450-2098/01 – Signal Processing in eHealth (ZSeH)

Gurantor departmentDepartment of Cybernetics and Biomedical EngineeringCredits4
Subject guarantorIng. Jan Kubíček, Ph.D.Subject version guarantorIng. Jan Kubíček, Ph.D.
Study levelundergraduate or graduateRequirementCompulsory
Year3Semestersummer
Study languageCzech
Year of introduction2019/2020Year of cancellation
Intended for the facultiesFEIIntended for study typesBachelor
Instruction secured by
LoginNameTuitorTeacher giving lectures
KUB631 Ing. Jan Kubíček, Ph.D.
Extent of instruction for forms of study
Form of studyWay of compl.Extent
Full-time Credit and Examination 2+2
Part-time Credit and Examination 0+16

Subject aims expressed by acquired skills and competences

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.

Teaching methods

Lectures
Individual consultations
Tutorials
Experimental work in labs

Summary

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.

Compulsory literature:

[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.

Recommended literature:

[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.

Way of continuous check of knowledge in the course of semester

Within the academic term, students will do the project from the area of the biomedical signal processing. The academic year will be concluded by the test.

E-learning

Other requirements

There are not further student’s requirements.

Prerequisities

Subject codeAbbreviationTitleRequirement
450-2097 PAT Devices for Assistive Technologies Compulsory

Co-requisities

Subject has no co-requisities.

Subject syllabus:

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.

Conditions for subject completion

Part-time form (validity from: 2019/2020 Winter semester)
Task nameType of taskMax. number of points
(act. for subtasks)
Min. number of points
Credit and Examination Credit and Examination 100 (100) 51
        Credit Credit 40  21
        Examination Examination 60  31
Mandatory attendence parzicipation: Students will solve 10 laboratory tasks within the exercises. For getting the index, it is necessary to attend at least 80 % of exercises and submit protocols from these exercises.

Show history

Occurrence in study plans

Academic yearProgrammeField of studySpec.ZaměřeníFormStudy language Tut. centreYearWSType of duty
2022/2023 (B0714A060018) Biomedical Assistive Technology AT P Czech Ostrava 3 Compulsory study plan
2022/2023 (B0714A060018) Biomedical Assistive Technology AT K Czech Ostrava 3 Compulsory study plan
2021/2022 (B0714A060018) Biomedical Assistive Technology AT P Czech Ostrava 3 Compulsory study plan
2021/2022 (B0714A060018) Biomedical Assistive Technology AT K Czech Ostrava 3 Compulsory study plan
2020/2021 (B0714A060018) Biomedical Assistive Technology AT K Czech Ostrava 3 Compulsory study plan
2020/2021 (B0714A060018) Biomedical Assistive Technology AT P Czech Ostrava 3 Compulsory study plan

Occurrence in special blocks

Block nameAcademic yearForm of studyStudy language YearWSType of blockBlock owner