Neural networks for identification of gastric contractions using abdominal electrodes

Zhiyue Lin, Jian De Z. Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A noninvasive method is developed in this paper for the identification of gastric contractions from the surface electrogastrogram (EGG) using neural networks. Using the EGG data in five subjects as the training set and the EGG data in another five subjects as the testing set, an accuracy of 92% for the identification of gastric contractions was achieved using a three-layer backpropagation neural network.

Original languageEnglish (US)
Title of host publicationProceedings of the Annual Conference on Engineering in Medicine and Biology
PublisherPubl by IEEE
Pages299-300
Number of pages2
Editionpt 1
ISBN (Print)0780313771
StatePublished - Dec 1 1993
Externally publishedYes
EventProceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Society - San Diego, CA, USA
Duration: Oct 28 1993Oct 31 1993

Publication series

NameProceedings of the Annual Conference on Engineering in Medicine and Biology
Numberpt 1
Volume15
ISSN (Print)0589-1019

Other

OtherProceedings of the 15th Annual International Conference of the IEEE Engineering in Medicine and Biology Society
CitySan Diego, CA, USA
Period10/28/9310/31/93

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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