455-0318/01 – Biological Signals Processing (ZBS)

Gurantor departmentDepartment of Measurement and ControlCredits4
Subject guarantorIng. Jitka Mohylová, Ph.D.Subject version guarantorIng. Jitka Mohylová, Ph.D.
Study levelundergraduate or graduateRequirementChoice-compulsory
YearSemesterwinter
Study languageCzech
Year of introduction2003/2004Year of cancellation2009/2010
Intended for the facultiesFEIIntended for study typesMaster
Instruction secured by
LoginNameTuitorTeacher giving lectures
KRA48 doc. Ing. Vladimír Krajča, CSc.
MOH35 Ing. Jitka Mohylová, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Combined Credit and Examination 2+12

Subject aims expressed by acquired skills and competences

The goal of this course is to give an information about several biomedical signals and their digital signal processing - spectral analysis (frequency and phase spectrum, autocorrelation and cross-correlation analysis), segmentation, classification, fuzzy analysis and methods of display. Acquired knowledge and skill in this subject and the whole alignment forms the basic presumption of knowledge of biomedical engineering. Graduates will have an appropriate knowledge of techniques, equipments, systems and facilities for acquiring, processing and transferring information and how to use such information in practice. They will be able to apply this knowledge in order to interpret, describe and solve engineering problems.

Teaching methods

Lectures
Individual consultations
Tutorials
Project work

Summary

Characteristics of biological signals, coding data structures, digital signal processing - time domain and frequency domain - spectral analysis (Fourier analysis random (biological) signal and parametric spectrum analysis of random (biological) signal. Adaptive segmentation, automatic classifying biological signal - learning operations, cluster analysis. Neural networks.Applications of signal processing EKG, EEG.

Compulsory literature:

Mohylová,J., Krajča, V.: Zpracování biosignálů. Skriptum VŠB TUO, 2007 Proakis, J.G., Manolakis, D.G.: Introduction to Digital Signal Processing. Macmillan Publishing Company , New York, 1988 (ISBN 0-02-396815-X)

Recommended literature:

Cohen A., Biomedical signal processing, CRC Press, Boca Raton, Florida Remond, A.: (Editor-in-chief): Handbook of electroencephalograph and clinical neuro-physiology, vol. 5. Elsevier, 1972 Dumermuth G., Fundamentals of spectral analysis in electroencephalography, In: A. Rémond (Ed.), EEG Informatics : A Didactic Review of Methods and Applications of EEG data Processing. Elsevier, Amsterdam,1977, pp. 83-105 Svatoš J., Biologické signály I. Geneze, zpracování a analýza. Skriptum ČVUT FEL,1995 Mohylová J.,Využití číslicového zpracování signálů EEG pro lokalizaci epileptického ložiska. Disertační doktorská práce, 1999 Literatura doporučená (separáty článků lze získat u přednášejícího)

Way of continuous check of knowledge in the course of semester

Evaluation criteria are oriented on outputs allowing: • Continuous verifying of student knowledge in the numerical exercises in a form of debate and inquiries to achieve student active participations in study process. Identify, deduce and search of problem solving and their interpretation by students. • Tests from numerical exercises, eventually from chosen theoretical circuits • Term work and projects on a given theme on the basis of selection, investigation, ordering and final compilation of facts and their processing into final form of given theme.

E-learning

Další požadavky na studenta

Prerequisities

Subject has no prerequisities.

Co-requisities

Subject has no co-requisities.

Subject syllabus:

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, Back-propagation algorithm, Independent component analysis - ICA. Hebbian learning. Principal Component Analysis (PCA), Multichannel signals - compression and reconstruction. Self-organized neural net (Doc. Ing. Vladimir Krajca, Csc). 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, fundamental algorithm and output 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.)

Conditions for subject completion

Full-time form (validity from: 1960/1961 Summer semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Exercises evaluation and Examination Credit and Examination 100 (100) 51
        Exercises evaluation Credit 40 (40) 0
                Laboratory work Laboratory work 40  0
        Examination Examination 60 (60) 0
                Written examination Written examination 30  0
                Oral Oral examination 30  0
Mandatory attendence parzicipation:

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Occurrence in study plans

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2006/2007 (M2612) Electrical Engineering and Computer Science (2601T004) Measurement and Control Engineering P Czech Ostrava 5 Optional study plan
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2006/2007 (M2612) Electrical Engineering and Computer Science (2612T018) Electronics and Communication Technology P Czech Ostrava Choice-compulsory study plan
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2006/2007 (N2649) Electrical Engineering (2601T004) Measurement and Control Engineering P Czech Ostrava 2 Optional study plan
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2005/2006 (M2612) Electrical Engineering and Computer Science (2601T004) Measurement and Control Engineering P Czech Ostrava Choice-compulsory study plan
2005/2006 (M2612) Electrical Engineering and Computer Science (2612T018) Electronics and Communication Technology P Czech Ostrava Choice-compulsory study plan
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2004/2005 (M2612) Electrical Engineering and Computer Science (2612T018) Electronics and Communication Technology P Czech Ostrava Choice-compulsory study plan
2004/2005 (M2612) Electrical Engineering and Computer Science (2642T004) Electrical Machines, Apparatus and Drives (10) Elektrické stroje a přístroje P Czech Ostrava Choice-compulsory study plan
2004/2005 (M2612) Electrical Engineering and Computer Science (2642T004) Electrical Machines, Apparatus and Drives (20) Elektrické pohony a výkonová elektronika P Czech Ostrava Choice-compulsory study plan
2004/2005 (M2612) Electrical Engineering and Computer Science (3902T023) Computer Science P Czech Ostrava Choice-compulsory study plan
2004/2005 (M2612) Electrical Engineering and Computer Science (3907T001) Electrical Power Engineering P Czech Ostrava Choice-compulsory study plan
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2003/2004 (M2612) Electrical Engineering and Computer Science (2601T004) Measurement and Control Engineering P Czech Ostrava Choice-compulsory study plan
2003/2004 (M2612) Electrical Engineering and Computer Science (2612T018) Electronics and Communication Technology P Czech Ostrava Choice-compulsory study plan
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2003/2004 (M2612) Electrical Engineering and Computer Science (2642T004) Electrical Machines, Apparatus and Drives (20) Elektrické pohony a výkonová elektronika P Czech Ostrava Choice-compulsory study plan
2003/2004 (M2612) Electrical Engineering and Computer Science (3902T023) Computer Science P Czech Ostrava Choice-compulsory study plan
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