Atrial Fibrillation Detection

Atrial Fibrillation Detection refers to the use of advanced signal processing and machine learning techniques to analyze electrocardiogram (ECG) data for the identification and diagnosis of atrial fibrillation, a common type of arrhythmia. The primary goal is to enhance the accuracy and efficiency of detection, enabling early discovery and timely treatment to reduce the risk of severe complications such as stroke, thereby improving the patient's quality of life and prognosis. This technology holds significant application value in clinical diagnostics, remote monitoring, and personal health management systems.