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Open Access

Studying the Effect of the Pre-Stimulation Paradigm on Steady-State Visual Evoked Potentials with Dynamic Models Based on the Zero-Pole Analytical Method

Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China.
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Abstract

This study explored methods for improving the performance of Steady-State Visual Evoked Potential (SSVEP)-based Brain-Computer Interfaces (BCI), and introduced a new analytical method to quantitatively analyze and reflect the characteristics of SSVEP. We focused on the effect of the pre-stimulation paradigm on the SSVEP dynamic models and the dynamic response process of SSVEP, and performed a comparative analysis of three pre-stimulus paradigms (black, gray, and white). Four dynamic models with different orders (second- and third-order) and with and without a zero point were used to fit the SSVEP envelope. The zero-pole analytical method was adopted to conduct quantitative analysis on the dynamic models, and the response characteristics of SSVEP were represented by zero-pole distribution characteristics. The results of this study indicated that the pre-stimulation paradigm affects the characteristics of SSVEP, and the dynamic models had good fitting abilities with SSVEPs under various types of pre-stimulation. Furthermore, the zero-pole characteristics of the models effectively characterize the damping coefficient, oscillation period, and other SSVEP characteristics. The comparison of zeros and poles indicated that the gray pre-stimulation condition corresponds to a lower damping coefficient, thus showing its potential to improve the performance of SSVEP-BCIs.

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Tsinghua Science and Technology
Pages 435-446

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Cite this article:
Zhang S, Han X, Gao X. Studying the Effect of the Pre-Stimulation Paradigm on Steady-State Visual Evoked Potentials with Dynamic Models Based on the Zero-Pole Analytical Method. Tsinghua Science and Technology, 2020, 25(3): 435-446. https://doi.org/10.26599/TST.2019.9010028

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Received: 21 June 2019
Revised: 18 July 2019
Accepted: 01 August 2019
Published: 07 October 2019
© The author(s) 2020

The articles published in this open access journal are distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/).