Department of Obstetrics and Gynecology, Máxima Medical Centre, Veldhoven, The Netherlands.
Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Physiol Meas. 2024 Jul 17;45(7). doi: 10.1088/1361-6579/ad605c.
Even though the electrocardiogram (ECG) has potential to be used as a monitoring or diagnostic tool for fetuses, the use of non-invasive fetal ECG is complicated by relatively high amounts of noise and fetal movement during the measurement. Moreover, machine learning-based solutions to this problem struggle with the lack of clean reference data, which is difficult to obtain. To solve these problems, this work aims to incorporate fetal rotation correction with ECG denoising into a single unsupervised end-to-end trainable method.This method uses the vectorcardiogram (VCG), a three-dimensional representation of the ECG, as an input and extends the previously introduced Kalman-LISTA method with a Kalman filter for the estimation of fetal rotation, applying denoising to the rotation-corrected VCG.The resulting method was shown to outperform denoising auto-encoders by more than 3 dB while achieving a rotation tracking error of less than 33. Furthermore, the method was shown to be robust to a difference in signal to noise ratio between electrocardiographic leads and different rotational velocities.This work presents a novel method for the denoising of non-invasive abdominal fetal ECG, which may be trained unsupervised and simultaneously incorporates fetal rotation correction. This method might prove clinically valuable due the denoised fetal ECG, but also due to the method's objective measure for fetal rotation, which in turn might have potential for early detection of fetal complications.
尽管心电图（ECG）有可能被用作胎儿监测或诊断工具，但由于在测量过程中存在相对较高的噪声和胎儿运动，非侵入性胎儿 ECG 的使用变得复杂。此外，基于机器学习的解决方案在缺乏清洁参考数据方面存在困难，而这些数据很难获取。为了解决这些问题，这项工作旨在将胎儿旋转校正与 ECG 去噪结合到一个单一的无监督端到端可训练方法中。该方法使用心向量图（VCG）作为输入，这是 ECG 的三维表示，并扩展了之前引入的 Kalman-LISTA 方法，使用卡尔曼滤波器来估计胎儿旋转，对旋转校正后的 VCG 进行去噪。结果表明，该方法的性能优于去噪自动编码器超过 3dB，同时实现了小于 33 的旋转跟踪误差。此外，该方法还表现出对心电图导联之间信噪比差异和不同旋转速度的鲁棒性。这项工作提出了一种新颖的方法来对非侵入性腹部胎儿 ECG 进行去噪，该方法可以进行无监督训练，并同时结合胎儿旋转校正。由于去噪后的胎儿 ECG，该方法可能具有临床价值，但由于该方法是对胎儿旋转的客观测量，也可能具有早期检测胎儿并发症的潜力。
