M.J.A. van Alphen
F. van der Heijden
- Simulation of facial expressions using person-specific sEMG signals controlling a biomechanical face model
- International Journal of Computer Assisted Radiology and Surgery
- Volume | Issue number
- 13 | 1
- Pages (from-to)
- Document type
- Faculty of Dentistry (ACTA)
Purpose: Functional inoperability in advanced oral cancer is difficult to assess preoperatively. To assess functions of lips and tongue, biomechanical models are required. Apart from adjusting generic models to individual anatomy, muscle activation patterns (MAPs) driving patient-specific functional movements are necessary to predict remaining functional outcome. We aim to evaluate how volunteer-specific MAPs derived from surface electromyographic (sEMG) signals control a biomechanical face model.
Methods: Muscle activity of seven facial muscles in six volunteers was measured bilaterally with sEMG. A triple camera set-up recorded 3D lip movement. The generic face model in ArtiSynth was adapted to our needs. We controlled the model using the volunteer-specific MAPs. Three activation strategies were tested: activating all muscles (Formula presented.), selecting the three muscles showing highest muscle activity bilaterally (Formula presented.)—this was calculated by taking the mean of left and right muscles and then selecting the three with highest variance—and activating the muscles considered most relevant per instruction (Formula presented.), bilaterally. The model’s lip movement was compared to the actual lip movement performed by the volunteers, using 3D correlation coefficients (Formula presented.).
Results: The correlation coefficient between simulations and measurements with (Formula presented.) resulted in a median (Formula presented.) of 0.77. (Formula presented.) had a median (Formula presented.) of 0.78, whereas with (Formula presented.) the median (Formula presented.) decreased to 0.45.
Conclusion: We demonstrated that MAPs derived from noninvasive sEMG measurements can control movement of the lips in a generic finite element face model with a median (Formula presented.) of 0.78. Ultimately, this is important to show the patient-specific residual movement using the patient’s own MAPs. When the required treatment tools and personalisation techniques for geometry and anatomy become available, this may enable surgeons to test the functional results of wedge excisions for lip cancer in a virtual environment and to weigh surgery versus organ-sparing radiotherapy or photodynamic therapy.
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- All raw data (excluding raw videos), are available from the Open Science Framework (Eskes, M. (2017, August 20). Simulation of facial expressions using person-specific sEMG signals controlling a biomechanical face model. Retrieved from osf.io/dux3w. doi: 10.17605/OSF.IO/DUX3W.
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