Motion Recommender for Preventing Injuries During Motion Gaming

Abstract

This paper presents an intelligent assistant for preventing the injuries during motion gaming. In our previous work, we invented UKI, a middleware that allows its users to play any existing game by using body motions. The goal of this paper is to add an intelligent module to the UKI for promoting healthy motion gameplay. According to the literature in sports science and medicine, several exercise injuries are caused by the unbalanced use of body segments and repetitive movement. To prevent such injuries, we present a module that monitors and promotes two health metrics of the player: balancedness in use of body segments and variability in body movement. The proposed module recommends motions that will improve the two health metrics during gameplay. We evaluate effectiveness of the module on 45 participants with normal health condition. Two methods for motion recommendation were compared: recommendation according to the health fitness functions (HFF) and recommendation by the random motion selection. Our results indicate significant improvement in the two health metrics when HFF is used.

Keywords

• AI
• games for health
• motion games
• health monitoring