基于运动单元的肌肉力估计新方法

A New Muscle Force Estimation Method Based on Motor Unit

目的从肌肉运动单元角度探索肌肉力与表面肌电信号(surface electromyoram,s EMG)的规律。方法首先利用梯度卷积核补偿算法(gradient convolution kernel compensation,GCKC)对实验采集得到的s EMG信号进行分解,然后采用棘波触发技术(spike triggered averaging,STA)提取运动单元MU波形,最后基于MU波形,运用最小二乘法拟合肌肉力,建立肌肉力与s EMG之间的关系。结果肌肉运动单元募集数目与幅值和基本上随肌肉力增大而增大,运动单元平均发放频率随肌肉力增大规律不明显。结论本文为肌肉力的估计提供了一种新思路,从肌肉运动单元幅值之和来估计肌肉力基本可行。

Objective To develop the relationship between muscle force and surface electromyogram（ s EMG）based on muscle motor unit. Methods First,the s EMG signals from experiments were decomposed using GCKC（ gradient convolution kernel compensation）,then MU waveform was extracted using STA（ spike triggered averaging）,finally the muscle forces were fitted to discuss the relationship between muscle force and s EMG with the application of the least squares method. Results According to the analysis results,the number of motor unit recruitment and the sum of amplitude increased basically with the muscle force,while average firing frequency change was not obvious with muscle force. Conclusion This paper provides a new idea for muscle force estimation,and it is feasible to estimate muscle force by using the amplitude sum of muscle motor units.