sEMG-based shoulder-elbow composite motion pattern recognition and control methods for upper limb rehabilitation robot
ISSN: 0144-5154
Article publication date: 16 October 2018
Issue publication date: 14 August 2019
Abstract
Purpose
This paper aims to develop a signal acquisition system of surface electromyography (sEMG) and use the characteristics of (sEMG) signal to interference action pattern.
Design/methodology/approach
This paper proposes a fusion method based on combining the coefficient of AR model and wavelet coefficient. It improves the recognition rate of the target action. To overcome the slow convergence speed and local optimum in standard BP network, the study presents a BP algorithm which combine with LM algorithm and PSO algorithm, and it improves the convergence speed and the recognition rate of the target action.
Findings
Experiments verify the effectiveness of the system from two aspects the target motion recognition rate and the corresponding reaction speed of the robotic system.
Originality/value
The study developed a signal acquisition system of sEMG and used the characteristics of (sEMG) signal to interference action pattern. The myoelectricity integral values are presented to determine the starting point and end point of target movement, which is more effective than using single sample point amplitude method.
Keywords
Citation
Zhang, X., Dai, J., Li, X., Li, H., Fu, H., Pan, G., Zhang, N., Yang, R. and Xu, J. (2019), "sEMG-based shoulder-elbow composite motion pattern recognition and control methods for upper limb rehabilitation robot", Assembly Automation, Vol. 39 No. 3, pp. 394-400. https://doi.org/10.1108/AA-11-2017-148
Publisher
:Emerald Publishing Limited
Copyright © 2018, Emerald Publishing Limited