RESUMEN
We present an artificial intelligence (AI) system to remotely assess the motor performance of individuals with Parkinson's disease (PD). In our study, 250 global participants performed a standardized motor task involving finger-tapping in front of a webcam. To establish the severity of Parkinsonian symptoms based on the finger-tapping task, three expert neurologists independently rated the recorded videos on a scale of 0-4, following the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS). The inter-rater reliability was excellent, with an intra-class correlation coefficient (ICC) of 0.88. We developed computer algorithms to obtain objective measurements that align with the MDS-UPDRS guideline and are strongly correlated with the neurologists' ratings. Our machine learning model trained on these measures outperformed two MDS-UPDRS certified raters, with a mean absolute error (MAE) of 0.58 points compared to the raters' average MAE of 0.83 points. However, the model performed slightly worse than the expert neurologists (0.53 MAE). The methodology can be replicated for similar motor tasks, providing the possibility of evaluating individuals with PD and other movement disorders remotely, objectively, and in areas with limited access to neurological care.
RESUMEN
PURPOSE: While there is strong evidence supporting the importance of telemedicine in stroke, its role in other areas of neurology is not as clear. The goal of this review is to provide an overview of evidence-based data on the role of teleneurology in the care of patients with neurologic disorders other than stroke. RECENT FINDINGS: Studies across multiple specialties report noninferiority of evaluations by telemedicine compared with traditional, in-person evaluations in terms of patient and caregiver satisfaction. Evidence reports benefits in expediting care, increasing access, reducing cost, and improving diagnostic accuracy and health outcomes. However, many studies are limited, and gaps in knowledge remain. SUMMARY: Telemedicine use is expanding across the vast array of neurologic disorders. More studies are needed to validate and support its use.