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

Ventricular beat classifier using fractal number clustering.

H Bakardjian1

  • 1Institute of Biomedical Engineering, Medical Academy, Sofia, Bulgaria.

Medical & Biological Engineering & Computing
|September 1, 1992
PubMed
Summary

This study introduces an efficient two-stage method for classifying ventricular beats, distinguishing normal beats from extrasystoles using shape and polarity. This approach enhances accuracy in analyzing heart rhythm abnormalities.

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

The Road Ahead to Cure Alzheimer's Disease: Development of Biological Markers and Neuroimaging Methods for Prevention Trials Across all Stages and Target Populations.

The journal of prevention of Alzheimer's disease·2015
Same author

Movement-related cortical evoked potentials using four-limb imagery.

The International journal of neuroscience·2009
See all related articles

Area of Science:

  • Cardiology
  • Biomedical Engineering
  • Signal Processing

Background:

  • Accurate classification of ventricular beats is crucial for diagnosing cardiac conditions.
  • Existing methods may struggle with borderline cases due to reliance on fixed thresholds.
  • Novel approaches are needed for robust and efficient heart rhythm analysis.

Purpose of the Study:

  • To develop and evaluate a two-stage associative classification procedure for ventricular beats.
  • To improve the accuracy and efficiency of distinguishing typical beats from extrasystoles.
  • To offer a real-time applicable method for cardiac rhythm analysis.

Main Methods:

  • A two-stage classification process was employed.
  • Stage one utilized area and polarity rules to separate typical beats from extrasystoles.
  • Stage two used self-organized clustering of shape parameters, including fractal number and polarity, for extrasystole classification.

Main Results:

  • The fractal number and polarity proved effective for waveform evaluation.
  • The method successfully classified ventricular beats without critical threshold values.
  • The computational efficiency allows for potential real-time system implementation.

Conclusions:

  • The described two-stage associative classification procedure offers an accurate and efficient method for ventricular beat analysis.
  • This approach overcomes limitations of threshold-dependent methods, particularly in complex cases.
  • The computational efficiency supports its application in real-time cardiac monitoring systems.

Related Experiment Videos