AGE-IT: Merging Virtual Reality and Artificial Intelligence to Innovate Elderly Assessment with Digital Biomarkers

Recent technological advances in virtual reality (VR) and artificial intelligence (AI) offer promising solutions to address current limitations in MCI and frailty assessment. VR technology creates simulated environments that enable the collection of digital biomarkers (DB)—objective, quantifiable data reflecting individual health status or disease progression. These biomarkers include precise measurements of hand movements, head positioning, and gait patterns during VR interactions. Studies have validated the effectiveness of these digital biomarkers in evaluating MCI and frailty conditions, yielding encouraging results. Machine learning (ML), a specialized branch of AI, complements VR capabilities by analyzing complex patterns within datasets to assess clinical conditions such as MCI. Research has demonstrated high diagnostic accuracy in identifying AD and MCI through ML analysis of medical imaging data. Given these technological advances and the urgent need for health care innovation, we propose developing an integrated diagnostic system that combines VR-derived digital biomarkers with ML models to enhance the assessment of frailty and MCI.