• Biomedical Engineering, Semester 2, position 3

Introduction to basic concepts and knowledge related to continuous-time and discrete-time signals, deterministic and stochastic signals, signal processing and analysis in time and frequency domain, digital filter design. Introduction to the specific nature of the biomedical signals, mainly electhophysiological signals, and various approaches to biomedical signal processing and analysis. Mastering digital signal processing methods and its application using MATLAB.

Upon successful completion of this course, students shall be able to: •Apply MATLAB software for the analysis and processing of the major electrophysiological time series •Form and implement program for signal acquisition and properly choose acquisition system parameters depending on the type of biomedical signal •Master the application and the characteristics of Fourier transform and Z-transform •Distinguish characteristics of different biomedical signals (EEG, ECG, EMG) in time and frequency domain •Select and apply different filtering methods depending on the characteristics of the signal being processed and the types of further applications of such signals •Form a user interface for signal processing and displaying, adequately present time series and signal processing results in the time, frequency and time-frequency domain.

Deterministic and stochastic signals. Biomedical signals. Electrophysiological signals - ENG, EMG, ECG, EEG. Signal analysis in time domain: averaging, correlation. Discrete signal analysis in frequency domain: Fourier transform, FTDS, DFT, FFT. Z-transform. Sampling theorem. Spectrogram. Digital processing of continuous signals: continuous signal discretization, systems for signal discretization and reconstruction (A/D, D/A conversion). IIR filters. FIR filters. Discrete stochastic signals.

Introduction to MATLAB for digital signal processing. Import of various biomedical signals from PhysioBank data bank. Signal processing in time domain. Signal spectral analysis. EMG, ECG and EEG signal processing and analysis. Detection of characteristic signal parameters. Digital filter design. Biological systems modelling.

None.

Auditory room equipped with computer, video beam, internet connection and accompanied inventory. Computer room with computers with needed software installed. [1] Handouts - lectures. [2] Handouts - Auditory exercises.

Total assigned hours: 75

New material: 20
Elaboration and examples (recapitulation): 10

Auditory exercises: 14
Laboratory exercises: 0
Calculation tasks: 16
Seminar paper: 0
Project: 0
Consultations: 0
Discussion/workshop: 0
Research study work: 0

Review and grading of calculation tasks: 5
Review and grading of lab reports: 0
Review and grading of seminar papers: 0
Review and grading of the project: 0
Test: 5
Test: 0
Final exam: 5

Activity during lectures: 5
Test/test: 60
Laboratory practice: 0
Calculation tasks: 0
Seminar paper: 0
Project: 0
Final exam: 35
Requirement for taking the exam (required number of points): 30

L. Popović Maneski, B. Jeftić, N. Malešević, Signals and Systems in Rehabilitation, 2nd Edition, Akademska Misao, Belgrade, 2019, ISBN: 978-86-7466-794-1; J. Semmlow, Circuits, Signals and Systems for Bioengineers, Elsevier Inc, 2018; K.J. Blinowska, J. Zygierewicz, Practical Biomedical Signal Analysis Using MATLAB, CRC Press, USA, 2022; R. Rangayyan, Biomedical signal analysis, Vol. 33. John Wiley & Sons, 2015; L. Popović-Maneski, I. Hut, B. Jeftić, I. Jovanov, Introduction to LabView i MATLAB, Akademska misao, Belgrade, 2015, ISBN: 978-86-7466-565-7 (in Serbian)