Grip Force and 3D Push-Pull Force Estimation Based on sEMG and GRNN.

Changcheng Wu,Aiguo Song,Baoguo Xu,Hong Zeng

doi:10.3389/fnins.2017.00343

Abstract

The estimation of the grip force and the 3D push-pull force (push and pull force in the three dimension space) from the electromyogram (EMG) signal is of great importance in the dexterous control of the EMG prosthetic hand. In this paper, an action force estimation method which is based on the eight channels of the surface EMG (sEMG) and the Generalized Regression Neural Network (GRNN) is proposed to meet the requirements of the force control of the intelligent EMG prosthetic hand. Firstly, the experimental platform, the acquisition of the sEMG, the feature extraction of the sEMG and the construction of GRNN are described. Then, the multi-channels of the sEMG when the hand is moving are captured by the EMG sensors attached on eight different positions of the arm skin surface. Meanwhile, a grip force sensor and a three dimension force sensor are adopted to measure the output force of the human's hand. The characteristic matrix of the sEMG and the force signals are used to construct the GRNN. The mean absolute value and the root mean square of the estimation errors, the correlation coefficients between the actual force and the estimated force are employed to assess the accuracy of the estimation. Analysis of variance (ANOVA) is also employed to test the difference of the force estimation. The experiments are implemented to verify the effectiveness of the proposed estimation method and the results show that the output force of the human's hand can be correctly estimated by using sEMG and GRNN method.

Highlights

Prosthetic hand is a kind of human-machine interface
In order to meet the requirements of the dexterous control of the prosthetic hand, the paper proposes a force estimation method of hand movement based on the surface EMG (sEMG) and Generalized Regression Neural Network (GRNN)
An experimental platform is set up to measure the multi-channels of the sEMG signals, the grip force and the 3D push-pull force

Summary

Introduction

Prosthetic hand is a kind of human-machine interface. The upper limb amputees can recover some hand function with the help of the prosthetic hand. Force Estimation of Hand Movement controlled by the amputee’s EMG signals. Where, φ is the non-linear function, X are the EMG signals measured from the arm skin surface, F is the force output by the hand.

Results

Conclusion