Processing signals from surface electrode arrays for noninvasive 3D mapping of muscle activity

R. Jesinger, V. Stonick
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引用次数: 14

Abstract

This paper presents a new technique for reconstruction and imaging of volumetric neuromuscular activity using digital signal processing of multichannel surface potential recordings. We use magnetic resonance images to model anatomical structures with finite element analysis and to quantify material properties within the inhomogeneous volume. Time-frequency distributions of the multichannel EMG array data decompose the broadband source localization problem into a narrowband framework. Poisson's equation is then solved using finite element methods coupled with signal processing estimation techniques to localize neuromuscular activity. This new imaging tool can be used to enhance clinical diagnosis of neuromuscular disorders and to improve understanding of human locomotion for biomechanics and robotics.<>
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处理来自表面电极阵列的信号,用于肌肉活动的非侵入性3D映射
本文提出了一种利用多通道表面电位记录的数字信号处理来重建和成像体积神经肌肉活动的新技术。我们使用磁共振图像模拟解剖结构与有限元分析,并量化材料性质在非均匀体积。多通道肌电阵列数据的时频分布将宽带源定位问题分解为一个窄带框架。然后用有限元方法结合信号处理估计技术求解泊松方程,以定位神经肌肉活动。这种新的成像工具可用于增强神经肌肉疾病的临床诊断,并提高对生物力学和机器人技术的人类运动的理解。
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