  Orofacial deficits are common in people with Parkinson's disease (PD) and
their evolution might represent an important biomarker of disease progression.
We are developing an automated system for assessment of orofacial function in
PD that can be used in-home or in-clinic and can provide useful and objective
clinical information that informs disease management. Our current approach
relies on color and depth cameras for the estimation of 3D facial movements.
However, depth cameras are not commonly available, might be expensive, and
require specialized software for control and data processing. The objective of
this paper was to evaluate if depth cameras are needed to differentiate between
healthy controls and PD patients based on features extracted from orofacial
kinematics. Results indicate that 2D features, extracted from color cameras
only, are as informative as 3D features, extracted from color and depth
cameras, differentiating healthy controls from PD patients. These results pave
the way for the development of a universal system for automatic and objective
assessment of orofacial function in PD.
