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Analysis of Muscle Synergy for Grip and Pinch Based on Recurrence Networks

机译:基于递归网络的握力和捏力肌肉协同作用分析

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The purpose of this study is to examine the muscle synergy during grip and pinch using recurrence networks (RNs). Twenty-four right-handed healthy young subjects participated in the experiment. The grip force and pinch force of the dominant hand were examined, during which the surface electromyographic (sEMG) signals were recorded from brachioradialis (BR), flexor carpi ulnaris (FCU), flexor carpi radialis (FCR), extensor digitorum communis (EDC), flexor digitorum superficialis (FDS), abductor pollicis brevis (APB), first dorsal interosseous (FDI) and abductor digiti minimi (ADM) of the dominant hand. The RNs were constructed based on the time series of sEMG signals. Two parameters-the average shortest path length ($mathcal{L}$) and the clustering coefficient ($mathcal{C}$) - were achieved from the RNs to analyze the sEMG. Results showed higher $mathcal{C}$ but lower $mathcal{L}$ in BR, FCU and FCR during grip than during pinch. In contrast, the FDI showed lower $mathcal{C}$ but higher $mathcal{L}$ during grip than during pinch. Significant differences of the two parameters were found among the three force levels in the BR, FCU, FCR. With increased force, the muscle networks of BR, FCU and FCR showed increases in $mathcal{C}$ or decreases in $mathcal{L}$. Our study suggests different muscle synergies between grip and pinch, and the extrinsic muscles play an important role in synergistic force production, the intrinsic muscles are performed well in fingers control for motor fine tasks. In addition, synergistic muscles will further coordinate in timing and strength with the force level increased. This finding might provide insights into the dynamical coordination across muscles with the force outputs and supply novel strategy for evaluating the neuromuscular function and making of the myoelectric prosthesis.
机译:本研究的目的是使用复制网络(RNS)在抓地力和捏合期间检查肌肉协同作用。二十四名右手健康的年轻科目参加了实验。检查了优势手的抓握力和夹紧力,在此期间从Brachioradialis(BR),屈肌Carpi ulnaris(FCU),屈肌Carpi Radialis(FCR),伸展位数字(EDC)中记录表面电偏振(SEMG)信号,屈肌Dietotorum Supervicialis(FDS),Abductor Pollicis Brevis(APB),首要手的第一背孔(FDI)和Abductor Digiti Minimi(ADM)。基于SEMG信号的时间序列构建RN。两个参数 - 平均最短路径长度( $ \ mathcal {l} $ )和聚类系数( $ \ mathcal {c} $ ) - 从RNS实现以分析SEMG。结果显示出更高 $ \ mathcal {c} $ 但是 $ \ mathcal {l} $ 在GR,FCU和FCR期间夹持在夹持期间。相比之下,FDI显示出较低 $ \ mathcal {c} $ 但更高 $ \ mathcal {l} $ 在抓地夹在夹持期间。在BR,FCU,FCR中的三个力水平中发现了两个参数的显着差异。随着力量增加,BR,FCU和FCR的肌肉网络表现出增加 $ \ mathcal {c} $ 或减少 $ \ mathcal {l} $ 。我们的研究表明,在协同力产量中,外在肌肉在协同力生产中发挥着重要作用,在手指控制中对电机精度控制进行了很​​好的表现。此外,协同肌肉将进一步坐标,力量水平增加。这一发现可能会对肌肉的动力输出和供应新策略进行评估,以评估神经肌肉假体的态度和供应新策略提供洞察力。

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