Published October 10, 2021
| Version v1
Conference paper
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Learn to drive a BMI based intelligent wheelchair
Authors/Creators
Description
Brain-machine interfaces (BMIs) are systems able
to translate human brain patterns into commands for robotic
devices. Despite the flourishing of brain-actuated prototypes,
after three decades of research, BMI is still lacking practicable
solutions for daily use by end-users. Current research approaches
that assume that BMI should be treated only as a decoder
tool, have not been able to face this translational challenge.
BrainGear (a two-year project, funded by the Dept. of Information
Engineering of the University of Padova) radically revolutionizes
the traditional approach by reformulating BMI as a multifaceted
symbiotic learning entity where the three actors involved —user,
decoder, and robotic device— have to mutually learn from each
other. Neuroscientific and robotic methodologies are combined
in order to create and explicitly promote the mutual learning
interactions between each of these actors.
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