Background: Evaluation of facial nerve paresis depends on visual assessment and naturally differs from examiner to examiner. An objective measurement instrument is presented.
Patients and method: Facial features are automatically localized by a parametric face model in videos of a face during relaxation and exercises. Gray-level information is analyzed by a special steerable filter and used to identify symmetries. The computer system was tested in 19 individuals.
Results: Automatic localization of facial features such as the upper arc of the head and ears was correct in 95%, the eyes in 82%, and the mouth in 73%. Lid paresis was correctly recognized in seven of ten (70%) and oral paresis in 10 of 12 (83%) cases. Unaffected eyelid movements were identified in eight of nine (89%) and healthy oral regions in all seven (100%) cases.
Conclusion: The computer system presented is able to automatically localize facial features and to identify facial nerve paresis. It is a considerable step toward automatic and objective grading of facial nerve paresis.