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Fetal QRS extraction from single-channel abdominal ECG using adaptive improved permutation entropy.
Nastaran Mansourian1, Sadaf Sarafan2, Farah Torkamani-Azar3
1Faculty of Electrical Engineering, University of Shahid Beheshti, Tehran, Iran.
Physical and Engineering Sciences in Medicine
|February 8, 2024
Summary
A new Adaptive Improved Permutation Entropy (AIPE) algorithm efficiently extracts fetal QRS from single-channel ECGs. This breakthrough enables wearable devices for continuous remote fetal monitoring.
Area of Science:
- Biomedical Engineering
- Signal Processing
- Maternal-Fetal Medicine
Background:
- Fetal electrocardiogram (fECG) monitoring is vital for fetal well-being during pregnancy.
- Existing fECG extraction methods are computationally intensive and require multi-channel signals, limiting their use in wearable devices.
Purpose of the Study:
- To introduce a novel, computationally efficient algorithm (AIPE) for extracting fetal QRS complexes from single-channel abdominal ECG (aECG).
- To validate the algorithm's suitability for wearable devices and continuous home-based fetal monitoring.
Main Methods:
- Developed and implemented the Adaptive Improved Permutation Entropy (AIPE) algorithm for single-channel aECG analysis.
- Evaluated AIPE using clinical data from a pilot study and simulated data from the PhysioNet 2013 Challenge bank.
Main Results:
- AIPE demonstrated high performance with an average positive predictive value of 91.02%, sensitivity of 90.47%, and F1 score of 90.65% on the PhysioNet 2013 dataset.
- The algorithm proved robust and computationally efficient, outperforming existing methods.
Conclusions:
- The AIPE algorithm is a reliable and effective solution for fECG extraction suitable for wearable technology.
- This innovation facilitates continuous, home-based monitoring of fetal health, enhancing prenatal care accessibility.
