Task: Build a system that uses the pilot's brain signals to control a game avatar.
Pilot: Person with complete or a severely affected incomplete tetraparesis, e.g. a spinal cord injury with impairment at and below the neck.
The goal of this subteam is to develop a BCI system that pushes the state of the art, with the goal of helping people with upper spine injuries. Using modern hardware and software approaches, we aim to decode the movement intentions of the pilots from their neural activity. The movement intentions are, for the sake of the competition, translated into 4 control signals used in a computer game environment. The long-term goal is to direct these commands from the user into the surrounding real world (smart environment & ubiquitious robotics).
Current research topics:
Deep learning for motor imagery classification
Game design for BCI evaluation
The TUM Library has provided us with a list of helpful and extensive books. To access their content, first login with your TUM ID via eAccess.
Event-based neuromorphic systems - Shih-Chii Liu et al. (2015)
Neuromorphic and brain-based robotics - Jeffrey krichmar (2011)
Neuroengineering - Daniel DiLorenzo, Joseph Bronzino (2008)
Handbook of neural engineering - Metin Akay (2007)
Bio-inspired artificial intelligence: theories, methods, and technologies - Dario Floreano (2008)
Neurotechnology: premises, potential, and problems - James Giordano, 2012
Photos: Nicolas Berberich (image carousel) , Fabian Vogl / TUM (last two photos)