A technology for obtaining a fetal heart rate from an electrocardiogram (ECG) signal. In one example, an artificial neural network model can be trained to predict a fetal heart rate using a training dataset containing ECG data. The artificial neural network model can include a first series of convolutional layers to separate a fetal ECG signal from a maternal ECG signal, a fast Fourier transform (FFT) layer to convert the fetal ECG signal to ECG frequency representations, and a dense layer to decode the ECG frequency representations to fetal heart rate predictions. After training the artificial neural network model, ECG data generated by an ECG monitor can be obtained, and the ECG data can be input to the artificial neural network model. The artificial neural network model outputs a fetal heart rate prediction, wherein the fetal heart rate prediction represents the fetal heart rate obtained from the ECG signal.
Fetal Heart Rate Prediction from Electrocardiogram