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

Volume

4

fYear

2000

fDate

2000

Firstpage

3040

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;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2000. Proceedings of the 22nd Annual International Conference of the IEEE

Conference_Location

Chicago, IL

ISSN

1094-687X

Print_ISBN

0-7803-6465-1

Type

conf

DOI

10.1109/IEMBS.2000.901522

Filename

901522