Facial Behaviour Analysis in Parkinson’s Disease

We describe a method for evaluating facial expressivity in order to improve related clinical assessments of Parkinson’s Disease (PD). There is a controversial evidence in the literature that PD facial impairment can be detected on certain emotional expressions. This study aimed to investigate the feasibility of discriminative and quantitive measures of PD from the ability of a subject to express facial expressions. Video clips of 8 subjects (4 healthy controls and 4 with patients with PD) were recorded during daily sessions over several weeks. Observations covered emotion variation over one week for control subjects and six weeks for patients with PD. A statistical shape model was used to track facial expressions and to measure the amount of expressivity exhibited by each subject. The study suggests that measures of the amount of movement during happiness, disgust and anger expressions are the most discriminative, with PD patients exhibiting less movement than controls. This work demonstrates that it may be possible to measure day-to-day variations in symptoms of PD automatically.