Our area of interest is robotic-based rehabilitation after stroke, and our goal is to help patients achieve optimal motor learning during high-intensity repetitive movement training through the assistance of robots. It is important, that the robotic assistance is adapted to the patients' abilities, thereby ensuring that the device is only supporting the patient as necessary ("assist-as-needed"). We hypothesize that natural and learning-effective human-machine interaction can be achieved by programming the robot's control, so that it emulates how a physiotherapist adaptively supports the patients' limb movement during stroke rehabilitation. This paper introduces the design of a novel interactive device Bi-Manu-Interact. This device is suited to be used as an experimental setup for the investigation of haptic human-human interaction and for collecting data to model therapists' haptic behavior. In this paper, we present mechanical and sensory specifications as well as tasks visualizations for future investigations. Results of a pilot clinical evaluation of the Bi-Manu-Interact with nine stroke patients are also presented in this work.
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http://dx.doi.org/10.1109/ICORR.2017.8009331 | DOI Listing |
Our area of interest is robotic-based rehabilitation after stroke, and our goal is to help patients achieve optimal motor learning during high-intensity repetitive movement training through the assistance of robots. It is important, that the robotic assistance is adapted to the patients' abilities, thereby ensuring that the device is only supporting the patient as necessary ("assist-as-needed"). We hypothesize that natural and learning-effective human-machine interaction can be achieved by programming the robot's control, so that it emulates how a physiotherapist adaptively supports the patients' limb movement during stroke rehabilitation.
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