sEMG-based variable impedance control of lower-limb rehabilitation robot using wavelet neural network and model reference adaptive control

Abstract

Purpose This paper aims to propose an innovative adaptive control method for lower-limb rehabilitation robots. Design/methodology/approach Despite carrying out various studies on the subject of rehabilitation robots, the flexibility and stability of the closed-loop control system is still a challenging problem. In the proposed method, surface electromyography (sEMG) and human force-based dual closed-loop control strategy is designed to adaptively control the rehabilitation robots. A motion analysis of human lower limbs is performed by using a wavelet neural network (WNN) to obtain the desired trajectory of patients. In the outer loop, the reference trajectory of the robot is modified by a variable impedance controller (VIC) on the basis of the sEMG and human force. Thenceforward, in the inner loop, a model reference adaptive controller with parameter updating laws based on the Lyapunov stability theory forces the rehabilitation robot to track the reference trajectory. Findings The experiment results confirm that the trajectory tracking error is efficiently decreased by the VIC and adaptively correct the reference trajectory synchronizing with the patients’ motion intention; the model reference controller is able to outstandingly force the rehabilitation robot to track the reference trajectory. The method proposed in this paper can better the functioning of the rehabilitation robot system and is expandable to other applications of the rehabilitation field. Originality/value The proposed approach is interesting for the design of an intelligent control of rehabilitation robots. The main contributions of this paper are: using a WNN to obtain the desired trajectory of patients based on sEMG signal, modifying the reference trajectory by the VIC and using model reference control to force rehabilitation robot to track the reference trajectory.

[Retracted] Analysis of Landscape Ecological Planning Based on the High‐Order Multiwavelet Neural Network Algorithm

“…The results show that the predicted value of the RF-WNN model is very close to the actual value. Hasanzadeh Fereydooni et al [ 10 ] used the wavelet neural network to obtain the expected trajectory of patients based on the sEMG signal and then guided the intelligent control design of the rehabilitation robot.…”

Feature Extraction and Classification of Lower Limb Motion Based on sEMG Signals

“…Since the WNN and BPNN were common methods of the sEMG signal recognition research [24], [26,27], We used the WNN and BPNN to classify the five movements of the lower limb. The classification accuracy was shown in Figure 9.…”

“…The sEMG signals have complex nonlinearity, strong coupling, and dynamic timevarying characteristics [23]. Researchers have mainly studied linear discriminant analysis, bayesian networks, neural networks, multilayer perceptrons, fuzzy approximation, support vector machines, fuzzy neural systems, backpropagation neural networks, and wavelet neural network classification methods [24][25][26][27]. Since the neural network has strong nonlinear approximation performance and the ability to handle unknown internal mechanism problems [28,29], which is suitable for complex lower limb motion classification.…”

Adaptive enhanced admittance force-tracking controller design for highly dynamic interactive tasks

“…With the development of robotics, the contact process control between robot end-effector and the environment is becoming an important part of robotic applications involving, surface handling (such as polishing (Cao et al , 2020; Kana et al , 2021; Lakshminarayanan et al , 2021; Ochoa and Cortesao, 2021), medical rehabilitation physiotherapy (Ajani and Assal, 2020; Hasanzadeh Fereydooni et al , 2020; Zhang et al , 2020; Ajani and Assal, 2021) and physical human–robot interaction (Keemink et al , 2018; Ferraguti et al , 2019; Mustafa Can Bingol and Aydogmus, 2020b; Mustafa Can Bingol and Aydogmus, 2020a; Sharifi et al , 2021). The main problem of contact establishment involves the scale of contact force, which may reach prohibitive value, which may directly lead to mission failure or even more serious consequences.…”