title: 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.
authors.affiliation: Department of Health and Human Development, Montana State University, Bozeman 59717, USA. dheil@montana.edu
authors.forename: Daniel P
authors.initials: DP
authors.lastname: Heil
mesh_terms: D000293:Adolescent; D000328:Adult; D000465:Algorithms; D002648:Child; D004734:Energy Metabolism / Q000502:physiology*; D015444:Exercise; D005260:Female; D006801:Humans; D008124:Locomotion; D008297:Male; D008875:Middle Aged; D008991:Monitoring, Physiologic / Q000295:instrumentation*; D009009:Montana