Annals of Biomedical Engineering

, Volume 38, Issue 4, pp 1511–1529 | Cite as

Falling-Edge, Variable Threshold (FEVT) Method for the Automated Detection of Gastric Slow Wave Events in High-Resolution Serosal Electrode Recordings

  • Jonathan C. EricksonEmail author
  • Gregory O’Grady
  • Peng Du
  • Chibuike Obioha
  • Wenlian Qiao
  • William O. Richards
  • L. Alan Bradshaw
  • Andrew J. Pullan
  • Leo K. Cheng


High resolution (HR) multi-electrode mapping is increasingly being used to evaluate gastrointestinal slow wave behaviors. To create the HR activation time (AT) maps from gastric serosal electrode recordings that quantify slow wave propagation, it is first necessary to identify the AT of each individual slow wave event. Identifying these ATs has been a time consuming task, because there has previously been no reliable automated detection method. We have developed an automated AT detection method termed falling-edge, variable threshold (FEVT) detection. It computes a detection signal transform to accentuate the high ‘energy’ content of the falling edges in the serosal recording, and uses a running median estimator of the noise to set the time-varying detection threshold. The FEVT method was optimized, validated, and compared to other potential algorithms using in vivo HR recordings from a porcine model. FEVT properly detects ATs in a wide range of waveforms, making its performance substantially superior to the other methods, especially for low signal-to-noise ratio (SNR) recordings. The algorithm offered a substantial time savings (>100 times) over manual-marking whilst achieving a highly satisfactory sensitivity (0.92) and positive-prediction value (0.89).


Gastric electrical activity Gastric slow wave Activation time map High-resolution mapping Energy operator 



The authors gratefully acknowledge the assistance of the animal care facilities at their respective Universities, including Linley Nisbett for her technical skills. This work was supported by NIH Grants R01 DK58197, RO1 DK58697-02, RO1 DK64775, and grants from the NZ Society of Gastroenterology and NZ Health Research Council.


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Copyright information

© Biomedical Engineering Society 2009

Authors and Affiliations

  • Jonathan C. Erickson
    • 1
    • 5
    Email author
  • Gregory O’Grady
    • 2
  • Peng Du
    • 2
  • Chibuike Obioha
    • 3
  • Wenlian Qiao
    • 2
  • William O. Richards
    • 4
  • L. Alan Bradshaw
    • 1
    • 3
  • Andrew J. Pullan
    • 2
    • 3
  • Leo K. Cheng
    • 2
  1. 1.Department of PhysicsVanderbilt UniversityNashvilleUSA
  2. 2.Auckland Bioengineering InstituteThe University of AucklandAucklandNew Zealand
  3. 3.Department of SurgeryVanderbilt University School of MedicineNashvilleUSA
  4. 4.University of South AlabamaMobileUSA
  5. 5.Department of Physics-EngineeringWashington and Lee UniversityLexingtonUSA

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