Whether this assignment was correct or incorrect, he learns from the EEG measurement in humans, through which he receives negative feedback, the error-correlated potential, in the event of a faulty action. This relieves the human in the interaction, since he does not have to give the feedback to the robot consciously, but thanks to eBR it is already picked up on the subconscious level. The Bremen researchers were able to apply the method, which is based on intrinsic feedback, for the first time in interaction with a real robot system and show that it leads to an improvement in the interaction between humans and robots. In rehabilitation with exoskeletons, the error potential could be used, for example, to gain insights into user acceptance.
However, the use of physiological data to improve functionality and user-friendliness in technical rehabilitation systems is linked to the possibility of their processing. This must be done in real time in order to support the movements as naturally as possible. In addition, mobile and miniaturized processing systems are needed that can be embedded in the rehabilitation facility. In their work the scientists of the DFKI and the University of Bremen – Dr. Hendrik Wöhrle, Marc Tabie, Dr. Su Kyoung Kim, Prof. Frank Kirchner and Dr. Elsa Andrea Kirchner - developed a compact brain-reading system for real-time motion prediction. They rely on Field Programmable Gate Arrays (FPGAs), reprogrammable circuits that enable parallel processing operations and can therefore process large amounts of data in the shortest possible time.
The researchers also developed the software framework reSPACE in order to make it usable for robotics. This defines the various application-specific computing operations that are combined into a data flow accelerator according to the modular principle and made available on the FPGA. By real-time evaluation of EEG data, the developed system can e.g. support the control of an exoskeleton. The FPGAs manage the huge amount of data within a few nanoseconds - only in this way can the exoskeleton support arm movement at exactly the right moment.
At the forthcoming CeBIT Expo from 12 to 15 June 2018 in Hanover, the DFKI will present a mobile exoskeleton based on this research work, which was developed for stroke patients. This exoskeleton can be controlled on the basis of EEG data. The findings and technologies for embedded brain reading were applied.
Project Recupera REHA https://robotik.dfki-bremen.de/en/research/projects/recupera-reha.html
Software-Framework reSPACE https://robotik.dfki-bremen.de/en/research/softwaretools/respace.html
DFKI auf der CEBIT https://www.dfki.de/web?set_language=en&cl=en