IM2

The idea of controlling machines not by manual control, but by mere
"thinking" (i.e., the brain activity of human subjects) has fascinated
humankind since ever, and researchers working at the crossroads of
computer science, neurosciences, and biomedical engineering have started
to develop the first prototypes of brain-machine interfaces (BMI) over
the last decade or so. Thus, researchers have been able to train
monkeys, who had implanted tens of microelectrodes in their brain, to
control a robot arm. Human subjects, on their side, have shown the
possibility to drive a mobile robot between rooms in a house model using
non-invasive EEG recordings .

Although these promising first results are attracting significant
attention from an increasing number of research laboratories around the
world, most of the issues being explored are related to "augmented
communication" where fast decision-making is not critical as it is the
case for real-time control of robotics devices and neuroprosthesis. The
latter kind of applications is the most challenging for BMI and it is
the goal of this project. In particular, we will explore mental
teleoperation of a mobile robot based on non-invasive brain activity
related to motor tasks (i.e., subjects imagine natural movements of
their body that are translated into similar actions of the robot) and
multiple modalities of feedback (visual, auditory, haptic and vestibular).