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QRS detection using zero crossing counting
Hanus, Rostislav ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
This master’s thesis deals with the detection of QRS complex detection using zero crossing counts. QRS detection is an important part of the analysis of ECG signal. From the point of determining the R wave detection is based on the other waves and intervals necessary for the diagnosis of heart. This method is very effective even for very noisy signals. Implementation of the method in Matlab, and the success of detection is tested on the CSE and MIT-BIH database. The optimization algorithm is an optional value for the detector.
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Biometric fingerprint liveness detection
Váňa, Tomáš ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
This master‘s thesis deals with biometric fingerprint liveness detection. The theoretical part of the work describes fingerprint recognition biometric systems, fingerprint liveness detection issues and methods for fingerprint liveness detection. The practical part of the work describes proposed set of discriminant features and preprocessing of fingerprint image. Proposed approach using neural network to detect a liveness. The algorithm is tested on LivDet database comprising real and fake images acquired with tree sensors. Classification performance approximately 93% was obtained.
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Methods of noise suppression for speech recognition systems
Moldříková, Zuzana ; Smital, Lukáš (referee) ; Odstrčilík, Jan (advisor)
This diploma thesis deals with methods of noise suppression for speech recognition systems. In theoretical part are discussed basic terms of this topic and also methods for noise suppression. These are spectral subtraction, Wiener filtering, RASTA, mapping of spectrogram or algorithms based on noise estimation. In second part types of noise are analyzed, there is proposal and implementation of spectral subtraction method of noise suppression for speech recognition system. Also extensive testing of spectral subtractive algorithms in comparison with Wiener filter is conducted. Assessment of this testing is done with defined metrics, successfulness of recognition, recognition system score and signal to noise ratio.
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Multilead decision rules in delineation of ECG signals
Richter, Zdeněk ; Smital, Lukáš (referee) ; Vítek, Martin (advisor)
This work deals with ECG signal measuring and methods of its processing. It compares some of the QRS detection methods and describes some of the testing databases. In this work a detector of QRS complex is realized, it is based on the approach of zero crossings. Next section makes combination of results from separate leads to one, which improves efficiency of detection. One section of this work deals with design and realization delination of ECG signal. In the last part outputs of this delineation are compared with the results of the other authors.
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Sleep stage classification
Lacinová, Michaela ; Smital, Lukáš (referee) ; Králík, Martin (advisor)
This bachelor thesis deals with analysis of polysomnography and its methods of measurement in electroencephalography, electromyography and electrooculography in the first part. It comprises an analysis of sleep stages recommended by the AASM. Polysomnographic data are further analysed in the domains of time and frequency, which are evaluated separately. In the second part the data are classified into particular classes using methods of decision trees and k-nearest neighbours in the MATLAB programming environment. These data are evaluated and compared with available literature.
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Wavelet Filtering of ECG Signal
Slezák, Pavel ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
The thesis deals with possibilities of using wavelet transform in applications dealing with noise reduction, primarily in the field of ECG signals denoising. We assess the impact of the various filtration parameters setting as the thresholding wavelet coefficients method, thresholds level setting and the selection of decomposition and reconstruction filter banks.. Our results are compared with the results of linear filtering. The results of wavelet Wieners filtration with pilot estimation are described below. Mainly, we tested a combination of decomposition and reconstruction filter banks. All the filtration methods described here are tested on real ECG records with additive myopotential noise character and are implemented in the Matlab environment.
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Detection of ischemia in ECG
Tichý, Pavel ; Smital, Lukáš (referee) ; Ronzhina, Marina (advisor)
This paper describes the manifestations of ischemia in the ECG signals and summarizes some methods allowing automatic detection of ischemia. Morphological features were then calculated from ECG signals available from UBMI and statistically evaluated to select features appropriate for further automatic classification. Multilayer feedforward neural network was used for classification of heart beats. The neural network was designed in Matlab. Classification performance up to 99.9% was obtained on available dataset.
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Wavelet Filtering of ECG Signals
Handl, Marek ; Smital, Lukáš (referee) ; Kozumplík, Jiří (advisor)
The work deals with the wavelet transformation, focusing on wavelet transforms with discrete time (DTWT). The practical part is focused on the implementation of redundant packet DTWT and its use in the filtration of ECG signals. The main part of the work is to design wiener filter that uses redundant packet DTWT, designed to eliminate interference myopotentials of ECG signals. The actual solution is implemented in Matlab. Testing is performed on the library CSE using noise model myopotentials used to noising original signals. For optimum parameters designed filter is used the genetic algorithm (GA). The work is carried out comparing the proposed filter redundant packet DTWT a variant of redundant dyadic DTWT.
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Heart sounds Detection in phonocardiogram
Pecníková, Michaela ; Čmiel, Vratislav (referee) ; Smital, Lukáš (advisor)
An algorithm is proposed for the detection of first and second heart sound in this Bachelor’s thesis. The first part describes the anatomy of heart, the activity of heart and creation of PCG signal. Next, typical characteristics of PCG signal are described in the thesis. Algorithm for the detection of first and second heart sound is based on the normalized average Shannon energy of PCG signal. The algorithm for the detection of first and second heart sound was implemented in MATLAB. The performance of the algorithm has been evaluated using 66 recordings of PCG signal with 1388 cycles.
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