1. Introduction to the cardiac diagnosis – course objectives, integration of anatomy, physiology and technical methods
2. Anatomy and physiology of the heart – heart structure and chambers, pulmonary and systemic circulation, valves, heart wall: endocardium, myocardium, epicardium, coronary circulation
3. Lead systems and vectorcardiography – multi-lead ECG, bipolar and unipolar leads, Goldberger leads, twelve-lead ECG, vectorcardiography, cardiac axis
4. ECG acquisition – hardware – electrodes and placement, isotonic gel, Ag/AgCl electrodes, dynamic range and bandwidth, input impedance, noise suppression, protection against impulses, amplifiers, galvanic isolation
5. ECG acquisition – software – detection of stimuli, global waves and intervals, ECG presentation (conventional and Cabrera), ECG testers, standards and regulations
6. ECG filtering – noise sources (baseline drift, hum, myopotentials), software filtering, QRS enhancement, linear, nonlinear and adaptive filters
7. R-wave detection – detection principles, QRS spectrum and morphology, Pan–Tompkins algorithm, alternative detection methods
8. Heart rate variability (HRV) – tachogram, preprocessing, detrending, R-wave error correction, time, geometric and frequency-domain methods, HRV parameters, non-clinical applications
9. Arrhythmology – ECG measurement and analysis, heart rate, intervals and segments, complex morphology, tachycardia/bradycardia, respiratory arrhythmia, multifocal, junctional and ventricular rhythms, extrasystoles, blocks, electrophysiology, catheter ablation
10. Optical mapping of the heart – action potential: origin, morphology, refractory periods, optical recording, propagation in the heart wall, vector visualization

1. Recording and evaluation of single-lead ECG using medical-grade and wearable systems.
2. Recording and assessment of changes in cardiac axis inclination during sitting, supine position, and controlled breathing.
3. Design and construction of a simple ECG sensor on a solderless breadboard.
4. Construction of an ECG sensor using an Olimex shield and the Arduino platform.
5. Real-time visualization of the ECG waveform in the Processing environment.
6. Software-based filtering of noise and artifacts in ECG signals, including analysis of their impact on ECG readability.
7. Implementation of algorithms for R-wave detection.
8. Use of software libraries for heart rate variability (HRV) analysis and their comparative evaluation (benchmarking).
9. Identification of arrhythmological phenomena in ECG recordings and work with cardiac arrhythmia simulators. 

During individual preparation for the final exam, students review the main principles, methods, and technical aspects covered in the course. They work through the provided list of exam questions and reinforce their understanding of diagnostic procedures and practical applications.