Title :
A discriminant method of blind source separation based on FECG correlations
Author :
Beihai Tan;Jinrong Lin;Weijun Li;Kun Cai
Author_Institution :
School of Automation, Guangdong University of Technology, China
fDate :
4/1/2015 12:00:00 AM
Abstract :
Extraction of fetal electrocardiogram (FECG) is currently focused as a prominent issue of medical research. Normally, FECG can be extracted from the maternal abdominal recordings by conventional blind source separation algorithm. However, the recordings need to meet the linear mixing model of blind source separation (BSS), which makes it difficult to apply in the practical environment. In view of this fact, our paper introduces a discriminant method of BSS based on FECG correlations analysis. The sparse areas of signals are located firstly, and then the correlation values of these areas are calculated out. A judging criterion based on these values can be built to decide that if the recordings meet the model of BSS. Therefore, FECG can be extracted from these observations by conventional BSS methods in practical. The simulation experiments also show that our discriminant method is available and can obtain better performance of extraction.
Keywords :
"Monitoring","Biomedical monitoring","Area measurement","Current measurement","Noise measurement","Noise","Noise reduction"
Conference_Titel :
Information Science and Technology (ICIST), 2015 5th International Conference on
DOI :
10.1109/ICIST.2015.7288981