Title :
An interference cancellation algorithm for noninvasive extraction of transabdominal fetal electroencephalogram (TaFEEG)
Author :
Shao, Min ; Barner, Kenneth E. ; Goodman, Michael H.
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Delaware, Newark, DE, USA
fDate :
3/1/2004 12:00:00 AM
Abstract :
The electroencephalogram is a noninvasive method of demonstrating cerebral function. The fetal electroencephalogram (FEEG) contains important information regarding the status of a fetus. It is believed that disorganization of normal FEEG development may help detect the onset of cerebral palsy and mental retardation syndromes. Unfortunately, noninvasive methods of monitoring FEEG are not currently available. Noninvasively obtained abdominal surface electrical recordings include FEEG components, but are dominated by large interfering components, and, thus, have very low signal to noise ratio. In this paper, we propose a multistep extraction procedure to separate the four main components in transabdominal recordings: 1) maternal ECG; 2) FECG; and 3) FEEG signals as well as 4) interfering baseline wander. The algorithm is tested on simulated and real transabdominal recordings. This study shows that the proposed method successfully extracts the desired FEEG signal.
Keywords :
electrocardiography; electroencephalography; interference (signal); iterative methods; obstetrics; FECG; cerebral function; cerebral palsy; electroencephalogram; fetal electroencephalogram; interference cancellation algorithm; interfering baseline wander; maternal ECG; mental retardation syndromes; multistep extraction procedure; noninvasive extraction; transabdominal fetal electroencephalogram; Abdomen; Birth disorders; Brain modeling; Data mining; Electrocardiography; Fetus; Interference cancellation; Monitoring; Signal to noise ratio; Testing; Abdomen; Algorithms; Artifacts; Brain; Computer Simulation; Diagnosis, Computer-Assisted; Electroencephalography; Female; Fetal Monitoring; Humans; Pregnancy; Signal Processing, Computer-Assisted; Stochastic Processes;
Journal_Title :
Biomedical Engineering, IEEE Transactions on
DOI :
10.1109/TBME.2003.821011