A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE‑adults study
Metadatos
Mostrar el registro completo del ítemEditorial
BMC
Materia
Accelerometer Accuracy Bias Measurement Pedometer Physical activity
Fecha
2022-09-08Referencia bibliográfica
Mora-Gonzalez, J... [et al.]. A catalog of validity indices for step counting wearable technologies during treadmill walking: the CADENCE-adults study. Int J Behav Nutr Phys Act 19, 117 (2022). [https://doi.org/10.1186/s12966-022-01350-9]
Patrocinador
United States Department of Health & Human Services National Institutes of Health (NIH) - USA NIH National Institute on Aging (NIA) 5R01AG049024Resumen
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 Acti‑
Graph 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.