Improving Responsiveness in Game-based Cognitive Assessment for Mild Cognitive Impairment

Mild Cognitive Impairment (MCI) affects up to 20% of older adults and often progresses to dementia. While brief cognitive screening tools like the Montreal Cognitive Assessment (MoCA) can aid in early detection and monitoring, their reliance on trained clinicians and susceptibility to test anxiety limit accessibility and ecological validity. Game-based cognitive monitoring presents a promising alternative, yet its sensitivity to cognitive changes in individuals with MCI remains underexplored. This study introduces an analytic pipeline for screening cognitive decline using Neuro-World, a serious gaming platform featuring six adaptive subgames that assess cognitive abilities through metrics such as accuracy and response time. Over 12 weeks, ten participants with MCI completed 24 game sessions. Gameplay data were analyzed using correlation-based feature selection and machine learning models to estimate cognitive function and track longitudinal changes. Results showed strong correlations between game-based assessments and clinician-administered MoCA scores ( r = 0.71), as well as with longitudinal cognitive changes ( r = 0.80). These findings highlight the potential of game-based cognitive assessments to provide self-administered, ecologically valid screening for cognitive decline in MCI, supporting early detection in aging populations.