Real-time detection of imminent ventricular fibrillation using mean and standard deviation of beat-to-beat HRV
AbstractIt is estimated that 50% of all cardiovascular deaths are caused by a sudden cardiac arrest (SCA), which represents 15% of global mortality, and its main cause is ventricular fibrillation (VF). Therefore, it is of interest to design new methods capable to detect changes in heart rate (HR or RR interval) that could announce the beginning of an imminent fibrillation. In this work, an effective novel indicator, based on mean and standard deviation of Heart Rate Variability (HRV), was studied and used to develop an algorithm that predicts imminent VF with 100% sensitivity and 100% specificity. The study was based on 65 RR intervals signals. The algorithm’s simplicity provides a quick-to-use implementation in a micro controller unit (MCU) for real-time VF detection, allowing its application in a variety of medical devices with electrocardiogram (ECG) modules.