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Module Number:
| 13500
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| Module Title: | Introduction to Neural Signal Analysis |
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Einführung in die neuronale Signalanalyse
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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.-Ing. habil. Glasauer, Stefan
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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 will demonstrate a comprehensive understanding of neural signaling and EEG signal acquisition. They will possess the ability to apply basic time and frequency domain analyses for processing EEG signals. |
| Contents: | - Introduction to Neural Signaling
- EEG Signal Acquisition
- Artifacts and preprocessing techniques
- Time Domain Analysis
- Evoked potentials
- Frequency Domain and EEG signals spectral analysis
- Applications in Computational Neuroscience
- Ethical aspects of brain wave measurements
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| Recommended Prerequisites: | Knowledge of the topics of the modules
- 11112 Mathematik IT-1 (Diskrete Mathematik)
- 11113 Mathematik IT-2 (Lineare Algebra)
- 11213 Mathematik IT-3 (Analysis)
- 11756 Algorithmen und Datenstrukturen
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| Mandatory Prerequisites: | None |
| Forms of Teaching and Proportion: | -
Lecture
/ 2 Hours per Week per Semester
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Exercise
/ 2 Hours per Week per Semester
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Self organised studies
/ 120 Hours
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| Teaching Materials and Literature: | - Biomedical Signal Analysis (IEEE Press Series on Biomedical Engineering), Rangaraj M. Rangayyan, Wiley-IEEE Press, ISBN:9780470911396
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| Module Examination: | Prerequisite + Final Module Examination (MAP) |
| Assessment Mode for Module Examination: | Prerequisite:
- Successful completion of homework
Final Module Examinatio: - Written exam, 120 minutes OR
- Oral examination, 30-45 minutes
In the first lecture it will be announced, if the examination will be offered in written or oral form. |
| Evaluation of Module Examination: | Performance Verification – graded |
| Limited Number of Participants: | 100 |
| Part of the Study Programme: | -
Master (research-oriented) /
Artificial Intelligence /
PO 2022
- 1. SÄ 2024
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Bachelor (research-oriented) /
Informatik /
PO 2008
- 2. SÄ 2024
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Bachelor (research-oriented) /
Informations- und Medientechnik /
PO 2017
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Master (research-oriented) /
Mathematical Data Science /
PO 2025
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Bachelor (research-oriented) /
Medizininformatik /
PO 2016
- 1. SÄ 2024
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| Remarks: | - Study programme Medizininformatik B.Sc.: Compulsory elective module in complex „Medizininformatik"
- Study programme Informations- und Medientechnik B. Sc.: Complex „Informatik", compulsory elective module module in the field of study „Kognitive Systeme"
- Study programme Informatik B.Sc.: Compulsory elective module in complex „Praktische Informatik" (level 300)
- Study programme Artificial Intelligence M.Sc.: Compulsory elective module in complex „Knowledge Acquisition, Representation, and Processing“
- Study programme Mathematical Data Science M.Sc.: Compulsory elective module in complex „Fundamentals of Data Science“
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| Module Components: | - Lecture: Introduction to neural signal analysis
- Accompanying exercise
- Related examination
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| Components to be offered in the Current Semester: | |
