Guangdong Police College, Guangzhou 510000, People's Republic of China.
Physiol Meas. 2021 Oct 29;42(10). doi: 10.1088/1361-6579/ac2c5b.
Fetal ECG (FECG) plays an important role in fetal monitoring. However, the abdominal ECG (AECG) recorded at the maternal abdomen is affected by various noises, making the extraction of FECG a challenging task. The main objective is to present a novel approach to FECG extraction using short time Fourier transform (STFT) and generative adversarial networks (GAN).Firstly, the AECG signals are transformed from one-dimensional (1D) time domain to two-dimensional (2D) time-frequency domain by using the STFT. Secondly, the 2D-STFT coefficients of FECG are estimated by the GAN model in the time-frequency domain. Finally, after the inverse STFT, the FECG can be reconstructed in the time domain.Experimental results on two databases demonstrate the effectiveness of the proposed method. Specifically, the SE, PPV andof the proposed method on PCDB are 92.37 ± 3.78%, 93.69 ± 3.96% and 93.02 ± 3.81%, respectively. And the SE, PPV andon ADFECGDB are 90.32 ± 10.70%, 89.79 ± 9.26% and 90.05 ± 9.81%, respectively.Unlike the previous studies based on the elimination of maternal ECG in the 1D time domain, the novelty of the proposed method relies on extracting the FECG directly from the AECG in the 2D time-frequency domain. It sheds some light to the topic of FECG extraction.
胎儿心电图（FECG）在胎儿监测中起着重要作用。然而，在母体腹部记录的腹部心电图（AECG）受到各种噪声的影响，使得 FECG 的提取成为一项具有挑战性的任务。本研究的主要目的是提出一种使用短时傅里叶变换（STFT）和生成对抗网络（GAN）提取 FECG 的新方法。
首先，使用 STFT 将 AECG 信号从一维（1D）时域转换到二维（2D）时频域。其次，GAN 模型在时频域中估计 FECG 的 2D-STFT 系数。最后，经过逆 STFT，可以在时域中重建 FECG。
在两个数据库上的实验结果证明了该方法的有效性。具体来说，在 PCDB 上，该方法的 SE、PPV 和的分别为 92.37±3.78%、93.69±3.96%和 93.02±3.81%。在 ADFECGDB 上，SE、PPV 和的分别为 90.32±10.70%、89.79±9.26%和 90.05±9.81%。
与以前基于在 1D 时域中消除母体 ECG 的研究不同，该方法的新颖之处在于直接从 2D 时频域中提取 FECG。它为 FECG 提取的主题提供了一些启示。
