Nov 17 – 18, 2022
Mercure Budapest Castle Hill
Europe/Budapest timezone

Classifying ECG signlas using linear laws

Not scheduled
20m
Mercure Budapest Castle Hill

Mercure Budapest Castle Hill

Budapest, Ntak:Sz19000364, Szálloda, Krisztina krt. 41-43, 1013•(06 1) 488 8100

Speaker

Peter Posfay (Eötvös Lóránd University)

Description

I introduce a new method called linear law-based feature space transformation (LLT) which can be applied in the analysis of time series. This method builds on ideas from physics and data science. It implements a transformation of the input time series in such a way that the resulting feature set can be effectively used for classification tasks. After describing the method, I present its application for classifying healthy and ectopic ECG signals. First the linear law-based transformation is applied on the ECG dataset than it is studied how different classification methods perform on it. Based on the method 93% - 97% accuracy can be achieved using simple methods like support vector machines, KNNs and random forests.

Primary authors

Peter Posfay (Eötvös Lóránd University) Antal Jakovác Marcell Tamás Kurbucz (Wigner RCP)

Presentation materials

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