Embedded systems in brain-computer-interfaces (Eingebettet Systeme für Gehirn-Computer-Schnittstellen)

Background

Brain-Computer-Interfaces (BCIs) have been experiencing some renewed interest recently, including new approaches in both analysis and technology. Advances in embedded systems have allowed for simplified and mobile use of some of the technologies used to image the brain, such as EEGs and fNIRS. While hardware-accelerated computation allows for better analysis, e.g. using machine learning, rapid prototyping approaches permit fast implementation of new hardware concepts. Both research and industry are working on leveraging these developments to gain deeper insights into the workings of the brain and apply these findings for brain-computer interactions and neurofeedback training.

Who are we

We are a group working on embedded systems of EEGs. We are focused on rapid prototyping of new hardware setups and statistical approaches, including machine learning, to improve the performance of BCIs. Areas of application we are looking at include wearables and dementia research. If you are interested, please get in touch for details.

Scope of tasks

• Development and improvement of EEG hardware
• Integration of hardware for other biomarkers (fNIRS, EKG, skin sensors, eye tracking, etc.)
• Using hardware accelerators for signal processing
• Embedded software development and QT/Unity development (Python,C,C++ or C#)

Requirements

• Motivation and independent work
• Cooperative approach
• Experience in one or more of the following skills: Embedded systems design, data science, CAD, KiCAD, programming (C, C++ or C#), rapid prototyping