콘텐츠 본문
논문 해외 국제전문학술지(SCI급) CNN based atrial fibrillation diagnosis with ECG signals
- 학술지 구분 국제전문학술지(SCI급)
- 게재년월 2021-11
- 저자명 정의림공동(교신),김성현
- 학술지명 Natural Volatiles and Essential Oils
- 발행처명 Badebio Biotechnololgy Ltd
- 발행국가 해외
- 논문언어 외국어
- 전체저자수 2
논문 초록 (Abstract)
Background/Objectives: Atrial Fibrillation (AFib), one of the arrhythmias, causes the atrium to beat irregularly. AFib can be diagnosed by observing electrocardiogram (ECG) signals. However, the degree of irregular running depends on the patient, and it is difficult to detect AFib in early patients. As a result, it is important to accurately judge Sinus Rhythm (SR) and AFib, and only doctors with extensive experience in cardiology are known to judge accurately. In this paper, we propose a convolutional neural network (CNN) to perform accurate AFib diagnosis from ECG signals.
