure (PAEE) for general consumers using wearable devices has not been sufficiently established. Objective We examined the validity of 12 wearable devices for determining PAEE during 1 standardized day in a metabolic chamber and 15 free-living days using the doubly labeled water (DLW) method. Methods A total of 19 healthy adults aged 21 to 50 years (9 men and 10 women) participated in this study. They followed a standardized PA protocol in a metabolic chamber for an entire day while simultaneously wearing 12 wearable devices: 5 devices on the waist, 5 on the wrist, and 2 placed in the pocket. In addition, they spent their daily lives wearing 12 wearable devices under free-living conditions while being subjected to the DLW method for 15 days. The PAEE criterion was calculated by subtracting the basal metabolic rate measured by the metabolic chamber and 0.1×total energy expenditure (TEE) from TEE. The TEE was obtained by the metabolic chamber and DLW methods. The PAEE values of wearable devices were also extracted or calculated from each mobile phone app or website. The Dunnett test and Pearson and Spearman correlation coefficients were used to examine the variables estimated by wearable devices. Results On the standardized day, the PAEE estimated using the metabolic chamber (PAEEcha) was 528.8±149.4 kcal/day. The PAEEs of all devices except the TANITA AM-160 (513.8±135.0 kcal/day; P>.05), SUZUKEN Lifecorder EX (519.3±89.3 kcal/day; P>.05), and Panasonic Actimarker (545.9±141.7 kcal/day; P>.05) were significantly different from the PAEEcha. None of the devices was correlated with PAEEcha according to both Pearson (r=−.13 to .37) and Spearman (ρ=−.25 to .46) correlation tests. During the 15 free-living days, the PAEE estimated by DLW (PAEEdlw) was 728.0±162.7 kcal/day. PAEE values of all devices except the Omron Active style Pro (716.2±159.0 kcal/day; P>.05) and Omron CaloriScan (707.5±172.7 kcal/day; P>.05) were significantly underestimated. Only 2 devices, the Omron Active style Pro (r=.46; P=.045) and Panasonic Actimarker (r=.48; P=.04), had significant positive correlations with PAEEdlw according to Pearson tests. In addition, 3 devices, the TANITA AM-160 (ρ=.50; P=.03), Omron CaloriScan (ρ=.48; P=.04), and Omron Active style Pro (ρ=.48; P=.04), could be ranked in PAEEdlw. Conclusions Most wearable devices do not provide comparable PAEE estimates when using gold standard methods during 1 standardized day or 15 free-living days. Continuous development and evaluations of these wearable devices are needed for better estimations of PAEE.

scholarly journals Accuracy of 12 Wearable Devices for Estimating Physical Activity Energy Expenditure Using a Metabolic Chamber and the Doubly Labeled Water Method: Validation Study (Preprint)

2019 ◽  
Author(s):  
Haruka Murakami ◽  
Ryoko Kawakami ◽  
Satoshi Nakae ◽  
Yosuke Yamada ◽  
Yoshio Nakata ◽  
...  
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Correlation Coefficients ◽  
Wearable Devices ◽  
Doubly Labeled Water ◽  
Free Living ◽  
Daily Lives ◽  
Self Monitoring ◽  
Metabolic Chamber ◽  
Positive Correlations

