A Multi-Mode Rehabilitation Robot With Magnetorheological Actuators Based on Human Motion Intention Estimation

Xu, Jiajun; Li, Youfu; Xu, Linsen; Chen, Peng; Chen, Shouqi; Liu, Jinfu; Xu, Chanchan; Cheng, Guiguang; Xu, Haiqing; Liu, Yang; Chen, Jian

doi:10.1109/tnsre.2019.2937000

Cited by 54 publications

(42 citation statements)

References 26 publications

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“…Whereas in the human-active mode, the human leg dominantly guides the movement of the robotic exoskeleton, and the MR actuator functions as a brake to help the user conduct anti-resistance training to strengthen muscles. Switching between these modes is allowed based on the user’s motion intention (Xu et al , 2019c, 2019a). In this mirror therapy framework, the MR actuators set at the leader robot work in the human-active mode and the MR actuators equipped at the follower exoskeleton are tuned to the robot-active mode.…”

Section: Methodsmentioning

confidence: 99%

A robotic system with reinforcement learning for lower extremity hemiparesis rehabilitation

Cheng

et al. 2021

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Purpose This paper aims to propose a bilateral robotic system for lower extremity hemiparesis rehabilitation. The hemiplegic patients can complete rehabilitation exercise voluntarily with the assistance of the robot. The reinforcement learning is included in the robot control system, enhancing the muscle activation of the impaired limbs (ILs) efficiently with ensuring the patients’ safety. Design/methodology/approach A bilateral leader–follower robotic system is constructed for lower extremity hemiparesis rehabilitation, where the leader robot interacts with the healthy limb (HL) and the follow robot is worn by the IL. The therapeutic training is transferred from the HL to the IL with the assistance of the robot, and the IL follows the motion trajectory prescribed by the HL, which is called the mirror therapy. The model reference adaptive impedance control is used for the leader robot, and the reinforcement learning controller is designed for the follower robot. The reinforcement learning aims to increase the muscle activation of the IL and ensure that its motion can be mastered by the HL for safety. An asynchronous algorithm is designed by improving experience relay to run in parallel on multiple robotic platforms to reduce learning time. Findings Through clinical tests, the lower extremity hemiplegic patients can rehabilitate with high efficiency using the robotic system. Also, the proposed scheme outperforms other state-of-the-art methods in tracking performance, muscle activation, learning efficiency and rehabilitation efficacy. Originality/value Using the aimed robotic system, the lower extremity hemiplegic patients with different movement abilities can obtain better rehabilitation efficacy.

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Section: Methodsmentioning

confidence: 99%

A robotic system with reinforcement learning for lower extremity hemiparesis rehabilitation

Cheng

et al. 2021

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“…The MRB model is developed by following the behaviour trend of MRB that is gathered through experiment. The MR brake actuator model is developed based on the characteristics of the MR brake, where the brake torque increases proportionally with apply current and independent speed [30], [31], [32]. In this model, the actuator is designed based on rotational wheel speed, and it is assumed that the torque remains the same at all speed.…”

Section: Hardware and Testing Apparatusmentioning

confidence: 99%

The Magnetorheological Fluid: Testing on Automotive Braking System

Zainordin¹,

Mohamed²,

Ahmad³

2021

IJAME

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This paper presents the testing of a Magnetorheological brake (MRB) in the braking system of a vehicle. Two techniques are used to determine the capability of the brake system which are the simulation via Matlab Simulink Software and experimental study by using a quarter vehicle test rig. A Proportional-Integral-Derivative (PID) is employed as a wheel speed control as well as to enforce the MRB to produce the required braking torque need by a vehicle. A dynamic test, namely sudden braking test is performed in three rotational speed conditions which are from 127.5 rad/s (1200 rpm) to 31.42 rad/s (300 rpm), 52.37 Rad/s (500 rpm) and 73.31 rad/s (700 rpm) in two different wheel load which are 10 kg and 15 kg, respectively. The behaviours to be assessed are wheel speed response and brake torque produced by the MRB. From the observation, it is concluded that the capability of the MRB in providing the required brake torque is promising and harmony between simulation and experimental response.

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“…where N is the number of the MR fluid working gaps, and R 1 and R 2 are the effective inner and outer radii of the working gap, respectively. The electromagnetic simulation of the MR actuator is conducted to verify the rationality of the structural design (Xu et al, 2019). The material properties of each component are assigned.…”

Section: Magnetorheological Actuatormentioning

confidence: 99%

Robotic mirror therapy system for lower limb rehabilitation

Cheng

et al. 2020

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Purpose This paper aims to develop a robotic mirror therapy system for lower limb rehabilitation, which is applicable for different patients with individual movement disability levels. Design/methodology/approach This paper puts forward a novel system that includes a four-degree-of-freedom sitting/lying lower limb rehabilitation robot and a wireless motion data acquisition system based on mirror therapy principle. The magnetorheological (MR) actuators are designed and manufactured, whose characteristics are detected theoretically and experimentally. The passive training control strategy is proposed, and the trajectory tracking experiments verify its feasibility. Also, the active training controller that is adapt to the human motor ability is designed and evaluated by the comparison experiments. Findings The MR actuators produce continuously variable and compliant torque for robotic joints by adjusting excitation current. The reference limb joint position data collected by the wireless motion data acquisition system can be used as the motion trajectory of the robot to drive the affected limb. The passive training strategy based on proportional-integral control proves to have great trajectory tracking performance through experiments. In the active training mode, by comparing the real-time parameters adjustment in two phases, it is certified that the proposed fuzzy-based regulated impedance controller can adjust assistance torque according to the motor ability of the affected limb. Originality/value The system developed in this paper fulfills the needs of robot-assisted mirror therapy for hemiplegic patients.

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A Multi-Mode Rehabilitation Robot With Magnetorheological Actuators Based on Human Motion Intention Estimation

Cited by 54 publications

References 26 publications

A robotic system with reinforcement learning for lower extremity hemiparesis rehabilitation

A robotic system with reinforcement learning for lower extremity hemiparesis rehabilitation

The Magnetorheological Fluid: Testing on Automotive Braking System

Robotic mirror therapy system for lower limb rehabilitation

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