A Survey of Stimulation Methods Used in SSVEP-Based BCIs

By Dan-hua Zhu, J. Bieger, G. G. Molina, Ronald M. Aarts. Computational Intelligence and Neuroscience, 2010

681 citations recorded by the source corpus.

Brain-computer interface (BCI) systems based on the steady-state visual evoked potential (SSVEP) provide higher information throughput and require shorter training than BCI systems using other brain signals. To elicit an SSVEP, a repetitive visual stimulus (RVS) has to be presented to the user. The RVS can be rendered on a computer screen by alternating graphical patterns, or with external light sources able to emit modulated light. The properties of an RVS (e.g., frequency, color) depend on the rendering device and influence the SSVEP characteristics. This affects the BCI information throughput and the levels of user safety and comfort. Literature on SSVEP-based BCIs does not generally provide reasons for the selection of the used rendering devices or RVS properties. In this paper, we review the literature on SSVEP-based BCIs and comprehensively report on the different RVS choices in terms of rendering devices, properties, and their potential influence on BCI performance, user safety and comfort.

Subfields: Cellular and Molecular Neuroscience, Cognitive Neuroscience, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/18f86e260650ff0f2103a685bf368c93cc2e89eb

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In Cellular and Molecular Neuroscience

  1. Tzyy-Ping Jung
  2. Masaki Nakanishi
  3. Yu-Te Wang
  4. Luis F. Nicolás-Alonso
  5. Jaime Gómez Gil
  6. Dezhong Yao
  7. Xiaogang Chen
  8. Xiaorong Gao

In Cognitive Neuroscience

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  2. Masaki Nakanishi
  3. Yu-Te Wang
  4. Lawrence Gregory Appelbaum
  5. Anthony M. Norcia
  6. Benoit R. Cottereau
  7. Justin M. Ales
  8. Luis F. Nicolás-Alonso

In Electrical and Electronic Engineering

  1. Luis F. Nicolás-Alonso
  2. Masaki Nakanishi
  3. Tzyy-Ping Jung
  4. Yu-Te Wang
  5. Jaime Gómez Gil
  6. Keum Shik Hong
  7. Noman Naseer

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