Abstract

Cardiotocography (CTG) is a method of monitoring fetal heart rate and uterine contractions during pregnancy. CTG is a methodology used to measure the fetal well-being in a pregnant woman. The objective of the paper is to reduce the fetal mortality. Data is being evaluated by applying pre-processing techniques, followed by Convolutional Neural Network (CNN) and dimensionality reduction using Principal Component Analysis (PCA). The approach adopted in the proposed method for detecting the fetal heart rate is evaluated using two methods, namely, conventional CNN and conventional CNN integrated with PCA. Using CNN algorithm around 77% has been achieved and CNN integrated with .PCA gave around 95% accuracy.

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