Objective grading of facial paralysis using artificial intelligence analysis of video data

Abstract

Facial paralysis is a debilitating condition in which sufferers experience unilateral paralysis of the left or right facial nerve. An evidence based assessment of a patient's condition is almost impossible because all current grading scales are subjective. A quantitative, practical, reliable system would be an invaluable tool in this field of neurootology. Demonstrated here is a system which intelligently quantifies the facial damage in 43 testing videos from 14 subjects. Using an artificial neural network the average mean squared error for the system is 1.6%.