Volodymyr Hrytsyk, Maksym Kochut, Uliana Marikutsa, Oleh Lytovchenko, Oleh Berezyuk, Vitalii Hrendus, Mariia Nazarkevych
Neurological disorders are a major cause of disability and mortality worldwide, and accessible methods for detecting tremor-related trajectory deviations remain an important research challenge. We present an augmented reality (AR)-based approach for evaluating trajectory deviations associated with tremor-related hand movements in Parkinson's disease (PD) and neurological sequelae of traumatic brain injury (TBI). Unlike conventional surface-based drawing tests, the proposed approach removes the physical support point that may facilitate compensatory stabilization of hand movements during task performance. The method implementing this concept was preliminarily evaluated in a pilot cohort of 131 participants, including 50 healthy controls, 6 patients with PD, and 75 combat veterans with TBI, and was compared with a standard geometric figure drawing test. In the PD subgroup, the AR protocol flagged algorithmically detected trajectory deviations in all six participants. Given the small PD sample and the limited number of additional findings in the TBI group, these observations should be interpreted as preliminary and hypothesis-generating rather than as evidence of proof-of-concept accuracy or sensitivity. The results suggest that the anchor-free AR-based trajectory-assessment method may warrant further investigation as a potential approach for tremor-related movement analysis. Larger clinically validated studies with independent confirmation and standard concept metrics will be required to determine the clinical utility of the proposed method.