Atrial fibrillation detection by DFA and SDCST methods

Article type: Research Article

Authors: Vargas, Regis Nunes^{a; *} | Veiga, Antônio Cláudio Paschoarelli^a | Linhares, Raquel Romes^b

Affiliations: [a] Electrical Engineering College, Federal University of Uberlândia, Minas Gerais, Brazil | [b] Faculty of Mathematics, Federal University of Uberlândia, Minas Gerais, Brazil

Correspondence: [*] Corresponding author: Regis Nunes Vargas, Electrical Engineering College, Federal University of Uberlândia, Minas Gerais, Brazil. E-mail: [email protected].

Abstract: Many cardiac disorders were diagnosed by analyzing an electrocardiogram signal, in particular, atrial fibrillation. We join the SDCST method with the Detrended Fluctuation Analysis (DFA) and the backpropagation net to identify atrial fibrillation in one hundred ECG signals obtained from Physionet Challenge 2017 database. The accuracy of the proposed classifier parameter is 97% for the training set and 95% for the test set.

Keywords: Atrial fibrillation, ECG, DFA, SDCST

DOI: 10.3233/MAS-210532

Journal: Model Assisted Statistics and Applications, vol. 16, no. 3, pp. 189-196, 2021