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

Giulia Baldazzi, D. Pani, Hau‐Tieng Wu
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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.
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形态学保存的无创多通道胎儿心电图提取算法
无创胎儿心电图(fECG)是一种很有前途的技术,可以实现低成本和无风险的诊断,并长期监测胎儿心脏健康。然而,从无创腹部记录中提取的fECG的低质量阻碍了其在临床实践中的应用。在这项工作中,提出了一种新的算法,用于从多通道跨腹部记录中恢复干净和形态学保存的fECG信号。所提出的方法利用最佳收缩和非局部中值算法,以及基于去形状的短时傅立叶变换检测,从形态学角度恢复高质量的fECG痕迹,同时确保胎儿QRS检测方面的高性能。在一个小数据集上,由三个真实的20分钟长的四通道腹部心电图记录组成,对所提出的feg提取方法在胎儿QRS检测能力方面的初步性能评估显示,中位准确率为95.8%,F1评分为97.9%。所获得的结果表明,成功地将这种方法应用于有效的非侵入性脑电图提取的可能性,值得在更大的真实和合成数据集上进一步研究。
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