450-2098/01 – Signal Processing in eHealth (ZSeH)
Gurantor department | Department of Cybernetics and Biomedical Engineering | Credits | 4 |
Subject guarantor | Ing. Jan Kubíček, Ph.D. | Subject version guarantor | Ing. Jan Kubíček, Ph.D. |
Study level | undergraduate or graduate | Requirement | Compulsory |
Year | 3 | Semester | summer |
| | Study language | Czech |
Year of introduction | 2019/2020 | Year of cancellation | |
Intended for the faculties | FEI | Intended for study types | Bachelor |
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:
Recommended literature:
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
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
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction
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