A Robust R Peak Detection Algorithm Using Wavelet Transform for Heart Rate Variability Studies

We propose in this work a method of electrocardiogram (ECG) signal pretreatment by the application of Discreet Wavelet Transform DWT by automatically determining the optimal order of decomposition. After the purification of the original signal, we describe an algorithm to detect R waves based on the Dyadic Wavelet Transform DyWT by applying a windowing process. This algorithm is validated on a sample of synthesis ECG signal with and without noise which we have proposed and on real data. Finally, once the R peaks of real data are detected, we use three methods of RR intervals analysis by calculating the standard deviation of heart rate and applying the Fast Fourier Transform FFT and the Wavelet Transform on detected RR intervals to study the Heart Rate Variability (HRV). A comparative study between the analysis results of detected RR intervals in healthy and diseased subjects through the application of the FFT and the Wavelet Transform will be given.