Step-Counting Validity of Wrist-Worn Activity Monitors During Activities With Fixed Upper Extremities

2020 ◽  
Vol 3 (3) ◽  
pp. 197-203 ◽  
Author(s):  
Rebekah Lynn ◽  
Rebekah Pfitzer ◽  
Rebecca R. Rogers ◽  
Christopher G. Ballmann ◽  
Tyler D. Williams ◽  
...  
Keyword(s):  
Treadmill Walking ◽  
Upper Extremities ◽  
Free Living ◽  
Arm Swing ◽  
Activity Monitors ◽  
Video Footage ◽  
Step Counting ◽  
Physical Activity Monitors ◽  
The Right ◽  
Baby Doll

Little is known about validity of wrist-worn physical activity monitors during activities when an arm-swing is not present. The purpose of this study was to compare the step-counting validity of wrist-worn activity monitors (Fitbit Charge HR Series 2, ActiGraph GT9X Link, Apple Watch Series 4) during functional physical activities with fixed upper extremities. Tasks included treadmill walking at 3 mph and five free-living tasks (walking with a baby doll on the left hip and the right hip, holding groceries, and pushing a stroller while walking and while jogging). Device step counts were compared to hand-counted steps from GoPro video footage. Fitbit Charge had less error when compared to the left ActiGraph in both stroller walking and jogging, treadmill walking, and grocery walking tasks (p < .001 to .020). For grocery walking, walking with a baby on the right, and walking with a baby on the left, device percentage errors ranged from 0 (0.5%) to −7.6 (15.8%). For stroller jogging, stroller walking, and treadmill walking, device percentage errors ranged from −8.3 (7.3%) to −94.3 (17.9%). Tasks with the hands fixed to an item that also had contact with the floor (stroller and treadmill) had more error than when participants held an item that was not in contact with the floor (doll and groceries). Though wrist-worn, consumer-grade step-counting devices typically undercount steps in general, consumers should be aware that their devices may particularly undercount steps during activities with the hands fixed. This may be especially true with items in contact with the floor.

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.

Effects of Body Mass Index on Step Count Accuracy of Physical Activity Monitors

2012 ◽  
Vol 9 (4) ◽  
pp. 594-600 ◽  
Author(s):  
Yuri Feito ◽  
David R. Bassett ◽  
Dixie L. Thompson ◽  
Brian M. Tyo
Keyword(s):  
Physical Activity ◽  
Body Mass Index ◽  
Body Mass ◽  
Step Count ◽  
Activity Monitors ◽  
Wide Range ◽  
Step Counting ◽  
Physical Activity Monitors ◽  
High Level ◽  
Walking Speeds

Background:Activity monitors are widely used in research, and are currently being used to study physical activity (PA) trends in the US and Canada. The purpose of this study was to determine if body mass index (BMI) affects the step count accuracy of commonly used accelerometer-based activity monitors during treadmill walking.Methods:Participants were classified into BMI categories and instructed to walk on a treadmill at 3 different speeds (40, 67, and 94 m·min−1) while wearing 4 accelerometer-based activity monitors (ActiGraph GT1M, ActiCal, NL-2000, and StepWatch).Results:There was no significant main effect of BMI on pedometer accuracy. At the slowest speed, all waist-mounted devices significantly underestimated actual steps (P < .001), with the NL-2000 recording the greatest percentage (72%). At the intermediate speed, the ActiGraph was the least accurate, recording only 80% of actual steps. At the fastest speed, all of the activity monitors demonstrated a high level of accuracy.Conclusion:Our data suggest that BMI does not greatly affect the step-counting accuracy of accelerometer-based activity monitors. However, the accuracy of the ActiGraph, ActiCal, and NL-2000 decreases at slower speeds. The ankle-mounted StepWatch was the most accurate device across a wide range of walking speeds.

