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一种新型的超声透明电极系统,用于同时检测骨骼肌的肌电活动和 B 模式超声图像。

A novel system of electrodes transparent to ultrasound for simultaneous detection of myoelectric activity and B-mode ultrasound images of skeletal muscles.

机构信息

Laboratorio di Ingegneria del Sistema Neuromuscolare, Dipartimento di Elettronica e Telecomunicazioni, Politecnico di Torino, Italy;

出版信息

J Appl Physiol (1985). 2013 Oct 15;115(8):1203-14. doi: 10.1152/japplphysiol.00090.2013. Epub 2013 Aug 1.

DOI:10.1152/japplphysiol.00090.2013
PMID:23908313
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC3798813/
Abstract

Application of two-dimensional surface electrode arrays can provide a means of mapping motor unit action potentials on the skin surface above a muscle. The resulting muscle tissue displacement can be quantified, in a single plane, using ultrasound (US) imaging. Currently, however, it is not possible to simultaneously map spatio-temporal propagation of activation and resulting tissue strain. In this paper, we developed and tested a material that will enable concurrent measurement of two-dimensional surface electromyograms (EMGs) with US images. Specific protocols were designed to test the compatibility of this new electrode material, both with EMG recording and with US analysis. Key results indicate that, for this new electrode material, 1) the electrode-skin impedance is similar to that of arrays of electrodes reported in literature; 2) the reflection of US at the electrode-skin interface is negligible; 3) the likelihood of observing missing contacts, short-circuits, and artifacts in EMGs is not affected by the US probe; 4) movement of tissues sampled by US can be tracked accurately. We, therefore, conclude this approach will facilitate multimodal imaging of muscle to provide new spatio-temporal information regarding electromechanical function of muscle. This is relevant to basic physiology-biomechanics of active and passive force transmission through and between muscles, of motor unit spatio-temporal activity patterns, of their variation with architecture and task-related function, and of their adaptation with aging, training-exercise-disuse, neurological disease, and injury.

摘要

二维表面电极阵列的应用可以提供一种在肌肉上方的皮肤表面上绘制运动单位动作电位的方法。通过超声(US)成像,可以在单个平面上对产生的组织位移进行定量。然而,目前还不可能同时对激活的时空传播和产生的组织应变进行映射。在本文中,我们开发并测试了一种材料,该材料将使二维表面肌电图(EMG)与 US 图像的同时测量成为可能。专门设计了特定的协议来测试这种新电极材料与 EMG 记录和 US 分析的兼容性。主要结果表明,对于这种新的电极材料,1)电极-皮肤的阻抗与文献中报道的电极阵列相似;2)电极-皮肤界面的 US 反射可以忽略不计;3)观察到 EMG 中缺失接触、短路和伪影的可能性不受 US 探头的影响;4)可以准确跟踪 US 采样的组织运动。因此,我们得出结论,这种方法将促进肌肉的多模态成像,为肌肉的机电功能提供新的时空信息。这与肌肉内和肌肉间主动和被动力传递的基本生理学-生物力学、运动单位时空活动模式、它们与结构和与任务相关的功能的变化以及它们与衰老、训练-运动-停用、神经疾病和损伤的适应有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/d5e69592425e/zdg0201307900007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/bb9d3ef5d318/zdg0201307900001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/3989e981df9b/zdg0201307900002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/b2fa4f1d29f0/zdg0201307900003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/c3e7da00541a/zdg0201307900004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/ec1bbd48a481/zdg0201307900005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/937ea8c05441/zdg0201307900006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/d5e69592425e/zdg0201307900007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/bb9d3ef5d318/zdg0201307900001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/3989e981df9b/zdg0201307900002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/b2fa4f1d29f0/zdg0201307900003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/c3e7da00541a/zdg0201307900004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/ec1bbd48a481/zdg0201307900005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/937ea8c05441/zdg0201307900006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/484f/3798813/d5e69592425e/zdg0201307900007.jpg

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The effect of external compression on the mechanics of muscle contraction.外部压迫对肌肉收缩力学的影响。
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Automated regional analysis of B-mode ultrasound images of skeletal muscle movement.
超声图像序列的前景检测分析可识别出与运动神经元病相关的骨骼肌标志物。
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