Blind Extraction for Noisy Fetal Electrocardiogram by Using Gaussian Moments

2008 ◽  
Author(s):  
Yumin Yang ◽  
Chonghui Guo
Keyword(s):  
Fetal Electrocardiogram ◽  
Gaussian Moments ◽  
Blind Extraction

scholarly journals Non-Invasive Fetal Electrocardiogram Monitoring Techniques: Potential and Future Research Opportunities in Smart Textiles

Signals ◽  
2021 ◽  
Vol 2 (3) ◽  
pp. 392-412
Author(s):  
Geetika Aggarwal ◽  
Yang Wei
Keyword(s):  
Heart Rate ◽  
Fetal Heart Rate ◽  
Fetal Heart ◽  
Skin Penetration ◽  
Future Research ◽  
Fetal Electrocardiogram ◽  
Smart Textiles ◽  
Non Invasive ◽  
Future Research Directions ◽  
Electrocardiogram Monitoring

During the pregnancy, fetal electrocardiogram (FECG) is deployed to analyze fetal heart rate (FHR) of the fetus to indicate the growth and health of the fetus to determine any abnormalities and prevent diseases. The fetal electrocardiogram monitoring can be carried out either invasively by placing the electrodes on the scalp of the fetus, involving the skin penetration and the risk of infection, or non-invasively by recording the fetal heart rate signal from the mother’s abdomen through a placement of electrodes deploying portable, wearable devices. Non-invasive fetal electrocardiogram (NIFECG) is an evolving technology in fetal surveillance because of the comfort to the pregnant women and being achieved remotely, specifically in the unprecedented circumstances such as pandemic or COVID-19. Textiles have been at the heart of human technological progress for thousands of years, with textile developments closely tied to key inventions that have shaped societies. The relatively recent invention of smart textiles is set to push boundaries again and has already opened the potential for garments relevant to medicine, and health monitoring. This paper aims to discuss the different technologies and methods used in non-invasive fetal electrocardiogram (NIFECG) monitoring as well as the potential and future research directions of NIFECG in the smart textiles area.

scholarly journals Recovery of the fetal electrocardiogram for morphological analysis from two trans-abdominal channels via optimal shrinkage

2019 ◽  
Vol 40 (11) ◽  
pp. 115005 ◽  
Author(s):  
Pei-Chun Su ◽  
Stephen Miller ◽  
Salim Idriss ◽  
Piers Barker ◽  
Hau-Tieng Wu
Keyword(s):  
Morphological Analysis ◽  
Fetal Electrocardiogram

Techniques for optimal enhancement and feature extraction of fetal electrocardiogram

1995 ◽  
Vol 142 (6) ◽  
pp. 482-489 ◽  
Author(s):  
N.J. Outram ◽  
.S.H. Curnow ◽  
E.C. Ifeachor ◽  
P.W.J. Van Eetvelt
Keyword(s):  
Feature Extraction ◽  
Fetal Electrocardiogram

A Novel Blind Watermark Extraction Algorithm Based on Nonsubsampled Contourlet Transform

2014 ◽  
Vol 989-994 ◽  
pp. 1901-1904
Author(s):  
Lei Feng ◽  
Xiao Fei Shi ◽  
Hong Yu Chen ◽  
Yan Hua Li ◽  
Yue Long Zhang
Keyword(s):  
Prior Knowledge ◽  
Blind Source Separation ◽  
Extraction Method ◽  
Low Frequency ◽  
Contourlet Transform ◽  
Nonsubsampled Contourlet Transform ◽  
Independent Components ◽  
Extraction Algorithm ◽  
Blind Extraction ◽  
Ica Algorithm

Most existing watermark extraction algorithms were dependent on prior knowledge. This paper proposed a blind extraction method without relying on prior knowledge. According to constructing new observation based on nonsubsampled contourlet transform, which utilizes low frequency and directional components of watermarked image, more independent components are generated. We involve these components into watermarked image and resort this solution to multichannel blind source separation. Estimated watermark is recovered by ICA algorithm. Experiment results indicate that the proposed method can achieve better results in contrast with two existing algorithms.

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