Accuracy of Physical Activity Monitors for Steps and Calorie Measurement During Pregnancy Walking

2019 ◽  
Vol 2 (3) ◽  
pp. 143-156 ◽  
Author(s):  
Alexander H.K. Montoye ◽  
Jordana Dahmen ◽  
Nigel Campbell ◽  
Christopher P. Connolly
Keyword(s):  
High Accuracy ◽  
Treadmill Walking ◽  
Walking Behavior ◽  
Step Counting ◽  
Physical Activity Monitors ◽  
Research Grade ◽  
All Speeds ◽  
Walking Speeds ◽  
Left Front ◽  
Calorie Expenditure

Purpose: This purpose of this study was to validate consumer-based and research-grade PA monitors for step counting and Calorie expenditure during treadmill walking. Methods: Participants (n = 40, 24 in second trimester and 16 in third trimester) completed five 2-minute walking activities (1.5–3.5 miles/hour in 0.5 mile/hour increments) while wearing five PA monitors (right hip: ActiGraph Link [AG]; left hip: Omron HJ-720 [OM]; left front pants pocket: New Lifestyles NL 2000 [NL]; non-dominant wrist: Fitbit Flex [FF]; right ankle: StepWatch [SW]). Mean absolute percent error (MAPE) was used to determine device accuracy for step counting (all monitors) and Calorie expenditure (AG with Freedson equations and FF) compared to criterion measures (hand tally for steps, indirect Calorimetry for Calories). Results: For step counting, the SW had MAPE ≤ 10% at all walking speeds, and the OM and NL had MAPE ≤ 10% for all speeds but 1.5 miles/hour. The AG had MAPE ≤ 10% for only 3.0–3.5 miles/hour speeds, and the FF had high MAPE for all speeds. For Calories, the FF and AG had MAPE > 10% for all speeds, with the FF overestimating Calories expended. Trimester did not affect PA monitor accuracy for step counting but did affect accuracy for Calorie expenditure. Conclusion: The ankle-worn SW and hip-worn OM had high accuracy for measuring step counts at all treadmill walking speeds, whereas the NL had high accuracy for speeds ≥2.0 miles/hour. Conversely, the monitors tested for Calorie expenditure have poor accuracy and should be interpreted cautiously for walking behavior.

Validity of Activity Monitor Step Detection Is Related to Movement Patterns

2016 ◽  
Vol 13 (2) ◽  
pp. 145-153 ◽  
Author(s):  
Amanda Hickey ◽  
Dinesh John ◽  
Jeffer E. Sasaki ◽  
Marianna Mavilia ◽  
Patty Freedson
Keyword(s):  
Low Frequency ◽  
Activity Monitor ◽  
Living Environment ◽  
Natural Setting ◽  
Rhythmic Movements ◽  
Free Living ◽  
Activity Monitors ◽  
Different Types ◽  
Step Counting ◽  
Free Living Conditions

Background:There is a need to examine step-counting accuracy of activity monitors during different types of movements. The purpose of this study was to compare activity monitor and manually counted steps during treadmill and simulated free-living activities and to compare the activity monitor steps to the StepWatch (SW) in a natural setting.Methods:Fifteen participants performed laboratory-based treadmill (2.4, 4.8, 7.2 and 9.7 km/h) and simulated free-living activities (eg, cleaning room) while wearing an activPAL, Omron HJ720-ITC, Yamax Digi-Walker SW-200, 2 ActiGraph GT3Xs (1 in “low-frequency extension” [AGLFE] and 1 in “normal-frequency” mode), an ActiGraph 7164, and a SW. Participants also wore monitors for 1-day in their free-living environment. Linear mixed models identified differences between activity monitor steps and the criterion in the laboratory/free-living settings.Results:Most monitors performed poorly during treadmill walking at 2.4 km/h. Cleaning a room had the largest errors of all simulated free-living activities. The accuracy was highest for forward/rhythmic movements for all monitors. In the free-living environment, the AGLFE had the largest discrepancy with the SW.Conclusion:This study highlights the need to verify step-counting accuracy of activity monitors with activities that include different movement types/directions. This is important to understand the origin of errors in step-counting during free-living conditions.

scholarly journals Criterion validity for step counting in four consumer-grade physical activity monitors among older adults with and without rollators

2020 ◽  
Vol 17 (1) ◽  
Author(s):  
Rasmus Tolstrup Larsen ◽  
Christoffer Brun Korfitsen ◽  
Carsten Bogh Juhl ◽  
Henning Boje Andersen ◽  
Henning Langberg ◽  
...  
Keyword(s):  
Physical Activity ◽  
Older Adults ◽  
Measurement Error ◽  
Criterion Validity ◽  
Measurement Properties ◽  
Activity Monitors ◽  
Prior Expectation ◽  
Step Counting ◽  
Physical Activity Monitors ◽  
Technical Issues

