An ECG R-wave detection algorithm based on adaptive threshold

ECG signal plays an important role in the early detection and treatment of atrial fibrillation diseases. Detection and treatment of atrial fibrillation diseases attracted a wide range of national and international experts. The electrophysiological mechanism of paroxysmal atrial fibrillation is the foundation of studying the therapy for atrial fibrillation. R peak detection has become an important part of the ECG processing due to the R-wave amplitude with a large, easy-detection feature. However, the ECG signal in the acquisition process will be subject to a certain degree of interference, such as frequency interference, baseline drift and other issues, common R peak threshold algorithm cannot detect lower baseline ECG waveform, resulting undetected. To solve this problem, this paper presents R peak adaptive threshold extraction algorithm by setting thresholds and reexamining the mechanism for each cardiac cycle to improve the accuracy of the threshold algorithm. Simulation results show that the method is much simpler and more effective, and can real-time processing, which significantly improves the accuracy of the R peak detection and meets the requirements of clinical applications.