Title :
An interference cancellation algorithm for non-invasive extraction of TaFEEG
Author :
Shao, Min ; Barner, Kenneth E. ; Goodman, Michael H.
Author_Institution :
Dept. of Electr. & Comput. Eng., Delaware Univ., Newark, DE, USA
Abstract :
Fetal electroencephalogram (FEEG) contains important information regarding the status of a fetus. To monitor FEEG signals non-invasively, transabdominal recordings of FEEG (TaFEEG) can be obtained. However, due to the poor Signal to Noise Ratio (SNR), extraction of FEEG from transabdominal recordings is very difficult. Here, a multi-step interference cancellation algorithm is developed to remove the major sources of interference in transabdominal recordings. The algorithm is applied to simulated data and true transabdominal recordings. The result shows that the developed method is able to extract the clinically important FEEG signal from transabdominal recordings
Keywords :
electroencephalography; feature extraction; interference (signal); medical signal processing; obstetrics; EEG analysis; clinically important FEEG signal; electrodiagnostics; fetal electroencephalogram; interference cancellation algorithm; noninvasive extraction; poor signal to noise ratio; simulated data; true transabdominal recordings; Abdomen; Brain modeling; Data mining; Electrocardiography; Filters; Interference cancellation; Medical simulation; Monitoring; Partitioning algorithms; Signal to noise ratio;
Conference_Titel :
Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE
Conference_Location :
Chicago, IL
Print_ISBN :
0-7803-6465-1
DOI :
10.1109/IEMBS.2000.901522
