A Novel Framework for Maternal ECG Removal from SingleChannel Abdominal Recording Objective: Abdominal ECG (AECG) recorded at the maternal abdomen is significantly affected by the maternal ECG (MECG), making the extraction of FECG a challenging task. This paper presents a new MECG elimination method based on Short Time Fourier Transform (STFT) and Convolutional Autoencoder (CAE). Methods: First, the STFT is used to transform the AECG from onedimensional (1D) time domain into twodimensional(2D) timefrequency domain. Next, the CAE model is applied to estimate the 2DSTFT coefficients of MECG. Finally, after the inverse STFT of MECG, we can extract the FECG by subtracting the MECG from the AECG in the time domain. Different from the methods estimated the MECG in the 1D time domain, the novelty of the proposed method relies on estimating the MECG in the 2D timefrequency domain. Specifically, the CAE model learns the endtoend mappings from the 2DSTFT coefficients of AECG to the MECG. Results: Experimental results show that the proposed method is effective in removing the MECG. Significance: This work enhances the clinical applications of FECG in the early detection of fetal heart diseases.

Generation of References by Minimum Norm Projection Operators for Frequency Dependent Subtraction Method in Fetal Biological Signals SUBTR, a frequency dependent subtraction method, is developed to remove mMCG and fMCG interference from fMEG data. But, in order to protect fMEG while attenuating fMCG, channels around the fetal head cannot be used in the subtraction and SUBTR will leave cardiac residual. We propose an algorithm that will use the channels around fetal head but will subtract only the fMCG signal components leaving any other signal included in these channels. We create fMCG only signals using MNPO and use it as a reference in the frequency dependent subtraction. After testing on 12 datasets where SUBTR has low fMCG attenuation performance, the algorithm is shown to remove fMCG interference better than SUBTR.