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Markov Modeling of Colonoscopy Gestures to Develop Skill Trainers

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Part of the Lecture Notes in Computer Science book series (LNIP,volume 7264)

Abstract

Colonoscopy is a complex procedure which requires considerable skill by the clinician in guiding the scope safely and accurately through the colon, and in a manner tolerable to the patient. Excessive pressure can cause the colon walls to distend, leading to excruciating pain or perforation. Concerted efforts by the ASGE have led to stipulating guidelines for trainees to reach necessary expertise. In this paper, we have analyzed the motion of the colonoscope by collecting kinematics data using 4 electromagnetic position sensors. Further, 36 feature vectors have been defined to capture all possible gestures. These feature vectors are used to train Hidden Markov Models to identify critical gestures that differentiate expertise. Five expert attending clinicians and four fellows were recruited as part of this study. Experimental results show that roll of the scope shows maximum differentiation of expertise.

Keywords

  • Feature Vector
  • Hide Markov Model
  • Cecal Intubation
  • Hide Markov Model Model
  • Position Trajectory

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

This work has been funded by the National Center for Research Resources, the National Institute of Biomedical Imaging and Bioengineering, and the National Cancer Institute of the National Institutes of Health through Grant Numbers P41EB015898, P41RR019703, 2 R42 CA115112-02A2 and the Center for Integration of Medicine and Innovative Technology (CIMIT), Boston, MA.

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Jayender, J., Spofford, I., Lengyel, B.I., Thompson, C.C., Vosburgh, K.G. (2012). Markov Modeling of Colonoscopy Gestures to Develop Skill Trainers. In: Linte, C.A., Moore, J.T., Chen, E.C.S., Holmes, D.R. (eds) Augmented Environments for Computer-Assisted Interventions. AE-CAI 2011. Lecture Notes in Computer Science, vol 7264. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32630-1_7

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  • DOI: https://doi.org/10.1007/978-3-642-32630-1_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32629-5

  • Online ISBN: 978-3-642-32630-1

  • eBook Packages: Computer ScienceComputer Science (R0)