New AI tool for Parkinson's diagnosis outperforms certified raters and nearly matches experts, using webcam-captured videos of finger-tapping tests. The technology holds promise for remote, automatic diagnosis, especially in regions lacking neurological care.
By Hugo Francisco de SouzaAug 28 2023 In a recent study published in the journal npj Digital Medicine, researchers evaluated a novel artificial intelligence tool aimed at assessing the motor performance of potential Parkinson's disease patients.
Most PD patients are adults above the age of 65. Even in areas with sufficient neurological support, arranging regular clinical visits for elderly, motor-function-impaired individuals is challenging. Artificial intelligence and machine learning models have recently been proposed to solve this challenge via automated PD diagnosis and clinical assessment.
About the study The present study aimed to develop, train, and performance-test ML models capable of using webcam-captured motor function videos to accurately diagnose PD severity remotely and automatically. Data was collected from 250 global participants using the online, publicly available ParkTest tool. Of these, 202 participants recorded themselves carrying out the finger-tapping task at home, while 48 participants were videoed using identical methodology in a clinic.
"The feature extraction process is comprised of five stages: distinguishing left and right-hand finger-tapping from the recorded video, locating the target hand for continuous tracking, quantifying finger-tapping movements by extracting key points on the hand, reducing noise, and computing features that align with established clinical guidelines, such as MDS-UPDRS."
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