A review on atrial fibrillation detection from ambulatory ECG

Caiyun Ma, Zhijun Xiao, Lina Zhao, Shany Biton, Joachim A. Behar, Xi Long (Corresponding author), Rik Vullings, Ronald M. Aarts, Jianqing Li, Chengyu Liu

Onderzoeksoutput: Bijdrage aan tijdschriftTijdschriftartikelAcademicpeer review

Samenvatting

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.

Originele taal-2Engels
Artikelnummer10274126
Pagina's (van-tot)876-892
Aantal pagina's17
TijdschriftIEEE Transactions on Biomedical Engineering
Volume71
Nummer van het tijdschrift3
Vroegere onlinedatum9 okt. 2023
DOI's
StatusGepubliceerd - 1 mrt. 2024

Financiering

This work was supported in part by the National Natural Science Foundation of China under Grants 62171123, 62071241, 62201144, and 62211530112, in part by the Natural Science Foundation of Jiangsu Province under Grant BK20192004, and in part by the Postgraduate Research & Practice Innovation Program of Jiangsu Province under Grant KYCX21_0089.

FinanciersFinanciernummer
Postgraduate Research & Practice Innovation Program of Jiangsu ProvinceKYCX21_0089
National Natural Science Foundation of China62171123, 62211530112, 62071241, 62201144
Natural Science Foundation of Jiangsu ProvinceBK20192004

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