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两个自由度,动态,使用最少数量电极的手腕肌电图-力

Two degrees of freedom, dynamic, hand-wrist EMG-force using a minimum number of electrodes.

作者信息

Dai Chenyun, Zhu Ziling, Martinez-Luna Carlos, Hunt Thane R, Farrell Todd R, Clancy Edward A

机构信息

Department of Electrical Engineering, Fudan University, Shanghai, China.

Worcester Polytechnic Institute, Worcester, MA 01609, USA.

出版信息

J Electromyogr Kinesiol. 2019 Aug;47:10-18. doi: 10.1016/j.jelekin.2019.04.003. Epub 2019 Apr 16.

Abstract

Few studies have related the surface electromyogram (EMG) of forearm muscles to two degree of freedom (DoF) hand-wrist forces; ones that have, used large high-density electrode arrays that are impractical for most applied biomechanics research. Hence, we researched EMG-force in two DoFs-hand open-close paired with one wrist DoF-using as few as four conventional electrodes, comparing equidistant placement about the forearm to optimized site selection. Nine subjects produced 1-DoF and 2-DoF uniformly distributed random forces (bandlimited to 0.75 Hz) up to 30% maximum voluntary contraction (MVC). EMG standard deviation (EMGσ) was related to force offline using linear dynamic regression models. For 1-DoF forces, average RMS errors using two optimally-sited electrodes ranged from 8.3 to 9.0 %MVC, depending on the DoF. For 2-DoFs, overall performance was best when training from both 1- and 2-DoF trials, giving average RMS errors using four optimally-sited electrodes of 9.2 %MVC for each DoF pair (hand open-close paired with one wrist DoF). For each model, additional optimally-sited electrodes showed little statistical improvement. Electrodes placed equidistant performed noticeably poorer than an equal number of electrodes that were optimally sited. The results suggest that reliable 2-DoF hand-wrist EMG-force with a small number of electrodes may be feasible.

摘要

很少有研究将前臂肌肉的表面肌电图(EMG)与双自由度(DoF)的手腕力联系起来;已有的相关研究使用的是大型高密度电极阵列,这对于大多数应用生物力学研究来说并不实用。因此,我们使用最少四个传统电极,研究了双自由度(一个是手部开合,另一个是一个手腕自由度)下的肌电图与力的关系,并将前臂上等距放置电极与优化电极位置选择进行了比较。九名受试者产生了单自由度和双自由度的均匀分布随机力(带宽限制在0.75赫兹),最大可达最大自主收缩(MVC)的30%。使用线性动态回归模型离线将肌电图标准差(EMGσ)与力相关联。对于单自由度力,根据自由度不同,使用两个最佳位置电极时的平均均方根误差范围为MVC的8.3%至9.0%。对于双自由度,当同时从单自由度和双自由度试验进行训练时,整体性能最佳,对于每个自由度对(手部开合与一个手腕自由度配对),使用四个最佳位置电极时的平均均方根误差为每个自由度对MVC的9.2%。对于每个模型,额外的最佳位置电极在统计学上几乎没有改善。等距放置的电极表现明显比相同数量的最佳位置电极差。结果表明,用少量电极实现可靠的双自由度手腕肌电图测力可能是可行的。

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1
The effect of time on EMG classification of hand motions in able-bodied and transradial amputees.
J Electromyogr Kinesiol. 2018 Jun;40:72-80. doi: 10.1016/j.jelekin.2018.04.004. Epub 2018 Apr 17.
2
Real-time robustness evaluation of regression based myoelectric control against arm position change and donning/doffing.
PLoS One. 2017 Nov 2;12(11):e0186318. doi: 10.1371/journal.pone.0186318. eCollection 2017.
3
Two degrees of freedom quasi-static EMG-force at the wrist using a minimum number of electrodes.
J Electromyogr Kinesiol. 2017 Jun;34:24-36. doi: 10.1016/j.jelekin.2017.03.004. Epub 2017 Mar 29.
4
Comparison of Constant-Posture Force-Varying EMG-Force Dynamic Models About the Elbow.
IEEE Trans Neural Syst Rehabil Eng. 2017 Sep;25(9):1529-1538. doi: 10.1109/TNSRE.2016.2639443. Epub 2016 Dec 14.
5
Evaluation of Linear Regression Simultaneous Myoelectric Control Using Intramuscular EMG.
IEEE Trans Biomed Eng. 2016 Apr;63(4):737-46. doi: 10.1109/TBME.2015.2469741. Epub 2015 Aug 20.
6
Context-Dependent Upper Limb Prosthesis Control for Natural and Robust Use.
IEEE Trans Neural Syst Rehabil Eng. 2016 Jul;24(7):744-53. doi: 10.1109/TNSRE.2015.2454240. Epub 2015 Jul 9.
7
Influence of Joint Angle on EMG-Torque Model During Constant-Posture, Torque-Varying Contractions.
IEEE Trans Neural Syst Rehabil Eng. 2015 Nov;23(6):1039-46. doi: 10.1109/TNSRE.2015.2405765. Epub 2015 Feb 20.
8
Channel selection for simultaneous and proportional myoelectric prosthesis control of multiple degrees-of-freedom.
J Neural Eng. 2014 Oct;11(5):056008. doi: 10.1088/1741-2560/11/5/056008. Epub 2014 Aug 1.
9
Using the electromyogram to anticipate torques about the elbow.
IEEE Trans Neural Syst Rehabil Eng. 2015 May;23(3):396-402. doi: 10.1109/TNSRE.2014.2331686. Epub 2014 Jun 30.
10
Enhanced dynamic EMG-force estimation through calibration and PCI modeling.
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