Courses – Fakultet tehničkih nauka u Novom Sadu

Subject: Biomedical signal processing (17.EK460)

Native organizations units: Department of Power, Electronic and Telecommunication Engineering

General information:

Category	Theoretical-methodological
Scientific or art field	Telecommunications and Signal Processing
ECTS	5

Types of 1D, 2D and 3D biomedical signals and specific methods of their processing. Application of stochastic signal processing theory. The aim is to estimate a parameter that could support the diagnostic and prognostic procedures related to the examined subject. The signal processing methods adopted to the biomedical signals are investigated. The types of signals would be explained, as well as the role of modelling.

An overview of different signals acquired by specific biomedical equipment, and particular features of their processing techniques.

1D signals: action potential; BP, ECG, SBP, DBP, HR, EEG, EMG, specific data processing, compression; statistical analysis, artifact recognition and removal; RR and PI extraction from ECG and SBP signals, and problems. 2D signals, Radon transform, algebraic method for image reconstruction. ART, SIRT, SART. X-ray tomography. 4 generation of tomography equipment, spiral tomography, electronic tomography, artifacts, beam hardening, solutions. SPET and acquisition, exponential Radon transform, artifacts and elimination. PET image principles, electronic colimatior, attenuation elimination. NMR, description and problems. Ultrasound. Medical statistics.

1. Lectures and written exercises; 2. 1D signal processing: self-recording and signal processing using Schiller AT- 101 ECG equipment; processing the cardiovascular data from the Bezanijska Kosa hospital ; processing animal data from Medical Faculty – Belgrade and Institutes Stankovic, Pupin and Physics (with written permission of the institution that provided the signals). 3. Excursion to Imaging center of Sremska Kamenica – tomography signals CT, PET, NMR, Digital mammography, ultrasound. Students would process real recently recorded data for their project. tures and computer practice classes.