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Automated Algorithm for GI Spike Burst Detection and Demonstration of Efficacy in Ischemic Small Intestine

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Abstract

We present a novel, fully-automated gastrointestinal spike burst detection algorithm. Following pre-processing with SALPA (Wagenaar and Potter, J. Neurosci. Methods 120:113–120, 2002) and a Savitzky–Golay filter to remove unwanted low and high frequency components, candidate spike waveforms are detected utilizing the non-linear energy operator. Candidate waveforms are classified as spikes or artifact by a support vector machine. The new method achieves highly satisfactory performance with >90% sensitivity and positive prediction value. We also demonstrate an application of the new method to detect changes in spike rate and spatial propagation patterns upon induction of mesenteric ischemia in the small intestine. Spike rates were observed to transiently increase 10–20 fold for a duration of ≈600 s, relative to baseline conditions. In ischemic conditions, spike activity propagation patterns included retrograde-longitudinal wavefronts with occasional spontaneous conduction blocks, as well as self-terminating concentric-circumferential wavefronts. Longitudinal and circumferential velocities were 6.8–8.0 cm/s and 18.7 cm/s, respectively.

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Acknowledgments

JCE and RVC gratefully acknowledge the financial support of the Washington and Lee University Lenfest Research and Robert E. Lee summer scholar grants. Financial support for the animal surgeries and data acquisition was provided by NIH Grants RO1 DK64775 and RO1 58197. The authors gratefully acknowledge the laboratories of William O Richards and L Alan Bradshaw for sharing some of the data sets analyzed in this study.

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Authors and Affiliations

  1. Department of Physics-Engineering, Washington and Lee University, Lexington, VA, USA

    Jonathan C. Erickson & Raisa Velasco-Castedo

  2. Department of Surgery, Vanderbilt University, Nashville, TN, USA

    Chibuike Obioha & Leo K Cheng

  3. Auckland Bioengineering Institute, The University of Auckland, Auckland, New Zealand

    Leo K Cheng, Timothy R. Angeli & Greg O’Grady

  4. Department of Surgery, The University of Auckland, Auckland, New Zealand

    Greg O’Grady

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  1. Jonathan C. Erickson
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  5. Timothy R. Angeli
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Correspondence to Jonathan C. Erickson.

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Associate Editor Nathalie Virag oversaw the review of this article.

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Erickson, J.C., Velasco-Castedo, R., Obioha, C. et al. Automated Algorithm for GI Spike Burst Detection and Demonstration of Efficacy in Ischemic Small Intestine. Ann Biomed Eng 41, 2215–2228 (2013). https://doi.org/10.1007/s10439-013-0812-8

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  • DOI: https://doi.org/10.1007/s10439-013-0812-8

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