Abstract

An electrocardiographic signal (ECG) is a signal that is generated from the continuous rhythm of the heartbeat. An ECG signal can detect and diagnose various heart conditions, including arrhythmia. A disturbance in the electrical impulses that control the heart's contractions can result in arrhythmia, which is a term for an irregular cardiac rhythm. This disruption can cause the heart to beat too quickly, too slowly, or irregularly. Depending on the underlying cause and the severity of the condition, arrhythmias may range from innocuous to life-threatening. This article examines recent advancements in deep learning concerning ECG signal arrhythmias. This article describes methods for detecting ECG signal arrhythmia that are based on deep learning. Database on arrhythmia signal research can use MIT-BIH Arrhythmia dataset, Chine Physiological Signal Challenge, Mediplex Sejong Hospital, Computing in Cardiology Challenge, China Medical University Hospital (CMUH), PhysioNet database, UVA Holter Recordings, Medical Center in Israel, namely BIDMC and UCI Repository. Deep learning methods are the most accurate, including Deep Learning Parallel Networks, Convolutional neural networks (CNN) with long short term memory (LSTM).

Original languageEnglish
Title of host publication2023 International Seminar on Intelligent Technology and Its Applications
Subtitle of host publicationLeveraging Intelligent Systems to Achieve Sustainable Development Goals, ISITIA 2023 - Proceeding
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages417-421
Number of pages5
ISBN (Electronic)9798350313956
DOIs
Publication statusPublished - 2023
Event24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023 - Hybrid, Surabaya, Indonesia
Duration: 26 Jul 202327 Jul 2023

Publication series

Name2023 International Seminar on Intelligent Technology and Its Applications: Leveraging Intelligent Systems to Achieve Sustainable Development Goals, ISITIA 2023 - Proceeding

Conference

Conference24th International Seminar on Intelligent Technology and Its Applications, ISITIA 2023
Country/TerritoryIndonesia
CityHybrid, Surabaya
Period26/07/2327/07/23

Keywords

  • Arrhythmia
  • Deep Learning
  • Signal ECG

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