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DOI 10.1007/s11517-016-1511-z

Медицинская библиотека · Medical & biological engineering & computing · 2016

Predicting 3D lip movement using facial sEMG: a first step towards estimating functional and aesthetic outcome of oral cancer surgery.

Eskes Merijn, van Alphen Maarten J A, Smeele Ludi E, Brandsma Dieta, Balm Alfons J M, van der Heijden Ferdinand

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Аннотация

In oral cancer, loss of function due to surgery can be unacceptable, designating the tumour as functionally inoperable. Other curative treatments can then be considered. Currently, predictions of these functional consequences are subjective and unreliable. We want to create patient-specific models to improve and objectify these predictions. A first step was taken by controlling a 3D lip model with volunteer-specific sEMG activities. We focus on the lips first, because they are essential for speech, oral food transport, and facial mimicry. Besides, they are more accessible to measurements than intraoral organs. 3D lip movement and corresponding sEMG activities are measured in five healthy volunteers, who performed 19 instructions repeatedly, to create a quantitative lip model by establishing the relationship between sEMG activities of eight facial muscles bilaterally on the input side and the corresponding 3D lip displacements on the output side. The relationship between 3D lip movement and sEMG activities was accommodated in a state-space model. A good relationship between sEMG activities and 3D lip movement was established with an average root mean square error of 2.43 mm for the first-order system and 2.46 mm for the second-order system. This information can be incorporated into biomechanical models to further personalise functional outcome assessment after treatment.

Для цитирования: Eskes Merijn, van Alphen Maarten J A, Smeele Ludi E, Brandsma Dieta, Balm Alfons J M, van der Heijden Ferdinand. Predicting 3D lip movement using facial sEMG: a first step towards estimating functional and aesthetic outcome of oral cancer surgery.. Medical & biological engineering & computing. 2016. DOI: 10.1007/s11517-016-1511-z.

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