Calculation of upper esophageal sphincter restitution time from high resolution manometry data using machine learning.

Journal: Physiology & behavior
PMID: 27521686

Abstract

OBJECTIVE: After swallowing, the upper esophageal sphincter (UES) needs a certain amount of time to return from maximum pressure to the resting condition. Disturbances of sphincter function not only during the swallowing process but also in this phase of pressure restitution may lead to globus sensation or dysphagia. Since UES pressures do not decrease in a linear or asymptotic manner, it is difficult to determine the exact time when the resting pressure is reached, even when using high resolution manometry (HRM). To overcome this problem a Machine Learning model was established to objectively determine the UES restitution time (RT) and moreover to collect physiological data on sphincter function after swallowing.

Authors

  • Michael Jungheim
    Department of Phoniatrics and Pediatric Audiology, Hannover Medical School, Germany. Electronic address: jungheim.michael@mh-hannover.de.
  • Andre Busche
    Brunel GmbH, Bereich Communications, Daimlerring 9, 31135 Hildesheim, Germany; Information Systems and Machine Learning Lab, University of Hildesheim, Germany. Electronic address: busche@ismll.uni-hildesheim.de.
  • Simone Miller
    Department of Phoniatrics and Pediatric Audiology, Hannover Medical School, Germany. Electronic address: miller.simone@mh-hannover.de.
  • Nicolas Schilling
    Information Systems and Machine Learning Lab, University of Hildesheim, Germany. Electronic address: schilling@ismll.uni-hildesheim.de.
  • Lars Schmidt-Thieme
    Information Systems and Machine Learning Lab, University of Hildesheim, Germany. Electronic address: schmidt-thieme@ismll.uni-hildesheim.de.
  • Martin Ptok
    Department of Phoniatrics and Pediatric Audiology, Hannover Medical School, Germany. Electronic address: ptok.martin@mh-hannover.de.

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