Combined Surface Electromyography and Motion Capture for Quantitative Analysis of Facial Movements

The aim of this work was to test the feasibility of integrating EMG into our motion capture protocol for quantitative analysis of facial movements, in order to measure at the same time the action potentials by sEMG and the markers displacement amplitudes for a determined movement. A prospective study for quantitative analysis of facial movements by the simultaneous use of surface electromyography (sEMG) was conducted. This study was approved by the local independent ethics committees (CPP Nord Ouest II, Amiens, France; references: ID-RCB 2011-A00532-39; CPP 2011-23), registered at clinicaltrials.gov (NCT02002572). This feasibility trial was performed on two healthy male volunteers without history of facial pathology. We used a motion capture system consisting of 10 Vantage optoelectronic cameras (Vicon Ltd, Oxford, UK). In addition, we used wireless bipolar PicoEMG sensors (Cometa Systems, Milan, Italy). They were placed on the subject's face, at the motor points of frontalis and zygomatic major muscles. Kinematic and EMG data was exported as a .csv file that combined EMG signals and markers displacement amplitudes over time. A custom algorithm was developed for processing and analyzing both signals. We obtained noiseless, rectified and filtered EMG signals, which allowed a readable visual graphical analysis. EMG signals analysis between sensors of each side of the face showed similar signal patterns between right and left muscles, for each acquisition and subject. Regarding motion capture data, the markers’ displacements amplitudes were compared between each side of the face according to the muscular zone, and we observed symmetry of the results between muscles on each side of the face. Here we showed the feasibility of using motion capture and electromyography for quantitative analysis of facial movements in one single acquisition. We obtained facial expression indicators that can be used for a simultaneous multimodal analysis. This work was supported by the "Agence Nationale de la Recherche", "FHU SURFACE", the "Fondation des Gueules Cassées", "FEDER-FSE Picardie 2014-2021" program (‘Facemocap’ project). This work uses the EquipEX FIGURES platform.