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 decision table and rule based interpretation system for epileptic discharges.

R B Mishra1

  • 1Dept. of Electrical Engg., IT-BHU, Varanasi, India.

International Journal of Clinical Monitoring and Computing
|October 1, 1992
PubMed
Summary

This study presents a low-cost system for diagnosing epilepsy using electroencephalogram (EEG) data. The system employs decision tables and a rule-based approach for effective analysis of EEG waveforms.

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

Knowledge and intelligent computing system in medicine.

Computers in biology and medicine·2009
Same author

Calcium and magnesium levels during automated plateletpheresis in normal donors.

Transfusion medicine (Oxford, England)·2005
Same author

A knowledge based interpretation system for EMG abnormalities.

International journal of clinical monitoring and computing·1993
Same author

Microprocessor based detection of epileptic discharges.

International journal of clinical monitoring and computing·1991

Area of Science:

  • Biomedical Engineering
  • Medical Informatics
  • Artificial Intelligence in Medicine

Background:

  • Expert systems are valuable for disease diagnosis using electroencephalogram (EEG) features.
  • Developing specialized hardware and software for EEG analysis can be expensive.
  • There is a need for cost-effective diagnostic tools for neurological conditions like epilepsy.

Purpose of the Study:

  • To design and develop an affordable system for diagnosing epileptic seizures.
  • To model physician reasoning processes for epilepsy diagnosis using computational methods.

Main Methods:

  • Utilized a two-stage approach combining decision tables and a rule-based system.
  • EEG waveform features were extracted using an 8086 microprocessor-based data acquisition system.
  • A rule-based system was implemented in Turbo-Prolog on a PC-AT for final diagnosis.

Main Results:

  • Decision tables provided intermediate data processing of EEG features.
  • The rule-based model achieved final-stage analysis of EEG data.
  • System performance, evaluated on epileptic patient EEGs, yielded comparable and appreciable results.

Conclusions:

  • The developed low-cost system demonstrates potential for epilepsy diagnosis.
  • The combined decision table and rule-based approach effectively models diagnostic reasoning.
  • Further evaluation is warranted, but initial results are promising for clinical application.

Related Experiment Videos