This chapter examines which method is most appropriate for controlling fetal well-being in childbirth in healthy women, when and how to use fetal monitoring and how to interpret it. The following methods of fetal control will be assessed: intermittent auscultation (IA), intermittent electronic fetal monitoring (CEFM), analysis of the ST segment of the fetal ECG (STAN), fetal pulse oximetry, fet...

ECG (Electrocardiogram) signals originating from heart muscles, generate massive volume of digital data. They need to be compressed or approximated for efficient transmission and storage. ECG signal compression is traditionally performed in three ways: direct, transform and parameter extraction. Polynomial approximation which is a form of parameter extraction method, is employed here. This pape...

In this paper, we propose a mew ECG pattern classification model based on a generic feature extraction method. The proposed classifier is applied for indicating supraventricual arrhythmia in order to verify the performance of the proposed approach. A generic approach based on a histogram of 1 derivative of signals is applied for feature extraction. Principal component analysis (PCA) is consider...

Noninvasive fetal health monitoring during pregnancy has become increasingly important in order to prevent complications, such as fetal hypoxia and preterm labor. With recent advances in signal processing technology using abdominal electrocardiogram (ECG) recordings, ambulatory fetal monitoring throughout pregnancy is now an important step closer to becoming feasible. The large number of electr...

Monitoring procedures are the basis to evaluate the clinical state of patients and to assess changes in their conditions, thus providing necessary interventions in time. Both these two objectives can be achieved by integrating technological development with methodological tools, thus allowing accurate classification and extraction of useful diagnostic information. The paper is focused on monito...

Automatic recognition of arrhythmias is particularly important in the diagnosis of heart diseases. This study presents an electrocardiogram (ECG) recognition system based on multi-domain feature extraction to classify ECG beats. An improved wavelet threshold method for ECG signal pre-processing is applied to remove noise interference. A novel multi-domain feature extraction method is proposed; ...

The paper presents a new algorithm for ECG signal compression based on local extreme extraction, adaptive hysteretic filtering and LZW coding. Basically the method consists in smoothing the ECG signal with a Savitzky-Golay filter, extraction of the local minima and maxima, a hysteretic filtering and LZW coding. The reconstruction of the ECG signal is done by cubic interpolation. The algorithm i...

Non-invasive fetal electrocardiograms (FECGs) are an alternative method to standard means of fetal monitoring which permit long-term continual monitoring. However, in abdominal recording, the FECG amplitude is weak in the temporal domain and overlaps with the maternal electrocardiogram (MECG) in the spectral domain. Research in the area of non-invasive separations of FECG from abdominal electro...

Fetal Electrocardiogram (FECG) can provide important clinical information for the assessment of fetal well-being. However, the extraction of FECG from the maternal abdominal wall remains an open problem due to various kinds of interferences and noises, where the maternal Electrocardiogram (MECG) is the dominant source of interference. In this study, a novel FECG extraction framework by combinin...