Our Current Projects

If you are interested in learning more about them, feel free to contact us!

Our Youtube Playlist “KI and We”

with currently 3 Episodes is the start of a podcast-like series going over the big topic of artificial intelligence.

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Mercur Project Neural Signal Processing Using Artificial Intelligence on an Embedded Platform


The goal of this project is to develop an end-to-end neural processing chain that implements online algorithms for spike sorting and neural decoding with analog and digital embedded hardware. This pipeline is a fundamental building block for the development of the next generation of neural implants.

Existing solutions do not allow accurate, fast and energy-efficient interpretation of brain signals. In the project we will define a common augmented dataset for embedded neural processing and develop hardware-based solutions for the different phases of spike sorting. We will optimise a neural decoder based on deep learning methods as well as integrate all parts into a demonstrator and evaluate system performance.




The terahertz.nrw research network is a collaboration between Ruhr University Bochum, Fraunhofer Institute for High-Frequency Physics and Radar Technology, University of Duisburg-Essen, Bergische Universität Wuppertal and the Fraunhofer Institute for Microelectronic Circuits.

The terahertz (THz) frequency range, beyond visible light and infrared radiation, has great potential in biomedical applications. Based on their biomacromolecule composition and water content, different tissues exhibit different THz spectrum characteristics which can help, for example in tomography, distinguish tumour from non-tumour tissue. We are interested in the detection of neuronal activity through THz radiation using deep learning to uncover intricate patterns.

Our Finished Projects

If you are interested in learning more about them, feel free to contact us!

Our Youtube Playlist “Transhumanismus: Denkbar? Machbar? Wünschenswert?”

Cryonics, nanobots, artificial intelligence, enhancement & co: What can we expect from new technologies and where do their dangers lie? In seven episodes, neuroscientist Christian Klaes and philosopher Benedikt Paul Göcke from Ruhr-Universität Bochum will explain the opportunities and consequences of transhumanism.

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SFB 874 A11 The Relationship between Implicit and Explicit Visuomotor Task Learning in Hippocampus and Parietal Cortex


Visuomotor tasks, such as motor sequence learning and motor adaptation, depend on various brain structures such as the hippocampus and the parietal cortex. These structures’ involvement might vary depending on the learning stage and on the explicitness of the task.

In this project, we are interested in investigating how brain structures such as the hippocampus and the parietal cortex are involved in implicit versus explicit forms of motor learning and across learning stages. More information about this project can be found here.

SFB 847 featured on the RUB Youtube Channel

Prof Dr Christian Klaes and Susanne Dyck showcase the Project and the opportunities for VR in research in an interesting experiment with Anke Maes.

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Impairment of arm and gripping functions after various neurological diseases limit the participation of affected patients in professional and everyday life. This poses a great challenge to the rehabilitation process. It is necessary to make use of independent and everyday training to foster conventional therapy and facilitate rehabilitation.

This project focuses on the design of a key component –a biomechanically designed, adaptive exoskeleton for the upper extremity –to explore and enable patients in their journey of rehabilitation. More information about this project can be found here.

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VAFES Motion Trackers and VR for the Diagnosis and Therapy of Neurological Diseases with Hand and Arm Dysfunctions


Restrictions in hand and arm function as a result of neurological diseases require
differentiated diagnosis both for therapy control and for early detection.

In this project a standardized test environment in Virtual Reality (VR) will be developed. Motion trackers and VR gloves cover a broad spectrum of relevant motion parameters. In particular, synchronous electroencephalographic (EEG) recordings supplement the motion data with neuronal signals. This combination makes it possible for the
first time to use modern Machine Learning (ML) algorithms in the context of diagnosis and therapy of neurological diseases with hand and arm dysfunctions.