Lectures:
Signals in medicine - origin, character and common principles processing biological signal, view of methods and algorithms processing biological signal, EEG, EMG, ECG, EOG. Origin, resources, diagnostics. Chances of exercise bioengineer.
Processing biological signal in real-time and off line. Statistical properties, probability distribution, stochastic processes, analysis of signals in time domain, analysis of signals in frequency domain
Data about patient, identification files. Collection and preprocessing biological data, A/D inverter, aliasing. Filtering. Trends.
Spectral analysis I. - fundamental method. Power spectral density, parametric and non-parametric method. Practical problems estimation of spectra. Cross spectrum, coherency and phase.
Spectral analysis II. - FFT. Application. Method compressed spectral array (CSA). Extraction of the hidden information from signals - local and interhemispheric coherence, phase, measurement of small time differences between EEG channels, time delay
Topographic mapping of brain activity - principle. Use in clinical diagnostics. Dynamic mapping
Adaptive segmentation - Adaptive segmentation with fixed and moving window, Segmentation using the two connected windows. Multichannel adaptive segmentation. Extraction symptoms.
Method automatic classification I - learning without teacher. Structure of data, classes, cluster analysis, fuzzy analysis. K-means algorithm. Limits and limitation fuzzy analyses.
Neural networks, Automatic classification II. - learning classifier, Kohonen layer, classification, classical set theory, fuzzy set theory. Compare with neural net.
Long-term EEG processing, automatic epileptic spike detection. Arithmetical detector, median detector, spike detector based on combination of classical filtering and median filtering
ECG signal, digital processing, characteristics. - frequency analysis, filtration, adaptive filtration. Data reduction, Holter's techniques patient identification.
Respirometry, description signal data. Demand on digital processing and graphic presence.
Video signal - image processing, Presentation in discrete form.
Computer labs:
Introduction into processing biosignal. Practical examples of EEG, EMG, ECG activities, epileptic graphoelements, artefacts.
Statistical characteristics of biosignals. Software. User's interface. Data format.
I Semester work - reading and displaying real signal, term: 1 week
Collection and preprocessing biological data. Data reading in classical and paperless apparatus. A/D inverter Nyquist theorem. Mistakes at transmission.
Spectral analysis I. Fundamental method. Spectral analysis and synthesis - FFT. Filtration, windowing.
II Semester work. Spectral analysis and synthesis of signal term: 2 weeks
Topographic mapping. Demonstration topographic of brain activity - spectral, phase, time delay and coherence mapping - iterative generation map. Animation.
Spectral analysis II - application CSA. Coherence analysis
III Semester work Topographic (brain) mapping - net with 20 point term: 2 weeks
Adaptive segmentation - setting parameter, preference and limitation, algorithm.
Method automatic classification I - learning without teacher. Fundamental algorithm of cluster analyses on simulated data. Examples classification EEG data. Using fuzzy set.
Analysis long-term signal. Summary information.
Extraction compressed information from long-term signal. Applications on real data, further method, programme WaveFinder.
Automatic classification II - learning classifier. Demonstration fundamental algorithm learning classifier on simulated and data. Using fuzzy set in to-NN classifier
IV semester work: 3-NN learning classifier for simulated data. Term: 2 for weeks
Automatic epileptic spike detection - Demonstration commercial programme (Gotman, Scherg, FOCUS).
Preprocessing ECG signal using of wavelet transformation: compression, filtration, artefacts. Calculation of frequency, amplitude and phase spectrum.
One detector algorithm of QRS complex - calculation and comparison, using method detection R-R internals depending on morbid state and variability heart rhythm. Practical demonstration fully automatic evaluative system signal ECG on regional hygienic station in Ostrava.
(Excurse in computerized EEG laboratory Neurological department FN Bulovka. Consultation record semester washing.)
Signals in medicine - origin, character and common principles processing biological signal, view of methods and algorithms processing biological signal, EEG, EMG, ECG, EOG. Origin, resources, diagnostics. Chances of exercise bioengineer.
Processing biological signal in real-time and off line. Statistical properties, probability distribution, stochastic processes, analysis of signals in time domain, analysis of signals in frequency domain
Data about patient, identification files. Collection and preprocessing biological data, A/D inverter, aliasing. Filtering. Trends.
Spectral analysis I. - fundamental method. Power spectral density, parametric and non-parametric method. Practical problems estimation of spectra. Cross spectrum, coherency and phase.
Spectral analysis II. - FFT. Application. Method compressed spectral array (CSA). Extraction of the hidden information from signals - local and interhemispheric coherence, phase, measurement of small time differences between EEG channels, time delay
Topographic mapping of brain activity - principle. Use in clinical diagnostics. Dynamic mapping
Adaptive segmentation - Adaptive segmentation with fixed and moving window, Segmentation using the two connected windows. Multichannel adaptive segmentation. Extraction symptoms.
Method automatic classification I - learning without teacher. Structure of data, classes, cluster analysis, fuzzy analysis. K-means algorithm. Limits and limitation fuzzy analyses.
Neural networks, Automatic classification II. - learning classifier, Kohonen layer, classification, classical set theory, fuzzy set theory. Compare with neural net.
Long-term EEG processing, automatic epileptic spike detection. Arithmetical detector, median detector, spike detector based on combination of classical filtering and median filtering
ECG signal, digital processing, characteristics. - frequency analysis, filtration, adaptive filtration. Data reduction, Holter's techniques patient identification.
Respirometry, description signal data. Demand on digital processing and graphic presence.
Video signal - image processing, Presentation in discrete form.
Computer labs:
Introduction into processing biosignal. Practical examples of EEG, EMG, ECG activities, epileptic graphoelements, artefacts.
Statistical characteristics of biosignals. Software. User's interface. Data format.
I Semester work - reading and displaying real signal, term: 1 week
Collection and preprocessing biological data. Data reading in classical and paperless apparatus. A/D inverter Nyquist theorem. Mistakes at transmission.
Spectral analysis I. Fundamental method. Spectral analysis and synthesis - FFT. Filtration, windowing.
II Semester work. Spectral analysis and synthesis of signal term: 2 weeks
Topographic mapping. Demonstration topographic of brain activity - spectral, phase, time delay and coherence mapping - iterative generation map. Animation.
Spectral analysis II - application CSA. Coherence analysis
III Semester work Topographic (brain) mapping - net with 20 point term: 2 weeks
Adaptive segmentation - setting parameter, preference and limitation, algorithm.
Method automatic classification I - learning without teacher. Fundamental algorithm of cluster analyses on simulated data. Examples classification EEG data. Using fuzzy set.
Analysis long-term signal. Summary information.
Extraction compressed information from long-term signal. Applications on real data, further method, programme WaveFinder.
Automatic classification II - learning classifier. Demonstration fundamental algorithm learning classifier on simulated and data. Using fuzzy set in to-NN classifier
IV semester work: 3-NN learning classifier for simulated data. Term: 2 for weeks
Automatic epileptic spike detection - Demonstration commercial programme (Gotman, Scherg, FOCUS).
Preprocessing ECG signal using of wavelet transformation: compression, filtration, artefacts. Calculation of frequency, amplitude and phase spectrum.
One detector algorithm of QRS complex - calculation and comparison, using method detection R-R internals depending on morbid state and variability heart rhythm. Practical demonstration fully automatic evaluative system signal ECG on regional hygienic station in Ostrava.
(Excurse in computerized EEG laboratory Neurological department FN Bulovka. Consultation record semester washing.)