|
|
Detection of true complete left bundle branch block
Opravilová, Kamila ; Vítek, Martin (referee) ; Smíšek, Radovan (advisor)
The aim of this bachelor thesis is to get acquainted with the theory regarding electrophysiology of the heart and the pathology of Left Bundle Branch Block, LBBB for short. One of the goals is to make annotated database of QRS complexes for testing the LBBB algorithms. Next step will be to write and test these algorithms. Detection of LBBB is important, because it is one of the predictors of successfulness of resynchronization therapy. Conventional criteria for detection are not usable because of their low accuracy, that is why Straus' criteria had been made, those are way more accurate. This programme will abide these criteria. The overall evaluation of successfulness of this algorithm's detection is 100 % sensitivity and 69 % specifity. Therefore we can determine which patients do not suffer from LBBB without the risk of being wrong.
|
|
|
Accelerometer-based quality estimation and segmentation of ECG signal and compression of high-quality segments
Opravilová, Kamila ; Smital, Lukáš (referee) ; Němcová, Andrea (advisor)
This diploma thesis is devoted to segmentation of ECG signal based on its quality and compression of quality segments suitable for diagnostics (in telemedicine). A completely new approach is to use accelerometer data to estimate ECG signal quality. This is possible thanks to the Bittium Faros mobile recorder. It records both the ECG signal motion – accelerometric data. A total of 34 features were extracted from accelerometric data. Using these features the predictive model was taught to classify the ECG signal into 3 quality groups according to the level of noise. Quality segments were compressed. The wavelet transform in combination with high-frequency bands zeroing and length encoding was used as a compression method.
|
|
|
Automatické měření efektivní refrakterní periody srdeční tkáně
Ředina, Richard ; Filipenská, Marina
Elektrofyziologické vyšetření jako jedna z možností léčby arytmií je i v dnešní době stále časově náročný výkon. S cílem snížení této časové zátěže prezentujeme vyvinutý algoritmus, který z měřeného EKG automaticky určuje efektivní refrakterní periodu (ERP) tkáně. Algoritmus sestává z především filtrace a detekce lokálních extrémů v signálech. Algoritmus byl testován na interní databázi signálů získaných od deseti pacientů, kteří podstoupili elektrofyziologické vyšetření. Výstup algoritmu se shodoval s elektrofyziologem stanovenou ERP v devíti z deseti případů (σ = 6 ms). Pro svou relativní úspěšnost a nenáročnou implementaci slibuje možné využití v real-time aplikaci během vyšetření, při kterém by mohl plně automatizovat a tím i urychlit stimulační protokoly.
|
|
|
Accelerometer-based quality estimation and segmentation of ECG signal and compression of high-quality segments
Opravilová, Kamila ; Smital, Lukáš (referee) ; Němcová, Andrea (advisor)
This diploma thesis is devoted to segmentation of ECG signal based on its quality and compression of quality segments suitable for diagnostics (in telemedicine). A completely new approach is to use accelerometer data to estimate ECG signal quality. This is possible thanks to the Bittium Faros mobile recorder. It records both the ECG signal motion – accelerometric data. A total of 34 features were extracted from accelerometric data. Using these features the predictive model was taught to classify the ECG signal into 3 quality groups according to the level of noise. Quality segments were compressed. The wavelet transform in combination with high-frequency bands zeroing and length encoding was used as a compression method.
|
|
|
Detection of true complete left bundle branch block
Opravilová, Kamila ; Vítek, Martin (referee) ; Smíšek, Radovan (advisor)
The aim of this bachelor thesis is to get acquainted with the theory regarding electrophysiology of the heart and the pathology of Left Bundle Branch Block, LBBB for short. One of the goals is to make annotated database of QRS complexes for testing the LBBB algorithms. Next step will be to write and test these algorithms. Detection of LBBB is important, because it is one of the predictors of successfulness of resynchronization therapy. Conventional criteria for detection are not usable because of their low accuracy, that is why Straus' criteria had been made, those are way more accurate. This programme will abide these criteria. The overall evaluation of successfulness of this algorithm's detection is 100 % sensitivity and 69 % specifity. Therefore we can determine which patients do not suffer from LBBB without the risk of being wrong.
|
guest ::
