Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Videos

A fuzzy pattern recognition method to classify esophageal motility records

F E Abou-Chadi1, F A Ezzat, A A Sif el-Din

  • 1Department of Electrical Communications, Faculty of Engineering, Mansoura University, Egypt.

Annals of Biomedical Engineering
|January 1, 1994
PubMed
Summary

This study introduces automatic classification for esophageal motility records using signal processing and fuzzy pattern recognition. Improved feature extraction and a novel fuzzy classifier enhance diagnostic accuracy for esophageal function.

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Automatic analysis and classification of surface electromyography.

Frontiers of medical and biological engineering : the international journal of the Japan Society of Medical Electronics and Biological Engineering·2001
Same author

Waveform estimation techniques for event-related bioelectric signals: a study of performance.

Frontiers of medical and biological engineering : the international journal of the Japan Society of Medical Electronics and Biological Engineering·1996
Same author

A pattern-analysis methodology for esophageal motility records.

Frontiers of medical and biological engineering : the international journal of the Japan Society of Medical Electronics and Biological Engineering·1994
Same author

Tauberian-prony feature extraction technique for esophageal motility patterns.

Annals of biomedical engineering·1993
Same author

Should both schistosomal and nonschistosomal variceal bleeders be disconnected?

World journal of surgery·1991
Same author

Selective shunt versus nonshunt surgery for management of both schistosomal and nonschistosomal variceal bleeders.

Annals of surgery·1990

Area of Science:

  • Gastroenterology
  • Biomedical Engineering
  • Signal Processing

Background:

  • Esophageal motility disorders require accurate analysis of complex physiological data.
  • Current methods for analyzing esophageal motility records can be labor-intensive and subjective.
  • Objective and automated analysis techniques are needed to improve diagnostic consistency.

Purpose of the Study:

  • To develop and evaluate an automated system for classifying esophageal motility records.
  • To improve feature extraction methods for esophageal motility data.
  • To apply fuzzy-set pattern recognition for enhanced classification accuracy.

Main Methods:

  • Signal processing techniques were applied to raw esophageal motility records.
  • New characterizing features were extracted from processed data.

Related Experiment Videos

  • A fuzzy classifier was designed using the enhanced feature set.
  • Classification accuracy was assessed using the leave-one-out cross-validation method.

    • Main Results:

    • The novel approach demonstrated improved feature extraction from esophageal motility data.
    • The fuzzy classifier achieved accurate classification of esophageal motility records.
    • This represents the first application of automatic classification to this type of data.

    Conclusions:

    • Automated classification using signal processing and fuzzy pattern recognition is feasible for esophageal motility records.
    • The developed method offers a promising tool for objective diagnosis of esophageal motility disorders.
    • Further research can build upon this foundational work for clinical application.