Li Ruilin, Frasch Martin G, Wu Hau-Tieng
Department of Mathematics, University of TorontoToronto, ON, Canada.
Department of Obstetrics and Gynecology, University of WashingtonSeattle, USA.
Front Physiol. 2017 May 16;8:277. doi: 10.3389/fphys.2017.00277. eCollection 2017.
There is a need for affordable, widely deployable maternal-fetal ECG monitors to improve maternal and fetal health during pregnancy and delivery. Based on the diffusion-based channel selection, here we present the mathematical formalism and clinical validation of an algorithm capable of accurate separation of maternal and fetal ECG from a two channel signal acquired over maternal abdomen. The proposed algorithm is the first algorithm, to the best of the authors' knowledge, focusing on the fetal ECG analysis based on two channel maternal abdominal ECG signal, and we apply it to two publicly available databases, the PhysioNet non-invasive fECG database (adfecgdb) and the 2013 PhysioNet/Computing in Cardiology Challenge (CinC2013), to validate the algorithm. The state-of-the-art results are achieved when compared with other available algorithms. Particularly, the score for the R peak detection achieves 99.3% for the adfecgdb and 87.93% for the CinC2013, and the mean absolute error for the estimated R peak locations is 4.53 ms for the adfecgdb and 6.21 ms for the CinC2013. The method has the potential to be applied to other fetal cardiogenic signals, including cardiac doppler signals.
需要价格合理、可广泛部署的母婴心电图监测仪，以改善孕期和分娩期间的母婴健康。基于基于扩散的通道选择，我们在此展示一种算法的数学形式和临床验证，该算法能够从在孕妇腹部采集的两通道信号中准确分离出母婴心电图。据作者所知，所提出的算法是第一种专注于基于两通道孕妇腹部心电图信号进行胎儿心电图分析的算法，我们将其应用于两个公开可用的数据库，即PhysioNet无创胎儿心电图数据库（adfecgdb）和2013年PhysioNet/心脏病学计算挑战赛（CinC2013），以验证该算法。与其他现有算法相比，取得了最先进的结果。特别是，对于adfecgdb，R波峰检测的得分达到99.3%，对于CinC2013为87.93%，估计的R波峰位置的平均绝对误差对于adfecgdb为4.53毫秒，对于CinC2013为6.21毫秒。该方法有可能应用于其他胎儿心源性信号，包括心脏多普勒信号。
