Brain-Computer Interface
KIB-BCI
ki2
1
V
3
PA
6
0
no
English/German
Project with presentation
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
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
Prof. Dr. Dr. Daniel Strauß
das
Farah Corona-Strauss, M.Sc.
fcs
Dr. Lars Haab
lha
Mario Korherr, B.Sc.
mko
• 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
SS 2024
SS 2023
SS 2022
SS 2021
Thu Mar 28 09:47:06 CET 2024, CKEY=kga, BKEY=ki2, CID=[?], LANGUAGE=en, DATE=28.03.2024