ICDHM'11 Proceedings of the Third international conference on Digital human modeling
ICIC'11 Proceedings of the 7th international conference on Advanced Intelligent Computing Theories and Applications: with aspects of artificial intelligence
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Accurate quantification of physical activity (PA) and energy expenditure (EE) is a basic prerequisite to evaluate activity promoting measures. A novel approach for determining EE by a person-centered measurement system which operates with motion sensors is presented. The new EE prediction model combines information on the type and intensity of PA as well as personal characteristics. For model calibration eight subjects performed standardized office and locomotion tasks while wearing the measurement system and an indirect calorimeter simultaneously. Via multiple regression analyses different EE prediction equations for sitting, standing, walking, climbing downstairs and climbing upstairs are developed. Model fit statistics revealed good results (adjusted R2 = 0.51 - 0.90). The developed model seems promising for precise EE prediction during the investigated activities.