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

You might also read

Related Articles

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

Sort by
Same author

RSV-associated acute otitis media in children under five years old: a systematic review and meta-analysis.

Journal of global health·2026
Same author

Source-space EEG alpha activity reveals brain age gaps due to neurodegeneration and disparity.

Communications biology·2026
Same author

Diversity-sensitive brain clocks linked to biophysical mechanisms in aging and dementia.

Nature. Mental health·2026
Same author

The exposome of brain aging across 34 countries.

Nature medicine·2026
Same author

Endotracheal surfactant for infants with life-threatening bronchiolitis (BESS): a randomised, blinded, sham-controlled, phase 2 trial.

The Lancet. Respiratory medicine·2026
Same author

Creative experiences and brain clocks.

Nature communications·2025

Related Experiment Video

Updated: Aug 28, 2025

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
11:15

Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

Published on: June 27, 2013

33.9K

Stratified Multivariate Multiscale Dispersion Entropy for Physiological Signal Analysis.

Evangelos Kafantaris, Tsz-Yan Milly Lo, Javier Escudero

    IEEE Transactions on Bio-Medical Engineering
    |September 19, 2022
    PubMed
    Summary

    Stratified Entropy prioritizes physiological time-series channels, enhancing information extraction from complex systems. This novel approach improves physiological state monitoring by preventing data overshadowing.

    More Related Videos

    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
    08:22

    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

    Published on: April 26, 2024

    2.1K
    Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
    08:08

    Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

    Published on: May 10, 2017

    14.8K

    Related Experiment Videos

    Last Updated: Aug 28, 2025

    Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy
    11:15

    Applications of EEG Neuroimaging Data: Event-related Potentials, Spectral Power, and Multiscale Entropy

    Published on: June 27, 2013

    33.9K
    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis
    08:22

    Author Spotlight: Advancing the Study of Brain-Heart Interplay with a Comprehensive EEGLAB Plugin for Multimodal Signal Analysis

    Published on: April 26, 2024

    2.1K
    Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities
    08:08

    Using Wavelet Entropy to Demonstrate how Mindfulness Practice Increases Coordination between Irregular Cerebral and Cardiac Activities

    Published on: May 10, 2017

    14.8K

    Area of Science:

    • Physiological signal processing
    • Information theory
    • Biomedical engineering

    Background:

    • Multivariate entropy algorithms extract information from multi-channel physiological time-series.
    • Analysis of heterogeneous organ systems can lead to information loss due to channel overshadowing.

    Purpose of the Study:

    • Introduce the Stratified Entropy framework to prioritize channel dynamics.
    • Develop algorithmic variations for richer multi-channel time-series description.
    • Enhance information extraction from heterogeneous physiological data.

    Main Methods:

    • Developed three algorithmic variations of Stratified Multivariate Multiscale Dispersion Entropy.
    • Applied algorithms to synthetic, waveform, and derivative physiological time-series.
    • Evaluated channel prioritization and discrimination capacity across strata.

    Main Results:

    • Stratified Entropy variations successfully prioritized channels based on strata allocation.
    • Variations maintained low computational time compared to the original algorithm.
    • Increased discrimination capacity observed in variations for physiological state monitoring.

    Conclusions:

    • Stratified Entropy offers a novel approach for analyzing multi-channel time-series from heterogeneous systems.
    • The variations improve information extraction and physiological state monitoring.
    • The framework allows modification using a priori knowledge for channel stratification.