基于肌电信号和拉盖尔估计技术的咬合力估计

Nazanin Goharian, S. Moghimi, Hadi Kalani
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引用次数: 3

摘要

咬合力根据咀嚼的食物种类而变化。为了全面研究人类咀嚼,最好考虑咀嚼肌的肌电活动和咬合力。本研究的目的是利用Laguerre展开技术(LET)来评估肌电-力的关系。在这项工作中,只测量了两块咀嚼肌的电活动,即咬肌和颞肌。结果表明,LET能够基于肌电信号预测咀嚼咬合力。此外,所提出的模型可以使用记录的肌电信号来控制咀嚼机器人。在这些应用中,与使用通常非常昂贵且需要大量结构的力传感器和相机相比,使用不昂贵且便携式的肌电图(EMG)电极具有优势。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimation biting force based using EMG signals and Laguerre estimation technique
Biting force varies based on type of food that is being chewed. To study human mastication comprehensively, it is better to consider the electromyography (EMG) activity of the masticatory muscles and bite force. The aim of this study is to evaluate SEMG-force relationship by utilizing Laguerre expansion technique (LET). In this work, the electrical activity of only two masticatory muscles, namely masseter and temporalis are measured. Results denote the ability of LET in predicting mastication biting force based on EMG signals. Additionally, the proposed model can be able to control masticatory robots using recorded EMG signals. In these applications, uses of non-expensive and portable of electromyography (EMG) electrodes have advantageous compared to the use of force sensors and cameras which are often very expensive and require massive structures.
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