體能活動有助於提升身體安適, 健康, 認知功能, 以及生活品質, 並且可減少失智疾患的產生. 藉由能量消耗可偵測一個人的健康及體適能表現. 而能量消耗遊戲(AVG)具有鼓勵人們從事有意義的休閒育樂之潛在效益. 依據生物力學原則, Kinect™對於身體關節移動的偵測有助於提升對於人類活動能量消耗(EE)的偵測. 本研究使用兩個公式以計算身體能量消耗, 包括: mechanical energy (KineticE) 以及 work (WorkE). 實驗中, 參與者執行四個任務, 包含超級瑪莉遊戲, 高爾夫球, 拳擊競賽, 以及舞蹈革命大賽. 效度驗證結果顯示, AEEkinetic (R-squared=0.254) 以及 AEEwork (R-squared=0.643)在熱量估計上, 有顯著相關. 整體而言, AEEwork模式可作為預測活動能量消耗的一個新的替代模式.

A physically active lifestyle will enhance the feelings of energy, well-being, quality of life, and cognitive function and is associated with lower risk of cognitive decline and dementia. Good personal health and fitness in general should be monitored by one’s energy expenditure (EE). The development of active video game (AVG) has the potential to encourage people to spend more active leisure time. By utilizing the biomechanical principle, Kinect™ body joint detection could also facilitate the calculation of human EE over time. There are two possible equations that could be used to estimate EE: mechanical energy (KineticE) and work (WorkE). Participants performed four task sessions, playing Wii™ Mario Kart, playing Wii™ Sports Golf, playing Wii™ Sports Boxing, and playing Wii™ Dance Dance Revolution Hottest Party 2. Validation result on holdout samples shows significant correlation between AEEkinetic (R-squared=0.254) and AEEwork (R-squared=0.643) with indirect calorimetry. Overall, AEEwork model can be utilized as a new alternative for predicting activity energy expenditure.

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