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 Experiment Videos

A novel multiple frequency stimulation method for steady state VEP based brain computer interfaces.

T M Srihari Mukesh1, V Jaganathan, M Ramasubba Reddy

  • 1Biomedical Engineering Division, Dept. of Applied Mechanics, Indian Institute of Technology-Madras, Chennai, India.

Physiological Measurement
|December 21, 2005
PubMed
Summary

This study enhances brain computer interfaces (BCI) by combining visual stimulation frequencies to increase user command options. This method boosts BCI selection capability using fewer frequencies.

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

CNN models in time-frequency domain for identification of motor imagery tasks from EEG signals.

Physical and engineering sciences in medicine·2026
Same author

Enhancing the performance of a deep convolutional neural network model for motor imagery classification using EEG channel-wise attention module.

Medical engineering & physics·2026
Same author

Frontal EEG correlation based human emotion identification and classification.

Physical and engineering sciences in medicine·2024
Same author

Narrow band-pass filtered canonical correlation analysis for frequency identification in SSVEP signals.

Biomedical physics & engineering express·2024
Same author

Classification of Motor Imagery EEG signals using high resolution time-frequency representations and convolutional neural network.

Biomedical physics & engineering express·2024
Same author

Performance of Empirical Mode Decomposition for Frequency Identification in SSVEP Based BCI.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference·2023

Area of Science:

  • Neuroscience
  • Biomedical Engineering
  • Signal Processing

Background:

  • Brain Computer Interfaces (BCI) translate neural signals into commands.
  • Steady State Visual Evoked Potential (SSVEP) based BCIs are limited by available stimulation frequencies.
  • Increasing command options is crucial for BCI usability.

Purpose of the Study:

  • To develop a method for increasing the number of selectable commands in SSVEP-based BCIs.
  • To investigate the efficacy of using combined stimulation frequencies to expand BCI command sets.
  • To analyze the spectral characteristics of SSVEP responses to simultaneous, overlapped stimulation.

Main Methods:

  • Recorded SSVEP signals (O(z)-A(1)) from 15 subjects using a biopotential amplifier with a driven right leg circuit.

Related Experiment Videos

  • Utilized simultaneous, overlapped stimulation frequencies (6, 7, 12, 13, 14 Hz and their half frequencies).
  • Analyzed 60-second epochs, obtaining power spectra via frequency domain averaging of 400 ms SSVEPs and normalizing spectral peaks.

    • Main Results:

    • Spectral peaks from combined stimulation frequencies were predominant over individual frequencies.
    • Demonstrated that combining frequencies significantly enhances the number of distinguishable SSVEP responses.
    • Showcased a method to achieve six BCI selections using only three distinct stimulation frequencies.

    Conclusions:

    • Combining stimulation frequencies is an effective strategy to increase the number of commands in SSVEP BCIs.
    • This approach overcomes the limitations of frequency bands in SSVEP BCI design.
    • The proposed method offers a practical way to expand BCI functionality with a limited frequency set.