Abstract
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 (act all) , selecting the three muscles showing highest muscle activity bilaterally (act 3) —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 (act rel) , bilaterally. The model’s lip movement was compared to the actual lip movement performed by the volunteers, using 3D correlation coefficients (ρ). Results: The correlation coefficient between simulations and measurements with act rel resulted in a median ρ of 0.77. act 3 had a median ρ of 0.78, whereas with act all the median ρ 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 ρ 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.
| Original language | English |
|---|---|
| Pages (from-to) | 47-59 |
| Number of pages | 13 |
| Journal | International journal of computer assisted radiology and surgery |
| Volume | 13 |
| Issue number | 1 |
| Early online date | 31 Aug 2017 |
| DOIs | |
| Publication status | Published - 1 Jan 2018 |
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Keywords
- UT-Hybrid-D
- Forward modelling
- Functional inoperability
- Head and neck cancer
- Lips
- Surface electromyography
- Biomechanical modelling
Cite this
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Simulation of facial expressions using person-specific sEMG signals controlling a biomechanical face model. / Eskes, Merijn (Corresponding Author); Balm, Alfonsus Jacobus Maria; van Alphen, Maarten J.A.; Smeele, Ludi E.; Stavness, Ian; van der Heijden, Ferdinand.
In: International journal of computer assisted radiology and surgery, Vol. 13, No. 1, 01.01.2018, p. 47-59.Research output: Contribution to journal › Article › Academic › peer-review
TY - JOUR
T1 - Simulation of facial expressions using person-specific sEMG signals controlling a biomechanical face model
AU - Eskes, Merijn
AU - Balm, Alfonsus Jacobus Maria
AU - van Alphen, Maarten J.A.
AU - Smeele, Ludi E.
AU - Stavness, Ian
AU - van der Heijden, Ferdinand
N1 - Springer deal
PY - 2018/1/1
Y1 - 2018/1/1
N2 - 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 (act all) , selecting the three muscles showing highest muscle activity bilaterally (act 3) —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 (act rel) , bilaterally. The model’s lip movement was compared to the actual lip movement performed by the volunteers, using 3D correlation coefficients (ρ). Results: The correlation coefficient between simulations and measurements with act rel resulted in a median ρ of 0.77. act 3 had a median ρ of 0.78, whereas with act all the median ρ 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 ρ 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.
AB - 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 (act all) , selecting the three muscles showing highest muscle activity bilaterally (act 3) —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 (act rel) , bilaterally. The model’s lip movement was compared to the actual lip movement performed by the volunteers, using 3D correlation coefficients (ρ). Results: The correlation coefficient between simulations and measurements with act rel resulted in a median ρ of 0.77. act 3 had a median ρ of 0.78, whereas with act all the median ρ 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 ρ 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.
KW - UT-Hybrid-D
KW - Forward modelling
KW - Functional inoperability
KW - Head and neck cancer
KW - Lips
KW - Surface electromyography
KW - Biomechanical modelling
UR - http://www.scopus.com/inward/record.url?scp=85028765698&partnerID=8YFLogxK
U2 - 10.1007/s11548-017-1659-5
DO - 10.1007/s11548-017-1659-5
M3 - Article
VL - 13
SP - 47
EP - 59
JO - International journal of computer assisted radiology and surgery
JF - International journal of computer assisted radiology and surgery
SN - 1861-6410
IS - 1
ER -