BACKGROUND Self-monitoring using certain types of pedometers and accelerometers has been reported to be effective for promoting and maintaining physical activity (PA). However, the validity of estimating the level of PA or PA energy expenditure (PAEE) for general consumers using wearable devices has not been sufficiently established. OBJECTIVE We examined the validity of 12 wearable devices for determining PAEE during 1 standardized day in a metabolic chamber and 15 free-living days using the doubly labeled water (DLW) method. METHODS A total of 19 healthy adults aged 21 to 50 years (9 men and 10 women) participated in this study. They followed a standardized PA protocol in a metabolic chamber for an entire day while simultaneously wearing 12 wearable devices: 5 devices on the waist, 5 on the wrist, and 2 placed in the pocket. In addition, they spent their daily lives wearing 12 wearable devices under free-living conditions while being subjected to the DLW method for 15 days. The PAEE criterion was calculated by subtracting the basal metabolic rate measured by the metabolic chamber and 0.1×total energy expenditure (TEE) from TEE. The TEE was obtained by the metabolic chamber and DLW methods. The PAEE values of wearable devices were also extracted or calculated from each mobile phone app or website. The Dunnett test and Pearson and Spearman correlation coefficients were used to examine the variables estimated by wearable devices. RESULTS On the standardized day, the PAEE estimated using the metabolic chamber (PAEEcha) was 528.8±149.4 kcal/day. The PAEEs of all devices except the TANITA AM-160 (513.8±135.0 kcal/day; P>.05), SUZUKEN Lifecorder EX (519.3±89.3 kcal/day; P>.05), and Panasonic Actimarker (545.9±141.7 kcal/day; P>.05) were significantly different from the PAEEcha. None of the devices was correlated with PAEEcha according to both Pearson (r=−.13 to .37) and Spearman (ρ=−.25 to .46) correlation tests. During the 15 free-living days, the PAEE estimated by DLW (PAEEdlw) was 728.0±162.7 kcal/day. PAEE values of all devices except the Omron Active style Pro (716.2±159.0 kcal/day; P>.05) and Omron CaloriScan (707.5±172.7 kcal/day; P>.05) were significantly underestimated. Only 2 devices, the Omron Active style Pro (r=.46; P=.045) and Panasonic Actimarker (r=.48; P=.04), had significant positive correlations with PAEEdlw according to Pearson tests. In addition, 3 devices, the TANITA AM-160 (ρ=.50; P=.03), Omron CaloriScan (ρ=.48; P=.04), and Omron Active style Pro (ρ=.48; P=.04), could be ranked in PAEEdlw. CONCLUSIONS Most wearable devices do not provide comparable PAEE estimates when using gold standard methods during 1 standardized day or 15 free-living days. Continuous development and evaluations of these wearable devices are needed for better estimations of PAEE.

Validity, Reliability and Sensitivity to Change of Three Consumer-grade Activity Trackers in Controlled and Free-living Conditions among Older Adults (Preprint)

2021 ◽  
Author(s):  
Kaja Kastelic ◽  
Marina Dobnik ◽  
Stefan Loefler ◽  
Christian Hofer ◽  
Nejc Šarabon
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Intraclass Correlation ◽  
Sleep Time ◽  
Living Conditions ◽  
Percentage Error ◽  
Sensitivity To Change ◽  
Free Living ◽  
Activity Trackers ◽  
Free Living Conditions

BACKGROUND Wrist worn consumer-grade activity trackers are popular devices, developed mainly for personal use, but with the potential to be used also for clinical and research purposes. OBJECTIVE The objective of this study was to explore the validity, reliability and sensitivity to change of movement behaviours metrics from three popular activity trackers (POLAR Vantage M, Garmin Vivosport and Garmin Vivoactive 4s) in controlled and free-living conditions when worn by older adults. METHODS Participants (n = 28; 74 ± 5 years) underwent a videotaped laboratory protocol while wearing all three activity trackers. On a separate occasion, participants wore one (randomly assigned) activity tracker and a research grade physical activity monitor ActiGraph wGT3X-BT simultaneously for six consecutive days for comparisons. RESULTS Both Garmin activity trackers showed excellent performance for step counts, with mean absolute percentage error (MAPE) below 20 % and intraclass correlation coefficient (ICC2,1) above 0.90 (P < .05), while Polar Vantage M substantially over counted steps (MAPE = 84 % and ICC2,1 = 0.37 for free-living conditions). MAPE for sleep time was within 10 % for all the trackers tested, while far beyond 20 % for all the physical activity and calories burned outputs. Both Garmin trackers showed fair agreement (ICC2,1 = 0.58–0.55) for measuring calories burned when compared with ActiGraph. CONCLUSIONS Garmin Vivoactive 4s showed overall best performance, especially for measuring steps and sleep time in healthy older adults. Minimal detectible change was consistently lower for an average day measures than for a single day measure, but still relatively high. The results provided in this study could be used to guide choice on activity trackers aiming for different purposes – individual use/care, longitudinal monitoring or in clinical trial setting.

Physical Activity Monitor Accuracy for Overground Walking and Free-Living Conditions Among Pregnant Women

2020 ◽  
Vol 3 (2) ◽  
pp. 100-109
Author(s):  
Christopher P. Connolly ◽  
Jordana Dahmen ◽  
Robert D. Catena ◽  
Nigel Campbell ◽  
Alexander H.K. Montoye
Keyword(s):  
Physical Activity ◽  
Pregnant Women ◽  
Living Conditions ◽  
Overground Walking ◽  
Third Trimester ◽  
Free Living ◽  
Activity Monitors ◽  
Step Counting ◽  
Physical Activity Monitors ◽  
Free Living Conditions

