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 Concept Videos

Cardiac Output I:Effect of Heart Rate on Cardiac Output01:19

Cardiac Output I:Effect of Heart Rate on Cardiac Output

Cardiac Output
Cardiac output (CO) refers to the total amount of blood ejected by one of the ventricles in liters per minute (L/min). In a resting adult, CO ranges from 5 to 6 L/min, adjusting according to the body's metabolic requirements.
Effect of Heart Rate on Cardiac Output
Cardiac output adapts to metabolic demands during stress, physical activity, or illness. The autonomic nervous system regulates heart rate via the sinoatrial node. The parasympathetic nervous system decreases heart rate...
Factors Influencing Heart Rate01:30

Factors Influencing Heart Rate

The heart rate, or pulse rate, is a vital indicator of cardiovascular health. It reflects the number of times the heart beats per minute. Various physiological and environmental factors influence heart rate, increasing or decreasing cardiac output. Understanding these factors is crucial for assessing heart function and identifying potential health issues.
Let us explore the significant factors affecting heart rate, including age, body temperature, posture, acute pain, chemical influences,...
Pathophysiology of Cardiac Performance01:29

Pathophysiology of Cardiac Performance

Typical heart performance is influenced by heart rate, rhythm, myocardial contraction, and metabolism or blood flow. The cardiac muscle exhibits distinct electrophysiological features, including pacemaker activity and calcium channel control, which play a vital role in the heart's response to various drugs. The autonomic nervous system, comprising the sympathetic and parasympathetic branches, regulates heart rate. Sympathetic activation increases heart rate, while parasympathetic activation...

You might also read

Related Articles

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

Sort by
Same author

Modeling the Frank-Starling Mechanism at the Cardiac Muscle and Ventricle Levels.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
Same author

Canine Smooth Muscle Contraction Model.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2022
Same author

Modeling Mouse Soleus Muscle Contraction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2020
Same author

Functional Requirements of a Mathematical Model of Muscle Contraction.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2020
Same author

Modeling muscle's nonlinear viscoelastic dynamics.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2015
Same author

What should determine loop time during CPR: a generic algorithm or the patient's initial rhythm?

Resuscitation·2014

Related Experiment Video

Updated: May 25, 2026

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
12:09

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

Published on: January 8, 2013

Left ventricular model parameters and cardiac rate variability.

Joseph L Palladino1, Ryan L Zukus, Andrei Marchidan

  • 1Department of Engineering, Trinity College, Hartford, CT, USA. joseph.palladino@trincoll.edu

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|January 19, 2012
PubMed
Summary
This summary is machine-generated.

This study presents a new functional model of the left ventricle using parameters to describe its contractile state. The model, based on crossbridge dynamics, accurately predicts ventricular elastance and heart rate variability in canine hearts.

More Related Videos

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
09:20

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

A Pacing-Controlled Procedure for the Assessment of Heart Rate-Dependent Diastolic Functions in Murine Heart Failure Models
07:49

A Pacing-Controlled Procedure for the Assessment of Heart Rate-Dependent Diastolic Functions in Murine Heart Failure Models

Published on: July 21, 2023

Related Experiment Videos

Last Updated: May 25, 2026

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations
12:09

Patient-specific Modeling of the Heart: Estimation of Ventricular Fiber Orientations

Published on: January 8, 2013

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction
09:20

Lumped-Parameter and Finite Element Modeling of Heart Failure with Preserved Ejection Fraction

Published on: February 13, 2021

A Pacing-Controlled Procedure for the Assessment of Heart Rate-Dependent Diastolic Functions in Murine Heart Failure Models
07:49

A Pacing-Controlled Procedure for the Assessment of Heart Rate-Dependent Diastolic Functions in Murine Heart Failure Models

Published on: July 21, 2023

Area of Science:

  • Cardiovascular Physiology
  • Biomedical Engineering
  • Computational Biology

Background:

  • Current left ventricular models often use variables, limiting their ability to capture complex dynamics.
  • Understanding the ventricle's contractile state requires a model that accounts for time and volume dependency.

Purpose of the Study:

  • To present a detailed functional model of a canine left ventricle using parameters.
  • To describe the ventricle as a pressure generator based on crossbridge dynamics.
  • To extend the model to incorporate heart rate variability.

Main Methods:

  • Developed a single equation based on crossbridge bond formation and relaxation.
  • Calculated dynamic ventricular elastance (E(v)) independently of load properties.
  • Extracted model parameters from measured pressure and volume data in isolated canine hearts.

Main Results:

  • The functional model successfully characterizes the left ventricle's contractile state using parameters.
  • Ventricular elastance is dynamic and reflects the changing number of crossbridge bonds.
  • The model naturally incorporates heart rate variability, with computed results aligning with experimental data.

Conclusions:

  • The proposed parameter-based model offers a novel approach to understanding left ventricular function.
  • The model's foundation in crossbridge dynamics provides mechanistic insight into heart mechanics.
  • The model's ability to predict ventricular elastance and heart rate variability demonstrates its physiological relevance.