Journal article
Assessment of the Esophageal Pressure in Gastroesophageal Reflux Disease by the Local Regression
Annals of biomedical engineering, v 33(6), pp 847-853
Jun 2005
PMID: 16078624
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
Gastroesophageal reflux disease (GERD) is one of the most prevalent gastrointestinal diseases. It is characterized by excessive reflux of gastric content (acid, pepsin, etc.) into the esophagus causing symptoms (heartburn, acid regurgitation, etc.) and mucosal inflammation and injuries. GERD occurs when the lower esophageal sphincter (LES) has a low resting pressure and stomach contents leak back, or reflux, into the esophagus. Therefore, the accurate measurement of the LES pressure is of great importance for the diagnosis of GERD. The LES pressure signal, involving severe respiratory contamination and motion artifacts, demands specific capabilities not provided by conventional data analysis methods. Recently, local regression has proved to be a very attractive technique to the nonparametric regression in statistics. In this contribution we apply the ideas of local regression to develop strategies for selecting smoothing parameters of local linear squares estimators, and present its application on the extraction of the LES pressure in GERD. The results from both extensive simulations and real data demonstrate the ability of local regression to characterize the LES pressure, which is consistent with the clinical observation.
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Details
- Title
- Assessment of the Esophageal Pressure in Gastroesophageal Reflux Disease by the Local Regression
- Creators
- Hualou Liang - School of Health Information Sciences University of Texas at Houston 7000 Fannin, Suite 600 Houston Texas 77030J Chen - Division of Gastroenterology University of Texas Medical Branch Galveston Texas
- Publication Details
- Annals of biomedical engineering, v 33(6), pp 847-853
- Publisher
- Kluwer Academic Publishers-Plenum Publishers; New York
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems
- Web of Science ID
- WOS:000230075100013
- Scopus ID
- 2-s2.0-21144439715
- Other Identifier
- 991014877857804721
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- Web of Science research areas
- Engineering, Biomedical