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

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

    Research output: Contribution to journalArticleAcademicpeer-review

    5 Citations (Scopus)
    62 Downloads (Pure)

    Abstract

    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.
    Original languageEnglish
    Pages (from-to)573–583
    Number of pages11
    JournalMedical & biological engineering & computing
    Volume55
    DOIs
    Publication statusPublished - 1 Jul 2016

    Keywords

    • Oral cancer
    • Surface electromyography (sEMG)
    • Lips
    • State-space estimation
    • Kalman filter
    • Principal component analysis (PCA)

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