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 new defibrillator discrimination algorithm utilizing electrogram morphology analysis

M R Gold1, W Hsu, A F Marcovecchio

  • 1University of Maryland School of Medicine, Baltimore 21201-1595, USA. mgold@medicine.ab.umd.edu

Pacing and Clinical Electrophysiology : PACE
|February 17, 1999
PubMed
Summary
This summary is machine-generated.

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

Identification of Apically Localized Endogenous Dental Pulp Stem Cells.

Journal of dental research·2025
Same author

Brain injury and inflammation genes common to a number of neurological diseases and the genes involved in the genesis of GABAnergic neurons are altered in monoamine oxidase B knockout mice.

Brain research·2021
Same author

Decreased medial entorhinal cortical thickness in olanzapine exposed female rats is not ameliorated by exercise.

Pharmacology, biochemistry, and behavior·2019
Same author

Hippocampal volume and vasculature before and after exercise in treatment-resistant schizophrenia.

Schizophrenia research·2018
Same author

Noninvasive tissue adhesive for cardiac implantable electronic device pocket closure: the TAPE pilot study.

Journal of interventional cardiac electrophysiology : an international journal of arrhythmias and pacing·2018
Same author

Sensor, Signal, and Imaging Informatics.

Yearbook of medical informatics·2017
Same journal

Dual Coronary Sinus Lead Strategy to Avoid Tricuspid Valve Traversal in Biventricular Pacing.

Pacing and clinical electrophysiology : PACE·2026
Same journal

A Case of Permanent Pacemaker Implantation via the Epicardial Approach Using the 3830 Lead in an 11-Day-Old Neonate (With Follow-Up of the Above Case).

Pacing and clinical electrophysiology : PACE·2026
Same journal

Cryoballoon Versus Radiofrequency Ablation for Persistent Atrial Fibrillation: Meta-Analysis of Randomized Trials.

Pacing and clinical electrophysiology : PACE·2026
Same journal

Tilt Test Duration in Suspected Vasovagal Syncope: Temporal Patterns and Diagnostic Yield in Patients From Central China.

Pacing and clinical electrophysiology : PACE·2026
Same journal

Combined Leadless Pacing and Subcutaneous ICD Therapy in Long QT Syndromes.

Pacing and clinical electrophysiology : PACE·2026
Same journal

Association of Anesthesia Modality With Procedural Parameters and Clinical Outcomes in PVI for Atrial Fibrillation.

Pacing and clinical electrophysiology : PACE·2026
See all related articles

A new SimDis algorithm accurately distinguishes ventricular tachycardia from supraventricular arrhythmias using implantable cardioverter defibrillators (ICDs). This improves therapy delivery by enhancing arrhythmia discrimination capabilities.

Area of Science:

  • Biomedical Engineering
  • Cardiology
  • Medical Devices

Background:

  • Inappropriate therapies from implantable cardioverter defibrillators (ICDs) for supraventricular arrhythmias are a significant clinical issue.
  • Distinguishing between ventricular tachycardia and supraventricular arrhythmias is crucial for effective ICD therapy.

Purpose of the Study:

  • To develop and evaluate a novel algorithm, SimDis, for improved arrhythmia discrimination in ICDs.
  • To utilize morphological features of electrograms for differentiating between various heart rhythms.

Main Methods:

  • The SimDis algorithm was developed using electrogram data from 36 patients and validated on a separate set of 25 patients.
  • It analyzes electrogram morphology, classifying wide complexes as ventricular tachycardia and using similarity/dissimilarity measures for narrow complexes against a sinus rhythm template.

Related Experiment Videos

Main Results:

  • The SimDis algorithm achieved 100% accuracy in classifying ventricular tachycardias and atrial fibrillation.
  • It demonstrated 98% accuracy for sinus tachycardias, with an overall high sensitivity (100%) and specificity (99%) for arrhythmia discrimination.

Conclusions:

  • The SimDis algorithm offers a highly sensitive and specific method for arrhythmia discrimination within ICD systems.
  • This algorithm enhances the ability of ICDs to deliver appropriate therapies by accurately identifying different arrhythmia types.