Combined Method for Reduction of High Frequency Interferences in Surface Electroenterogram (EEnG)

Surface electroenterogram (EEnG) recording is a novel technique for monitoring intestinal motility non-invasively. However, surface EEnG recordings are contaminated by cardiac activity, the respiratory artefact, movement artefacts and other types of interference. The goal of this work is to remove electrocardiogram (ECG) interference and movement artefacts from surface EEnG by means of a combined method of empirical mode decomposition and independent component analysis. For this purpose, 11 recording sessions were conducted on animal models. In order to quantify the effectiveness of the proposed method, several parameters were calculated from each session: signal-to-ECG interference ratio (S/I), energy over 2 Hz (EF2) which quantifies the intestinal motility index of external EEnG recording and the variation of EF2. The proposed method removes both ECG interference and movement artefacts from surface EEnG, obtaining a significantly higher S/I ratio and considerably reducing the non-physiological variation of EF2. Furthermore, after applying the combined method, the correlation coefficient between internal recording EF2 and surface recording EF2 rises significantly. The proposed method could therefore be a useful tool to reduce high frequency interference in EEnG recording and to provide more robust non-invasive intestinal motility indexes.

[1]  E. Quigley,et al.  Gastric and small intestinal motility in health and disease. , 1996, Gastroenterology clinics of North America.

[2]  A. Akin,et al.  Time-frequency methods for detecting spike activity of stomach , 1999, Medical & Biological Engineering & Computing.

[3]  Andrei Irimia,et al.  Artifact reduction in magnetogastrography using fast independent component analysis , 2005, Physiological measurement.

[4]  S. Van Huffel,et al.  Wavelet-Independent Component Analysis to remove Electrocardiography Contamination in surface Electromyography , 2007, 2007 29th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[5]  Manuel Blanco-Velasco,et al.  ECG signal denoising and baseline wander correction based on the empirical mode decomposition , 2008, Comput. Biol. Medicine.

[6]  P. Fleckenstein,et al.  Migrating electrical spike activity in the fasting human small intestine , 1978, The American Journal of Digestive Diseases.

[7]  Zhou Ming-tian.  Adaptive Independent Component Analysis under Multisensing , 2007 .

[8]  Robert W. Summers,et al.  Computerized Analysis of Spike Burst Activity in the Small Intestine , 1982, IEEE Transactions on Biomedical Engineering.

[9]  Emery N. Brown,et al.  Motion and Ballistocardiogram Artifact Removal for Interleaved Recording of EEG and EPs during MRI , 2002, NeuroImage.

[10]  Francesco Carlo Morabito,et al.  Artifact Cancellation from Electrocardiogram by Mixed Wavelet-ICA Filter , 2005, WIRN/NAIS.

[11]  Nw Weisbrodt,et al.  MOTILITY OF THE SMALL INTESTINE , 2007 .

[12]  Y. Ye,et al.  Design and development of an active Laplacian sensor for non-invasive recordings of the intestinal bioelectrical signal , 2008, 2008 IEEE Biomedical Circuits and Systems Conference.

[13]  K.J. Lee,et al.  Development of a new signal processing algorithm based on independent component analysis for single channel ECG data , 2004, The 26th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[14]  Husebye,et al.  The patterns of small bowel motility: physiology and implications in organic disease and functional disorders , 1999, Neurogastroenterology and motility : the official journal of the European Gastrointestinal Motility Society.

[15]  Zhishun Wang,et al.  Blind separation of slow waves and spikes from gastrointestinal myoelectrical recordings , 2001, IEEE Transactions on Information Technology in Biomedicine.

[16]  J Garcia-Casado,et al.  Enhancement of the non-invasive electroenterogram to identify intestinal pacemaker activity , 2009, Physiological measurement.

[17]  B. Schirmer,et al.  Measurement of electrical activity of the human small intestine using surface electrodes , 1993, 1992 14th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[18]  Z. S. Wang,et al.  Blind separation of multichannel electrogastrograms using independent component analysis based on a neural network , 2006, Medical & Biological Engineering & Computing.

[19]  E. Oja,et al.  Independent Component Analysis , 2013 .

[20]  W. Lammers,et al.  Origin and propagation of individual slow waves along the intact feline small intestine , 2008, Experimental physiology.

[21]  Christopher J. James,et al.  An Efficient Time-Frequency Approach to Blind Source Separation Based on Wavelets , 2004, ICA.

[22]  J P Wikswo,et al.  Correlation and comparison of magnetic and electric detection of small intestinal electrical activity. , 1997, The American journal of physiology.

[23]  J L Ponce,et al.  Small bowel motility: relationship between smooth muscle contraction and electroenterogram signal. , 2000, Medical engineering & physics.

[24]  B. Schirmer,et al.  Measurement of electrical activity of the human small intestine using surface electrodes , 1992, IEEE Transactions on Biomedical Engineering.

[25]  Javier Garcia-Casado,et al.  Adaptive filtering of ECG interference on surface EEnGs based on signal averaging , 2006, Physiological measurement.

[26]  Jie Liang,et al.  Detection and deletion of motion artifacts in electrogastrogram using feature analysis and neural networks , 1997, Annals of Biomedical Engineering.

[27]  Maurizio Varanini,et al.  Empirical mode decomposition to approach the problem of detecting sources from a reduced number of mixtures , 2003, Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (IEEE Cat. No.03CH37439).

[28]  Peter P. Tarjan,et al.  Pasteless, Active, Concentric Ring Sensors for Directly Obtained Laplacian Cardiac Electrograms , 2002 .

[29]  Christopher J James,et al.  Independent component analysis for biomedical signals , 2005, Physiological measurement.

[30]  E M Quigley,et al.  Antroduodenal manometry: an evaluation of an emerging methodology. , 1997, Digestive diseases.

[31]  H Liang,et al.  Adaptive independent component analysis of multichannel electrogastrograms. , 2001, Medical engineering & physics.

[32]  Michael Camilleri,et al.  Measurement of gastrointestinal motility in the GI laboratory. , 1998, Gastroenterology.

[33]  Gabriel Rilling,et al.  On empirical mode decomposition and its algorithms , 2003 .

[34]  P. Bass,et al.  Electrical and extraluminal contractile-force activity of the duodenum of the dog , 1965, The American Journal of Digestive Diseases.

[35]  Javier Garcia-Casado,et al.  Noninvasive measurement and analysis of intestinal myoelectrical activity using surface electrodes , 2005, IEEE Transactions on Biomedical Engineering.

[36]  G. Prats-Boluda,et al.  Identification of the slow wave component of the electroenterogram from Laplacian abdominal surface recordings in humans , 2007, Physiological measurement.