Brain-Machine Interfaces to Improve Human-Machine Interaction

CITEC Interdisciplinary Project (IP) 19: Brain-Machine Interfaces to Improve Human-Machine Interaction Using Resource Efficiency and Adaptivity

Complex human-machine interfaces often impose a high cognitive workload on the user. The goal of this interdisciplinary project is to create a multi-modal brain-machine interface (BMI) which facilitates human-machine interaction (HMI) by improving resource efficiency and system adaptivity. We investigate cortical activity (using Electroencephalography, EEG), eye movements (using eye-tracking) and mental representation structures (using Structural Dimensional Analysis of Mental Representation, SDA-M) to identify relevant features for decoding processing difficulties during HMI.To this end, we develop and implement novel classification tools for the single-trial classification of fixation-related potentials (FRP). FRP is a neural response that is aligned to the onset of a fixation when a relevant piece of visual information is processed. As fixations occur naturally and independently from any control interface, they offer a means to reduce cognitive load and to create a BMI that allows for unrestricted natural interaction. This project progresses along a series of experiments with increasingly more real life like tasks. This structure allows to get insight into the workings of FRP and ensures BMI and classifier robustness and adaptability in natural situations.

This project is a collaboration with the Neurocognition and Action Group.

CITEC project web page