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|Title||A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study.|
|Publication Type||Journal Article|
|Year of Publication||2022|
|Authors||Mora-Gonzalez, J, Gould, ZR, Moore, CC, Aguiar, EJ, Ducharme, SW, Schuna, Jr, JM, Barreira, TV, Staudenmayer, J, McAvoy, CR, Boikova, M, Miller, TA, Tudor-Locke, C|
|Journal||Int J Behav Nutr Phys Act|
|Keywords||Adult, Child, Cross-Sectional Studies, Exercise Test, Female, Fitness Trackers, Humans, Male, Reproducibility of Results, Walking, Wearable Electronic Devices|
BACKGROUND: Standardized validation indices (i.e., accuracy, bias, and precision) provide a comprehensive comparison of step counting wearable technologies.
PURPOSE: To expand a previously published child/youth catalog of validity indices to include adults (21-40, 41-60 and 61-85 years of age) assessed across a range of treadmill speeds (slow [0.8-3.2 km/h], normal [4.0-6.4 km/h], fast [7.2-8.0 km/h]) and device wear locations (ankle, thigh, waist, and wrist).
METHODS: Two hundred fifty-eight adults (52.5 ± 18.7 years, 49.6% female) participated in this laboratory-based study and performed a series of 5-min treadmill bouts while wearing multiple devices; 21 devices in total were evaluated over the course of this multi-year cross-sectional study (2015-2019). The criterion measure was directly observed steps. Computed validity indices included accuracy (mean absolute percentage error, MAPE), bias (mean percentage error, MPE), and precision (correlation coefficient, r; standard deviation, SD; coefficient of variation, CoV).
RESULTS: Over the range of normal speeds, 15 devices (Actical, waist-worn ActiGraph GT9X, activPAL, Apple Watch Series 1, Fitbit Ionic, Fitbit One, Fitbit Zip, Garmin vivoactive 3, Garmin vivofit 3, waist-worn GENEActiv, NL-1000, PiezoRx, Samsung Gear Fit2, Samsung Gear Fit2 Pro, and StepWatch) performed at < 5% MAPE. The wrist-worn ActiGraph GT9X displayed the worst accuracy across normal speeds (MAPE = 52%). On average, accuracy was compromised across slow walking speeds for all wearable technologies (MAPE = 40%) while all performed best across normal speeds (MAPE = 7%). When analyzing the data by wear locations, the ankle and thigh demonstrated the best accuracy (both MAPE = 1%), followed by the waist (3%) and the wrist (15%) across normal speeds. There were significant effects of speed, wear location, and age group on accuracy and bias (both p < 0.001) and precision (p ≤ 0.045).
CONCLUSIONS: Standardized validation indices cataloged by speed, wear location, and age group across the adult lifespan facilitate selecting, evaluating, or comparing performance of step counting wearable technologies. Speed, wear location, and age displayed a significant effect on accuracy, bias, and precision. Overall, reduced performance was associated with very slow walking speeds (0.8 to 3.2 km/h). Ankle- and thigh-located devices logged the highest accuracy, while those located at the wrist reported the worst accuracy.
TRIAL REGISTRATION: Clinicaltrials.gov NCT02650258. Registered 24 December 2015.
|Alternate Journal||Int J Behav Nutr Phys Act|
|PubMed Central ID||PMC9461139|
|Grant List||5R01AG049024 / AG / NIA NIH HHS / United States|