Predicting activity energy expenditure using the Actical activity monitor

Abstract

This study developed algorithms for predicting activity energy expenditure (AEE) in children (n = 24) and adults (n = 24) from the Actical activity monitor. Each participant performed 10 activities (supine resting, three sitting, three house cleaning, and three locomotion) while wearing monitors on the ankle, hip, and wrist; AEE was computed from oxygen consumption. Regression analysis, used to create AEE prediction equations based on Actical output, varied considerably for both children (R2 = .45-.75; p < .001) and adults (R2 = .14-.85; p < .008). Most of the resulting algorithms accurately predicted accumulated AEE and time within light, moderate, and vigorous intensity categories (p > .05). The Actical monitor may be useful for predicting AEE and time variables at the ankle, hip, or wrist locations.