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Updated: Jul 14, 2025

Patient Directed Recording of a Bipolar Three-Lead Electrocardiogram using a Smartwatch with ECG Function
Published on: December 11, 2019
A Review on Atrial Fibrillation Detection From Ambulatory ECG
Insights
Early screening for atrial fibrillation (AF) is crucial for preventing stroke and heart failure. Wearable electrocardiograph (ECG) devices using AI and IoT offer effective AF detection, improving patient management.
Area of Science:
- Cardiology
- Biomedical Engineering
- Digital Health
Background:
- Atrial fibrillation (AF) is a common arrhythmia linked to stroke, heart failure, and sudden death.
- Subtle onset and lack of clear symptoms hinder optimal AF diagnosis and treatment.
- Early detection and screening are vital for effective AF management.
Conclusions:
- Ambulatory ECG monitoring using advanced technologies is essential for early AF detection.
- Addressing challenges in signal quality, QRS detection, and rhythm interference is key.
- Future directions involve refining devices, algorithms, and clinical applications for comprehensive AF care.
Abstract:
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.
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