TY - JOUR
T1 - A Review on Atrial Fibrillation Detection from Ambulatory ECG
AU - Ma, Caiyun
AU - Xiao, Zhijun
AU - Zhao, Lina
AU - Biton, Shany
AU - Behar, Joachim A.
AU - Long, Xi
AU - Vullings, Rik
AU - Aarts, Ronald M.
AU - Li, Jianqing
AU - Liu, Chengyu
N1 - Publisher Copyright:
IEEE
PY - 2023
Y1 - 2023
N2 - Atrial fibrillation (AF) is a prevalent clinical arrhythmia disease and is an important cause of stroke, heart failure, and sudden death. Due to the insidious onset and no obvious clinical symptoms of AF, the status of AF diagnosis and treatment is not optimal. Early AF screening or detection is essential. Internet of Things (IoT) and artificial intelligence (AI) technologies have driven the development of wearable electrocardiograph (ECG) devices used for health monitoring, which are an effective means of AF detection. The main challenges of AF analysis using ambulatory ECG include ECG signal quality assessment to select available ECG, the robust and accurate detection of QRS complex waves to monitor heart rate, and AF identification under the interference of abnormal ECG rhythm. Through ambulatory ECG measurement and intelligent detection technology, the probability of postoperative recurrence of AF can be reduced, and personalized treatment and management of patients with AF can be realized. This work describes the status of AF monitoring technology in terms of devices, algorithms, clinical applications, and future directions.
AB - Atrial fibrillation (AF) is a prevalent clinical arrhythmia disease and is an important cause of stroke, heart failure, and sudden death. Due to the insidious onset and no obvious clinical symptoms of AF, the status of AF diagnosis and treatment is not optimal. Early AF screening or detection is essential. Internet of Things (IoT) and artificial intelligence (AI) technologies have driven the development of wearable electrocardiograph (ECG) devices used for health monitoring, which are an effective means of AF detection. The main challenges of AF analysis using ambulatory ECG include ECG signal quality assessment to select available ECG, the robust and accurate detection of QRS complex waves to monitor heart rate, and AF identification under the interference of abnormal ECG rhythm. Through ambulatory ECG measurement and intelligent detection technology, the probability of postoperative recurrence of AF can be reduced, and personalized treatment and management of patients with AF can be realized. This work describes the status of AF monitoring technology in terms of devices, algorithms, clinical applications, and future directions.
KW - Ambulatory ECG
KW - Artificial intelligence
KW - Atrial fibrillation
KW - Atrial fibrillation (AF)
KW - Biomedical monitoring
KW - Electrocardiogram (ECG)
KW - Electrocardiography
KW - Monitoring
KW - Rhythm
KW - Wearable computers
UR - http://www.scopus.com/inward/record.url?scp=85174856587&partnerID=8YFLogxK
U2 - 10.1109/TBME.2023.3321792
DO - 10.1109/TBME.2023.3321792
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C2 - 37812543
AN - SCOPUS:85174856587
SN - 0018-9294
SP - 1
EP - 17
JO - IEEE Transactions on Biomedical Engineering
JF - IEEE Transactions on Biomedical Engineering
ER -