13M054MAS - Advanced Methods of Biosignal Analysis
| Course specification | ||||
|---|---|---|---|---|
| Course title | Advanced Methods of Biosignal Analysis | |||
| Acronym | 13M054MAS | |||
| Study programme | Electrical Engineering and Computing | |||
| Module | ||||
| Type of study | master academic studies | |||
| Lecturer (for classes) | ||||
| Lecturer/Associate (for practice) | ||||
| Lecturer/Associate (for OTC) | ||||
| ESPB | 6.0 | Status | elective | |
| Condition | none | |||
| The goal | Applying modern computer methods of physiological signal processing and analysis for diagnostics and automatic diagnosis. | |||
| The outcome | The ability to apply modern computational methods for the analysis electrophysiological signals in research and in clinical conditions; as well as signal processing for diagnostic and automatic diagnosis. | |||
| Contents | ||||
| URL to the subject page | https://automatika.etf.bg.edu.rs/sr/13e054mas | |||
| Contents of lectures | Dynamic characteristics of electrophysiological (EF) signal. Application of Fourier's and Laplace's transform in the analysis of EF signal. Correlation, crosscorrelation, and autocorrelation. Digital filters and window functions. Application of Z - transformation. Adaptive Filters. Model and state estimation. Time series analysis. Application of selected methods for EF signal analysis. | |||
| Contents of exercises | computer-based analysis of biological signals | |||
| Literature | ||||
| ||||
| Number of hours per week during the semester/trimester/year | ||||
| Lectures | Exercises | OTC | Study and Research | Other classes |
| 3 | 1 | 1 | ||
| Methods of teaching | Lectures, supervised exercises, exercises, application of methods on real-life signals | |||
| Knowledge score (maximum points 100) | ||||
| Pre obligations | Points | Final exam | Points | |
| Activites during lectures | 0 | Test paper | 30 | |
| Practical lessons | 50 | Oral examination | 0 | |
| Projects | ||||
| Colloquia | 20 | |||
| Seminars | ||||

