Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Classification of Signals

Classification of Signals

In signal processing, signals are classified based on various characteristics: continuous-time versus discrete-time, periodic versus aperiodic, analog versus digital, and causal versus noncausal. Each category highlights distinct properties crucial for understanding and manipulating signals.
A continuous-time signal holds a value at every instant in time, representing information seamlessly. In contrast, a discrete-time signal holds values only at specific moments, often denoted as x(n), where...

Correlation between ECG and Cardiac Cycle

Correlation between ECG and Cardiac Cycle

The electrical signals recorded on an electrocardiogram (ECG) occur before the mechanical processes of contraction and relaxation during the cardiac cycle.
A cardiac action potential originates in the SA node and spreads throughout the atria and the AV node in approximately 0.03 seconds. This results in the P wave in an ECG and triggers atrial contraction. The action potential is then briefly slowed at the AV node, allowing the atria to contract and fill the ventricles with blood before...

ECG Interpretation of Rhythms

ECG Interpretation of Rhythms

An electrocardiogram (ECG)graphically represents the heart's electrical activity on ECG paper or a monitor.
Components of the Electrocardiogram
The primary components of a normal ECG waveform in Normal sinus rhythm(NSR) include the P wave, PR interval, QRS complex, ST segment, T wave, and occasionally a U wave.
ECG waveforms are divided by vertical and horizontal lines at standard intervals.
The horizontal axis measures time and rate, and the vertical axis measures amplitude or voltage. When...

Linear Approximation in Frequency Domain

Linear Approximation in Frequency Domain

Linear systems are characterized by two main properties: superposition and homogeneity. Superposition allows the response to multiple inputs to be the sum of the responses to each individual input. Homogeneity ensures that scaling an input by a scalar results in the response being scaled by the same scalar.
In contrast, nonlinear systems do not inherently possess these properties. However, for small deviations around an operating point, a nonlinear system can often be approximated as linear.

Routh-Hurwitz Criterion II

Routh-Hurwitz Criterion II

In the application of the Routh-Hurwitz criterion, two specific scenarios can arise that complicate stability analysis.
The first scenario occurs when a singular zero appears in the first column of the Routh table. This situation creates a division by zero issues. To resolve this, a small positive or negative number, denoted as epsilon (∈), is substituted for the zero. The stability analysis proceeds by assuming a sign for ∈. If ∈ is positive, any sign change in the first column of the Routh...

Kendall's Coefficient of Concordance

Kendall's Coefficient of Concordance

Kendall's Coefficient of Concordance (W), also known as Kendall's W, is a non-parametric statistical measure used to assess the agreement or concordance between multiple raters or judges when they rank a set of items. It is often used when you have ordinal data (ranks) and you want to see if there is consistency or consensus among the raters. It is widely applied in research areas such as psychology, medicine, and social sciences, where multiple judges are asked to rank or rate subjects or...

You might also read

Related Articles

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

Sort by

Same author

Hemodynamics-guided treatment of hypertensive disorders of pregnancy: systematic review and meta-analysis.

Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology·2026

Same author

The IADR Policy Statement on Antimicrobial Resistance.

Journal of dental research·2025

Same author

Effective and safe use of alirocumab in spinal and bulbar muscular atrophy with high cardiovascular risk: a case report.

European review for medical and pharmacological sciences·2025

Same author

Culturomics: Deciphering the Microbial Dark Matter in the Oral Cavity.

Journal of dental research·2025

Same author

Genomic and Transcriptomic Adaptation to Chlorhexidine in <i>Streptococcus</i> spp.

Journal of dental research·2025

Same author

Species differences in opsonization and phagocyte recognition of preclinical poly-2-alkyl-2-oxazoline-coated nanoparticles.

Nature communications·2025

Search research articles

Related Experiment Video

Updated: Jun 26, 2026

Uncovering Beat Deafness: Detecting Rhythm Disorders with Synchronized Finger Tapping and Perceptual Timing Tasks

Uncovering Beat Deafness: Detecting Rhythm Disorders with Synchronized Finger Tapping and Perceptual Timing Tasks

Published on: March 16, 2015

A covariance-based algorithm: a novel technique for rhythm discrimination in ICDs.

B Kamousi¹, B Lin, A Al-Ahmad

¹School of Medicine, Stanford University, Stanford, CA, USA.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

|January 24, 2009

Summary

A new covariance-based algorithm effectively distinguishes ventricular tachycardia from other arrhythmias in implantable cardioverter-defibrillators (ICDs). This method promises to reduce inappropriate shocks for patients with ICDs.

Related Experiment Videos

Last Updated: Jun 26, 2026

Uncovering Beat Deafness: Detecting Rhythm Disorders with Synchronized Finger Tapping and Perceptual Timing Tasks

Uncovering Beat Deafness: Detecting Rhythm Disorders with Synchronized Finger Tapping and Perceptual Timing Tasks

Published on: March 16, 2015

Area of Science:

Biomedical Engineering
Cardiology
Medical Devices

Background:

Inappropriate shocks from implantable cardioverter-defibrillators (ICDs) are a significant clinical issue.
Misclassification of supraventricular and ventricular arrhythmias leads to these shocks.
Current ICDs require improved rhythm classification accuracy.

Purpose of the Study:

To evaluate a novel covariance-based algorithm for distinguishing ventricular tachycardia (VT) from supraventricular tachycardia (SVT).
To assess the algorithm's applicability and efficacy in implantable cardioverter-defibrillators.
To determine the potential of the algorithm in reducing inappropriate shocks.

Main Methods:

Development and testing of a new covariance-based algorithm for arrhythmia classification.
Application of the algorithm to single-chamber and dual-chamber ICDs with minor adjustments.
Computational demand analysis of the proposed algorithm.

Main Results:

The covariance-based algorithm demonstrated a promising ability to differentiate VT from SVT.
The algorithm is computationally efficient.
The algorithm showed adaptability for both single-chamber and dual-chamber ICD systems.

Conclusions:

The novel covariance-based algorithm is a potentially effective tool for ICD rhythm classification.
Implementation of this algorithm could significantly decrease the incidence of inappropriate shocks in ICD patients.
Further validation is warranted to confirm clinical utility.