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

Unobtrusive sleep posture estimation using pressure sensor in home sleep.

Computers in biology and medicine·2026
Same author

Effect of closed-loop vibration stimulation on sleep quality for poor sleepers.

Frontiers in neuroscience·2024
Same author

Modulation of sleep using noninvasive stimulations during sleep.

Biomedical engineering letters·2023
Same author

Semiautomated Algorithm for the Diagnosis of Multiple System Atrophy With Predominant Parkinsonism.

Journal of movement disorders·2022
Same author

Noninvasive Versus Invasive Brain Temperature Measurement During Targeted Temperature Management: A Preclinical Study in a Swine Cardiac Arrest Model.

Therapeutic hypothermia and temperature management·2022
Same author

Signal Quality Index Based on Template Cross-Correlation in Multimodal Biosignal Chair for Smart Healthcare.

Sensors (Basel, Switzerland)·2021
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: May 7, 2026

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
06:34

A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

Published on: July 7, 2023

3.6K

Frequency recognition methods for dual-frequency SSVEP based brain-computer interface.

Min Hye Chang, Kwang Suk Park

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 11, 2013
    PubMed
    Summary
    This summary is machine-generated.

    This study explored multi-frequency recognition for dual-frequency steady-state visual evoked potentials (SSVEP) in brain-computer interfaces. Canonical correlation analysis (CCA) with novel features, including harmonic frequencies, demonstrated superior classification performance.

    More Related Videos

    SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
    11:01

    SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

    Published on: November 24, 2015

    12.5K
    Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI
    11:00

    Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI

    Published on: March 19, 2021

    5.3K

    Related Experiment Videos

    Last Updated: May 7, 2026

    A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare
    06:34

    A Single-Channel and Non-Invasive Wearable Brain-Computer Interface for Industry and Healthcare

    Published on: July 7, 2023

    3.6K
    SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots
    11:01

    SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots

    Published on: November 24, 2015

    12.5K
    Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI
    11:00

    Reliable Acquisition of Electroencephalography Data during Simultaneous Electroencephalography and Functional MRI

    Published on: March 19, 2021

    5.3K

    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Steady-state visual evoked potentials (SSVEP) offer a promising avenue for brain-computer interface (BCI) development.
    • Dual-frequency SSVEP aims to increase stimulus options using limited flicker frequencies.
    • Previous research has not fully explored multi-frequency recognition strategies for dual-frequency SSVEP.

    Purpose of the Study:

    • To investigate and compare various signal processing methods for classifying dual-frequency SSVEP.
    • To evaluate the efficacy of incorporating harmonic frequencies into classification algorithms.
    • To identify the optimal strategy for enhancing BCI performance using dual-frequency SSVEP.

    Main Methods:

    • Tested three modified Power Spectral Density Analysis (PSDA) methods.
    • Evaluated two modified Canonical Correlation Analysis (CCA) methods.
    • Compared conventional features against novel features, specifically incorporating harmonic frequencies.

    Main Results:

    • Canonical Correlation Analysis (CCA) with novel features achieved the highest Brain-Computer Interface (BCI) performance.
    • The inclusion of harmonic frequencies significantly improved the BCI performance of dual-frequency SSVEP.
    • Modified CCA methods outperformed modified PSDA methods in dual-frequency SSVEP classification.

    Conclusions:

    • Novel feature extraction, particularly leveraging harmonic frequencies, is crucial for effective dual-frequency SSVEP classification.
    • CCA demonstrates superior performance over PSDA for this specific BCI application.
    • Future BCI development should consider multi-frequency recognition strategies for enhanced dual-frequency SSVEP utilization.