Compressed sensing reconstruction: Comparative study with applications to ECG bio-signals

Compressed sensing (CS) is a rapidly emerging signal processing technique that enables accurate capture and reconstruction of sparse signals from only a fraction of Nyquist- rate samples, significantly reducing the data-rate and system power consumption. This paper presents an in-depth comparative study on current state-of-the-art CS reconstruction algorithms. Reliability, accuracy, noise tolerance, computation time and are used as key metrics. Further, experiments on ECG signals are used to assess performance on real-world bio-signals.