| Course Unit Code | 450-2098/01 |
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| Number of ECTS Credits Allocated | 4 ECTS credits |
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| Type of Course Unit * | Compulsory |
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| Level of Course Unit * | First Cycle |
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| Year of Study * | Third Year |
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| Semester when the Course Unit is delivered | Summer Semester |
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| Mode of Delivery | Face-to-face |
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| Language of Instruction | Czech |
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| Prerequisites and Co-Requisites | |
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| Prerequisities | Course Unit Code | Course Unit Title |
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| 450-2097 | Devices for Assistive Technologies |
| Name of Lecturer(s) | Personal ID | Name |
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| KUB631 | Ing. Jan Kubíček, Ph.D. |
| Summary |
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Basic characteristics and classification of biological signals.
Time analysis of biological signals.
Frequency analysis of biological signals.
Introduction to time-frequency analysis of biological signals.
Filtration of biological signals.
Methods of decomposition and extraction of clinical parameters.
Basic methods for ECG, EEG and EMG analysis.
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| Learning Outcomes of the Course Unit |
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| The goal of the subject signal processing in eHealth is to introduce students with the general methods for the biological signal processing, and specific methods, which are associated with particular kinds of the biological signals. Within the subject, individual domains of the signal processing will be discussed and analyzed: time, frequency and time frequency domain. Consequently, attention will be paid to basic approaches for the filtration and decomposition of the biological signals with the goal of the clinical information extraction. The last part of the subject will deal with basics of the ECG, EEG and EMG processing. |
| Course Contents |
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Lectures:
Basic characteristics and classification of the biologic signals: computer representation, discretization, types, biological origin, diagnostic, time, frequency, and time-frequency analysis.
Convolution analysis of the biological signals: analysis of the continuous and discrete convolution.
Spectral analysis of the biologic signals: Fourier series, Fourier transformation, algorithms for the FFT, spectral density, spectral energy, frequency spectra.
Filtration of the biological signals: synthesis of the analog and digital filters, FIR and IIR filters, notch filter, recursive filters, and filter frequency analysis.
The EEG signal analysis: the ECG signal representation, compressed spectral array (CSA), topographic mapping of the electrophysiological activity, interpolation of the spatial information, amplitude and frequency mapping, local coherency and phase measuring.
The ECG signal analysis: the noise analysis of the ECG signal, ECG signal representation, algorithms for the QRS complex extraction, Pan Tompkins algorithm, the R peak detection, ECG signal classification and calculation of the heart rate variability (HRV).
The PPG signal analysis: the PPG signal noise analysis, representation of the PPG signal, detection of the heart systolic phase and comparison of the heart rate from the PPG and ECG signal.
Analysis of the EMG signal: genesis, representation, features, measuring of the EMG signal, and basic methods of the EMG processing.
Laboratories:
Introduction to MATLAB and basic signal characteristics.
Implementation of convolution for biological sig nal processing.
Implementation of basic methods for frequency analysis: Fourier series and transformation, calculation of FFT.
Proposal of basic digital filters in MATLAB.
Basic algorithms for EEG processing.
Implementation of algorithms for filtration and detection ECG significant parts.
Algorithms for PPG processing.
Algorithms for time-frequency signal analysis in application of EMG signal processing.
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| Recommended or Required Reading |
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| Required Reading: |
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[1] De Luca, G.: Fundamental Concepts in EMG Signal Acquisition; DelSys Inc, 2001.
[2] OWEN, Mark. Practical signal processing. Cambridge: Cambridge University Press, 2007. ISBN 978-0-521-85478-8.
[3] UNCINI, Aurelio. Fundamentals of adaptive signal processing. Cham: Springer, [2015]. ISBN 978-3-319-02806-4.
[4] BRUCE, Eugene N. Biomedical signal processing and signal modeling. New York: Wiley, c2001. ISBN 0-471-34540-7.
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[1] KRAJČA, Vladimír a Jitka MOHYLOVÁ. Číslicové zpracování neurofyziologických signálů. V Praze: České vysoké učení technické, 2011. ISBN 978-80-01-04721-7.
[2] UHLÍŘ, Jan a Pavel SOVKA. Číslicové zpracování signálů. Praha: České vysoké učení technické, 1995. ISBN 80-01-01303-0.
[3] BRTNÍK, Bohumil a David MATOUŠEK. Algoritmy číslicového zpracování signálů. Praha: BEN - technická literatura, 2011. ISBN 978-80-7300-400-2.
[4] HLAVÁČ, Václav a Miloš SEDLÁČEK. Zpracování signálů a obrazů. Praha: Vydavatelství ČVUT, 2001 dotisk. ISBN 80-01-02114-9.
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| Recommended Reading: |
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[1] STRANNEBY, Dag. Digital signal processing: DSP and applications. Oxford: Newnes, 2001. ISBN 0-7506-4811-2.
[2] OPPENHEIM, Alan V a Ronald W SCHAFER. Discrete-time signal processing. 3rd ed., Pearson new international ed. Harlow: Pearson, c2014. ISBN 978-1-292-02572-8.
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[1] JAN, Jiří. Číslicová filtrace, analýza a restaurace signálů. 2. upr. a rozš. vyd. Brno: VUTIUM, 2002. ISBN 80-214-1558-4.
[2] GACEK, Adam a Witold PEDRYCZ, ed. ECG signal processing, classification and interpretation: a comprehensive framework of computational intelligence. London: Springer, c2012. ISBN 978-085729-867-6.
[3] VONDRÁK, Ivo. Umělá inteligence a neuronové sítě. 2. vyd. Ostrava: VŠB - Technická univerzita Ostrava, 2002. ISBN 80-7078-949-2.
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| Planned learning activities and teaching methods |
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| Lectures, Individual consultations, Tutorials, Experimental work in labs |
| Assesment methods and criteria |
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| Task Title | Task Type | Maximum Number of Points
(Act. for Subtasks) | Minimum Number of Points for Task Passing |
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| Credit and Examination | Credit and Examination | 100 (100) | 51 |
| Credit | Credit | 40 | 21 |
| Examination | Examination | 60 | 31 |