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Abstract: Robot assisted gait training may help in producing rapid improvements in functional gait parameters. This paper presents new experimental results with an intrinsically compliant robotic gait training orthosis. The newly developed robotic orthosis has 6 degrees of freedom (DOFs). A trajectory tracking controller based on the boundary layer augmented sliding control (BASMC) law was implemented to guide the subject’s limbs on physiological gait trajectories. The compliance of the robotic orthosis sagittal plane hip and knee joints was also controlled, independently of the trajectory tracking control. The robotic orthosis and the control scheme were evaluated on three neurologically intact subjects walking on a treadmill. A maximum trajectory tracking error of 10° was recorded at the hip and knee sagittal plane joints. The results showed that subjects can walk in the robotic orthosis with comfort and the BASMC law was able to guide the subject’s limbs on reference physiological trajectories. [Copyright &y& Elsevier]

The novelty of this paper is the adjustable workspace and torque capacity of a compliant ankle rehabilitation robot (CARR). The robot has three rotational degrees of freedom (DOFs) redundantly actuated by four compliant actuators. It suffers from conflicting workspace and actuation torque due to the use of a parallel mechanism and compliant actuators. To address this issue, also considering physical constraints imposed by human users, the CARR is designed with reconfigurability to make a trade-off between workspace and torque capacity for meeting different training requirements. Theoretical analysis indicates that varying kinematic and dynamic performance of the robot can be achieved by reconfiguring the layout of the actuators. Experiments with/without load also demonstrate the validity of the reconfigurable robotic design for practical applications. [ABSTRACT FROM AUTHOR]

This paper proposes a new robot-assisted bilateral upper limb training strategy, focusing on the bilateral coordination of users' upper limbs. The strategy is implemented and evaluated on a bilateral upper limb rehabilitation device (BULReD) that is an H-bot mechanism actuated by two Maxon DC motors. The control system consists of a position controller, an admittance controller and an adaptive algorithm, where the BULReD stiffness is modified session by session based on training performance. This strategy is also integrated with subject-specific workspace for enhanced training safety. Experiments were carried out with five subjects through active reaching tasks. Results indicate that the proposed training strategy requires significant coordination of bilateral upper limbs for task completion, and is able to tune control parameters to an appropriate difficulty level based on participants' training performance. Future work will focus on its clinical evaluation on patients with upper limb disabilities. • A robot-assisted bilateral upper limb coordination training strategy. • The strategy enables subject-specific workspace determination. • Experimental results support its potential for upper limb coordination training. [ABSTRACT FROM AUTHOR]