Title :
Fetal ECG extraction from a single sensor by a non-parametric modeling
Author :
Niknazar, Mohammad ; Rivet, Bertrand ; Jutten, Christian
Author_Institution :
GIPSA-Lab., Univ. of Grenoble, St. Martin d´´Hères, France
Abstract :
This study deals with fetal ECG and MCG extraction from a single-channel recording. A recently proposed nonparametric model to describe second-order statistical properties of ECG signal, is simplified in this paper to make it computationally faster and easier to implement. In the proposed method an ECG signal is first decomposed to sub-bands, then each sub-band is modeled separately, so less complex model is required. There is no assumption about shape of ECG signal in the model, and experimental results show its high performance on extraction of fetal cardiac signals.
Keywords :
electrocardiography; feature extraction; medical signal processing; nonparametric statistics; obstetrics; statistical analysis; ECG signal; MCG extraction; fetal ECG extraction; fetal cardiac signal extraction; nonparametric modeling; single channel recording; single sensor; statistical properties; Computational modeling; Correlation; Educational institutions; Electrocardiography; Kalman filters; Mathematical model; Noise; Non-parametric modeling; fetal ECG extraction; single sensor extraction;
Conference_Titel :
Signal Processing Conference (EUSIPCO), 2012 Proceedings of the 20th European
Conference_Location :
Bucharest
Print_ISBN :
978-1-4673-1068-0