Category: Technology
Objective: To develop a scalable and interpretable computer-vision based algorithm to measure the severity of facial impairment in Parkinson’s disease.
Background: Neurological disorders frequently manifest themselves through impairment, or loss, of facial expressions. Consequently, facial expression examination is a component of routine assessments such as the Movement Disorder Society (MDS) Unified PD Rating Scale (UPDRS) [1]. Such assessments require rating by highly trained clinicians and take significant time to perform, making them unscalable and operator-dependent.
Method: We used markerless facial keypoints detection to extract biomarkers from videos (N=436) of routine assessments of Parkinson’s disease patients. Patients were rated by an experienced clinician on the UPDRS (0-4) at five separate clinical sites and recorded using commercially available mobile devices. Our derived set of features characterizes the general movement of the face as well as relates facial movements to emotions and facial muscles using Action Units (AUs). Two distinct parts of the UPDRS facial expression assessment, patient at rest and patient speaking, were considered separately. A machine learning model was then applied to provide an estimate of the severity as well as interpret the importance of individual features.
Results: Our model achieved 47.7% balanced accuracy for severity prediction with 72.6% accuracy in detecting impairment (Figure 1). Mapping of the features’ importance to facial keypoints indicates that eyes, brows, and mouth areas are the most important to estimation (Figure 2). This concurs with the MDS-UPDRS instructions.
Conclusion: Computer-assisted facial expression can provide cost-effective scalable routine assessments to patients with clear applications in telehealth. Moreover, this could be done using short video clips recorded using commercially available hardware.
References: [1] Goetz, Christopher G., et al. “Movement Disorder Society sponsored revision of the Unified Parkinson’s Disease Rating Scale (MDS-UPDRS): scale presentation and clinimetric testing results.” Movement disorders: official journal of the Movement Disorder Society 23.15 (2008): 2129-2170.
To cite this abstract in AMA style:
Y. Dushin, G. Morinan, G. Sarapata, J. O'Keeffe. Clinically interpretable severity estimation of facial expression impairment in Parkinson’s disease [abstract]. Mov Disord. 2022; 37 (suppl 2). https://www.mdsabstracts.org/abstract/clinically-interpretable-severity-estimation-of-facial-expression-impairment-in-parkinsons-disease/. Accessed October 4, 2024.« Back to 2022 International Congress
MDS Abstracts - https://www.mdsabstracts.org/abstract/clinically-interpretable-severity-estimation-of-facial-expression-impairment-in-parkinsons-disease/