SSVEP-based BCI control of the DASHER writing system

被引:0
|
作者
Garrido-del Angel, Pavel [1 ]
Bojorges-Valdez, Erik [2 ]
Yanez-Suarez, Oscar [2 ]
机构
[1] Univ Autonoma Metropolitana Iztapalapa, Grad Program, Av San Rafael Atlixco 186, Mexico City 09340, DF, Mexico
[2] Univ Autonoma Metropolitana Iztapalapa, Neuroimaging Lab Elect Engn Dept, Mexico City, DF, Mexico
关键词
BRAIN-COMPUTER INTERFACES; COMMUNICATION;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Steady state visual evoked potentials represent the least training-dependent brain computer interface paradigm, a condition that significantly improves the user experience with this kind of interfaces. On the other hand, the opensource DASHER writing system is an unconventional machine interface paradigm on its own, for which their developers encourage the search of new controlling mechanisms. In this paper, we report the use of a single steady-state visual stimulus approach to control the navigation vector of the DASHER writing system. Fourier-based power estimation was used to compute the power around the fundamental band of the evoked response detected in occipital electrodes, and user-dependent threshold was used as the directional control. In an online trial, a short word was successfully -albeit inefficiently-written by a naive user, which suggests the feasibility of the application of such a paradigm for performing this task.
引用
收藏
页码:446 / 448
页数:3
相关论文
共 50 条
  • [31] Online SSVEP-based BCI using Riemannian geometry
    Kalunga, Emmanuel K.
    Chevallier, Sylvain
    Barthelemy, Quentin
    Djouani, Karim
    Monacelli, Eric
    Hamam, Yskandar
    NEUROCOMPUTING, 2016, 191 : 55 - 68
  • [32] Single-Channel EEG SSVEP-based BCI for Robot Arm Control
    Karunasena, Sanduni P.
    Ariyarathna, Darshana C.
    Ranaweera, Ruwan
    Wijayakulasooriya, Janaka
    Kim, Kwangtaek
    Dassanayake, Tharaka
    2021 IEEE SENSORS APPLICATIONS SYMPOSIUM (SAS 2021), 2021,
  • [33] Using Modular Neural Network to SSVEP-based BCI
    Chen, Yeou-Jiunn
    Chen, Shih-Chung
    Wu, Chung-Min
    PROCEEDINGS OF 2016 INTERNATIONAL CONFERENCE ON APPLIED SYSTEM INNOVATION (ICASI), 2016,
  • [34] Calibration-free SSVEP-based BCI Switch
    Sastry, R., V
    Karthik, S.
    Adithya, R.
    Ravi, Aravind
    Indrapriyadarsini, S.
    Panwar, Gagandeep
    Ramakrishnan, A. G.
    2019 IEEE 16TH INDIA COUNCIL INTERNATIONAL CONFERENCE (IEEE INDICON 2019), 2019,
  • [35] A comprehensive benchmark dataset for SSVEP-based hybrid BCI
    Sadeghi, Sahar
    Maleki, Ali
    EXPERT SYSTEMS WITH APPLICATIONS, 2022, 200
  • [36] The Effect of Harmonics Count on SSVEP-Based BCI Results
    Kancaoglu, Murat
    Kuntalp, Mehmet
    2019 INNOVATIONS IN INTELLIGENT SYSTEMS AND APPLICATIONS CONFERENCE (ASYU), 2019, : 110 - 113
  • [37] A high-ITR SSVEP-based BCI speller
    Chen, Xiaogang
    Chen, Zhikai
    Gao, Shangkai
    Gao, Xiaorong
    BRAIN-COMPUTER INTERFACES, 2014, 1 (3-4) : 181 - 191
  • [38] Information Bottleneck as Optimisation Method for SSVEP-Based BCI
    Ingel, Anti
    Vicente, Raul
    FRONTIERS IN HUMAN NEUROSCIENCE, 2021, 15
  • [39] A Multi-Channel SSVEP-based BCI for Computer Games with Analogue Control
    Wong, Chi Man
    Tang, Qi
    da Cruz, Janir Nuno
    Wan, Feng
    2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE AND VIRTUAL ENVIRONMENTS FOR MEASUREMENT SYSTEMS AND APPLICATIONS (CIVEMSA), 2015, : 119 - 124
  • [40] An Asynchronous P300 BCI With SSVEP-Based Control State Detection
    Panicker, Rajesh C.
    Puthusserypady, Sadasivan
    Sun, Ying
    IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING, 2011, 58 (06) : 1781 - 1788