设计和建造一个低成本的原型,用于讲座和使用多通道技术和空间滤波处理肌电信号

Andrés Olaya Patiño, David Martínez Cifuentes, Carlos Andres Perilla Rozo
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引用次数: 0

摘要

肌电图(EMG)信号分析是必要的,以了解肌肉的行为在一些疾病或疲劳的研究。虽然需要复杂的设备和算法,但可以使用更简单的技术获取信息。所开发的原型具有高共模抑制(CMR)、高耦合阻抗、高增益和2级有源滤波器等特征。此外,模拟到数字的转换是通过一个ADC Delta-Sigma转换器进行的。此外,我们提出了一种分解算法,分为预处理、分割、聚类、分类和空间过滤5个阶段。我们成功地获得了表面肌电信号,并检测了相同运动单元(MU)的运动单元动作电位(MUAPs),它们之间的相似性超过80%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design and construction of a low cost prototype for lecture and processing of electromyographic signals using multichannel techniques and spatial filtering
The electromyographic (EMG) signals analysis is imperative to understand the muscles behaviour under several diseases or fatigue studies. Although there are required sophisticated devices and algorithms, it is possible to obtain information using simpler techniques. The prototype that was developed has features for sEMG recording, such as high common mode reject (CMR), high coupling impedance, high gain and 2 stages of active filters. Besides, the analog to digital conversion is performed with an ADC Delta-Sigma converter. Besides, we propose a decomposition algorithm with 5 stages: pre-processing, segmentation, clustering, classification and a spatial filtering stage. We obtained successfully sEMG signals and we detect Motor Unit Action Potentials (MUAPs) of the same Motor Unit (MU) with a similarity over 80% between them.
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