Remote Evaluation of Parkinson's Disease Using a Conventional Webcam and Artificial Intelligence

Objective: This study aimed to prove the concept of a new optical video-based system to measure Parkinson's disease (PD) remotely using an accessible standard webcam. Methods: We consecutively enrolled a cohort of 42 patients with PD and healthy subjects (HSs). The participants were recorded pe...

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Vydáno v:Frontiers in neurology Ročník 12; s. 742654
Hlavní autoři: Monje, Mariana H. G., Domínguez, Sergio, Vera-Olmos, Javier, Antonini, Angelo, Mestre, Tiago A., Malpica, Norberto, Sánchez-Ferro, Álvaro
Médium: Journal Article
Jazyk:angličtina
Vydáno: Switzerland Frontiers Media S.A 23.12.2021
Témata:
artificial intelligence and bio-inspired algorithms
kinematics
Neurology
Parkinson's disease
telemedicine
webcam
telemedicine
kinematics
Parkinson's disease
webcam
artificial intelligence and bio-inspired algorithms
ISSN:1664-2295, 1664-2295
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Shrnutí:Objective: This study aimed to prove the concept of a new optical video-based system to measure Parkinson's disease (PD) remotely using an accessible standard webcam. Methods: We consecutively enrolled a cohort of 42 patients with PD and healthy subjects (HSs). The participants were recorded performing MDS-UPDRS III bradykinesia upper limb tasks with a computer webcam. The video frames were processed using the artificial intelligence algorithms tracking the movements of the hands. The video extracted features were correlated with clinical rating using the Movement Disorder Society revision of the Unified Parkinson's Disease Rating Scale and inertial measurement units (IMUs). The developed classifiers were validated on an independent dataset. Results: We found significant differences in the motor performance of the patients with PD and HSs in all the bradykinesia upper limb motor tasks. The best performing classifiers were unilateral finger tapping and hand movement speed. The model correlated both with the IMUs for quantitative assessment of motor function and the clinical scales, hence demonstrating concurrent validity with the existing methods. Conclusions: We present here the proof-of-concept of a novel webcam-based technology to remotely detect the parkinsonian features using artificial intelligence. This method has preliminarily achieved a very high diagnostic accuracy and could be easily expanded to other disease manifestations to support PD management.
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Reviewed by: J. Lucas McKay, Emory University, United States; Norbert Brüggemann, University of Lübeck, Germany
Edited by: Letizia Leocani, San Raffaele Hospital (IRCCS), Italy
This article was submitted to Movement Disorders, a section of the journal Frontiers in Neurology
These authors have contributed equally to this work and share first authorship
These authors have contributed equally to this work and share last authorship
ISSN:1664-2295
1664-2295
DOI:10.3389/fneur.2021.742654