24/07/2026
How can brain activity help people regain mobility after a stroke?
Welcome to another project presentation! This time, we are introducing Online EEG Analysis for Neurofeedback in Neurorehabilitation of Lower Extremities after Stroke, led by Prof. Dr. Ing. habil. Jens Haueisen and Prof. Dr. Ing. Daniel Baumgarten.
After a stroke, many people experience movement impairments, especially in their legs. This is exactly where the project comes in. The researchers use electroencephalography (EEG), to measure the brain’s electrical activity. This method is not only highly precise, but also relatively mobile, cost effective and non invasive. 🧠⚙️
Using these EEG signals, the team develops a Brain Computer Interface (BCI), creating a direct connection between the brain and a machine. Through the BCI, users receive visual and sensory feedback while imagining the movement of their legs, a process known as motor imagery.
One of the most innovative aspects of the project: It combines the Brain Computer Interface with a rehabilitation robot for the lower limbs. The robot has six degrees of freedom, allowing it to perform highly complex and precisely timed movements. To accurately recognize what the brain intends, advanced classification algorithms based on Convolutional Neural Networks (CNNs), are being developed. These algorithms analyse both the sources of brain activity and the communication between different brain regions in real time, improving the detection of motor imagery.
In summary, OnEEG Neuroflow collects EEG data from both healthy participants and stroke patients while they either imagine moving their legs or are passively moved by the rehabilitation robot. These data are then analysed to train and continuously improve the AI algorithms.
We believe that the combination of EEG, artificial intelligence and robotic rehabilitation has the potential to make a real difference, not only for scientific research, but also for improving the quality of life of people recovering from a stroke. 💡
Funding: Deutsche Forschungsgemeinschaft (DFG)
Sources: Interview, Prof. Haueisen (2025); DFG
