Gupta Praveen, Sharma K K, Joshi S D
Senior Lecturer in the Department of Electronics Engineering at Government Polytechnic College, Jaipur, India.
Professor in the Department of Electronics and Communication Engineering at Malviya National Institute of Technology, Jaipur, India.
Comput Biol Med. 2016 Jan 1;68:121-36. doi: 10.1016/j.compbiomed.2015.11.007. Epub 2015 Nov 29.
Assessment of fetal heart rate (FHR) and fetal heart rate variability (fHRV) reveals important information about fetal well-being, specifically in high risk pregnancies. Abdominal electrocardiogram (abdECG) recording is a non-invasive method to capture fetal electrocardiograms. In this paper, we propose a methodology to extract FHR (fetal RR time series) from the abdECG recordings using the recently introduced multivariate empirical mode decomposition (MEMD) technique. MEMD breaks a signal into a finite set of intrinsic mode functions (IMFs). First, elimination of the noisier abdECG channels, based on comparison of similar indexed IMFs that were obtained through the MEMD technique, is conducted. Thereafter, denoising of the remaining abdECG channels is performed by eliminating certain similar indexed IMFs. The unwanted mother QRS complexes are removed from these noise-free abdECG channels, and the candidate fetal R-peaks are detected through a wavelet based approach. The proposed methodology is validated using an open source real-life clinical database. The proposed technique resulted in a high value (0.983) of cross correlation between the detected and true FHR signals.
评估胎儿心率(FHR)和胎儿心率变异性(fHRV)可揭示有关胎儿健康状况的重要信息,尤其是在高危妊娠中。腹部心电图(abdECG)记录是一种获取胎儿心电图的非侵入性方法。在本文中,我们提出了一种使用最近引入的多变量经验模态分解(MEMD)技术从abdECG记录中提取FHR(胎儿RR时间序列)的方法。MEMD将一个信号分解为一组有限的固有模态函数(IMF)。首先,基于通过MEMD技术获得的相似索引IMF的比较,对噪声较大的abdECG通道进行消除。此后,通过消除某些相似索引IMF对剩余的abdECG通道进行去噪。从这些无噪声的abdECG通道中去除不需要的母亲QRS复合波,并通过基于小波的方法检测候选胎儿R波峰。使用开源真实临床数据库对所提出的方法进行了验证。所提出的技术在检测到的FHR信号与真实FHR信号之间产生了较高的互相关值(0.983)。