Subject: Biomedical signals processing and analysis (17.BMI123 )
Native organizations units: Department of Power, Electronic and Telecommunication Engineering
Study programmes of the course:
| Type of studies | Title |
|---|---|
| Undergraduate Academic Studies | Biomedical Engineering (Godina: 3, Winter) |
Educational goal:
Introduction of advanced biomedical signal processing methods adapted to high demands in practice, considering the limitations of signal processing methods and ways of overcoming them, learning about time-frequency analysis methods and multiresolution analysis with applications to one-dimensional signals
Educational outcome:
Analysis of correlated processes and specific processing methods; power spectral density estimation; adjustment of processing methods for the analysis of non-stationary signals, types of time-frequency analysis, wavelets transformation, feature selection principles and relevant classification methods in diagnostic decision making
Course content:
Analysis of coupled and correlated physiological processes, examples of coupled processes and interactions between systems - Signal characterization in the frequency domain: estimation of power spectral density (PSD) (parametric and non-parametric methods, the use of window functions, resolution and spectral leakage), measures that can be derived from the spectral density: relation of power, moments. Illustrative examples of application of the methods in the frequency domain - Specific analysis of non-stationary signal illustration of the examples of non-stationary biomedical signals, the use of time-frekvecnisjkih methods and specific, signal segmentation for further analysis, adaptive filters - Time-frequency methods, Multiresolution analysis, wavelets transform and discrete filter banks, the application of one-dimensional biomedical signals - The application of pattern recognition in the diagnostic decision-making, application examples and unsupervised classification methods, selecting relevant features with respect to the physiological background, the measures of diagnostics accuracy and reliability of the classifier
Teaching methods:
Lectures, laboratory analysis using the signals from patients and laboratory animals, obtained by courtesy of various research institutions from Belgrade; visit to hospital and cardiovascular laboratory to observe 1D signal acquisition, and to Imaging center to observe CT, PET, NMR.
Literature:
| Authors | Title | Year | Publisher | Language |
|---|---|---|---|---|
| BAJIĆ, D. | Električna i elektronska kola, uređaji i merni instrumenti | 1972 | BIGZ, Beograd | Serbian language |
| Dejan Popović | Medicinska instrumentacija i merenja | 2014 | Akademska misao | Serbian language |
| 1999 | English | |||
| Tamara Škorić, Dragana Bajić | Praktikum iz obrade biomedicinskih signala | 2019 | Novi Sad, Fakultet tehničkih nauka | Serbian language |
| 1999 | English | |||
| 2006 | Serbian/English language | |||
| 1972 | Serbian language |
Knowledge evaluation:
| Course activity | Pre-examination | Obligations | Number of points |
|---|---|---|---|
| Project | Yes | Yes | 30.00 |
| Theoretical part of the exam | No | Yes | 70.00 |
Lecturers:
prof. dr Bajić Dragana
Full Professor
Practical classes
prof. dr Bajić Dragana
Full Professor
Lectures
vanr. prof. dr Škorić Tamara
Associate Professor
Practical classes
Faculty of Technical Sciences
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Contact:
Address: Trg Dositeja Obradovića 6, 21102 Novi Sad
© 2024. Faculty of Technical Sciences.