Purpose: We aimed to determine the step-count validity of commonly used physical activity monitors for pregnancy overground walking and during free-living conditions. Methods: Participants (n = 39, 12–38 weeks gestational age) completed six 100-step overground walking trials (three self-selected “normal pace”, three “brisk pace”) while wearing five physical activity monitors: Omron HJ-720 (OM), New Lifestyles 2000 (NL), Fitbit Flex (FF), ActiGraph Link (AG), and Modus StepWatch (SW). For each walking trial, monitor-recorded steps and criterion-measured steps were assessed. Participants also wore all activity monitors for an extended free-living period (72 hours), with the SW used as the criterion device. Mean absolute percent error (MAPE) was calculated for overground walking and free-living protocols and compared across monitors. Results: For overground walking, the OM, NL, and SW performed well (<5% MAPE) for normal and brisk pace walking trials, and also when trials were analyzed by actual speeds. The AG and FF had significantly greater MAPE for overground walking trials (11.9–14.7%). Trimester did affect device accuracy to some degree for the AG, FF, and SW, with error being lower in the third trimester compared to the second. For the free-living period, the OM, NL, AG, and FF significantly underestimated (>32% MAPE) actual steps taken per day as measured by the criterion SW (M [SD] = 9,350 [3,910]). MAPE for the OM was particularly high (45.3%). Conclusion: The OM, NL, and SW monitors are valid measures for overground step-counting during pregnancy walking. However, the OM and NL significantly underestimate steps by second and third trimester pregnant women in free-living conditions.

Assessment of Physical Activity Under Free-Living Conditions in Children

2004 ◽  
Vol 36 (Supplement) ◽  
pp. S329
Author(s):  
Jennifer L. Caputo ◽  
Richard S. Farley ◽  
Wayland Tseh
Keyword(s):  
Physical Activity ◽  
Living Conditions ◽  
Free Living ◽  
Free Living Conditions

scholarly journals Evaluations of Actiheart, IDEEA® and RT3 monitors for estimating activity energy expenditure in free-living women

2013 ◽  
Vol 2 ◽  
Author(s):  
Marie Löf ◽  
Hanna Henriksson ◽  
Elisabet Forsum
Keyword(s):  
Physical Activity ◽  
Energy Expenditure ◽  
Living Conditions ◽  
Reproductive Age ◽  
Women Of Reproductive Age ◽  
Free Living ◽  
Doubly Labelled Water ◽  
Further Development ◽  
Activity Energy ◽  
Free Living Conditions

AbstractActivity energy expenditure (AEE) during free-living conditions can be assessed using devices based on different principles. To make proper comparisons of different devices' capacities to assess AEE, they should be evaluated in the same population. Thus, in the present study we evaluated, in the same group of subjects, the ability of three devices to assess AEE in groups and individuals during free-living conditions. In twenty women, AEE was assessed using RT3 (three-axial accelerometry) (AEERT3), Actiheart (a combination of heart rate and accelerometry) (AEEActi) and IDEEA (a multi-accelerometer system) (AEEIDEEA). Reference AEE (AEEref) was assessed using the doubly labelled water method and indirect calorimetry. Average AEEActi was 5760 kJ per 24 h and not significantly different from AEEref (5020 kJ per 24 h). On average, AEERT3 and AEEIDEEA were 2010 and 1750 kJ per 24 h lower than AEEref, respectively (P < 0·001). The limits of agreement (± 2 sd) were 2940 (Actiheart), 1820 (RT3) and 2650 (IDEEA) kJ per 24 h. The variance for AEERT3 was lower than for AEEActi (P = 0·006). The RT3 classified 60 % of the women in the correct activity category while the corresponding value for IDEEA and Actiheart was 30 %. In conclusion, the Actiheart may be useful for groups and the RT3 for individuals while the IDEEA requires further development. The results are likely to be relevant for a large proportion of Western women of reproductive age and demonstrate that the procedure selected to assess physical activity can greatly influence the possibilities to uncover important aspects regarding interactions between physical activity, diet and health.

Evaluation of methods to assess physical activity in free-living conditions

2001 ◽  
pp. 1233-1240 ◽  
Author(s):  
NICOLE Y. J. M. LEENDERS ◽  
W. MICHAEL SHERMAN ◽  
H. N. NAGARAJA ◽  
C. LAWRENCE KIEN
Keyword(s):  
Physical Activity ◽  
Living Conditions ◽  
Free Living ◽  
Evaluation Of Methods ◽  
Free Living Conditions
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