TY - GEN
T1 - Extraction Algorithm for Morphologically Preserved Non-Invasive Multi-Channel Fetal ECG
AU - Baldazzi, Giulia
AU - Pani, Danilo
AU - Wu, Hau Tieng
N1 - Funding Information:
This work is supported by the Italian Government-Progetti di Interesse Nazionale (PRIN) under the grant agreement 2017RR5EW3 - ICT4MOMs project
Publisher Copyright:
© 2022 Creative Commons.
PY - 2022
Y1 - 2022
N2 - Non-invasive fetal ECG (fECG) is a promising technique that could allow low-cost and risk-free diagnosis, and long-term monitoring of fetal cardiac wellbeing. However, the low quality of the fECG extracted from non-invasive abdominal recordings hampers its adoption in clinical practice. In this work, a new algorithm for the recovery of clean and morphologically preserved fECG signals from multi-channel trans-abdominal recordings is presented. The proposed method exploits optimal shrinkage and nonlocal median algorithms, along with a de-shape short-time Fourier transform-based detection, to recover high-quality fECG traces from a morphological perspective, while ensuring very high performance also in terms of fetal QRS detection. On a small dataset, composed of three real 20 min-long four-channel abdominal ECG recordings, a preliminary performance assessment of the proposed fECG extraction method in terms of fetal QRS detection capabilities revealed a median accuracy of 95.8% and F1 score of 97.9%. The obtained results suggest the possibility of successfully applying this approach for an effective non-invasive fECG extraction, deserving further investigations on larger real and synthetic datasets.
AB - Non-invasive fetal ECG (fECG) is a promising technique that could allow low-cost and risk-free diagnosis, and long-term monitoring of fetal cardiac wellbeing. However, the low quality of the fECG extracted from non-invasive abdominal recordings hampers its adoption in clinical practice. In this work, a new algorithm for the recovery of clean and morphologically preserved fECG signals from multi-channel trans-abdominal recordings is presented. The proposed method exploits optimal shrinkage and nonlocal median algorithms, along with a de-shape short-time Fourier transform-based detection, to recover high-quality fECG traces from a morphological perspective, while ensuring very high performance also in terms of fetal QRS detection. On a small dataset, composed of three real 20 min-long four-channel abdominal ECG recordings, a preliminary performance assessment of the proposed fECG extraction method in terms of fetal QRS detection capabilities revealed a median accuracy of 95.8% and F1 score of 97.9%. The obtained results suggest the possibility of successfully applying this approach for an effective non-invasive fECG extraction, deserving further investigations on larger real and synthetic datasets.
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U2 - 10.22489/CinC.2022.373
DO - 10.22489/CinC.2022.373
M3 - Conference contribution
AN - SCOPUS:85152945198
T3 - Computing in Cardiology
BT - 2022 Computing in Cardiology, CinC 2022
PB - IEEE Computer Society
T2 - 2022 Computing in Cardiology, CinC 2022
Y2 - 4 September 2022 through 7 September 2022
ER -