(2019) Liquid Gastroesophageal Reflux Characterization by Investigating Multichannel Intraluminal Impedance-pH Monitoring Data. In: 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2019, 23 July 2019through 27 July 2019, Berlin.
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Abstract
Multichannel Intraluminal Impedance-pH (MII-pH) monitoring is designed to detect intraluminal bolus movement without the use of radiation and allows for detection of Gastroesophageal reflux (GER). Automatic analysis of MII-pH data are available however since the recordings are complex and filled with artifacts; a thorough and time-consuming review of the recordings, episode by episode, is still required. The proposed method was designed to segment GER events in a set of 100 episodes of two minutes interval of MII data based on a decision tree approach. An amount of 24 hours of MII-pH data belonging to eight patients were recorded, digitized and stored along with standardized timings of GER events that had been characterized by two gastroenterologist experts. The performance of the algorithm was evaluated using 100 individual GER events. The algorithm has been shown to perform correctly in over 95 of cases. © 2019 IEEE.
Item Type: | Conference or Workshop Item (Paper) |
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Keywords: | decision tree GERD LGER characterization MII-pH Decision trees Automatic analysis Intraluminal Multichannel pH monitoring Trees (mathematics) algorithm gastroesophageal reflux human impedance pH Algorithms Electric Impedance Humans Hydrogen-Ion Concentration |
Subjects: | WI Digestive System |
Divisions: | Faculty of Medicine > Departments of Clinical Sciences > Department of Internal Medical Image and Signal Processing Research Center School of Advanced Technologies in Medicine > Department of Bioelectrics and Biomedical Engineering |
Page Range: | pp. 4636-4639 |
Journal Index: | Scopus |
Publisher: | Institute of Electrical and Electronics Engineers Inc. |
Identification Number: | https://doi.org/10.1109/EMBC.2019.8856986 |
ISBN: | 1557170X (ISSN); 9781538613115 (ISBN) |
Depositing User: | Zahra Otroj |
URI: | http://eprints.mui.ac.ir/id/eprint/18225 |
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