ECG noise removal and QRS complex detection using UWT

Abstract

The electrocardiogram (ECG) is widely used for diagnosis of heart diseases. Generally, the recorded ECG signal is often contaminated by noise. In order to extract useful information from the noisy ECG signals, the raw ECG signals has to be processed. The baseline wandering is significant and can strongly affect ECG signal analysis. The detection of QRS complexes in an ECG signal provides information about the heart rate, the conduction velocity, the condition of tissues within the heart as well as various abnormalities. It supplies evidence for the diagnosis of cardiac diseases. The signal denoising can be done by Discrete Wavelet Transforms but the results obtained from it are not optimal mainly due to the loss of the invariant translation property. This takes us to the Undecimated Wavelet Transform(UWT) which has invariant translation characteristic, better capacity to reduce noise and better peak detection. In this study, we propose an effective technique for the denoising of ECG signals corrupted by nonstationary noises using UWT, which is implemented with Laboratory Virtual Instrumentation Engineering Workbench (LabVIEW) platform.