Abstract Background Few studies have investigated the measurement properties of consumer-grade physical activity monitors (PAMs) in older adults. Therefore, we investigated the criterion validity of consumer-grade PAMs in older adults and whether the measurement properties differed between older adults with and without rollators and whether worn on the hip or at the wrist. Methods Consumer-grade PAMs were eligible for inclusion in this study if they: 1) could be fastened at the hip as well as on the wrist, 2) were simple in function and design and thus easy to use for participants with minimal technical skills, 3) included step-counting as outcome measure and 4) were powered by a button cell battery. Participants performed self-paced walking for six minutes while two physiotherapists counted their steps with a click-counter. The average of the two counts was used as criterion. The participants wore 16 monitors, four located bilaterally on both hips and wrists. Our prior expectation was that all monitors would have at least moderate criterion validity for all participants, good criterion validity for participants walking without a rollator and poor criterion validity for participants walking with a rollator. Results Four physical activity monitors were included in this study; Misfit Shine, Nokia GO, Jawbone UP Move and Garmin Vivofit 3. A total of 103 older adults participated. Nokia GO was excluded from this study due to technical issues. Therefore, we present results on the frequency of data loss, ICC (1, 2) and percentage measurement error for Misfit Shine, Garmin Vivofit 3 and Jawbone UP Move located on four different positions. Conclusions The hip-worn PAMs did not differ significantly in terms of measurement error or criterion validity. Wrist-worn monitors cannot adequately measure number of steps in a population of older adults using rollators. The hip-worn PAMs were superior to wrist-worn PAMs among older adults with and without rollators.

scholarly journals Use of consumer monitors for estimating energy expenditure in youth

2020 ◽  
Vol 45 (2) ◽  
pp. 161-168 ◽  
Author(s):  
Samuel R. LaMunion ◽  
Andrew L. Blythe ◽  
Paul R. Hibbing ◽  
Andrew S. Kaplan ◽  
Brandon J. Clendenin ◽  
...  
Keyword(s):  
Physical Activity ◽  
Oxygen Consumption ◽  
Energy Expenditure ◽  
Left Wrist ◽  
Activity Monitors ◽  
Individual Level ◽  
Mean Absolute Percent Error ◽  
Physical Activity Monitors ◽  
The Right ◽  
Absolute Percent Error

The purpose of this study was to compare energy expenditure (EE) estimates from 5 consumer physical activity monitors (PAMs) to indirect calorimetry in a sample of youth. Eighty-nine youth (mean (SD); age, 12.3 (3.4) years; 50% female) performed 16 semi-structured activities. Activities were performed in duplicate across 2 visits. Participants wore a Cosmed K4b2(criterion for EE), an Apple Watch 2 (left wrist), Mymo Tracker (right hip), and Misfit Shine 2 devices (right hip; right shoe). Participants were randomized to wear a Samsung Gear Fit 2 or a Fitbit Charge 2 on the right wrist. Oxygen consumption was converted to EE by subtracting estimated basal EE (Schofield’s equation) from the measured gross EE. EE from each visit was summed across the 2 visit days for comparison with the total EE recorded from the PAMs. All consumer PAMs estimated gross EE, except for the Apple Watch 2 (net Active EE). Paired t tests were used to assess differences between estimated (PAM) and measured (K4b2) EE. Mean absolute percent error (MAPE) was used to assess individual-level error. The Mymo Tracker was not significantly different from measured EE and was within 15.9 kcal of measured kilocalories (p = 0.764). Mean percent errors ranged from 3.5% (Mymo Tracker) to 48.2% (Apple Watch 2). MAPE ranged from 16.8% (Misfit Shine 2 – right hip) to 49.9% (Mymo Tracker).Novelty Only the Mymo Tracker was not significantly different from measured EE but had the greatest individual error. The Misfit Shine 2 – right hip had the lowest individual error. Caution is warranted when using consumer PAMs in youth for tracking EE.

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