Preschoolers

Ahmadi, 2020- four machine learning models to predict energy expenditure of preschoolers from raw acceleration features from hip or non-dominant wrist-worn ActiGraph accelerometers

Roscoe, 2017- cut-points for signal magnitude vector from GENEActiv worn on non-dominant wrist in preschool-aged children

Steenbock, 2019- twenty-four machine learning models to predict energy expenditure of preschoolers using acceleration metrics from an ActiGraph on either hip, GENEActiv right hip, GENEActiv on either wrist, and/or ActivPal right thigh

Tanaka, 2019- the ratio of unfiltered to filtered acceleration is used to determine non-locomotive vs. locomotive activities, then activity-specific equations are used to predict energy expenditure in young children wearing a waist-worn Omron accelerometer

Tanaka, 2007- linear and non-linear equations were developed to predict energy expenditure in young children wearing an ActivTracer on the left hip

Zakeri, 2012- Cross-sectional time series and multivariate adaptive regression splines for ActiHeart, ActiGraph, or ActiGraph plus heart rate inputs, resulting in six total models for predicting total energy expenditure in preschool-aged children