Accurate RR-Interval Detection with Daubechies Filtering and Adaptive Thresholding

摘要

Abstract QRS detection is needed for electrocardiogram (ECG) signal analysis, including the Heart Rate Variability (HRV) analysis, which is the physiological phenomenon of variation of the time intervals between two consecutive heartbeats. R is the point corresponding to the peak of a QRS complex of ECG waves. RR-interval is defined as the interval between two successive Rs. We proposed an algorithm to acquire RR-interval based on a leveI-4 Stationary Wavelet Transform (SWT) to decompose ECG signal followed by an adaptive thresholding algorithm to separate QRS complex from other unwanted signals. Daubechies filter is chosen as the mother wavelet, because its shape of the scaling function resembles a QRS complex. The proposed algorithm is simulated by MATLAB, where 48 files from MIT-BIH arrhythmia database are used as benchmarks to verify the algorithm. Simulation results show 99.64% of sensitivity and 99.48% of positive predictivities.