Subject-Specific Methodology in the Frequency Scanning Phase of SSVEP-Based BCI

被引:1
|
作者
Rejer, Izabela [1 ]
Cieszynski, Lukasz [1 ]
机构
[1] West Pomeranian Univ Technol Szczecin, Fac Comp Sci & Informat Technol, Szczecin, Poland
关键词
SSVEP; BCI; Brain Computer Interface; EEG;
D O I
10.1007/978-3-319-48429-7_12
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Steady State Visual Evoked Potentials (SSVEPs) often used in Brain Computer Interfaces (BCIs) differ across subjects. That is why a new SSVEP-based BCI user should always start the session from the frequency scanning phase. During this phase the stimulation frequencies evoking the most prominent SSVEPs are determined. In our opinion not only the stimulation frequencies specific for the given user should be chosen in the scanning phase but also the methodology used for SSVEP detection. The paper reports the results of a survey whose aim was to find out whether using subject specific methodology for identifying stimulation frequencies would increase the number of frequencies found. We analyzed three factors: length of time window used for power spectrum calculation, combination of channels, and number of harmonics used for SSVEP detection. According to the outcome of the experiment (performed with 6 subjects) the mean drop in the number of SSVEPs detected with any other but the best combination of factors was very large for all subjects (from 31.52 % for subject S3 to 51.76 % for subject S4).
引用
收藏
页码:123 / 132
页数:10
相关论文
共 50 条
  • [31] A new SSVEP-based BCI utilizing frequency and space to encode visual targets
    Zhang, Min
    Wang, Zhenyu
    Hu, Honglin
    [J]. SCIENCE CHINA-INFORMATION SCIENCES, 2020, 63 (08)
  • [32] A new SSVEP-based BCI utilizing frequency and space to encode visual targets
    Min ZHANG
    Zhenyu WANG
    Honglin HU
    [J]. Science China(Information Sciences), 2020, 63 (08) : 257 - 259
  • [33] FREQUENCY RECOGNITION IN SSVEP-BASED BCI USING MULTISET CANONICAL CORRELATION ANALYSIS
    Zhang, Yu
    Zhou, Guoxu
    Jin, Jing
    Wang, Xingyu
    Cichocki, Andrzej
    [J]. INTERNATIONAL JOURNAL OF NEURAL SYSTEMS, 2014, 24 (04)
  • [34] A new SSVEP-based BCI utilizing frequency and space to encode visual targets
    Min Zhang
    Zhenyu Wang
    Honglin Hu
    [J]. Science China Information Sciences, 2020, 63
  • [35] An Efficient Frequency Recognition Method Based on Likelihood Ratio Test for SSVEP-Based BCI
    Zhang, Yangsong
    Dong, Li
    Zhang, Rui
    Yao, Dezhong
    Zhang, Yu
    Xu, Peng
    [J]. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE, 2014, 2014
  • [36] A prototype of SSVEP-based BCI for home appliances control
    Anindya, Sinantya Feranti
    Rachmat, Hendi Handian
    Sutjiredjeki, Ediana
    [J]. 2016 1ST INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING (IBIOMED): EMPOWERING BIOMEDICAL TECHNOLOGY FOR BETTER FUTURE, 2016, : 5 - 10
  • [37] Motion Visual Stimulus for SSVEP-based BCI system
    Punsawad, Yunyong
    Wongsawat, Yodchanan
    [J]. 2012 ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2012, : 3837 - 3840
  • [38] SSVEP-based BCI control of the DASHER writing system
    Garrido-del Angel, Pavel
    Bojorges-Valdez, Erik
    Yanez-Suarez, Oscar
    [J]. 2011 5TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), 2011, : 446 - 448
  • [39] Effect of posterized naturalistic stimuli on SSVEP-based BCI
    Ng, Kian B.
    Bradley, Andrew P.
    Cunnington, Ross
    [J]. 2013 35TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2013, : 3105 - 3108
  • [40] Online SSVEP-based BCI using Riemannian geometry
    Kalunga, Emmanuel K.
    Chevallier, Sylvain
    Barthelemy, Quentin
    Djouani, Karim
    Monacelli, Eric
    Hamam, Yskandar
    [J]. NEUROCOMPUTING, 2016, 191 : 55 - 68