Human-Machine Interfaces Lab

High bandwidth brain-computer interfaces (BCIs) could create a whole new world of opportunities: they could allow us to type with our inner voice, control wheelchairs, exoskeletons and robots telekinetically, etc. However, current brain-computer interfaces lack the necessary information transfer rate for these applications, so they are very inaccurate and slow compared to everyday input devices such as the keyboard, the touchpad and the mouse. In order to increase the efficiency of BCIs, our research group is developing of state of the art artificial intelligence based neural signal processor algorithms for both electroencephalographic (EEG) and electrocorticographic (ECoG) signals.

We are eager to participate in the Cybathlon 2020 competition in Zurich, during which movement impaired users have to control a computer game with their thoughts only. The neural signals which we exploit for this competition are generated by imaginary movements.

Video about the Cybathlon 2016.

Within the Hungarian National Bionic Program, we are developing a wearable eye tracker device with additional gesture recognition functionalities realized via electromyography (EMG). Our primary goal is to help disabled people in communication and allow them to control various electronic devices. Eye-tracking can also be used to identify children who will be probably affected by dyslexia, even before they start to learn how to read.