Abstract
The fetal heart rate (FHR) signal processing based on Artificial Neural Networks (ANN),Fuzzy Logic (FL) and frequency domain Discrete Wavelet Transform(DWT) were analysis in order to perform automatic analysis using personal computers. Cardiotocography (CTG) is a primary biophysical method of fetal monitoring. The assessment of the printed CTG traces was based on the visual analysis of patterns that describing the variability of fetal heart rate signal. Fetal heart rate data of pregnant women with pregnancy between 38 and 40 weeks of gestation were studied. The first stage in the system was to convert the cardiotocograghy (CTG) tracing in to digital series so that the system can be analyzed ,while the second stage ,the FHR time series was transformed using transform domains Discrete Wavelet Transform(DWT) in order to obtain the system features .At the last stage the approximation coefficients result from the Discrete Wavelet Transform were fed to the Artificial Neural Networks and to the Fuzzy Logic, then compared between two results to obtain the best for classifying fetal heart rate.
Highlights
IntroductionMany methods are used in fetal heart rate analysis, time and frequency domain analysis of heart rate variability are the most commonly used noninvasive methods to evaluate autonomic regulation of heart rate in healthy fetus [1]
Many methods are used in fetal heart rate analysis, time and frequency domain analysis of heart rate variability are the most commonly used noninvasive methods to evaluate autonomic regulation of heart rate in healthy fetus [1].Cardiotocography (simultaneous recording of fetal heart rate (FHR) and uterine contractions) is one of the most used diagnostic techniques to evaluate fetal well-being and to investigate the functional state of the fetal autonomic nervous system
Fetal heart rate monitoring-signal intervals were determined in a high precision autocorrelation method, and a time series of fetal heart rate fluctuation was obtained
Summary
Many methods are used in fetal heart rate analysis, time and frequency domain analysis of heart rate variability are the most commonly used noninvasive methods to evaluate autonomic regulation of heart rate in healthy fetus [1]. Cardiotocography (simultaneous recording of fetal heart rate (FHR) and uterine contractions) is one of the most used diagnostic techniques to evaluate fetal well-being and to investigate the functional state of the fetal autonomic nervous system. A comparison between DWT combined with neural networks and DWT combined with Fuzzy Logic System based on fetal heart rate baseline record in (20min)are done. This will allow adding a new mode for fetal HR device(EFM) as an indicator of fetal state. This will assist the physician in early diagnosis of fetal abnormalities especially in fetal hypoxia
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