Extraction Algorithm for Morphologically Preserved Non-Invasive Multi-Channel Fetal ECG

Baldazzi G.
;
Pani D.;
2022-01-01

Abstract

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.
2022
Inglese
Computing in Cardiology
IEEE Computer Society
2022
4
2022 Computing in Cardiology, CinC 2022
Esperti anonimi
September 4-7, 2022
Tampere, Finland
internazionale
scientifica
4 Contributo in Atti di Convegno (Proceeding)::4.1 Contributo in Atti di convegno
Baldazzi, G.; Pani, D.; Wu, H. -T.
273
3
4.1 Contributo in Atti di convegno
none
info:eu-repo/semantics/conferencePaper
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