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

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models00:57

Physiological Pharmacokinetic Models: Blood Flow-Limited Versus Diffusion-Limited Models

Physiological pharmacokinetic models, often called flow-limited or perfusion models, typically assume a swift drug distribution between tissue and venous blood, creating a rapid drug equilibrium. This premise is based on the idea that drug diffusion is extremely fast, and the cell membrane presents no barrier to drug permeation. In this scenario, where no drug binding occurs, the drug concentration in the tissue equals that of the venous blood leaving the tissue. This greatly simplifies the...
Applications of Integration to Find Blood Flow01:27

Applications of Integration to Find Blood Flow

Blood flow through a cylindrical blood vessel can be mathematically described using the principles of laminar flow, a regime in which fluid moves smoothly in parallel layers. In this model, the velocity of the blood is not uniform across the cross-section of the vessel; rather, it varies with the radial distance from the center. The maximum velocity occurs along the central axis, decreasing progressively toward the vessel walls, where it reaches zero due to viscous drag.Approximating Blood...
Multiple Pipe Systems01:21

Multiple Pipe Systems

Multipipe systems consist of complex configurations of interconnected pipes designed to transport fluids efficiently across intricate networks. They are essential in engineering applications requiring precise control over flow distribution, pressure, and head loss. They are categorized into series, parallel, loop, and network configurations, each distinguished by unique flow characteristics and applications.
Series Configuration
In a series configuration, fluid flows sequentially from one pipe...
Autoregulation of Blood Flow01:17

Autoregulation of Blood Flow

Autoregulation mechanisms are characterized by their inherent capacity for self-regulation without necessitating specific nervous stimulation or endocrine control. These mechanisms facilitate the adjustment of blood flow and, therefore, perfusion specific to each tissue region. This self-regulation encompasses chemical signals and myogenic controls.
Chemical Signaling in Autoregulation
Chemical signaling operates at the precapillary sphincter level, inciting either contraction or relaxation.
Bernoulli's Equation for Flow Along a Streamline01:30

Bernoulli's Equation for Flow Along a Streamline

Bernoulli's equation relates the energy conservation in a fluid moving along a streamline. The equation applies to incompressible and inviscid fluids under steady flow. For such a flow, Newton's second law is applied to a small fluid element, which experiences forces due to pressure differences, gravity, and velocity variations. The force balance leads to the following form of Bernoulli's equation:
Steady, Laminar Flow Between Parallel Plates01:17

Steady, Laminar Flow Between Parallel Plates

Understanding steady, laminar flow between parallel plates is essential for analyzing and designing flow in narrow rectangular channels, commonly found in various water conveyance and drainage systems. The Navier-Stokes equations govern fluid motion and are generally challenging to solve due to their nonlinearity. However, simplifications are possible in certain cases, like the steady laminar flow between parallel plates. For this scenario, we assume steady, incompressible, laminar flow.

You might also read

Related Articles

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

Sort by
Same author

MITO END-3: efficacy of avelumab immunotherapy according to molecular profiling in first-line endometrial cancer therapy.

Annals of oncology : official journal of the European Society for Medical Oncology·2024
Same author

The impact of COVID-19 pandemic control on vaccine-preventable invasive bacterial diseases in Piedmont (Italy).

Infection·2022
Same author

A multicenter validation of the revised version of the Milan system for reporting salivary gland cytology (MSRSGC).

Oral oncology·2020
Same author

Carboplatin-paclitaxel compared to Carboplatin-Paclitaxel-Bevacizumab in advanced or recurrent endometrial cancer: MITO END-2 - A randomized phase II trial.

Gynecologic oncology·2019
Same author

Radiofrequency ablation of functioning and non-functioning thyroid nodules: a single institution 12-month survey.

Journal of endocrinological investigation·2019
Same author

Diagnostic role of (18)F-FDG-PET or PET/CT in salivary gland tumors: A systematic review.

Revista espanola de medicina nuclear e imagen molecular·2015

Related Experiment Video

Updated: May 7, 2026

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

Inverse problems in 1D hemodynamics on systemic networks: a sequential approach.

D Lombardi1

  • 1INRIA Paris-Rocquencourt, Domaine de Voluceau, Rocquencourt-B.P. 105, 78153 Le Chesnay, France.

International Journal for Numerical Methods in Biomedical Engineering
|September 17, 2013
PubMed
Summary

This study uses an unscented Kalman filter to solve inverse problems in 1D hemodynamics, estimating arterial stiffness from blood flow data. The method offers a novel approach for analyzing systemic networks and peripheral circulation.

Keywords:
1D hemodynamicsinverse problemssequential approachsystemic networks

More Related Videos

Particle Image Velocimetry Investigation of Hemodynamics via Aortic Phantom
06:26

Particle Image Velocimetry Investigation of Hemodynamics via Aortic Phantom

Published on: February 25, 2022

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature
09:39

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Published on: November 18, 2019

Related Experiment Videos

Last Updated: May 7, 2026

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

Particle Image Velocimetry Investigation of Hemodynamics via Aortic Phantom
06:26

Particle Image Velocimetry Investigation of Hemodynamics via Aortic Phantom

Published on: February 25, 2022

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature
09:39

Spatial Temporal Analysis of Fieldwise Flow in Microvasculature

Published on: November 18, 2019

Area of Science:

  • Biomedical Engineering
  • Computational Fluid Dynamics
  • Physiology

Background:

  • Hemodynamics involves complex blood flow dynamics in arteries.
  • Estimating arterial properties like stiffness is crucial for diagnosing cardiovascular conditions.
  • Inverse problems in hemodynamics are challenging due to limited observational data.

Purpose of the Study:

  • To apply a sequential approach using the unscented Kalman filter to solve 1D inverse problems in hemodynamics.
  • To estimate arterial stiffness by analyzing cross-sectional area and mean speed observations.
  • To explore the identification of terminal model parameters and peripheral circulation models.

Main Methods:

  • A sequential approach based on the unscented Kalman filter (UKF) was implemented.
  • The method was applied to a systemic arterial network model.
  • Arterial stiffness was estimated using simulated observational data (cross-sectional area, mean speed).
  • Results were compared against pulse wave velocity and Moens-Korteweg formula estimations.

Main Results:

  • The unscented Kalman filter effectively solved inverse problems in 1D hemodynamics.
  • Arterial stiffness was successfully estimated using the proposed method.
  • The UKF-based estimation showed comparable results to traditional methods.
  • A perspective on identifying Windkessel circuit parameters for peripheral circulation was presented.

Conclusions:

  • The unscented Kalman filter provides a robust sequential method for inverse problems in hemodynamics.
  • This approach enables accurate estimation of arterial stiffness from observational data.
  • The study highlights potential for advanced modeling of systemic and peripheral circulation.