Key result
A novel Ensemble Kalman filter-based algorithm for single-channel fetal ECG extraction achieved an average positive predictive value of 97.59%, sensitivity of 96.91%, and F1-score of 97.25%.
Why the study?
Non-invasive fetal ECG extraction from abdominal ECG signals is challenging due to high noise, especially when using only a single-channel recording from compact patch devices.
Does an Ensemble Kalman filter (EnKF) algorithm improve non-invasive fetal ECG extraction from single-channel maternal abdominal signals compared to an extended Kalman filter?
Does an Ensemble Kalman filter (EnKF) algorithm improve non-invasive fetal ECG extraction from single-channel maternal abdominal signals compared to an extended Kalman filter?
The Ensemble Kalman filter algorithm effectively extracts fetal ECG from single-channel maternal abdominal signals with high accuracy, outperforming existing extended Kalman filter methods.
EnKF shows promise for single-channel fetal ECG extraction; hypothesis-generating and requires prospective clinical validation before any adoption.
Fetal electrocardiogram (fECG) assessment is essential throughout pregnancy to monitor the wellbeing and development of the fetus, and to possibly diagnose potential congenital heart defects. Due to the high noise incorporated in the abdominal ECG (aECG) signals, the extraction of fECG has been challenging. And it is even a lot more difficult for fECG extraction if only one channel of aECG is provided, i.e., in a compact patch device. In this paper, we propose a novel algorithm based on the Ensemble Kalman filter (EnKF) for non-invasive fECG extraction from a single-channel aECG signal. To assess the performance of the proposed algorithm, we used our own clinical data, obtained from a pilot study with 10 subjects each of 20 min recording, and data from the PhysioNet 2013 Challenge bank with labeled QRS complex annotations. The proposed methodology shows the average positive predictive value (PPV) of 97.59%, sensitivity (SE) of 96.91%, and F1-score of 97.25% from the PhysioNet 2013 Challenge bank. Our results also indicate that the proposed algorithm is reliable and effective, and it outperforms the recently proposed extended Kalman filter (EKF) based algorithm.
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Sarafan et al. (2022) studied Pregnancy (fetal ECG monitoring) (n=10). Ensemble Kalman filter (EnKF) based algorithm vs. Extended Kalman filter (EKF) based algorithm was evaluated on Positive predictive value (PPV), sensitivity (SE), and F1-score for fetal ECG extraction. A novel Ensemble Kalman filter-based algorithm for single-channel fetal ECG extraction achieved an average positive predictive value of 97.59%, sensitivity of 96.91%, and F1-score of 97.25%.
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