Adaptive gravity and joint stiffness compensation methods for force-controlled arm supports

People with muscular weakness can benefit from arm supports that compensate the weight of their arms. Due to the disuse of the arms, passive joint stiffness increases and providing only gravity compensation becomes insufficient to support the arm function. Hence, joint stiffness compensation is also required, for which the use of active arm supports is essential. Force-based control interfaces are a solution for the operation of arm supports. A critical aspect of force-based interfaces, to properly detect the movement intention of the user, is the ability to distinguish the voluntary forces from any other force, such as gravity or joint stiffness forces. Model- and calibration-based strategies for the estimation of gravity and joint stiffness forces lack adaptability and are time consuming since they are measurement dependent. We propose two simple, effective and adaptive methods for the compensation of forces resulting from gravity and joint stiffness. The compensation methods are based on the estimation of the ompensation force using a low-pass filter, and switching of control parameters using a finite state machine. The compensation methods were evaluated with an adult man suffering from Duchenne muscular dystrophy with very limited arm function. The results show that when gravity and joint stiffness forces were adaptively compensated the reachable workspace of the user was increased more than 50% compared to the workspace reached when only constant gravity compensation was provided.