A combined application of independent component analysis and projective filtering of the time-aligned ECG beats is proposed to solve the problem of fetal ECG extraction from multi-channel maternal abdominal electric signals. The developed method is employed to process the four-channel abdominal signals recorded during twin pregnancy. The signals are complicated mixtures of the maternal ECG, the...

Electrocardiogram (ECG) is the cheap and noninvasive method of depicting the heart activity and abnormalities. It provides information about the functionality of the heart. It is the record of variation of bioelectric potential with respect to time as the human heart beats. The classification of ECG signals is an important application since the early detection of heart diseases/abnormalities ca...

ECG signals i.e. electrocardiogram are the significant physiological signals. In spotting and diagnosis of lots of cardiac arrhythmias, analyzing ECG signals is a crucial task. ECG signals can be generated severally by heart construction as a unique system, via heart compression. Atrial fibrillation (AF) is the almost usual confirmed heart beat arrhythmia and it disrupts the heart’s normal beat...

Electrocardiogram (ECG) and magnetocardiogram (MCG) signals are among the most considerable sources of noise for other biomedical signals. In some recent works, a Bayesian filtering framework has been proposed for denoising the ECG signals. In this paper, it is shown that this framework may be effectively used for removing cardiac contaminants such as the ECG, MCG and ballistocardiographic arti...

With the development of wireless sensing, researchers have proposed many contactless vital sign monitoring systems, which can be used to monitor respiration rates, heart cardiac cycles and etc. However, these signs are ones coarse granularity, so they less helpful in diagnosis cardiovascular diseases (CVDs). Considering that electrocardiogram (ECG) is an important evidence base for diagnoses CV...