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Module Number:
| 13335
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| Module Title: | Brain-Computer Interfaces (BCIs) for Neuroadaptive Technology |
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Brain-Computer-Interfaces für Neuroadaptive Technologien
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| Department: |
Faculty 1 - Mathematics, Computer Science, Physics, Electrical Engineering and Information Technology
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| Responsible Staff Member: | -
Prof. Dr. rer. nat. Zander, Thorsten
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| Language of Teaching / Examination: | English |
| Duration: | 1 semester |
| Frequency of Offer: |
On special announcement
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| Credits: |
6
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| Learning Outcome: | After successfully completing the module, students possess a basic understanding of the methodology of Brain-Computer Interfaces (BCIs), including measurement of brain activity, signal processing, machine learning and the principle of automated interpretation of brain activity to assess information of changes in cognitive states. Furthermore, they are familiar with the use of BCIs in current and to-be-created human-computer interactions which includes the current development of beneficial Artificial Intelligence. |
| Contents: | The module will consist of lectures describing the methodology and use of Brain-Computer Interfaces from the scratch. This includes knowledge from machine learning and signal processing, as well as psychophysiology and psychology, and human-computer interaction. In the seminar, students will read, present and discuss relevant papers published in scientific journals, reflecting different perspectives on Neuroadaptive Technologies and Artificial Intelligence. |
| Recommended Prerequisites: | Programming experience, MATLAB in particular |
| Mandatory Prerequisites: | None |
| Forms of Teaching and Proportion: | -
Lecture
/ 2 Hours per Week per Semester
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Seminar
/ 2 Hours per Week per Semester
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Exercise
/ 2 Hours per Week per Semester
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Self organised studies
/ 90 Hours
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| Teaching Materials and Literature: | - Zander, T. O. (2011). Utilizing Brain-Computer Interfaces for Human-Machine Systems (Doctoral dissertation, Universitätsbibliothek der Technischen Universität Berlin).
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| Module Examination: | Continuous Assessment (MCA) |
| Assessment Mode for Module Examination: | - Poster presentation (30%)
- Oral Exam, 30 minutes (40%)
- Housework every two weeks (20%)
- Active participation in Exercises (10%)
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| Evaluation of Module Examination: | Performance Verification – graded |
| Limited Number of Participants: | None |
| Part of the Study Programme: | -
Master (research-oriented) /
Artificial Intelligence /
PO 2022
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Master (research-oriented) /
Informatik /
PO 2008
- 2. SÄ 2017
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Master (research-oriented) /
Informations- und Medientechnik /
PO 2017
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Master (research-oriented) /
Künstliche Intelligenz Technologie /
PO 2022
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Bachelor (research-oriented) /
Medizininformatik /
PO 2016
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| Remarks: | - Study programme Medizininformatik: B.Sc.: Compulsory elective module in complex „Medizininformatik"
- Study programme Informatik M.Sc.: Compulsory elective module in complex „Praktischer Informatik" (level 400)
- Study programme Informations- and Medientechnologie M.Sc.: Compulsory elective module in complex „Kognitive Systeme"
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| Module Components: | - Lecture: Brain-Computer Interfaces (BCIs) for Neuroadaptive Technology
- Accompanying seminar
- Accompanying exercise
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| Components to be offered in the Current Semester: | |
