Features Characterization of Facial sEMG Signals for a Facial Paralysis Application

Facial paralysis is characterized by sudden weakness or paralysis in the muscles on one side of the face, resulting in an asymmetrical facial appearance and difficulty performing normal facial movements, such as closing one eye or smiling. In this article our aim is to characterize the values of 5 features that describe 5 facial expressions in healthy subjects. To this end, signal processing is performed to find quantitative values for the facial expressions. From the calculated features, discrepancies of 3.55% to 23.35% were found between both sides of the face in healthy subjects for the smile facial expression. This algorithm will be integrated as a user interface for facial mapping and recovery follow-up in future work.