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

Area Computation by the Alternative Coordinate Method01:24

Area Computation by the Alternative Coordinate Method

860
The alternative coordinate method, also known as the Shoelace Formula, is a technique for determining the area of a traverse using Cartesian coordinates. This method relies on the sequential arrangement of x and y coordinates for each point of the shape, ensuring accuracy and ease of application.In this approach, each corner's x and y coordinates are listed as fractions, with the x-coordinate as the numerator and the y-coordinate as the denominator. These coordinates are arranged sequentially...
860
Response Surface Methodology01:16

Response Surface Methodology

904
Response Surface Methodology (RSM) is a collection of statistical and mathematical techniques used to develop, improve, and optimize processes. It is particularly valuable when many input variables or factors potentially influence a response variable.
The process of RSM involves several key steps:
904

You might also read

Related Articles

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

Sort by
Same author

TACE Combined with Ralox-HAIC (Oxaliplatin Puls Raltitrexed) and System Therapy in Patients with Unresectable Hepatocellular Carcinoma.

Journal of hepatocellular carcinoma·2026
Same author

A "Three-in-One" AuNRs@ZIF-8/AuNPs Nanoplatform: Nanoenzyme-Mediated SERS-Colorimetric Bimodal Detection of Intracellular Glutathione and Photothermal Therapy.

ACS applied materials & interfaces·2026
Same author

Central nervous system multiple myeloma: An update for 2026.

Annals of hematology·2026
Same author

Entropy-Stabilized High-Entropy Sulfide Anodes for Fast-Charging and Long-Life Sodium-Ion Batteries.

ACS applied materials & interfaces·2026
Same author

Dissipative quantum geometric phase in the spin-boson system.

The Journal of chemical physics·2026
Same author

Gelsolin amyloidosis presenting with nephrotic syndrome: a case report and molecular insights.

Frontiers in medicine·2026
Same journal

Graph Convolutional Neural Network based Depression Detection using Brain Functional Connectivity Measures.

IEEE journal of biomedical and health informatics·2026
Same journal

Improving Multi-Sensor Non-Invasive Glucose Detection through AI: A Domain Generalization Approach.

IEEE journal of biomedical and health informatics·2026
Same journal

Unmixing the Neck: Accurate Jugular Venous Pulse Detection From Wearable PPG.

IEEE journal of biomedical and health informatics·2026
Same journal

AD-DAE: Alzheimer's Disease Progression Modeling with Unpaired Longitudinal MRI using Diffusion Auto-Encoders.

IEEE journal of biomedical and health informatics·2026
Same journal

EEG Connectivity Signatures in Active vs. Passive Mental Fatigue Settings.

IEEE journal of biomedical and health informatics·2026
Same journal

Privacy-Enhanced Vertical Federated Learning for Healthcare via Directional Noise and Subset Representations.

IEEE journal of biomedical and health informatics·2026
See all related articles

Related Experiment Video

Updated: May 3, 2026

STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces
05:36

STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces

Published on: March 10, 2026

114

Unified Online Adaptation Framework for Correlation Analysis-based Spatial Filtering Methods in SSVEP-based BCIs.

Ze Wang, Lu Shen, Xinran Mi

    IEEE Journal of Biomedical and Health Informatics
    |May 1, 2026
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces a unified framework for online adaptation in brain-computer interfaces (BCIs), enabling calibration-free recognition for steady-state visual evoked potential (SSVEP) detection. The new method significantly improves recognition accuracy compared to previous approaches.

    More Related Videos

    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
    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

    15.2K

    Related Experiment Videos

    Last Updated: May 3, 2026

    STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces
    05:36

    STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces

    Published on: March 10, 2026

    114
    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
    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

    15.2K

    Area of Science:

    • Neuroscience
    • Biomedical Engineering
    • Signal Processing

    Background:

    • Online adaptation is crucial for user-friendly brain-computer interfaces (BCIs), but its application to steady-state visual evoked potential (SSVEP) recognition is limited.
    • Existing methods like online multi-stimulus canonical correlation analysis (OMSCCA) for SSVEP spatial filter adaptation are effective but not broadly extensible.
    • This limits the development of generalizable calibration-free BCI algorithms.

    Purpose of the Study:

    • To propose a unified online adaptation framework for correlation analysis (CA)-based spatial filtering methods in SSVEP recognition.
    • To enable calibration-free, continuous updates of spatial filters for advanced filtering techniques.
    • To enhance the development of user-friendly, zero-calibration SSVEP-based BCIs.

    Main Methods:

    • Extended the least-squares (LS) unified framework for online adaptation without pre-calibration, allowing continuous spatial filter updates.
    • Introduced a cross-stimulus transfer method for adapting common impulse response and generating user-specific templates using limited online unlabeled data.
    • Adapted three advanced spatial filtering methods to online paradigms using the proposed framework and validated through simulations.

    Main Results:

    • The unified framework effectively promotes the development of zero-calibration SSVEP-based BCIs.
    • The proposed online adaptation methods improved recognition performance by over 12% compared to OMSCCA.
    • Demonstrated the framework's generalizability for transforming calibration-based methods into adaptive solutions.

    Conclusions:

    • The proposed unified framework provides a generalizable approach for online adaptation in SSVEP recognition.
    • This work facilitates the creation of more practical and user-friendly BCI systems by eliminating the need for pre-calibration.
    • The enhanced performance and adaptability pave the way for wider adoption of SSVEP-based BCIs.