Brain-Computer Interface based on Steady-State Visual Evoked Potentials (SSVEP)

被引：0
|
作者：
Nawrocka, Agata [1 ]
Holewa, Karolina [1 ]
机构：
[1] AGH Univ Sci & Technol, Fac Mech Engn & Robot, Dept Proc Control, Krakow, Poland
来源：
PROCEEDINGS OF THE 2013 14TH INTERNATIONAL CARPATHIAN CONTROL CONFERENCE (ICCC) | 2013年
关键词：
Electroencephalography (EEG); EEG signal; biological signals; brain - computer interface (BCI); Steady - State Visual Evoked Potentials (SSVEP);
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The paper describes a virtual keyboard based on a brain computer interface, controlled by Steady - State Visual Evoked Potentials (SSVEP). Steady-State Visual Evoked Potentials are natural responses when the retina is excited by a visual stimulus ranging from 3.5 Hz to 75 Hz. The SSVEPs are characterized by an increase in EEG activity around the stun alas frequency. The SSVEP component has been detected using Welsch 's method. The Virtual Keyboard is characterized by high signal-to-noise ratio (SNR)
引用
收藏
页码：251 / 254
页数：4
相关论文
共 50 条
  • [31] Research on possibilities of transporter movement using brain-computer interface based on Steady-State Visually Evoked Potential (SSVEP)
    Kubacki, Arkadiusz
    Jakubowski, Arkadiusz
    Rybarczyk, Dominik
    2017 22ND INTERNATIONAL CONFERENCE ON METHODS AND MODELS IN AUTOMATION AND ROBOTICS (MMAR), 2017, : 218 - 221
  • [32] Enhanced Plasticity of Human Evoked Potentials by Visual Noise During the Intervention of Steady-State Stimulation Based Brain-Computer Interface
    Xie, Jun
    Xu, Guanghua
    Zhao, Xingang
    Li, Min
    Wang, Jing
    Han, Chengcheng
    Han, Xingliang
    FRONTIERS IN NEUROROBOTICS, 2018, 12
  • [33] An Application of Digital Signal Processor in Brain-computer Interface Based on Steady-State Visual Evoked Potential
    Zhao, Li
    Hu, Daofu
    Xiao, Longteng
    Shen, Hui
    Meng, Qingguo
    2ND IEEE INTERNATIONAL CONFERENCE ON ADVANCED COMPUTER CONTROL (ICACC 2010), VOL. 2, 2010, : 579 - 583
  • [34] Stimulus specificity of a steady-state visual-evoked potential-based brain-computer interface
    Ng, Kian B.
    Bradley, Andrew P.
    Cunnington, Ross
    JOURNAL OF NEURAL ENGINEERING, 2012, 9 (03)
  • [35] A hybrid steady-state visual evoked response-based brain-computer interface with MEG and EEG
    Li, Xiang
    Chen, Jingjing
    Shi, Nanlin
    Yang, Chen
    Gao, Puze
    Chen, Xiaogang
    Wang, Yijun
    Gao, Shangkai
    Gao, Xiaorong
    EXPERT SYSTEMS WITH APPLICATIONS, 2023, 223
  • [36] Brain-computer interfaces based on the steady-state visual-evoked response
    Middendorf, M
    McMillan, G
    Calhoun, G
    Jones, KS
    IEEE TRANSACTIONS ON REHABILITATION ENGINEERING, 2000, 8 (02): : 211 - 214
  • [37] A Secure Cryptographic System Based on Steady-State Visual Evoked Potential Brain-Computer Interface Technology
    Xu XIAO
    Feiyang ZHANG
    Wenhan YIN
    Dezhi ZHENG
    JournalofSystemsScienceandInformation, 2024, 12 (03) : 423 - 432
  • [38] Data Analytics in Steady-State Visual Evoked Potential-Based Brain-Computer Interface: A Review
    Zhang, Yue
    Xie, Shane Q.
    Wang, He
    Zhang, Zhiqiang
    IEEE SENSORS JOURNAL, 2021, 21 (02) : 1124 - 1138
  • [39] Advances in brain-computer interface based on high-frequency steady-state visual evoked potential
    Zheng C.
    Liu Y.
    Xiao X.
    Zhou X.
    Xu F.
    Xu M.
    Ming D.
    Shengwu Yixue Gongchengxue Zazhi/Journal of Biomedical Engineering, 2023, 40 (01): : 155 - 162
  • [40] Enhancement of Steady-State Visual Evoked Potential-Based Brain-Computer Interface Systems via a Steady-State Motion Visual Stimulus Modality
    Punsawad, Yunyong
    Wongsawat, Yodchanan
    IEEJ TRANSACTIONS ON ELECTRICAL AND ELECTRONIC ENGINEERING, 2017, 12 : S89 - S94
12345