Clinical Research Directory

An AI-Based Prediction of Cognitive Capacity in Older Adults and Individuals With Mild Cognitive Impairment During Virtual Reality Driving Tasks

Driving ability in older adults is essential for independent mobility and social participation, yet declines under high cognitive load or distraction often lead to visual attention failures such as "look-but-fail-to-see," increasing crash risk. Older adults and individuals with mild cognitive impairment (MCI) show impairments in visual attention, executive control, and visuomotor integration, which are not adequately captured by conventional assessments. Virtual reality (VR) integrated with eye-tracking and upper-limb motion analysis enables ecologically valid simulation of driving scenarios and precise quantification of visuomotor behavior. However, current studies are limited by single-scenario designs, unimodal AI models, and insufficient integration of action-related data. This study proposes a multi-phase framework: Year 1 develops an eye-movement-based AI model for MCI identification; Year 2 integrates multimodal data in VR driving tasks; and Year 3 establishes an explainable AI system with longitudinal validation. The study aims to advance cognitive assessment and develop a digital tool for early MCI detection and driving risk prediction.

Eye Movement and Cognitive Dysfunction

There is association between eye movement disorder and cognitive dysfunction. Therefore, utilizing eye movement and screening for cognitive dysfunction is feasible. In the present study, the investigators will develop an artificial intelligence platform to screening for cognitive dysfunction by inspecting the function of eye movement. Futher more, based on the screening results, the platform will offer referral suggestions.