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Real-Time Fetal Heart Monitoring in Biomagnetic Measurements Using Adaptive Real-Time ICA

机译:使用自适应实时ICa进行生物磁测量中的实时胎儿心脏监测

摘要

Electrophysiological signals of the developing fetal brain and heart can be investigated by fetal magnetoencephalography (fMEG). During such investigations, the fetal heart activity and that of the mother should be monitored continuously to provide an important indication of current well-being. Due to physical constraints of an fMEG system, it is not possible to use clinically established heart monitors for this purpose. Considering this constraint, we developed a real-time heart monitoring system for biomagnetic measurements and showed its reliability and applicability in research and for clinical examinations. The developed system consists of real-time access to fMEG data, an algorithm based on Independent Component Analysis (ICA), and a graphical user interface (GUI). The algorithm extracts the current fetal and maternal heart signal from a noisy and artifact-contaminated data stream in real-time and is able to adapt automatically to continuously varying environmental parameters. This algorithm has been na med Adaptive Real-time ICA (ARICA) and is applicable to real-time artifact removal as well as to related blind signal separation problems.
机译:发育中的胎儿脑和心脏的电生理信号可以通过胎儿脑磁图(fMEG)进行研究。在进行此类检查期间,应连续监测胎儿的心脏活动和母亲的心脏活动,以提供当前健康状况的重要指示。由于fMEG系统的物理限制,无法为此目的使用临床上建立的心脏监护仪。考虑到这一限制,我们开发了一种用于生物磁测量的实时心脏监测系统,并显示了其在研究和临床检查中的可靠性和适用性。开发的系统包括对fMEG数据的实时访问,基于独立成分分析(ICA)的算法以及图形用户界面(GUI)。该算法可从嘈杂且受假象污染的数据流中实时提取当前的胎儿和产妇心脏信号,并能够自动适应不断变化的环境参数。该算法已被命名为自适应实时ICA(ARICA),适用于实时伪像去除以及相关的盲信号分离问题。

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