Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal ComEngApp : Computer Engineering and Applications Journal
Ghina Auliya
Computer Engineering Department
Computer Science & IT Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Detection of Atrial Fibrillation Based on Long Short-Term Memory Ghina Auliya; Jannes Effendi
Computer Engineering and Applications Journal Vol 10 No 1 (2021)
Publisher : Universitas Sriwijaya

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (518.744 KB) | DOI: 10.18495/comengapp.v10i1.361

Abstract

Atrial fibrillation is a quivering or irregular heartbeat (arrhythmia) that can lead to blood clots, stroke, heart failure, and even sudden cardiac death. This study used several public datasets of electrocardiogram (ECG) signals, including MIT-BIH Atrial Fibrillation, China Physiological Signal Challenge 2018, MIT-BIH Normal Sinus Rhythm based on QT-Database, and Fantasia Database. All datasets were divided into 3 cases with the experiment windows size 10, 5, and 2 seconds for two classes, namely Normal and Atrial Fibrillation. The recurrent neural networks method is appropriate for processing sequential data such as ECG signals, and k-fold Cross-Validation can help evaluate models effectively to achieve high performance. Overall, LSTM performance achieved accuracy, sensitivity, specificity, precision, F1-score, is 94.56% 94.67%, 94.67%, 94.43%, and 94.51%.
Co-Authors Jannes Effendi