Energy expenditure prediction in preschool children: a machine learning approach using accelerometry and external validation.

This study aimed to develop convolutional neural networks (CNNs) models to predict the energy expenditure (EE) of children from raw accelerometer data. Additionally, this study sought to external validation of the CNN models in addition to the linear regression (LM), random forest (RF), and full connected neural network (FcNN) models published in Steenbock(201994-102).Included in this study were 41 German children (3.