Wavelet-based denoising and beat detection of ECG signal

This paper presents the design and implementation of an automatic ECG beat detection system. We proposed modifications to the existing Pan-Tompkins algorithm by introducing only one set of adaptive threshold computations to reduce the amount of data processing significantly. LabVIEW signal processing tools were used to test the performance of wavelet based analysis for denoising and feature extraction of the ECG signal. Our design achieved an overall accuracy of 99.51% when applied on the MIT/BIH Arrhythmia Database, which is far better than the old method of digital filtering.