Classification of fetal heart rate using grammatical evolution

There is an ongoing effort to develop advanced methods and computer-based systems to assist obstetricians in the difficult task of feature extraction and classification of the cardiotocogram (CTG), which is the most widely used electronic fetal monitoring (EFM) method worldwide. A novel method for feature construction is presented for efficient classification of CTG based on information extracted from fetal heart rate (FHR) signal. The proposed method is based on grammatical evolution in order to construct new features from existing ones using nonlinear transformations. This method is tested on a data set of intrapartum cases achieving accuracy of 92.5%.