This paper provides a comprehensive review of compressed sensing or compressive
sampling (CS) in bioelectric signal compression applications. The aim is to provide a …

Compressed Sensing (CS) is a fast growing signal processing technique that compresses
the signal while sensing and enables exact reconstruction of the signal if the signal is sparse …

Electrocardiogram (ECG) is an important diagnostic biosignal, indicative of many signs of
health. Recent advances in biological data processing require improvements in the ability to …

Effective compression of Electrocardiogram (ECG) is a vital task in telecardiology
application. Compressed sensing (CS) offers a low energy implementation based solution to …

Multiclass motor imagery classification is essential for brain–computer interface systems
such as prosthetic arms. The compressive sensing of EEG helps classify brain signals in real …

Non-negative constrained dictionary learning for compressed sensing of ECG signals -
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In this paper, we have investigated the different Daubechies (DB) wavelet-based
compressed sensing (CS) matrices, namely db3, db4, db5, db6, db7, db8, db9, and db10 …

Compressed Sensing (CS) is a novel approach of compressing, which can reconstruct a
sparse signal much below Nyquist rate of sampling. Though ECG signals can be well …

Cardiovascular disease is the leading cause of death in the United States. Tracking daily
changes in one's cardiovascular health can be critical in diagnosing and managing …

The recent growth of the personal medical devices and the precision medicine markets has
renovated the interest in searching extremely low power signal acquisition solutions …