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13M051TOBS - Biomedical signal processing techniques

Course specification
Course title Biomedical signal processing techniques
Acronym 13M051TOBS
Study programme Electrical Engineering and Computing
Module Applied Mathematics, Audio and Video Communications, Audio and Video Technologies, Biomedical and Environmental Engineering, Biomedical and Nuclear Engineering, Computer Engineering and Informatics, Electronics, 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, System Engineering and Radio Communications
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 Application of analysis and visualization methods on biomedical signals for diagnostics and therapy assessment.
    The outcome Mastering techniques for biomedical signals analysis and its practical application.
    Contents
    URL to the subject page https://automatika.etf.bg.ac.rs/sr/13m051tobs
    Contents of lectures Data types, vector operations, design and optimization of control structures, and simulation of biomedical systems for generation of biosignals. Basic statistical and numerical processing methods. Principal component analysis. Data visualization for topography representation. Application of specific signal processing methods on biomedical data for diagnostics and therapy assessment.
    Contents of exercises Biomedical data manipulation, and application of various analysis methods using R programming: simulations and application of numerical and statistical methods of signal analysis.
    Literature
    1. Biomedical Engineering Theory And Practice. (2015, November 9). Wikibooks, The Free Textbook Project. Retrieved 12:53, May 27, 2016. (Original title)
    2. R. D. Peng. R programming for data science, Leanpub book, 2014-2016. (Original title)
    3. Cerutti S., Marchesi C. Advanced Methods of Biomedical Signal Processing, Wiley-IEEE Press, 2011. (Original title)
    4. Sornmo L., Laguna P. Bioelectric signal processing in cardiac and neurological applications, Elsevier Inc., 2005. (Original title)
    5. Miljković, N. Biosignal analysis with practical examples in the R programming language, University of Belgrade - School of Electrical Engineering, 2024.
    Number of hours per week during the semester/trimester/year
    Lectures Exercises OTC Study and Research Other classes
    2 2
    Methods of teaching Lectures and practical computer implementation.
    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 20
    Colloquia 30
    Seminars 0