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Gait and balance training is an essential ingredient for locomotor rehabilitation of patients with neurological impairments. Robotic overhead support systems may help these patients train, for example by relieving them of part of their body weight. However, there are only very few systems that provide support during overground gait, and these suffer from limited degrees of freedom and/or undesired interaction forces due to uncompensated robot dynamics, namely inertia. Here, we suggest a novel mechanical concept that is based on cable robot technology and that allows three-dimensional gait training while reducing apparent robot dynamics to a minimum. The solution does not suffer from the conventional drawback of cable robots, which is a limited workspace. Instead, displaceable deflection units follow the human subject above a large walking area. These deflection units are not actuated, instead they are implicitly displaced by means of the forces in the cables they deflect. This leads to an underactuated design, because the deflection units cannot be moved arbitrarily. However, the design still allows accurate control of a three-dimensional force vector acting on a human subject during gait. We describe the mechanical concept, the control concept, and we show first experimental results obtained with the device, including the force control performance during robot-supported overground gait of five human subjects without motor impairments

Adaptive position anticipation in a support robot for overground gait training enhances transparency

Rehabilitation robots being developed nowadays rely on force and/or impedance control. This is guided by clinical evidence showing better performance if the patient is left with the capacity to influence the robot trajectory. The simplest, yet fundamental, mode of force control is when the robot has to be transparent, i.e. to apply no forces/torques on the patient. This mode is useful both in scenarios where the robot has to apply pinpointed support during some training phases and be transparent otherwise, and for any force controller in general, to avoid the reference forces to be polluted by the robot own dynamics. This contribution proposes a method to improve transparency on a support robot for overground training. The method consists in learning the patient's movement by using adaptive oscillators and then anticipate its future evolution in order to synchronize the robot movement. In experiments with human subjects walking in the gait support robot FLOAT, this method can decrease the undesired oscillations of the support force applied to the human user by up to 50%. © 2013 IEEE