Robot-assisted rehabilitation of gait still faces many challenges, one of which is improving physical human-robot interaction. The use of pleated pneumatic artificial muscles to power a step rehabilitation robot has the potential to meet this challenge. This paper reports on the development of a gait rehabilitation exoskeleton with a knee joint powered by pleated pneumatic artificial muscles. It is intended as a platform for the evaluation of design and control concepts in view of improved physical human-robot interaction. The design was focused on the optimal dimensioning of the actuator configuration. Safety being the most important prerequisite, a proxy-based sliding mode controller (PSMC) was implemented as it combines accurate tracking during normal operation with a smooth, slow and safe recovery from large position errors. Treadmill walking experiments of a healthy subject wearing the powered exoskeleton show the potential of PSMC as a safe robot-in-charge control strategy for robot-assisted gait training.

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One of the approaches to study the human motor system, and specifically the motor strategies implied during postural tasks of the upper limbs, is to manipulate the mechanical conditions of each joint of the upper limbs independently. At the same time, it is essential to pick up biomechanical signals and bio-potentials generated while the human motor system adapts to the new condition. The aim of this paper is two-fold: first, to describe the design, development and validation of an experimental platform designed to modify or perturb the mechanics of human movement, and simultaneously acquire, process, display and quantify bioelectric and biomechanical signals; second, to characterise the dynamics of the elbow joint during postural control. A main goal of the study was to determine the feasibility of estimating human elbow joint dynamics using EMG-data during maintained posture. In particular, the experimental robotic platform provides data to correlate electromyographic (EMG) activity, kinetics and kinematics information from the upper limb motion. The platform aims consists of an upper limb powered exoskeleton, an EMG acquisition module, a control unit and a software system. Important concerns of the platform such as dependability and safety were addressed in the development. The platform was evaluated with 4 subjects to identify, using system identification methods, the human joint dynamics, i.e. visco-elasticity. Results obtained in simulations and experimental phase are introduced.

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In this paper we describe the design and evaluation of a passive lower limb assistive exoskeleton based on omnidirectional rehabilitation vehicle. According to the leg dynamics during assisted walking, we optimize the design parameters to make the lower limb obtain the most positive energy. We employ MACCEPA (mechanically adjustable compliance and controllable equilibrium position actuator) in design which generates the constant torque in knee joint. Experiments were performed on injured people and their results verify the system effect in reducing physical power.

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Robotic rehabilitation for physical therapy has several advantages over conventional manual rehabilitation, especially in the aspects of accuracy and repeatability. Initial attempts at robotic rehabilitation focused on training muscles by moving limbs in a fixed repetitive pattern. Later it was realized that such an approach could be suboptimal. Better approach would be the use of ‘assist-as-needed’ paradigm, where an orthotic device provides just enough assistance to enable the patient to move his leg under his own control. However, at this time, lower extremity devices which can apply appropriate forces to implement this paradigm are still in research and not commercially available. The goal of this work is to develop lower extremity orthotic devices using assist-as-needed paradigm for robotic rehabilitation. To achieve this goal two orthotic devices were developed. They are Gravity Balancing leg Orthosis (GBO) and Active Leg EXoskeleton (ALEX).

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This paper presents the design, control and performance of a high fidelity four degree-of-freedom wrist exoskeleton robot, RiceWrist, for training and rehabilitation. The RiceWrist is intended to provide kinesthetic feedback during the training of motor skills or rehabilitation of reaching movements. Motivation for such applications is based on findings that show robot-assisted physical therapy aids in the rehabilitation process following neurological injuries. The exoskeleton device accommodates forearm supination and pronation, wrist flexion and extension and radial and ulnar deviation in a compact parallel mechanism design with low friction, zero backlash and high stiffness. As compared to other exoskeleton devices, the RiceWrist allows easy measurement of human joint angles and independent kinesthetic feedback to individual human joints. In this paper, joint-space as well as task-space position controllers and an impedance-based force controller for the device are presented. The kinematic performance of the device is characterized in terms of its workspace, singularities, manipulability, backlash and backdrivability. The dynamic performance of RiceWrist is characterized in terms of motor torque output, joint friction, step responses, behavior under closed loop set-point and trajectory tracking control and display of virtual walls. The device is singularity-free, encompasses most of the natural workspace of the human joints and exhibits low friction, zero-backlash and high manipulability, which are kinematic properties that characterize a high-quality impedance display device. In addition, the device displays fast, accurate response under position control that matches human actuation bandwidth and the capability to display sufficiently hard contact with little coupling between controlled degrees-of-freedom.

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