ABSTRACT
Background Among motor symptoms of Parkinson’s disease (PD), including rigidity and resting tremor, bradykinesia is a mandatory feature to define the parkinsonian syndrome. MDS-UPDRS III is the worldwide reference scale to evaluate the parkinsonian motor impairment, especially bradykinesia. However, MDS-UPDRS III constitutes an agent-based score making reproducible measurements and follow-up challenging.
Objectives Using a deep learning approach, we developed a tool to compute an objective score of bradykinesia based on the gold-standard MDS-UPDRS III.
Methods In the Movement Disorder unit of Avicenne University Hospital, we acquired a large database of videos of parkinsonian patients performing MDS-UPDRS III protocols. We applied two deep learning algorithms to detect a two-dimensional (2D) skeleton of the hand composed of 21 predefined points, and transposed it into a three-dimensional (3D) skeleton.
Results We developed a 2D and 3D automated analysis tool to study the evolution of several key parameters during the protocol repetitions of the MDS-UPDRS III. Scores from 2D automated analysis showed a significant correlation with gold-standard ratings of MDS-UPDRS III, measured with coefficients of determination for the tapping (0.609) and hand movements (0.701) protocols using decision tree algorithms. The individual correlations of the different parameters measured with MDS-UPDRS III scores carry meaningful information and are consistent with MDS-UPDRS III guidelines.
Conclusion We developed a deep learning-based tool to reliably score and analyze bradykinesia for parkinsonian patients.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
Financial Disclosure/Conflict of interest: GV, CD, QS, MM, BG LV declare no conflicts of interest. BD received research support from Orkyn, Merz-Pharma and Contrat de Recherche Clinique 2021 (CRC 2021). No sponsorship was obtained for this study.
Data availability: The data are not available for public access because of patient privacy concerns but are available from the corresponding author BD on reasonable request.