Open AccessMethod of fetal electrocardiogram extraction based on ν ‐support vector regression
Author(s) -
Han Liang,
Pu Xiujuan,
Chen Xiaojun
Publication year - 2015
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/iet-spr.2013.0201
Subject(s) - pattern recognition (psychology) , artificial intelligence , signal (programming language) , support vector machine , computer science , noise (video) , independent component analysis , component (thermodynamics) , image (mathematics) , physics , thermodynamics , programming language
A new method based on v ‐support vector regression ( v ‐SVR) is proposed to extract the fetal electrocardiogram (FECG) from the abdominal signal recorded at the abdominal areas of the pregnant woman. The maternal electrocardiogram (MECG) component in the abdominal signal is a non‐linearly transformed version of the MECG and the non‐linear transform is estimated by v ‐SVR. The optimal estimation of the MECG component is obtained by the MECG undergoing the estimated non‐linear transform. Then the FECG is extracted by subtracting the estimated MECG component from the abdominal signal. The method is validated by the experiments on both synthetic and real electrocardiogram (ECG) signals. The visual results and signal‐to‐noise ratio (SNR) are used to evaluate the performance of the FECG extraction methods. The experimental results indicated that the proposed method can be used for extracting the FECG from the abdominal signal.