A simulation-based methodology to test and assess designs of mechatronic neural interface systems

Neural interface systems (NISs) are widely used in rehabilitation and upper limb prosthetics. These systems usually involve robots, such as robotic exoskeletons or electric arms, as terminal devices. We propose a methodology to assess the feasibility of implementing these kind of neural interfaces by means of an online kinematic simulation of the robot. It allows the researcher or developer to make tests and improve the design of the mechatronic devices when they have not been built yet or are not available. Moreover, it may be used in biofeedback applications for rehabilitation. The simulation makes use of the CAD model of the robot, its Denavit-Hartenberg parameters, and biosignals recorded from a human being. The proposed methodology was tested using surface electromyography signals acquired from the upper limb of a 25-year-old healthy male. Both real-time and prerecorded signals were used. The robot simulated was the commercial robotic arm KUKA KR6. The tests proved that the online simulation can be effectively implemented and controlled by meansofabiosignal.