Enhancing Elderly Exergaming with AI Components for Assessing Cognitive Status

Maintaining physical and cognitive health is challenging for the older population, and thus creative ways to promote active lives are needed. The GAME2AWE platform is an exergaming platform that promotes the well-being of older people by utilizing serious games to encourage movement in a fun and engaging way. To improve the GAME2AWE experience, the platform's capabilities have been enhanced with AI components that provide user-aware functionalities. One of the GAME2AWE components is responsible for assessing the cognitive as well as the physical condition of the user playing in real-time. In this paper, we extend our investigation into this AI component by exploring the development of relevant models for assessing user cognitive status. In our machine learning (ML) training experiments, we extensively explored the area of ML hyperparameter tuning in order to achieve performance that is competitive with the standards set by related work. This study highlights the potential of AI to turn exergaming into a more effective tool for the well-being of the elderly by promoting exercise in a safe and controllable manner.