Multimodal Sensing and Digital Biomarkers in Virtual Reality-Based Cognitive Rehabilitation: Clinical Validation, Adaptive Systems, and Real-World Translation

Virtual reality (VR) is evolving from a platform for cognitive exercises into an instrumented rehabilitation environment capable of simultaneously delivering treatment and quantifying behavior. This critical narrative review examines how behavioral, ocular, kinematic, physiological, and neurophysiological signals can be transformed into clinically meaningful digital measures, candidate biomarkers, adaptive interventions, and real-world functional outcomes. PubMed/MEDLINE, Scopus, and IEEE Xplore were searched from database inception to 20 September 2026, supplemented by backward and forward citation searching and targeted searches. Clinical, methodological, validation, and directly relevant technical studies were considered, including studies in healthy participants when methodologically informative. Of 690 records identified, 145 duplicates were removed; 545 unique records were screened and 303 formed the candidate evidence pool for critical narrative appraisal. Behavioral and interaction-derived measures are the most established, while eye tracking, kinematic sensing, autonomic monitoring, EEG, and fNIRS provide complementary information on attention, strategy, workload, and engagement. Quantitatively, combined hand- and eye-tracking features distinguished mild cognitive impairment from healthy controls with 93.3% accuracy, 100% sensitivity, and 83.3% specificity, while immersive VR life-skills training produced real-world functional gains of d = 1.00 post-training and d = 1.12 at 1-week follow-up. However, most sensor-derived variables remain digital measures or candidate biomarkers rather than clinically validated biomarkers; physiology-informed closed-loop adaptation is uncommon, and evidence that such adaptation produces sustained ADL or assisted-living benefits is lacking. Progress now depends on standardized reporting, external and multicenter validation, clinically interpretable adaptive models, and objective demonstration of real-world transfer.