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

Receiver Operating Characteristic Plot01:15

Receiver Operating Characteristic Plot

204
A ROC (Receiver Operating Characteristic) plot is a graphical tool used to assess the performance of a binary classification model by illustrating the trade-off between sensitivity (true positive rate) and specificity (false positive rate). By plotting sensitivity against 1 - specificity across various threshold settings, the ROC curve shows how well the model distinguishes between classes, with a curve closer to the top-left corner indicating a more accurate model. The area under the ROC curve...
204
Classification of Signals01:30

Classification of Signals

471
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...
471
Residual Plots01:07

Residual Plots

4.6K
A residual plot is a statistical representation of data used to analyze correlation and regression results. It helps verify the requirements for drawing specific conclusions about correlation and regression. To obtain the residual plot, first, the residual for each data value is calculated, which is simply the vertical distance between the observed and the predicted value obtained from the regression equation.
When the residual values are plotted against the variable x, it is called a residual...
4.6K
Classification of Systems-II01:31

Classification of Systems-II

149
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,
149
Time-Series Graph00:54

Time-Series Graph

4.4K
A time-series graph is a line graph with repeated measurements taken at successive intervals of time. It is also called a time series chart. To construct a time-series graph, one must look at both pieces of a paired data set. The horizontal axis is used to plot the time increments, and the vertical axis is used to plot the values of the variable that one is measuring. By using the axes in this way, each point on the graph will correspond to time and a measured quantity. The points on the graph...
4.4K
Classification of Systems-I01:26

Classification of Systems-I

188
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:
188

You might also read

Related Articles

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

Sort by
Same author

Efficacy and safety of neoadjuvant apatinib plus PD-1 inhibitor with SOX for locally advanced gastric cancer: A multicenter, retrospective cohort study.

International journal of cancer·2026
Same author

Entropy Production in Non-Gaussian Active Matter: A Unified Fluctuation Theorem and Deep Learning Framework.

Physical review letters·2026
Same author

Effect of whole-course nutrition management on skeletal muscle mass in patients with gastric cancer undergoing neoadjuvant treatment.

European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology·2026
Same author

<i>STAT3<sup>R152W</sup></i> Mutation Model Reveals Temporal Changes in Hematopoietic Populations.

International journal of molecular sciences·2026
Same author

Chromatin modifiers KMT2D, BAF, and p300 are required for <i>de novo</i> binding of transcription factors on enhancers.

bioRxiv : the preprint server for biology·2026
Same author

Non-contact seismocardiogram measurement and HRV analysis using cardiac beamforming with FMCW radar.

Frontiers in physiology·2026
Same journal

Analysis of End-Tidal CO2 Variability During Plateau Waves Episodes: An Information Theoretic Approach<sup></sup>.

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

AI and Tomosynthesis for Breast Cancer Molecular Subtyping: A step toward precision medicine<sup></sup>.

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

Towards Sustainable Protein Recovery from Biological Waste: Assessing Polyethersulfone-based Microfiltration.

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

Analysis of the cardiovascular response to standardized polymicrobial peritonitis experimental model.

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

Automated Wrist Ultrasound Image Bone Enhancement and Segmentation Using Deep Learning.

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

A Deep Learning approach for Depressive Symptoms assessment in Parkinson's disease patients using facial videos.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2025
See all related articles

Related Experiment Video

Updated: Jul 8, 2025

Automated Detection and Analysis of Exocytosis
13:28

Automated Detection and Analysis of Exocytosis

Published on: September 11, 2021

3.5K

AF automatic classification based on different time-delay values of the recurrence plot.

Hua Zhang, Chengyu Liu, Fangfang Tang

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |December 12, 2023
    PubMed
    Summary
    This summary is machine-generated.

    This study optimizes Recurrence Plot (RP) analysis for atrial fibrillation (AF) prediction using electrocardiogram (ECG) data. Optimal time-delay parameter τ=1 significantly improves AF classification performance based on cardiac electrical signal patterns.

    More Related Videos

    A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
    10:46

    A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

    Published on: December 9, 2015

    10.7K
    Measurement & Analysis of the Temporal Discrimination Threshold Applied to Cervical Dystonia
    10:05

    Measurement & Analysis of the Temporal Discrimination Threshold Applied to Cervical Dystonia

    Published on: January 27, 2018

    9.8K

    Related Experiment Videos

    Last Updated: Jul 8, 2025

    Automated Detection and Analysis of Exocytosis
    13:28

    Automated Detection and Analysis of Exocytosis

    Published on: September 11, 2021

    3.5K
    A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data
    10:46

    A Method of Trigonometric Modelling of Seasonal Variation Demonstrated with Multiple Sclerosis Relapse Data

    Published on: December 9, 2015

    10.7K
    Measurement & Analysis of the Temporal Discrimination Threshold Applied to Cervical Dystonia
    10:05

    Measurement & Analysis of the Temporal Discrimination Threshold Applied to Cervical Dystonia

    Published on: January 27, 2018

    9.8K

    Area of Science:

    • Cardiology
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Recurrence Plots (RPs) visualize 1D ECG signals as 2D images to reveal cardiac electrical activity patterns.
    • The optimal time-delay parameter (τ) for RP construction is crucial but not well-established for AF prediction.

    Purpose of the Study:

    • To investigate the impact of various time-delay (τ) values on Recurrence Plot-based atrial fibrillation (AF) prediction.
    • To identify the optimal τ parameter for enhancing ECG-based AF classification accuracy.

    Main Methods:

    • Generated Recurrence Plots (RPs) from 1D ECG waveforms using a range of time-delay (τ) parameters.
    • Evaluated the classification performance of RPs generated with different τ values for AF detection.

    Main Results:

    • The study found that a time-delay parameter (τ) of 1 yielded the best classification performance for AF prediction.
    • This optimal τ value captured the full characteristics of the cardiac dynamic system in the RP.

    Conclusions:

    • An effective AF classification system was established using recurrence features derived from ECG.
    • The optimal time-delay parameter (τ=1) for Recurrence Plots significantly improves ECG-based AF classification performance.