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首页> 外文期刊>Medical and Biological Engineering and Computing: Journal of the International Federation for Medical and Biological Engineering >Predicting 3D lip movement using facial sEMG: a first step towards estimating functional and aesthetic outcome of oral cancer surgery
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Predicting 3D lip movement using facial sEMG: a first step towards estimating functional and aesthetic outcome of oral cancer surgery

机译：使用面部半决预测3D唇缘运动：探讨口腔癌手术功能和审美结果的第一步

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摘要

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.
机译：在口腔癌中，由于手术导致的功能丧失可以是不可接受的，将肿瘤指定在功能上不可操作。然后可以考虑其他疗法处理。目前，预测这些功能后果是主观和不可靠的。我们希望创建患者特定的模型来改进和象观这些预测。通过控制具有志愿者特异性SEMG活动的3D唇模型采取第一步。我们首先专注于嘴唇，因为它们对言语，口服食品运输和面部模仿至关重要。此外，测量比口腔器官更易于测量。 3D唇部运动和相应的SEMG活动是在五个健康的志愿者中测量的，他们反复执行19条指令，通过在输入侧的输入侧和相应的3D唇位移中建立八个面部肌肉的半肌肉的半决赛活动之间的关系和相应的3D唇位移来创造定量唇模型。输出侧。在状态空间模型中容纳3D唇移动和SEMG活动之间的关系。 SEMG活动与3D唇部运动之间的良好关系是建立的，平均均线平均误差为2.43 mm，为一阶系统，用于二阶系统2.46 mm。该信息可以纳入生物力学模型中，以在治疗后进一步个性化功能结果评估。

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