Title: Real-time brain machine interaction via social robot gesture control,
Abstract: Brain-Machine Interaction (BMI) system motivates interesting and promising
results in forward/feedback control consistent with human intention. It holds
great promise for advancements in patient care and applications to
neurorehabilitation. Here, we propose a novel neurofeedback-based BCI robotic
platform using a personalized social robot in order to assist patients having
cognitive deficits through bilateral rehabilitation and mental training. For
initial testing of the platform, electroencephalography (EEG) brainwaves of a
human user were collected in real time during tasks of imaginary movements.
First, the brainwaves associated with imagined body kinematics parameters were
decoded to control a cursor on a computer screen in training protocol. Then,
the experienced subject was able to interact with a social robot via our
real-time BMI robotic platform. Corresponding to subject's imagery performance,
he/she received specific gesture movements and eye color changes as
neural-based feedback from the robot. This hands-free neurofeedback interaction
not only can be used for mind control of a social robot's movements, but also
sets the stage for application to enhancing and recovering mental abilities
such as attention via training in humans by providing real-time neurofeedback
from a social robot.