An Electrocardiogram (ECG) signal describes the electrical activity of the heart recorded by electrodes placed on the surface of human body. It summarizes an important electrical activity used for the primary diagnosis of heart abnormalities such as Tachycardia, Bradycardia, Normalcy, Regularity and Heart Rate Variation. The most clinically useful information of the ECG signal is found in the t...

Electrocardiogram (ECG) signal for human identity recognition is a new area on biometrics research. The ECG is a vital signal of human body, unique, robustness to attack, universality and permanence, difference to others traditional biometrics technic. This study also proposes Adaptive Multilayer Generalized Learning Vector Quantization (AMGLVQ), that integrating feature extraction and classifi...

Early fetal cardiac diseases and heart abnormalities can be detected appropriately treated by monitoring health during pregnancy. Advancements in computer sciences the technology of sensors show that is possible to monitor electrocardiogram (fECG). Both signal processing experimental aspects are needed investigated fECG. In this study, we aim design realize a non invasive fECG system. first par...

The aim of this paper is to detect fetal heart beats temporally overlapping with the transabdominally-measured QRS-complexes of the mother, non-invasively. Modified, Weighted and uterine contraction interference signal covariance matrix incorporated spectral MUSIC technique is applied. It is based on partitioning the subspace containing the ECG signal bearing the mother and fetal, and the ortho...

Abstract— In this paper we report on the separation of maternal and fetal heartbeats from electrocardiogram (ECG) recordings based on a sparse generative signal model. The proposed algorithm uses Bayesian learning strategies to both learn the characteristic PQRST complexes and then infer their time location. Reconstruction of the signal based on each of the learned PQRST complexes leads to a se...

An inference engine for classification of Electrocardiogram (ECG) signals is developed with the help of a rule based rough set decision system. For this purpose an automated data extraction system from ECG strips is being developed by using a few image processing techniques. A knowledge base is developed after consulting different medical books as well as feedback of reputed cardiologists on in...

Due to the low percentage of fetal DNA present in maternal plasma (< 10%) during early gestation, efficient extraction processes are required for successful downstream detection applications in non-invasive prenatal diagnostic testing. In this study, two extraction methods using similar chemistries but different workflows were compared for isolation efficiency and percent fetal DNA recovery. Th...