Neuroinformatics Group

Universität BielefeldTechnische FakultätNI

Brain-Computer Interfaces

Brain-computer interfaces (BCI) provide an alternative communication channel that bypasses all muscular functions by directly decoding brain activity. When using electroencephalography (EEG) to acquire brain signals, they are non-invasive, affordable and safe. Having originally been designed as a communication tool for patients with severe physical disabilities, e.g. paraplegia or locked-in state, the application areas have grown in recent years. Our research follows a two fold approach. Firstly, we aim at improving the reliability and the communication speed of the systems. Furthermore, we investigate the usage of BCI as a research tool, in particular to study human-machine and human-robot interaction in more real-world like settings. To this end, BCI allows to investigate cognitive processes during the interaction, in almost real time and without having to rely solely on group-level data.

Related Research Projects


Brain-Machine Interfaces to Improve Human-Machine Interaction

This project investigates the relationship between cortical activity (Electroencephalography, EEG), eye movements and mental representation structures (Structural Dimensional Analysis of Mental Representation, SDA-M) as a complex measure of ongoing cognitive processes during human-machine interaction (HMI) - an approach that has so far received little attention.

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NeuroCommTrainer

Every year thousands of people in Germany suffer severe traumatic brain injuries resulting in a permanent loss of consciousness and the ability to communicate. Our project aims at combining innovative interaction concepts with novel technology to improve the every day life of patients, care takers and relatives. We develop an adaptive, multi-modal training and communication system based on neural activity (EEG) and other sensor data to reinforce the patient's residual reactions and build up basal communication possibilities.

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Code-Modulated Visual Potentials for Fast and Flexible BCI

We explore a new BCI design for the control of robotic devices. Specifically, we show the first use of a code-modulating, Visually-Evoked Potential (cVEP)-based BCI for a navigation and control task.

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MONARCA

MONARCA bipolar butterfly MONARCA will develop and validate solutions for multi-parametric, long term monitoring of behavioural and physiological information relevant to bipolar disorder.

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A Brain-Robot Interface for Controlling ASIMO

Acquiring a profound knowledge about the cognitive processes underlying human-robot interaction is essential to better exploit the measurable components for brain-robot interfaces. The better the processes are understood, the better the EEG components originating from these processes can be used. A systematic evaluation of these components in connection with human-robot interaction is missing until today. Hence, it appears to be worthwhile to take a closer and impartial look at what is really happening on the cognitive level, as far as determinable by EEG signals.

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Augmented Reality based Brain-Computer Interfaces

For a long time Brain-Computer Interfaces (BCI) had been destined to act as pur spelling devices which enabled paralyzed people to communicate by mere thought. Our current projects aim to extend the scope of these devices and develop novel techniques for brain-robot interaction. A successful application of BCIs to robotic devices will have the tremendous advantage that the users will not be limited to pure communication tasks but also be able to manipulate their surrounding directly by only imagining actions.

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Alignment of Attention in Mediated Communication

Do you prefer audio books over printed ones, and if so, what is the advantage? Why is video conferencing so awkward? Why do you rely on SMS messages as a means of communication in some situations but on e-mailing in others? Did you ever notice that you raise your eyebrows when asking people a question – even on the telephone? And did you ever wonder how to make your point in a discussion most convincingly?

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