MTM.BCI P231-0128 mechm 1 V 3 PA 6 0 no English/German Project with presentation BMT2613.BCI Biomedical Engineering 0 optional course BMT2613.BCI Biomedical Engineering 0 optional course KIB-BCI Computer Science and Communication Systems 0 optional course KIB-BCI Computer Science and Communication Systems 0 optional course MTM.BCI Mechatronics 0 optional course MST2.BCI Mechatronics and Sensor Technology 0 optional course MST2.BCI Mechatronics and Sensor Technology 0 optional course PIB-BCI Applied Informatics 0 optional course PIB-BCI Applied Informatics 0 optional course TIB-BCI Technical Computer Science 0 optional course 60 class hours (= 45 clock hours) over a 15-week period.The total student study time is 180 hours (equivalent to 6 ECTS credits).There are therefore 135 hours available for class preparation and follow-up work and exam preparation. Prof. Dr. Dr. Daniel Strauß das Prof. Dr. Martina Lehser ml • After successfully completing this module, students will be able to apply their basic knowledge about biosignal processing as it relates to movements of collaborative robots. • Based on their interdisciplinary knowledge of programming and biosignal processing, they will be able to solve simple tasks involving collaborative industrial robots and then record and interpret the relevant neural activity data and control the robot. • Students will be able to collaborate with students from other disciplines (BMT, Computer Science, Mechatronics) in their project assignments and in doing so, use different skills. • In addition to professional qualifications, students will have acquired experience in assuming professional and organizational responsibility within their (interdisciplinary) project team. • As study participants, students will have learned essential soft skills in dealing with subjects and patients. • The basics of direct dialog between man and machine • Setting up experiments to measure and detect relevant patterns in human neural signals, in particular the electroencephalogram (EEG) • The interpretation and analysis of neural signals by means of signal processing and pattern recognition to control a robot • Simple programming of collaborative industrial robots • Handling robot hardware and system-dependent scripting language (based on UR as an example) • Implementing the control of the robot hardware based on interpreted data Lecture, practical exercises, workshop/training, meeting Bruce, Eugene N.: Biomedical Signal Processing and Signal Modeling, John Wiley & Sons, 2001 Nunez, Paul L; Shrinivasan, Ramesh: Electric Fields of the Brain: the neurophysics of EEG, Oxford University Press, 1991 Semmlow, John L.: Biosignal and Biomedical Image Processing, Marcel Dekker, 2004 Clément, Claude. Brain-Computer Interface Technologies, Springer, 2019 http://www.i-botics.de/wp-content/uploads/2016/08/UR3_User_Manual_de_Global.pdf https://www.universal-robots.com/download/?option=15833 Mon Apr 20 08:17:20 CEST 2026, CKEY=kga, BKEY=mechm, CID=[?], LANGUAGE=en, DATE=20.04.2026