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

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation

This lesson introduces two critical methods in pharmacokinetics, the Wagner-Nelson and Loo-Riegelman methods, used for estimating the absorption rate constant (ka) for drugs administered via non-intravenous routes. The Wagner-Nelson method relates ka to the plasma concentration derived from the slope of a semilog percent unabsorbed time plot. However, it is limited to drugs with one-compartment kinetics and can be impacted by factors like gastrointestinal motility or enzymatic degradation.
On...
Methods of Classification and Identification01:28

Methods of Classification and Identification

Bacterial identification relies on a diverse array of techniques to classify and understand microorganisms, each tailored to uncover specific characteristics. Traditional morphological approaches, while still valuable, are limited for closely related or structurally simple organisms. Modern methods integrate biochemical, serological, genetic, and advanced molecular tools to achieve greater accuracy.Morphological and Biochemical TechniquesMorphological characteristics, such as cell shape and...
Classification of Systems-II01:31

Classification of Systems-II

Continuous-time systems have continuous input and output signals, with time measured continuously. These systems are generally defined by differential or algebraic equations. For instance, in an RC circuit, the relationship between input and output voltage is expressed through a differential equation derived from Ohm's law and the capacitor relation,
Routh-Hurwitz Criterion II01:19

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...
Cluster Sampling Method01:20

Cluster Sampling Method

Appropriate sampling methods ensure that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest.
To choose a cluster sample, divide the population into clusters (groups) and then randomly select some of the clusters. All the members from these clusters are in the cluster sample. For example, if you randomly sample four departments from your...
Classification of Systems-I01:26

Classification of Systems-I

Linearity is a system property characterized by a direct input-output relationship, combining homogeneity and additivity.
Homogeneity dictates that if an input x(t) is multiplied by a constant c, the output y(t) is multiplied by the same constant. Mathematically, this is expressed as:

You might also read

Related Articles

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

Sort by
Same author

Correction: Luo et al. Dietary Anti-Aging Polyphenols and Potential Mechanisms. <i>Antioxidants</i> 2021, <i>10</i>, 283.

Antioxidants (Basel, Switzerland)·2026
Same author

Effect of acupuncture on monoaminergic neurotransmitters in animal models of vascular dementia: a preclinical systematic review and meta-analysis.

Frontiers in physiology·2026
Same author

The Impact of Adjuvant Radiotherapy Combined With Targeted or Immunotherapy on the Heart in Breast Cancer.

Thoracic cancer·2026
Same author

Elevated asprosin in hypertension: evidence from an exploratory case-control study.

Scientific reports·2026
Same author

Olive-derived elenolic acid surpasses metformin and rivals liraglutide in managing blood glucose and obesity in a mouse model of type 2 diabetes.

The Journal of nutritional biochemistry·2025
Same author

Impacts of Chitosan Coating on Shelf Life and Quality of Ready-to-Cook Beef Seekh Kabab During Refrigeration Storage.

Foods (Basel, Switzerland)·2025

Related Experiment Video

Updated: Jun 18, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

[Chaotic identification of HRV based on surrogate data method].

Dongmin Liu1

  • 1Shandong Cathay Biotechnology Co., Ltd., Jining 272073, China. hadron70@163.com

Sheng Wu Yi Xue Gong Cheng Xue Za Zhi = Journal of Biomedical Engineering = Shengwu Yixue Gongchengxue Zazhi
|December 2, 2009
PubMed
Summary
This summary is machine-generated.

This study identifies chaos in heart rate variability (HRV) using a surrogate data method. The approach analyzes healthy and unhealthy HRV signals, comparing characteristic parameters for better understanding of cardiac dynamics.

More Related Videos

Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis
08:46

Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis

Published on: August 26, 2020

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver
14:28

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Published on: June 27, 2025

Related Experiment Videos

Last Updated: Jun 18, 2026

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data
14:27

Identification of Disease-related Spatial Covariance Patterns using Neuroimaging Data

Published on: June 26, 2013

Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis
08:46

Genetic Variant Detection in the CALR gene using High Resolution Melting Analysis

Published on: August 26, 2020

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver
14:28

Software for Analysis of Heart Rate and Blood Pressure Time-series Data from the Valsalva Maneuver

Published on: June 27, 2025

Area of Science:

  • Cardiovascular Physiology
  • Nonlinear Dynamics
  • Biomedical Signal Processing

Context:

  • Heart rate variability (HRV) analysis is crucial for assessing autonomic nervous system function.
  • Identifying chaotic dynamics in HRV may reveal subtle physiological changes.
  • Existing methods may not fully capture the complex, nonlinear nature of HRV.

Purpose:

  • To introduce and validate a surrogate data method for identifying chaotic patterns in HRV.
  • To establish the median absolute error (MAE) of one-step prediction as a key statistic for chaotic identification.
  • To compare characteristic parameters derived from surrogate data analysis in healthy and unhealthy HRV.

Summary:

  • A novel application of the surrogate data method is presented to detect chaos in heart rate variability (HRV).
  • The method's efficacy is confirmed using a known chaotic system and a colored noise signal, with median absolute error (MAE) as the primary metric.
  • Analysis of typical healthy and unhealthy HRV datasets demonstrates the method's potential for differentiating cardiac states based on chaotic parameters.

Impact:

  • Provides a new tool for objective assessment of cardiac autonomic function through nonlinear analysis.
  • Enhances the understanding of physiological complexity in cardiovascular health and disease.
  • Potential for improved diagnostic capabilities in cardiology by detecting subtle chaotic markers in HRV.