Advanced Methods of Data Analysis and Processing

This course comprehends/deals methods of biosignal generation, biosignal acquisition and basic parameters of biosignals required for diagnostics. Methods and algorithms for biosignal processing, analysis and evaluation used for biological signals, mainly electrophysiological signals. Preprocessing, filtering, time and frequency analysis. Use of modern spectral analysis methods. Visualisation of results, topographic mapping, method of compressed spectral arrays (CSA). Adaptive segmentation of non-stationary signals is discussed. Application of methods using artificial intelligence. Methods of automated signal classification - supervised/unsupervised, cluster analysis, learning classifier. Artificial neural networks (ANN). Practical application of biosignal processing. Case studies of ANN application on epileptogenic recordings and neural recordings in general. Genetic algorithms and simulated annealing is presented.

Comprehend and be able to apply methods of biosignal processing.

Requirements for credit: Compulsory active attendance at the exercise. Successfully completed credit test (min. 50%).

The evaluation is carried out according to the ECTS scale on the basis of the results of the credit test.

• Mandatory:
• 1. SÖRNMO, Leif a Pablo LAGUNA. Bioelectrical signal processing in cardiac and neurological applications. Amsterdam: Elsevier Academic Press, ©2005. xiii, 668 s. ISBN 0-12-437552-9
• 2. SANEI, Saeid a Jonathon A. CHAMBERS. EEG signal processing. Chichester: Wiley, ©2007. xxii, 289 s. ISBN 978-0-470-02581-9
• 3. COHEN, Mike X. Analyzing neural time series data: theory and practice. Cambridge, Massachusetts: MIT, ©2014. xv, 578 s. Issues in clinical and cognitive neuropsychology. ISBN 978-0-262-01987-3
• Recommended:
• 4. MALMIVUO, Jaakko. a Robert PLONSEY. Bioelectromagnetism: principles and applications of bioelectric and biomagnetic fields. New York: Oxford University Press, 1995. xxii, 482 s., příl. ISBN 0-19-505823-2
• 5. PRINCIPE, José C., Neil R. EULIANO a W. Curt LEFEBVRE. Neural and adaptive systems: fundamentals through simulations. New York: Wiley, c2000. ISBN 0-471-35167-9.
• 6. HAYKIN, Simon S. Neural networks and learning machines. 3rd ed. New York: Pearson, c2009. ISBN 978-0-13-147139-9.

lectures and tutorian sessions