Comparison of QRS peak detection algorithms in extracting HRV signal

Heart Rate Variability (HRV) represents an instantaneous heart rate signal including the beat-to-beat fluctuation in heart rate. In obtaining this signal, nonlinear filtering with thresholding is a common approach by which QRS complex in the ECG signal can be detected. In this paper, two QRS detection algorithms are described and compared. These algorithms involve adaptive thresholding and fixed thresholding methods, respectively. Each algorithm has its advantages and disadvantages in terms of accuracy and speed. Future work can be done to improve the algorithms with a better tradeoff between accuracy and speed. By processing the accurate and real time HRV signals, useful physiological information can be obtained.