13M054MAS - Advanced Methods of Biosignal Analysis
Course specification | ||||
---|---|---|---|---|
Course title | Advanced Methods of Biosignal Analysis | |||
Acronym | 13M054MAS | |||
Study programme | Electrical Engineering and Computing | |||
Module | Applied Mathematics, Audio and Video Technologies, Biomedical and Environmental Engineering, Biomedical and Nuclear Engineering, Computer Engineering and Informatics, Electronics and Digital Systems, Energy Efficiency, Information and Communication Technologies, Microwave Engineering, Nanoelectronics and Photonics, Power Systems - Networks and Systems, Power Systems - Renewable Energy Sources, Power Systems - Substations and Power Equipment, Signals and Systems, Software Engineering | |||
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 methods of physiological signal analysis for application in diagnostics and automatic diagnosis. | |||
The outcome | The ability to apply modern computational methods for the analysis physiological signals in research and in clinical conditions, as well as signal processing with the aim of diagnostic and automatic diagnosis. | |||
Contents | ||||
Contents of lectures | Dynamic characteristics of physiological signals with an emphasis on electrophysiological (EF) signals. Application of Fourier's transformation in the analysis of EF signals. Correlation, cross-correlation, and auto-correlation. Digital filters and window functions. 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, and application of methods on real-life signals. | |||
Knowledge score (maximum points 100) | ||||
Pre obligations | Points | Final exam | Points | |
Activites during lectures | 0 | Test paper | 50 | |
Practical lessons | 0 | Oral examination | 0 | |
Projects | ||||
Colloquia | 20 | |||
Seminars | 30 |