a pca/ica based fetal ecg extraction from mother abdominal recordings by means of a novel data-driven approach to fetal ecg quality assessment

background: fetal electrocardiography is a developing field that provides valuable information on the fetal health during pregnancy. by early diagnosis and treatment of fetal heart problems, more survival chance is given to the infant. objective: here, we extract fetal ecg from maternal abdominal recordings and detect r-peaks in order to recognize fetal heart rate. on the next step, we find a better and more qualified extracted fetal ecg by using a novel approach. materials and methods: in this paper, a pca/ica-based algorithm is proposed for extracting fetal ecg, and fetal r-peaks are detected as well. the method validates the quality of extracted ecgs and selects the best candidate fetal ecg to provide the required morphological ecg features such as fetal heart rate and rr interval for more clinical examinations. the method was evaluated using the dataset which was provided by physionet/computing in cardiology challenge 2013. the dataset consists of 75 recordings of 4-channel ecgs each containing 1-minute length for training and 100 similar recordings for testing. results: when the proposed algorithm was applied to the test set, the scores of 85.853 bpm2 for fetal heart rate and an error of 9.725 ms rms for fetal rr-interval estimation were obtained. conclusion: the results obtained with the mentioned algorithm shows the robustness of the research, and it is suggested to be used in practical fetal ecg monitoring systems.