Abstract
We propose a surface-electromyographic (sEMG) assisted inverse-modelling (IM) approach for a biomechanical model of the face to obtain realistic person-specific muscle activations (MA) by tracking movements as well as innervation trajectories. We obtained sEMG data of facial muscles and 3D positions of lip markers in six volunteers and, using a generic finite element (FE) face model in ArtiSynth, performed inverse static optimisation with and without sEMG tracking on both simulation data and experimental data. IM with simulated data and experimental data without sEMG data showed good correlations of tracked positions (0.93 and 0.67) and poor correlations of MA (0.27 and 0.20). When utilising the sEMG-assisted IM approach, MA correlations increased drastically (0.83 and 0.59) without sacrificing performance in position correlations (0.92 and 0.70). RMS errors show similar trends with an error of 0.15 in MA and of 1.10 mm in position. Therefore, we conclude that we were able to demonstrate the feasibility of an sEMG-assisted inverse modelling algorithm for the perioral region. This approach may help to solve the ambiguity problem in inverse modelling and may be useful, for instance, in future applications for preoperatively predicting treatment-related function loss.
Highlights
Similar models are urgently needed in the field of Head and Neck Surgery, as well
When using all cost terms together, including our surface EMG (sEMG) term, we found that muscle activation patterns were still good (Fig. 3) while used muscle activation strategies improved considerably over performance with individual cost terms or all cost terms combined with exclusion of the sEMG term
It should be noted that the solution depends on the weighing factors of the cost terms, e.g. when too much sEMG information is used, the result will mimic the forward solution
Summary
Similar models are urgently needed in the field of Head and Neck Surgery, as well. Modelling of the perioral region may improve treatment and counselling of head and neck cancer patients, by assessing functional inoperability, when surgical resection of a tumour will lead to unwanted severe loss of function[2], and other organ-sparing treatments should be considered instead, e.g. chemotherapy, radiotherapy, photodynamic therapy, or any combination thereof. Inverse problems in biomechanical modelling are often mathematically ill-posed because of muscle redundancy: similar functional movements can be performed by different sets of muscles This so-called load-sharing problem[17,18] poses a significant challenge: to predict a patient’s motor behaviour accurately, the simulations must “share” muscle activations in the same way the patient does. Such so-called EMG-assisted, EMG-informed, EMG-calibrated, or EMG-tracking algorithms were successfully applied in biomechanical models of the trunk[26,27,28], shoulder and arm[29], and legs[30,31]. Reports on inverse modelling of the perioral region are scarce[33,34,35], and only few involve EMG measurements[36]
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