Using our tools backwards, AF detection by confusing time and frequency
M. Kraaijeveld (TU Delft - Electrical Engineering, Mathematics and Computer Science)
Richard Hendriks – Mentor (TU Delft - Signal Processing Systems)
Carolina Varon – Mentor (TU Delft - Signal Processing Systems)
Jorge Martinez – Graduation committee member (TU Delft - Multimedia Computing)
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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.