2007
DOI: 10.1088/0967-3334/28/9/012
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Identification of the slow wave component of the electroenterogram from Laplacian abdominal surface recordings in humans

Abstract: The electroenterogram (EEnG) is a surface recording of the myoelectrical activity of the smooth muscle layer of the small intestine. It is made up of two signals: a low-frequency component, known as the slow wave (SW), and high-frequency signals, known as spike bursts (SB). Most methods of studying bowel motility are invasive due to the difficult anatomic access of the intestinal tract. Abdominal surface EEnG recordings could be a noninvasive solution for monitoring human intestinal motility. However, surface … Show more

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Cited by 13 publications
(17 citation statements)
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References 47 publications
(69 reference statements)
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“…However, the applicability of adaptive filtering for this purpose has been questioned by some authors (Liang, Lin, & Mccallum 2000d;Wang, Cheung, & Chen 1999c), given that it requires a reference signal that is the comprehensive signal of the various interferences to be removed. Therefore, its ability to reduce interferences strongly depends on the reference signal which is used Lin and Chen 1994;Prats-Boluda et al 2007). Like the adaptive filter, in this work it has been proved that the EMD method could also be employed to reduce the respiratory interference in external myoelectrical recording, In this context, the advantage of the EMD-based method lies in the fact that there is no need to find an optimal reference signal, since it is only necessary to know the respiration frequency.…”
Section: Removal Of Interferences In Surface Eengmentioning
confidence: 95%
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“…However, the applicability of adaptive filtering for this purpose has been questioned by some authors (Liang, Lin, & Mccallum 2000d;Wang, Cheung, & Chen 1999c), given that it requires a reference signal that is the comprehensive signal of the various interferences to be removed. Therefore, its ability to reduce interferences strongly depends on the reference signal which is used Lin and Chen 1994;Prats-Boluda et al 2007). Like the adaptive filter, in this work it has been proved that the EMD method could also be employed to reduce the respiratory interference in external myoelectrical recording, In this context, the advantage of the EMD-based method lies in the fact that there is no need to find an optimal reference signal, since it is only necessary to know the respiration frequency.…”
Section: Removal Of Interferences In Surface Eengmentioning
confidence: 95%
“…Besides the above mentioned method, other techniques, such as adaptive filtering Lin and Chen 1994;Prats-Boluda et al 2007) and independent component analysis (ICA) (Irimia and Bradshaw 2005;Wang et al 1999), also have been proposed to remove the interferences from external myoelectrical…”
Section: Removal Of Interferences In Surface Eengmentioning
confidence: 99%
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“…ET. AL, 1993], causando cambios de la línea base de los registros de señales, lo que puede causar una confusión entre la señal respiratoria y la señal intestinal al tener valores de frecuencia cercanos LIN Z. Y., CHEN J. D. 1994;PRATS-BOLUDA G. ET. AL, 2007].…”
Section: -4unclassified