Signal Processing and AI for Biomedical Engineering - Interaktive Studienpläne der TU Ilmenau
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| Modulinformationen zu Modulnummer 201388 - allgemeine Informationen | |
|---|---|
| Modulnummer | 201388 |
| Fakultät | Fakultät für Informatik und Automatisierung |
| Fachgebietsnummer | 2225 (JP Datenanalyse in den Lebenswissenschaften) |
| Modulverantwortliche(r) | Prof. Dr. Patrique Fiedler |
| Sprache | Deutsch |
| Turnus | Wintersemester |
| Vorkenntnisse | - Signals and Systems - Fundamentals of biosignal processing - Fundamentals of Statistics - Anatomy and physiology - Electro- and Neurophysiology - Fundamentals of Measurement electronics - Imaging in biomedical engineering |
| Lernergebnisse und erworbene Kompetenzen | Students are familiar with measurement systems, signal characteristics and technological solutions in selected areas of diagnostics and therapy, such as electrography, oxygen saturation, bioimpedance and electrical current therapy. . Students are able to apply special methods of signal processing, analysis and detection, incl. selected approaches of AI, in interdisciplinary areas of biosignal processing and, if necessary, adapt and develop them. . Students have subject-specific skills acquired in courses, especially in the exercises, in teams through discussion and experimental investigations on real biosignals. |
| Inhalt | Theory, methodology and approaches to pulse oximetric determination of oxygen saturation in the blood, SpO2 . Electrography: overview of electrographic recording methods, measurement principles, signal analysis and diagnostic value: EGG, EOlfG, GEP, ECochG, EHG . ECG: recording, processing, computer-aided signal detection and curve measurement, pathological patterns and suggested diagnosis . Bioimpedance: theory and methodology of electrically based metrological recording, aspects of the measurement setup, recording and evaluation of the plethysmographic curve . Detection of biosignals: Theory of signal detection, energy and matched detector, classification methods using AI, application examples on EEG and ECG . Electrotherapy: effect of low-frequency and high-frequency electrical current . - Signal forms for electrotherapy: galvanization, iontophoresis, diadynamics, high-voltage current, TENS, faradic currents, electrode systems and technologies. |
| Medienformen und technische Anforderungen bei Lehr- und Abschlussleistungen in elektronischer Form | Transparencies with projector for lectures, blackboard, computer simulations. Whiteboard and computing cabinet in seminars. |
| Literatur | Bronzino, J. D. (Ed.): The Biomedical Engineering Handbook, Vol. I + II, 2nd ed., CRC Press, Boca Raton 2000 2. Husar, P.: Electrical Biosignals in Biomedical Engineering , Springer, 2023, 1st edition. 3. Akay M.: Time-Frequency and Wavelets in Biomedical Signal Processing. IEEE Press, 1998 4. Bendat J., Piersol A.: Measurement and Analysis of Random Data. John Wiley, 1986. 5. Proakis, J.G, Manolakis, D.G.: Digital Signal Processing, Pearson Prentice Hall, 2007 |
| Lehrevaluation | |
| Spezifik Referenzmodul | |
|---|---|
| Modulname | Signal Processing and AI for Biomedical Engineering |
| Prüfungsnummer | 2200916 |
| Leistungspunkte | 5 |
| SWS | 12 (2 V, 1 Ü, 9 P) |
| Präsenzstudium (h) | 135 |
| Selbststudium (h) | 15 |
| Verpflichtung | Pflichtmodul |
| Abschluss | schriftliche Prüfungsleistung, 90 Minuten |
| Details zum Abschluss | |
| Link zum Moodle-Kurs | |
| Lehrende | Prof. Dr. Patrique Fiedler |
| Anmeldemodalitäten für alternative PL oder SL | |
| max. Teilnehmerzahl | |