OBJECTIVE To determine the incidence and clinical characteristics of persistent left superior vena cava (PLSVC) among low-risk pregnancies. We have also compared electrocardiography (ECG) parameters of infants with PLSVC with those of normal controls. METHOD At our institute, fetal echocardiogram is routinely performed in the midtrimester. We retrospectively reviewed the records of prenatally...

FPGAs (Field Programmable Gate Arrays) are finding wide acceptance in medical systems for their ability for rapid prototyping of a concept that requires hardware/software co-design, for performing custom processing in parallel at high data rates and be programmed in the field after manufacturing. The main tasks in ECG signal analysis are the detection of how fast heart is beating, whether the r...

ECG is a method using to measure the rate and regularity of heartbeats to detect any irregularity in a heart. ECG translates heart electrical activity into wave-line on paper or screen. Our investigations show that heartbeat modulation exists in human voice signal and can be extracted by transformations in frequency domain. In this paper, the 2D spectrum of human vowel speech will be used to ex...

Mental stress is one of the well-known major risk factors for many diseases such as Hypertension, Coronary Artery Disease, and Heart Attack. This research paper places the emphasis on ECG signal processing for recognition of stress. Feature extraction of ECG is done with the help of lab view and then those features which are affected are classified. Results shown that ST wave, QRS wave, T wave ...

An Electrocardiogram signals change their statistical property over time and ECG signals are highly non-stationary signals. Growing of embedded technology has provided powerful tools to analysis of ECG. ECG is advanced recording method of bioelectric signal which is originated in the heart and it provides valuable information about the activity of human heart. Different types of features of the...

This paper presents a novel maximum margin clustering method with immune evolution (IEMMC) for automatic diagnosis of electrocardiogram (ECG) arrhythmias. This diagnostic system consists of signal processing, feature extraction, and the IEMMC algorithm for clustering of ECG arrhythmias. First, raw ECG signal is processed by an adaptive ECG filter based on wavelet transforms, and waveform of the...

Electrocardiogram is used to measure the rate and regularity of heartbeats to detect any irregularity to the heart. An ECG translates the heart electrical activity into wave-line on paper or screen. For the feature extraction and classification task we will be using discrete wavelet transform (DWT) as wavelet transform is a two-dimensional timescale processing method, so it is suitable for the ...

OBJECTIVE To assess the value of the STAN fetal heart monitor for intrapartum fetal monitoring using cardiotocography (CTG) and fetal electrocardiography (ECG). DESIGN Prospective observational study. MATERIAL AND METHODS Between August 2000 and November 2002, 637 high-risk labors were monitored using a STAN S21 fetal heart monitor, providing CTG plus automatic ST analysis of the fetal ECG....

The recognition of data from the electrocardiogram (ECG) is the important area of the biomedical signal processing. Identification of ECG signals in real time is closely related to the classification of the patient's diagnosis, inspected for the purpose of diagnosis of the cardiac status. In our paper we analyze the suitable alorithms for the extraction of QRS complex from the raw ECG data. Thi...

In this paper, we address the imminent problem which arises when researchers unjudiciously use a linear and instantaneous (memoryless) model for the source mixing structures of independent component analysis (ICA), also known as blind source separation (BSS), in persuit of separating noisy and frequently nonstationary combined mother and fetal electrocardiogram (ECG) signals from cutaneous meas...