Calibration and evaluation of MET models for estimating energy expenditure using thigh and ankle-worn move 4 accelerometer

$\textbf{Objectives}$
Valid estimation of energy expenditure remains a challenge, particularly when using ankle- and thigh-worn devices. The Move 4 is a research-grade accelerometer previously tested for predicting metabolic equivalents (METs) when worn at the waist or wrist. This study aimed to calibrate and evaluate regression models to estimate METs from Move 4 data when worn at the ankle and thigh.

$\textbf{Methods}$
Participants completed walking and jogging tasks under laboratory conditions while wearing Move 4 sensors and with indirect calorimetry as a reference measure. Models were calibrated using study 1 (n=160) and evaluated in an independent dataset (study 2; n=15). Performance was assessed using mean absolute error (MAE), root mean square error (RMSE), and Bland-Altman analyses.

$\textbf{Results}$
The MET models demonstrated strong agreement across both locations and datasets. For the thigh position, the MAE ranged from 0.60 METs (walking) to 1.38 METs (jogging), with RMSE of 0.82 and 1.70 in the evaluation data. Calibration metrics were comparable (jogging: MAE=1.24, RMSE=1.63). The ankle models showed similar accuracy, with MAEs of 0.66 (walking) and 1.39 (jogging), and RMSEs of 0.85 and 1.67, respectively. ... mehrSystematic bias remained low (mean differences between −0.34 and −0.01 METs).

$\textbf{Conclusion}$
This study provides the first calibration and evaluation for estimating METs from ankle- and thigh-worn Move 4 accelerometers. The model indicated accurate, high-resolution MET estimation for walking and jogging. Future work should expand independent performance evaluations, including diverse activities such as static activities, and diverse samples under free-living conditions.