Classification of fetal abnormalities based on CTG signal

Abstract EN

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.