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

Francois-Régis Sarhan (1, 2) , Emilien Colin , Baptiste Choteau , Khalil Ben Mansour (3) , Felix Marcellin (2) , Eder Alejandro Rodriguez Martineza , Frederic Marin (4) , Stéphanie Dakpé (1, 2)

1 CMF et Stomatologie - Chirurgie maxillofaciale et Stomatologie [CHU Amiens]
2 CHIMERE - CHirurgie, IMagerie et REgénération tissulaire de l’extrémité céphalique - Caractérisation morphologique et fonctionnelle - UR UPJV 7516
3 BMBI - Biomécanique et Bioingénierie
4 BGS - Biogéosciences [UMR 6282]

Research Objectives 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. Design A prospective study for quantitative analysis of facial movements by the simultaneous use of surface electromyography (sEMG) was conducted. Setting 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). Participants This feasibility trial was performed on two healthy male volunteers without history of facial pathology. Interventions 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. Main Outcome Measures 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. Results 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. Conclusions 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.

Domaines: Chirurgie

Francois-Régis Sarhan, Emilien Colin, Baptiste Choteau, Khalil Ben Mansour, Felix Marcellin, et al.. Combined Surface Electromyography and Motion Capture for Quantitative Analysis of Facial Movements. Archives of Physical Medicine and Rehabilitation, 2023, 104 (3), pp.e17-e18. ⟨10.1016/j.apmr.2022.12.048⟩. ⟨hal-04082038⟩