Fetal QRS extraction from single-channel abdominal ECG using adaptive improved permutation entropy
Year: 2024
Type: article
Abstract: The fetal electrocardiogram (fECG), extracted from the abdominal ECG (aECG) signal of an expectant mother, provides vital information about the fetal condition. There is an increased interest in continuous fECG monitoring during pregnancy to ensure the well-being and development of the fetus. The implementation of continuous fECG monitoring devices necessitates robust and efficient signal processing techniques for extracting the fECG from the aECG. However, existing fECG extraction algorithms are not suitable for wearables due to the requirement of multi-channel signals and/or their high computational cost. In this paper, we propose a novel algorithm for fetal QRS extraction from a single-channel aECG signal, which is robust and computationally less complex. The algorithm is based on a novel Permutation Entropy (PE) method we developed and referred to as the Adaptive Improved Permutation Entropy (AIPE) method. To evaluate the performance of the proposed algorithm, we utilized our own clinical data obtained from a pilot study with 10 subjects, each recording lasting 20 minutes, as well as data from the PhysioNet 2013 Challenge bank with labeled QRS complex annotations. The proposed methodology demonstrates an average positive predictive value (PPV) of 91.0227\%, sensitivity (SE) of 90.4726\%, and F1-score of 90.6525\% from the PhysioNet 2013 Challenge bank, outperforming other methods. These results indicate that our proposed algorithm is reliable and effective, making it suitable for deployment in wearable devices for continuous home-based monitoring of unborn babies.
Language: English
Topic: ECG Monitoring and Analysis
Subfield: Cardiology and Cardiovascular Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4391651700