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19D051OMO - Advanced Methods of Electrophysiological Signal Analysis

Course specification
Course title Advanced Methods of Electrophysiological Signal Analysis
Acronym 19D051OMO
Study programme Electrical Engineering and Computing
Module System Control and Signal Processing
Type of study doctoral studies
Lecturer (for classes)
Lecturer/Associate (for practice)
    Lecturer/Associate (for OTC)
      ESPB 9.0 Status elective
      Condition None.
      The goal Application of up-to-date computational methods in biosignal analysis, with an emphasis on automatic diagnostics of physiological states with application in personalized medicine. The focus is on improving existing noise elimination techniques (for wearable technologies and dynamic measurements), efficient extraction of relevant features, and on the application of advanced reasoning methods.
      The outcome The ability to apply up-to-date computational methods in the analysis of biosignals, with the aim of improving automated diagnostic systems and their potential integration into personalized medicine. This incorporates critical analysis and comparative evaluation of existing and newly developed methods.
      Contents
      Contents of lectures Specifics of biosignal analysis methods. Digital filters and window functions. Modeling and system state estimation. Adaptive and optimal processing methods. Application of methods from nonlinear dynamics. Feature extraction. Statistical analysis and machine learning (ML) algorithms. Interpretability and explainability of ML. Analysis of multimodal signals. Examples of biosignal analysis.
      Contents of exercises Project work (computer-based analysis of biosignals, i.e., electrophysiological signals).
      Literature
      1. Naik G. "Biomedical Signal Processing", Springer Singapore, 2020. (Original title)
      2. Dunn S. M., Constantinides A., Moghe P. V. "Numerical methods in biomedical engineering", Elsevier, 2006. (Original title)
      3. Rangayyan R. M. "Biomedical signal analysis", John Wiley & Sons, 2015. (Original title)
      4. Biosignal analysis with practical examples in the R programming language
      5. Naït-Ali A. (Ed.). "Advanced biosignal processing", Springer Science & Business Media, 2009. (Original title)
      Number of hours per week during the semester/trimester/year
      Lectures Exercises OTC Study and Research Other classes
      8
      Methods of teaching Lectures, consultations, and application of methods from recommended scientific papers.
      Knowledge score (maximum points 100)
      Pre obligations Points Final exam Points
      Activites during lectures 0 Test paper
      Practical lessons Oral examination 30
      Projects 70
      Colloquia
      Seminars