Using second generation wavelets for ECG characteristics points detection

Recently, there is a growing need to apply wavelet techniques within embedded applications, like biomedical wearable sensors. This paper presents our method of using second generation wavelets via lifting scheme in electrocardiogram (ECG) denoising, detrending and characteristic points detection using just one decomposition phase. We also present application of enhanced level-based detail coefficients thresholding method to reduce overlapping energy between QRS-complex signal and P/T waves signal which further simplifies detection rules. A total of 11 characteristics points are detected from the ECG waves that describes the various ECG waves and segments and achieved 99.50% positive predictivity performance for QRS complex detection.