An Innovative Method for Fetal Health Monitoring Based on Artificial Neural Network Using Cardiotocography Measurements

摘要

This work proposes an ANN based method for fetal heart rate monitoring. Various measurements are taken and given as input to the ANN based classifier to detect fetal health such as 'Normal', 'Suspect' and 'Pathologic'. All the design and simulation works are carried out with MATLAB software. ANN based classifier is trained with data from various recordings of cardiotocography. After the network is trained it is tested with various test cases. Performance of the network is checked in terms of percentage accuracy. The proposed method is found to be 99.9% accurate in detecting the fetal health. Hence the proposed ANN based method can be used effectively for fetal health monitoring.