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Calibration and validation of accelerometer-based activity monitors: A systematic review of machine-learning approaches
2019
Gait & Posture
A B S T R A C T Background: Objective measures using accelerometer-based activity monitors have been extensively used in physical activity (PA) and sedentary behavior (SB) research. To measure PA and SB precisely, the field is shifting towards machine learning-based (ML) approaches for calibration and validation of accelerometer-based activity monitors. Nevertheless, various parameters regarding the use and development of ML-based models, including data type (raw acceleration data versus
doi:10.1016/j.gaitpost.2018.12.003
fatcat:522byta52nbgte4fnflve4qr2e