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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