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National Repository of Grey Literature 2 records found  Search took 0.01 seconds. 
Detection of atrial fibrillation using ECG Signals
 Běhunčíková, Vendula ; Ronzhina, Marina (referee) ; Kozumplík, Jiří (advisor)
Atrial fibrillation is one of the most common cardiac rhythm disorders. The prevalence of atrial fibrillation is reported at 1-6 % of the adult population. The chances of developing atrial fibrillation increase with age. An early detection of this arrhythmia is a key to prevent more serious conditions. Many ways have been found to detect atrial fibrillation episodes in ECG including deep learning methods. The aim of this bachelor’s thesis is to describe the problem of atrial fibrillation and the methods used for detection in the ECG record, design an atrial fibrillation detector and test its results. Detector is implemented using a Matlab R2020b software.
Detailed record
Detection of atrial fibrillation using ECG Signals
 Běhunčíková, Vendula ; Ronzhina, Marina (referee) ; Kozumplík, Jiří (advisor)
Atrial fibrillation is one of the most common cardiac rhythm disorders. The prevalence of atrial fibrillation is reported at 1-6 % of the adult population. The chances of developing atrial fibrillation increase with age. An early detection of this arrhythmia is a key to prevent more serious conditions. Many ways have been found to detect atrial fibrillation episodes in ECG including deep learning methods. The aim of this bachelor’s thesis is to describe the problem of atrial fibrillation and the methods used for detection in the ECG record, design an atrial fibrillation detector and test its results. Detector is implemented using a Matlab R2020b software.
Detailed record

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