Mapping spontaneous facial expression in people with Parkinson’s disease: A multiple case study design

Abstract

People with Parkinson’s disease (PD) often experience a decrease in their facial expressivity, but little is known about how the coordinated movements across regions of the face are impaired in PD. The face has neurologically independent regions that coordinate to articulate distinct social meanings that others perceive as gestalt expressions, and so understanding how different regions of the face are affected is important. Using the Facial Action Coding System, this study comprehensively measured spontaneous facial expression across 600 frames for a multiple case study of people with PD who were rated as having varying degrees of facial expression deficits, and created correlation matrices for frequency and intensity of produced muscle activations across different areas of the face. Data visualization techniques were used to create temporal and correlational mappings of muscle action in the face at different degrees of facial expressivity. Results showed that as severity of facial expression deficit increased, there was a decrease in number, duration, intensity, and coactivation of facial muscle action. This understanding of how regions of the parkinsonian face move independently and in conjunction with other regions will provide a new focus for future research aiming to model how facial expression in PD relates to disease progression, stigma, and quality of life.

Keywords

• parkinson’s disease
• facial expression
• emotion
• smiling
• data visualization
• case series