The course introduces techniques and procedures for analysis of biomedical signals and images like: cardiology signals (electrocardiogram - ECG), neurophysiology signals (electromyogram - EMG, electroencephalogram - EEG), medical images (computed tomography – CT images) with the emphasis on problems of biomedical researches. We will recognize how we can automatically, non-invasive and punctually, within 24-hour electrocardiogram signals, detect heart beats, classify them, and detect transient ischaemic disease, which is one of the most terrible heart diseases; and if we do not discover it punctually, it may lead to heart infarct. We will see how we can, using some non-linear signal processing techniques, analyze electromyograms recorded from the abdomen of a pregnant women, early during pregnancy (23 rd week), estimate, or try to predict, danger of pre-term birth. We will recognize techniques of analyzing electroencephalographic signals, which are recorded from the head of a person, with the aim of human-computer interaction, without using classic input devices. We will also recognize techniques of analysis of 3-dimensional tomographic images with the aim of extraction and visualization of anatomic structures of human body organs. The topics cover: representation of international standardized databases of signal samples (MIT/BIH DB, LTST DB, TPEHG DB, EEGMMI DS, BCI DB, CTIMG DB), techniques of feature extraction from signals and images (band-pass filters, morphological algorithms, principal components, Karhunen-Loeve transform, sample entropy, contour extraction), noise extraction, techniques of visualization of diagnostic and morphology feature-vector time series, and anatomic structures, analysis of feature-vector time series, spectral analysis, modelling, event detection, clustering, classifications, as well as metrics, techniques and protocols to evaluate performance and robustness of biomedical computer systems.