Print Email Facebook Twitter Using our tools backwards, AF detection by confusing time and frequency Title Using our tools backwards, AF detection by confusing time and frequency Author Kraaijeveld, Michael (TU Delft Electrical Engineering, Mathematics and Computer Science; TU Delft Signal Processing Systems) Contributor Hendriks, R.C. (mentor) Varon, Carolina (mentor) Martinez, Jorge (graduation committee) Degree granting institution Delft University of Technology Programme Electrical Engineering | Signals and Systems Date 2024-01-09 Abstract Atrial Fibrillation or AF is the most common heart rhythm anomaly affecting millions of people. This work explores the possibilities of reinterpreting speech processing techniques for use in atrial fibrillation detection. An existing method of modelling single heartbeat, single lead ECG signals by means of an ARMA model's amplitude response as a time domain signal is implemented. The parameters of the models are then used for AF detection by means of detecting P wave absence. For this detection, the distribution of the P wave associated parameters is compared to a GMM model of normal sinus rhythm beats obtained from a large number of recordings from different sources. Subject heartAtrial FibrillationElectrocardiogram (ECG)ModellingDetectionARMA modelsGaussian Mixture Modeling (GMM) To reference this document use: http://resolver.tudelft.nl/uuid:fc37f3d2-2cd6-4068-ad79-893ffd9cdc1d Part of collection Student theses Document type master thesis Rights © 2024 Michael Kraaijeveld Files PDF Thesis_Michael_Kraaijeveld.pdf 4.59 MB Close viewer /islandora/object/uuid:fc37f3d2-2cd6-4068-ad79-893ffd9cdc1d/datastream/OBJ/view