# A New Approach to Extract Fetal Electrocardiogram Using Affine Combination of Adaptive Filters

arXiv: https://arxiv.org/abs/2210.11658 · HTML: https://mlsanity.com/paper/2210.11658/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 21 Oct 2022.

## Built on by (most cited first, 1 of 1)

- [Unidirectional brain-computer interface: Artificial neural network encoding natural images to fMRI response in the visual cortex](https://mlsanity.com/paper/2309.15018/) (2023)

## Abstract (arXiv)

The detection of abnormal fetal heartbeats during pregnancy is important for monitoring the health conditions of the fetus. While adult ECG has made several advances in modern medicine, noninvasive fetal electrocardiography (FECG) remains a great challenge. In this paper, we introduce a new method based on affine combinations of adaptive filters to extract FECG signals. The affine combination of multiple filters is able to precisely fit the reference signal, and thus obtain more accurate FECGs. We proposed a method to combine the Least Mean Square (LMS) and Recursive Least Squares (RLS) filters. Our approach found that the Combined Recursive Least Squares (CRLS) filter achieves the best performance among all proposed combinations. In addition, we found that CRLS is more advantageous in extracting FECG from abdominal electrocardiograms (AECG) with a small signal-to-noise ratio (SNR). Compared with the state-of-the-art MSF-ANC method, CRLS shows improved performance. The sensitivity, accuracy, and F1 scores improved by 3.58%, 2.39%, and 1.36%, respectively.