Teaching brain-machine interfaces as an alternative paradigm to neuroprosthetics control
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We developed a new generation of neuroprostheses. They are capable of learning good control policies based on error-related brain activity.
For example, if we fail to grasp a glass of water placed in front of us, the neuroprosthesis will understand that the action was unsuccessful and the next movements will change accordingly until the desired result is achieved. The machine knows that the goal is reached when the actions performed no longer generate such signals.
More info:
ricardo.chavarriaga.me
actu.epfl.ch/news/when-the-neuroprosthetics-learn-from-the-patient-5/
(c) EPFL 2015
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