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Wavelet Based Filtering of Electrocardiograms
Smital, Lukáš ; Smékal, Zdeněk (referee) ; Halámek, Josef (referee) ; Kozumplík, Jiří (advisor)
This dissertation deals with possibilities of using wavelet transforms for elimination of broadband muscle noise in ECG signals. In this work, the characteristics of ECG signals and particularly the most frequently occurring type of interference are discussed firstly. The theory of wavelet transforms is also introduced and followed by design of the simple wavelet filter and the more sophisticated version with wiener filtering of wavelet coefficients. Next part is devoted to the design of our filter, which is based on wavelet wiener filtering and is complemented by algorithms that ensure full adaptability of its parameters when the properties of the input signal are changing. Suitable parameters of the proposed system are searched automatically and the algorithm is tested on the complete standard electrocardiograms database CSE, where it achieves significantly better results than other published methods.
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Wavelet Filtering of ECG Signals
Mrázek, Jiří ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
This thesis deals myopotential denoising of ECG signals with using wavelet transform. There was used wavelet denoising subsequently wiener wavelet filtering. In both cases were found the most suitable coeficients for the best denoising. It is meant mainly settings suitable parameters for ideal filtration setting value of threshold, number of decomposition level, selection of thresholding and type of filter. These parameters are tested on real signals. Denoising is realized in Matlab version R2009b.
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Muscle noise filtering in ECG signals
Fedorov, Vasilii ; Smíšek, Radovan (referee) ; Smital, Lukáš (advisor)
This work deals with problematic of muscle noise filtration in ECG signals. It contains theoretical and practical parts. In theoretical part we first mentioned a topicality of ECG scanning and filtration. Then we got acquainted with the origin of ECG, it's properties, and types of noises, that typically occurring there. Further different known methods of linear and non-linear techniques in EMG filtration were discussed. After we got acquainted with wavelet transform and its possibilities practical part was carried out in environment MATLAB 2020b®. Wiener wavelet filter was implemented and supplemented by a threshold adaptive function. Parameters were optimized with brute force method in reduced range. The evaluation of the filter took place on a CSE database, where the results were compared with the authors of other methods. In result the filter shows good filtration capabilities and stability.
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Muscle noise filtering in ECG signals
Fedorov, Vasilii ; Smíšek, Radovan (referee) ; Smital, Lukáš (advisor)
This work deals with problematic of muscle noise filtration in ECG signals. It contains theoretical and practical parts. In theoretical part we first mentioned a topicality of ECG scanning and filtration. Then we got acquainted with the origin of ECG, it's properties, and types of noises, that typically occurring there. Further different known methods of linear and non-linear techniques in EMG filtration were discussed. After we got acquainted with wavelet transform and its possibilities practical part was carried out in environment MATLAB 2020b®. Wiener wavelet filter was implemented and supplemented by a threshold adaptive function. Parameters were optimized with brute force method in reduced range. The evaluation of the filter took place on a CSE database, where the results were compared with the authors of other methods. In result the filter shows good filtration capabilities and stability.
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|
|
Wavelet Based Filtering of Electrocardiograms
Smital, Lukáš ; Smékal, Zdeněk (referee) ; Halámek, Josef (referee) ; Kozumplík, Jiří (advisor)
This dissertation deals with possibilities of using wavelet transforms for elimination of broadband muscle noise in ECG signals. In this work, the characteristics of ECG signals and particularly the most frequently occurring type of interference are discussed firstly. The theory of wavelet transforms is also introduced and followed by design of the simple wavelet filter and the more sophisticated version with wiener filtering of wavelet coefficients. Next part is devoted to the design of our filter, which is based on wavelet wiener filtering and is complemented by algorithms that ensure full adaptability of its parameters when the properties of the input signal are changing. Suitable parameters of the proposed system are searched automatically and the algorithm is tested on the complete standard electrocardiograms database CSE, where it achieves significantly better results than other published methods.
|
|
|
Wavelet Filtering of ECG Signals
Mrázek, Jiří ; Vítek, Martin (referee) ; Smital, Lukáš (advisor)
This thesis deals myopotential denoising of ECG signals with using wavelet transform. There was used wavelet denoising subsequently wiener wavelet filtering. In both cases were found the most suitable coeficients for the best denoising. It is meant mainly settings suitable parameters for ideal filtration setting value of threshold, number of decomposition level, selection of thresholding and type of filter. These parameters are tested on real signals. Denoising is realized in Matlab version R2009b.
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