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电极系统的几何参数对电阻抗肌图的影响:一项初步研究。

Determination of the Geometric Parameters of Electrode Systems for Electrical Impedance Myography: A Preliminary Study.

机构信息

Department of Medical and Technical Information Technology, Bauman Moscow State Technical University, 105005 Moscow, Russia.

Chair of Medical Information Technology, RWTH Aachen University, 52074 Aachen, Germany.

出版信息

Sensors (Basel). 2021 Dec 24;22(1):97. doi: 10.3390/s22010097.

Abstract

The electrical impedance myography method is widely used in solving bionic control problems and consists of assessing the change in the electrical impedance magnitude during muscle contraction in real time. However, the choice of electrode systems sizes is not always properly considered when using the electrical impedance myography method in the existing approaches, which is important in terms of electrical impedance signal expressiveness and reproducibility. The article is devoted to the determination of acceptable sizes for the electrode systems for electrical impedance myography using the Pareto optimality assessment method and the electrical impedance signals formation model of the forearm area, taking into account the change in the electrophysical and geometric parameters of the skin and fat layer and muscle groups when performing actions with a hand. Numerical finite element simulation using anthropometric models of the forearm obtained by volunteers' MRI 3D reconstructions was performed to determine a sufficient degree of the forearm anatomical features detailing in terms of the measured electrical impedance. For the mathematical description of electrical impedance relationships, a forearm two-layer model, represented by the skin-fat layer and muscles, was reasonably chosen, which adequately describes the change in electrical impedance when performing hand actions. Using this model, for the first time, an approach that can be used to determine the acceptable sizes of electrode systems for different parts of the body individually was proposed.

摘要

基于电阻抗成像的肌电方法在仿生控制问题中得到了广泛应用,其通过实时评估肌肉收缩过程中电阻抗幅值的变化来实现。然而,在现有的方法中,在使用基于电阻抗成像的肌电方法时,并不总是适当考虑电极系统尺寸的选择,而这对于电阻抗信号的表达和可重复性是很重要的。本文采用 Pareto 最优评估方法和前臂区域的电阻抗信号形成模型,针对基于电阻抗成像的肌电方法中的电极系统尺寸选择问题进行了研究,该模型考虑了在执行手部动作时皮肤和脂肪层以及肌肉群的电物理和几何参数的变化。采用志愿者的 MRI 3D 重建获得的前臂人体测量模型进行了数值有限元仿真,以确定在测量电阻抗时,前臂解剖特征的足够详细程度。为了对电阻抗关系进行数学描述,本文合理地选择了一个由皮肤-脂肪层和肌肉组成的前臂两层模型,该模型能够很好地描述执行手部动作时电阻抗的变化。利用该模型,本文首次提出了一种可用于单独确定身体不同部位的电极系统可接受尺寸的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6599/8747741/a9ca3a8723f1/sensors-22-00097-g0A1.jpg

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