The research group Brain-machine interfaces (BMI) deals with the development and improvement of the central components of BMIs. A BMI is defined as a device which analyzes signals from the brain and converts the contained information into control commands for external applications to represent the user's intentions this way. A BMI is a communication system which is not dependent on the usual exit paths of the brain, i.e. the peripheral nerves and muscles. It replaces the function of nerves and muscles - and the changes they cause - through electrophysiological signals and the hardware and software required for the processing.
In the area of data collection, there are different priorities within the research group: The AP 1 "microelectrode array" deals with developing a bio- and MR-compatible, minimally invasive implantable microelectrode array. Hereby, High-quality signals should be acquired and the exposure of the patient should drastically be reduced towards the conventional electrode grid implantation. To guarantee the best possible signal acquisition the optimal placement of the electrodes is fundamental.
The methods needed for this purpose are examined in AP 2 "surgical planning and selection process". The central interface between data acquisition and appliance control describes the signal processing. The aim is to reliably and solidly detect the intentions of the patient from the measured brain signals.
The AP 3 "signal analysis, classification" deals with the adjustment and optimization of existing algorithms as well as particularly with the development of new methods for the classification of signals. One research focus is on the Hidden Markov Models which are known from voice recognition.
In AP 4 "in-ear BMI" a miniaturized system is developed for the detection of brain activity with in-ear electrodes. Due to the holistic concept, from electrode conception to measuring electronics and the implementation of a matching smart phone environment, the AP 4 bends a practical bow over the majority of the issues arising in the course of BMIs.
Dr. Christoph Reichert
FG Brain-Machine-Interfaces (BMI)
ExFa Raum 4.09