A new method for extraction of fetal electrocardiogram signal based on Adaptive Nero-Fuzzy Inference System

This paper proposes a new method for extracting the Foetal Electrocardiogram (FECG) signal from two ECG signals recorded at thoracic and abdominal areas of mother. The thoracic ECG is assumed to be completely maternal ECG (MECG) while the abdominal ECG is assumed to be a combination of mother's and fetus's ECG signals and random noise. The maternal component of the abdominal ECG is a nonlinearly transformed version of MECG. The method uses Adaptive Nero-Fuzzy Inference System (ANFIS) structure to identify the nonlinear transformation. We have used Particle Swarm Optimization (PSO) as a new tool for training the ANFIS structure. By identifying the nonlinear transformation, we have extracted FECG by subtracting the aligned version of the MECG signal from the abdominal ECG (AECG) signal. We validate our new method on both real and synthetic ECG signals. The results shows improvement in extraction of foetal electrocardiogram signal with our proposed method.

[1]  J. A. Newell,et al.  A clinical foetal electrocardiograph , 1966, Medical and biological engineering.

[2]  Michio Sugeno,et al.  Fuzzy identification of systems and its applications to modeling and control , 1985, IEEE Transactions on Systems, Man, and Cybernetics.

[3]  Jyh-Shing Roger Jang,et al.  ANFIS: adaptive-network-based fuzzy inference system , 1993, IEEE Trans. Syst. Man Cybern..

[4]  Gustavo Camps-Valls,et al.  Foetal ECG recovery using dynamic neural networks , 2004, Artif. Intell. Medicine.

[5]  G. Camps,et al.  Fetal ECG extraction using an FIR neural network , 2001, Computers in Cardiology 2001. Vol.28 (Cat. No.01CH37287).

[6]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[7]  Earl R. Ferrara,et al.  Fetal Electrocardiogram Enhancement by Time-Sequenced Adaptive Filtering , 1982, IEEE Transactions on Biomedical Engineering.

[8]  Karim Faez,et al.  Signal Processing Based Techniques for Fetal Electrocardiogram Extraction , 2008 .

[9]  Dirk Callaerts,et al.  Comparison of SVD methods to extract the foetal electrocardiogram from cutaneous electrode signals , 1990, Medical and Biological Engineering and Computing.

[10]  Asoke K. Nandi,et al.  Noninvasive fetal electrocardiogram extraction: blind separation versus adaptive noise cancellation , 2001, IEEE Transactions on Biomedical Engineering.

[11]  Shahriar Negahdaripour,et al.  A new method for the extraction of fetal ECG from the composite abdominal signal , 2000, IEEE Transactions on Biomedical Engineering.

[12]  I. I. Christov,et al.  High-pass filtering of ECG signals using QRS elimination , 2006, Medical and Biological Engineering and Computing.

[13]  Marco Winzker,et al.  2011 IEEE International Conference on Signal and Image Processing Applications, ICSIPA 2011, Kuala Lumpur, Malaysia, November 16-18, 2011 , 2011, International Conference on Signal and Image Processing Applications.

[14]  Khaled Assaleh,et al.  Extraction of Fetal Electrocardiogram Using Adaptive Neuro-Fuzzy Inference Systems , 2007, IEEE Transactions on Biomedical Engineering.

[15]  Ee-Chien Chang,et al.  Blind separation of fetal ECG from single mixture using SVD and ICA , 2003, Fourth International Conference on Information, Communications and Signal Processing, 2003 and the Fourth Pacific Rim Conference on Multimedia. Proceedings of the 2003 Joint.