Analysis techniques. All these techniques and algorithms have their advantages and limitations. This proposed paper discusses various techniques and transformations proposed earlier in literature for extracting feature from an ECG signal. In addition this paper also provides a comparative study of various methods proposed by researchers in extracting the feature from ECG signal.

Fetal MRI is an essential tool for analyzing morphological changes of fetal brain structure. The automated methods developed for adult brain extraction are unsuitable for fetal brain extraction because of the differences in tissue types and tissue properties between adult and fetal brain. However, only few automated fetal brain segmentation methods are available. In this paper we propose a full...

This paper presents the experimental pilot study to investigate the effects of pulsed electromagnetic field (PEMF) at extremely low frequency (ELF) in response to photoplethysmographic (PPG), electrocardiographic (ECG), electroencephalographic (EEG) activity. The assessment of wavelet transform (WT) as a feature extraction method was used in representing the electrophysiological signals. Consid...

Fetal cardiac function is increasingly recognized as a marker of disease severity and prognosis in selected fetal conditions. Magnetic resonance imaging (MRI) has been used in experimental (animal) fetal cardiology but the lack of a noninvasive fetal electrocardiogram (ECG) to trigger image acquisition remains a major limiting factor precluding its application in humans. Fetal medicine speciali...

Methods for handling imprecision and uncertainty in computer-based analysis of fetal heart rate patterns and ECG wave shape during childbirth are presented. Computational intelligence models, based on fuzzy logic techniques, that explicitly handle the imprecision and uncertainty inherent in the data obtained during childbirth and methods of interpreting the data are proposed. The ability to han...

In this paper we present the benefits of long-term ECG data collection. Extraction of “nontraditional” variables and multimodal information from ECG signals can be used to estimate current, predict future health status, and detect any health anomalies and trends of an individual before subjective signs appear.

Extraction of the foetal electrocardiogram from single-channel maternal abdominal signals without disturbing its morphology is difficult. We propose to solve the problem by application of projective filtering of time-aligned ECG beats. The method performs synchronization of the beats and then employs the rules of principal component analysis to the desired ECG reconstruction. In the first stage...

Feature extraction and classification of electrocardiogram (ECG) signals are necessary for the automatic diagnosis of cardiac diseases. In this study, a novel method based on genetic algorithm-back propagation neural network (GA-BPNN) for classifying ECG signals with feature extraction using wavelet packet decomposition (WPD) is proposed. WPD combined with the statistical method is utilized to ...

Applications based on electrocardiogram (ECG) signal feature extraction and classification are of major importance to the autodiagnosis of heart diseases. Most studies on ECG classification methods have targeted only 1or 2-lead ECG signals. This limitation results from the unavailability of real clinical 12-lead ECG data, which would help train the classification models. In this study, we propo...