Muscle weakness is one of the major deficits after stroke but specific strength training is seldom included in robot-assisted rehabilitation. At the same time, the emergence of robotic devices for stroke therapy offers technical possibilities for strength training. We propose a control strategy for strength training that is based on a viscous force field shaped towards the patient's performance abilities at different positions and directions during a movement. The controller was implemented in the arm rehabilitation robot ARMin in combination with a one-degree-of-freedom repetitive tracking task. The viscous force field is adapted in each round as a function of the local performance profile (shape) and the performance sum of each round (task level). The patient gets feedback by visual representation of the tracking task displaying the position of the moving target object and the position of the patient cursor. We hypothesize that the performance-shaped task level of the viscous force field demands the maximum effort of the participant at each point of the trajectory. Furthermore, we hypothesize that the participants are more motivated by this controller for strength training than by controllers using a constant task level. The controller was tested in a feasibility study with 31 healthy subjects. The resulting individual task level of the viscous force field increased compared to the initial state but did not reach a steady state by (visual inspection). No differences in motivation compared to a controller using a constant viscous force field were identified. We propose the framework of differentiation in shape and task level of a viscous force field for difficulty adaptation in future rehabilitation games.
['Kilian Baur', 'Verena Klamroth-Marganska', 'Chiara Giorgetti', 'Daniela Fichmann', 'Robert Riener']
Performance-based viscous force field adaptation in upper limb strength training for stroke patients