Stealth-Adaptive Exergame Design Framework for Elderly and Rehabilitative Users

摘要

Adaptive exergames have been developed to encourage regular exercise and support rehabilitative motion for improved health outcomes in today's ageing population. However, existing approaches often fail to provide evidence for a direct link between physical performance and gameplay outcomes, which makes it difficult to accurately adapt gameplay mechanics. The Stealth-Adaptive Exergame Design (SAED) Framework addresses this limitation by mapping the design of exergame mechanics to performance characteristics and utilizing real-time learning in a seamless (stealth) manner to adapt the system to the individual. Two cases of implementation of the SAED framework from prior work are presented, one modeling the rehabilitative exercise program of a specific individual and physical trainer in a self-defense arm-swing motion and the other utilizing the two-leg standing squat motion to reduce risk of locomotive degeneration in the Japanese elderly population. Design characteristics of the two cases, including the mapping between spatial and temporal characteristics of the motion and corresponding game objectives, are presented along with models for real-time stealth adaptation. Applications of the framework toward a variety of exercise domains are discussed with limitations on usable game scenarios and designs.