Deep Learning-Based Approach for Atrial Fibrillation Detection

Lazhar Khriji*, Marwa Fradi, Mohsen Machhout, Abdulnasir Hossen

*المؤلف المقابل لهذا العمل

نتاج البحث: Conference contribution

12 اقتباسات (Scopus)

ملخص

Atrial Fibrillation (AF) is a health-threatening condition, which is a violation of the heart rhythm that can lead to heart-related complications. Remarkable interest has been given to ECG signals analysis for AF detection in an early stage. In this context, we propose an artificial neural network ANN application to classify ECG signals into three classes, the first presents Normal Sinus Rhythm NSR, the second depicts abnormal signal with Atrial Fibrillation (AF) and the third shows noisy ECG signals. Accordingly, we achieve 93.1% accuracy classification results, 95.1% of sensitivity, 90.5% of specificity and 98%. Furthermore, we yield a value of zero error and a low value of cross entropy, which prove the robustness of the proposed ANN model architecture. Thus, we outperform the state of the art by achieving high accuracy classification without pre-processing step and without high level of feature extraction, and then we enable clinicians to determine automatically the class of each patient ECG signal.

اللغة الأصليةEnglish
عنوان منشور المضيفThe Impact of Digital Technologies on Public Health in Developed and Developing Countries - 18th International Conference, ICOST 2020, Proceedings
المحررونMohamed Jmaiel, Hamdi Aloulou, Mounir Mokhtari, Bessam Abdulrazak, Slim Kallel
ناشرSpringer
الصفحات100-113
عدد الصفحات14
رقم المعيار الدولي للكتب (المطبوع)9783030515164
المعرِّفات الرقمية للأشياء
حالة النشرPublished - ديسمبر 1 2020
الحدث18th International Conference on Smart Homes and Health Telematics, ICOST 2020 - Hammamet, Tunisia
المدة: يونيو ٢٤ ٢٠٢٠يونيو ٢٦ ٢٠٢٠

سلسلة المنشورات

الاسمLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
مستوى الصوت12157 LNCS
رقم المعيار الدولي للدوريات (المطبوع)0302-9743
رقم المعيار الدولي للدوريات (الإلكتروني)1611-3349

Conference

Conference18th International Conference on Smart Homes and Health Telematics, ICOST 2020
الدولة/الإقليمTunisia
المدينةHammamet
المدة٦/٢٤/٢٠٦/٢٦/٢٠

ASJC Scopus subject areas

  • ???subjectarea.asjc.2600.2614???
  • ???subjectarea.asjc.1700.1700???

بصمة

أدرس بدقة موضوعات البحث “Deep Learning-Based Approach for Atrial Fibrillation Detection'. فهما يشكلان معًا بصمة فريدة.

قم بذكر هذا