Objective Grading of Facial Paralysis Using Artificial Intelligence Analysis of Video Data

Authors:
Stewart McGrenary;Brian F. O'Reilly;John J. Soraghan
Affiliations:
Strathclyde University;-;Strathclyde University
Venue:
CBMS '05 Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems
Year:
2005

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Biomedical image sequence analysis with application to automatic quantitative assessment of facial paralysis

Journal on Image and Video Processing
Biomedical image sequence analysis with application to automatic quantitative assessment of facial paralysis

Journal on Image and Video Processing

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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 patientýs 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%.