Le Tai, Fortunato Joseph, Maritato Nicholas, Cho Yeeun, Nguyen Quoc-Dinh, Ghirmai Tadesse, Lau Michael P H, Han Huy-Dung, Nguyen Cuong Kieu, Nguyen Vu Cong, Cao Hung
Electrical Engineering, The Henry Samueli School of Engineering, UC Irvine, Irvine, CA 92697.
University of Washington, Bothell campus, Bothell, WA 98011.
IEEE MTT-S 2019 Int Microw Biomed Conf IMBioC 2019 (2019). 2019 May;2019. doi: 10.1109/imbioc.2019.8777741. Epub 2019 Jul 29.
Electrocardiogram (ECG) monitoring of the fetus during pregnancy, before and during labor, can provide crucial information for the assessment of fetal well-being and development, as well as labor progress. An out-of-clinics fetal ECG monitoring system may pave the way for instant diagnosis, suggesting immediate intervention, which could help reduce the fetal mortality rate. In this paper, we present an unobtrusive fetal maternal ECG monitoring system which can operate in the home setting. The acquisition of the mother's abdominal ECG is done using the non-contact electrode approach. The extraction of the fetal ECG from the combined fetal/maternal ECG signal is investigated using both Fast Independent Component Analysis (FastICA) and RobustICA algorithms. An accelerometer is integrated for motion artifact detection which would help reduce interferences due to movement. The device also is connected to a cloud server, allowing doctors to access the data in real time.
孕期、分娩前及分娩期间对胎儿进行心电图（ECG）监测，可为评估胎儿健康状况与发育情况以及产程进展提供关键信息。门诊外胎儿心电图监测系统可能为即时诊断铺平道路，提示立即进行干预，这有助于降低胎儿死亡率。在本文中，我们展示了一种可在家庭环境中运行的无创胎儿-母亲心电图监测系统。母亲腹部心电图的采集采用非接触电极方法。使用快速独立成分分析（FastICA）算法和稳健独立成分分析（RobustICA）算法研究从胎儿/母亲混合心电图信号中提取胎儿心电图。集成了一个加速度计用于运动伪影检测，这将有助于减少因运动产生的干扰。该设备还连接到云服务器，使医生能够实时访问数据。
