December 2022
Volume 22, Issue 14
Open Access
Vision Sciences Society Annual Meeting Abstract  |   December 2022
Frequency parameter optimization method for SSVEP visual acuity evaluation based on Chirp-VEP
Author Affiliations & Notes
  • Yuhui Du
    School of Mechanical Engineering, Xi'an Jiaotong University
  • Guanghua Xu
    School of Mechanical Engineering, Xi'an Jiaotong University
    Stata Key Laboratory for Manufacturing Systems Engineering, Xi'an Jiaotong University
  • Xiaowei Zheng
    School of Mechanical Engineering, Xi'an Jiaotong University
  • Chengcheng Han
    School of Mechanical Engineering, Xi'an Jiaotong University
  • Chenghang Du
    School of Mechanical Engineering, Xi'an Jiaotong University
  • Sicong Zhang
    School of Mechanical Engineering, Xi'an Jiaotong University
  • Footnotes
    Acknowledgements  Supported by grants from the Independent Innovation Capacity Improvement Project of Xi’an Jiaotong University (PY3A071).
Journal of Vision December 2022, Vol.22, 3458. doi:https://doi.org/10.1167/jov.22.14.3458
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      Yuhui Du, Guanghua Xu, Xiaowei Zheng, Chengcheng Han, Chenghang Du, Sicong Zhang; Frequency parameter optimization method for SSVEP visual acuity evaluation based on Chirp-VEP. Journal of Vision 2022;22(14):3458. https://doi.org/10.1167/jov.22.14.3458.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Steady-state visual evoked potentials (SSVEPs) can provide an objective method to evaluate visual functions such as visual acuity (VA). In previous studies, the most commonly used temporal frequency for SSVEP-based VA evaluation is 7.5 Hz, but there are also other frequencies. The widespread diversity of the frequencies across studies indicates that there is no consensus regarding the optimal frequencies for the SSVEP-based VA evaluation. Rapid measurement of frequency response of individual subjects to specific stimuli paradigms will help to find the optimal stimulus frequency for individual subjects. In this study, Chirp-VEP (6-28 Hz, 3 Hz/s) and SSVEP (6-28 Hz, in step of 2 Hz) were elicited by flicker stimuli and grating stimuli (3.75cpd, 7.5cpd, 15cpd), which is commonly used in SSVEP-based VA evaluation studies. Both stimuli were presented by pattern reversal mode, respectively determine the frequency response curves of the paradigm, that is, the magnitude of the evoked signal as a function of frequency. The data were obtained from 10 subjects. Statistical analysis were conducted both on the level of individual subjects and for the group. The frequency response curves show that there are significant differences in the frequency response of different paradigms. For the same paradigm, the frequency response of different subjects is significantly different. Therefore, it is meaningful to adopt different frequency for different subjects. The frequency response curves obtained by SSVEP and Chirp-VEP are consistent, which proves Chirp-VEP can rapidly elicited wideband VEP and quickly determine the frequency response curve of individual subjects to specific paradigm. The results show that Chirp-VEP can reduce time of multiple experiments and provides a rapid method for the selection of frequency used in SSVEP-based VA evaluation. It is conducive to the refinement and standardization of SSVEP-based VA examination, and can also be used in frequency selection of other SSVEP-BCIs.

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