ECG Signal Denoising and Reconstruction Based on Basis Pursuit

The electrocardiogram (ECG) is widely used for the diagnosis of heart diseases. However, ECG signals are easily contaminated by different noises. This paper presents efficient denoising and compressed sensing (CS) schemes based on basis pursuit (BP). In process signal reconstruction, low-pass filtering method alternating direction multipliers (ADMM) optimization algorithm used. introduces dual variables, adds a secondary penalty term, reduces constraint conditions through alternate to optimize original variable at same time. able remove both baseline wander Gaussian white noise. effectiveness validated records MIT-BIH arrhythmia database. simulations show that proposed ADMM-based performs better in denoising. Furthermore, this keeps details reconstruction achieves higher signal-to-noise ratio (SNR) smaller mean square error (MSE).