Aug 2026· 2026 IEEE International Conference on Mechatronics and Automation (ICMA)· pp. 2102-2107· 0 citations· 22 references
Abstract
To address the coupling between ambiguous sEMG-based intention recognition and mechanical safety constraints in cable-driven lower-limb rehabilitation, this study proposes a multimodal perception-based adaptive admittance control framework. Mechanical, interaction, and physiological indicators, including stiffness, end-effector position, coupling force, velocity, joint motion, and sEMG, were fused to estimate active participation, passive/flaccid tracking, and spasticity risk. The identified state was then used to adjust admittance parameters online, while an RBFNN-SMC inner loop improved trajectory tracking. Experiments showed high-damping, low-stiffness protection during spasticity bursts and milder responses during passive conditions. Compared with PID, RBFNN-SMC reduced tracking errors, supporting safer adaptive rehabilitation control.
Home-based rehabilitation exoskeletons often suffer from control instability due to low-cost force sensors. This paper presents a robust, sensorless Composite Variable Impedance Control architecture that separates trajectory tracking (virtual stiffness K) from active assistance (adaptive feedforward torque τassist). By...
Jun Leng, Pengcheng Li, Hanze Wang et al.· 2026 IEEE International Conf...· 0 citations
This study proposes a composite control framework for upper-limb rehabilitation exoskeletons integrating fractional-order impedance control, computed-torque compensation, and a momentum-based nonlinear disturbance observer that enhances compliant yielding and tracking robustness under non-ideal dynamics.
Chun Liu, Xin-Rong Liu, Yuhang Xue· Computer Methods in Biomecha...· 0 citations
This paper presents a wrist rehabilitation robot based on a 3R spherical linkage and proposes a multimodal human–robot interaction (HRI) control method integrating surface electromyography (sEMG) and force sensing. The proposed robot provides three degrees of freedom (DoFs) of posture adjustment for wrist rehabilitatio...
Zeyi Huang, Qi-Zhou Guo, Qing-Lei Wang et al.· 2026 IEEE International Conf...· 0 citations
Knee rehabilitation robots can effectively assist the recovery of patients with lower limb motor dysfunction. This paper presents a lightweight single-drive adaptive knee rehabilitation robot for supine training. The robot consists of a waist support, a thigh mechanism, and a shank-foot mechanism, and provides continuo...
Mei Feng, Xiang Chen, Chao Han et al.· 2026 IEEE International Conf...· 0 citations
The proposed BS–ST-SMC architecture outperforms classical and traditional robust approaches, particularly in mitigating chattering and managing human–robot interaction uncertainties, particularly in mitigating chattering and managing human–robot interaction uncertainties.
Yukio Rosales-Luengas, Sergio Salazar, Saúl J. Rangel-Popoca et al.· Electronics· 0 citations
The findings indicate that integrating reinforcement learning with Sigmoid parameter adaptation provides a systematic and effective solution for adaptive compliance regulation in mobile exoskeleton systems, enhancing adaptability, safety, and functional relevance for stroke patients undergoing lower limb rehabilitation...
