Atrial Fibrillation detection based on ECG-Features Extraction in WBSN

Wireless Body Sensor Networks (WBSNs) and wearable technology are the new trends in healthcare applications. This technology can provide real-time monitoring of the patient's bio-signals and health condition. In this context, the analysis of ECG signals, reflecting the heart activity, is considered as key tool in diagnosing cardiac disorders such as Atrial Fibrillation (AF) that can lead to strokes and heart failure. Classical approaches for sensor-based AF detection require continuous transmission of ECG signals to a remote server which can rapidly exhaust the sensor energy and shortens the lifetime of the application. In this paper, we propose a new low-power scheme for AF episodes detection in ECG signal that is intended for implementation in WBSN. The paper details the design of this scheme and demonstrates its high accuracy for AF detection.