Noninvasive fetal ECG estimation using adaptive comb filter.
This paper describes a robust and simple algorithm for fetal electrocardiogram (FECG) estimation from abdominal signal using adaptive comb filter (ACF). The ACF can adjust itself to the temporal variations in fundamental frequency, which makes it qualified for the estimation of quasi-periodic component from physiologic signal, such as ECG. The validity and performance of the described method are confirmed through experiments on real fetal ECG data. A comparison with the well-known independent component analysis (ICA) method has also been presented.
School of Electronic Information, Jiangsu University of Science and Technology, ZhenJiang, China. Electronic address: zhweiweixy@gmail.com.
Zheng
Z
Wei
Wei
W
Xueyun
Zhong
Z
Jian  jian
Liu
L
Hongxing
D000465:Algorithms; D016208:Databases, Factual; D004562:Electrocardiography / Q000706:statistics & numerical data*; D005260:Female; D005323:Fetal Monitoring / Q000706:statistics & numerical data*; D006801:Humans; D011247:Pregnancy; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio
ACF; Adaptive comb filter; BSS; EMG; FECG; Fetal electrocardiogram estimation; ICA; MECG; Quasi-periodic physiologic signal; SNR; adaptive comb filter; blind source separation; electromyogram; fetal electrocardiogram; independent component analysis; maternal ECG; signal to noise ratio