Literature DB >> 26695712

Effect of higher frequency on the classification of steady-state visual evoked potentials.

Dong-Ok Won1, Han-Jeong Hwang, Sven Dähne, Klaus-Robert Müller, Seong-Whan Lee.   

Abstract

OBJECTIVE: Most existing brain-computer interface (BCI) designs based on steady-state visual evoked potentials (SSVEPs) primarily use low frequency visual stimuli (e.g., <20 Hz) to elicit relatively high SSVEP amplitudes. While low frequency stimuli could evoke photosensitivity-based epileptic seizures, high frequency stimuli generally show less visual fatigue and no stimulus-related seizures. The fundamental objective of this study was to investigate the effect of stimulation frequency and duty-cycle on the usability of an SSVEP-based BCI system. APPROACH: We developed an SSVEP-based BCI speller using multiple LEDs flickering with low frequencies (6-14.9 Hz) with a duty-cycle of 50%, or higher frequencies (26-34.7 Hz) with duty-cycles of 50%, 60%, and 70%. The four different experimental conditions were tested with 26 subjects in order to investigate the impact of stimulation frequency and duty-cycle on performance and visual fatigue, and evaluated with a questionnaire survey. Resting state alpha powers were utilized to interpret our results from the neurophysiological point of view. MAIN
RESULTS: The stimulation method employing higher frequencies not only showed less visual fatigue, but it also showed higher and more stable classification performance compared to that employing relatively lower frequencies. Different duty-cycles in the higher frequency stimulation conditions did not significantly affect visual fatigue, but a duty-cycle of 50% was a better choice with respect to performance. The performance of the higher frequency stimulation method was also less susceptible to resting state alpha powers, while that of the lower frequency stimulation method was negatively correlated with alpha powers. SIGNIFICANCE: These results suggest that the use of higher frequency visual stimuli is more beneficial for performance improvement and stability as time passes when developing practical SSVEP-based BCI applications.

Entities:  

Mesh:

Year:  2015        PMID: 26695712     DOI: 10.1088/1741-2560/13/1/016014

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  20 in total

1.  Anti-fatigue Performance in SSVEP-Based Visual Acuity Assessment: A Comparison of Six Stimulus Paradigms.

Authors:  Xiaowei Zheng; Guanghua Xu; Yubin Zhang; Renghao Liang; Kai Zhang; Yuhui Du; Jun Xie; Sicong Zhang
Journal:  Front Hum Neurosci       Date:  2020-07-31       Impact factor: 3.169

Review 2.  A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives.

Authors:  Inchul Choi; Ilsun Rhiu; Yushin Lee; Myung Hwan Yun; Chang S Nam
Journal:  PLoS One       Date:  2017-04-28       Impact factor: 3.240

3.  A Novel Hybrid Mental Spelling Application Based on Eye Tracking and SSVEP-Based BCI.

Authors:  Piotr Stawicki; Felix Gembler; Aya Rezeika; Ivan Volosyak
Journal:  Brain Sci       Date:  2017-04-05

4.  A convolutional neural network for steady state visual evoked potential classification under ambulatory environment.

Authors:  No-Sang Kwak; Klaus-Robert Müller; Seong-Whan Lee
Journal:  PLoS One       Date:  2017-02-22       Impact factor: 3.240

5.  Evaluating the Influence of Chromatic and Luminance Stimuli on SSVEPs from Behind-the-Ears and Occipital Areas.

Authors:  Alan Floriano; Pablo F Diez; Teodiano Freire Bastos-Filho
Journal:  Sensors (Basel)       Date:  2018-02-17       Impact factor: 3.576

6.  Introducing chaotic codes for the modulation of code modulated visual evoked potentials (c-VEP) in normal adults for visual fatigue reduction.

Authors:  Zahra Shirzhiyan; Ahmadreza Keihani; Morteza Farahi; Elham Shamsi; Mina GolMohammadi; Amin Mahnam; Mohsen Reza Haidari; Amir Homayoun Jafari
Journal:  PLoS One       Date:  2019-03-06       Impact factor: 3.240

7.  Using brain-computer interfaces: a scoping review of studies employing social research methods.

Authors:  Johannes Kögel; Jennifer R Schmid; Ralf J Jox; Orsolya Friedrich
Journal:  BMC Med Ethics       Date:  2019-03-07       Impact factor: 2.652

8.  Application of a single-flicker online SSVEP BCI for spatial navigation.

Authors:  Jingjing Chen; Dan Zhang; Andreas K Engel; Qin Gong; Alexander Maye
Journal:  PLoS One       Date:  2017-05-31       Impact factor: 3.240

9.  Use of Sine Shaped High-Frequency Rhythmic Visual Stimuli Patterns for SSVEP Response Analysis and Fatigue Rate Evaluation in Normal Subjects.

Authors:  Ahmadreza Keihani; Zahra Shirzhiyan; Morteza Farahi; Elham Shamsi; Amin Mahnam; Bahador Makkiabadi; Mohsen R Haidari; Amir H Jafari
Journal:  Front Hum Neurosci       Date:  2018-05-28       Impact factor: 3.169

10.  An Efficient Asynchronous High-Frequency Steady-State Visual Evoked Potential-Based Brain-Computer Interface speller: The Problem of Individual Differences.

Authors:  Saba Ajami; Amin Mahnam; Samane Behtaj; Vahid Abootalebi
Journal:  J Med Signals Sens       Date:  2018 Oct-Dec
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