Evaluation of an online SSVEP-BCI with fast system setup

被引:1
|
作者
Li, Xiaodong [1 ,2 ]
Wang, Junlin [1 ,2 ]
Cao, Xiang [2 ]
Huang, Yong [3 ,4 ]
Huang, Wei [5 ]
Wan, Feng [6 ]
To, Michael Kai-Tsun [1 ,2 ]
Xie, Sheng Quan [7 ]
机构
[1] Univ Hong Kong, Shenzhen Hosp, Orthoped Ctr, Shenzhen 518000, Guangdong, Peoples R China
[2] Univ Hong Kong, Dept Orthopaed & Traumatol, Hong Kong 999077, Peoples R China
[3] Southern Med Univ, Sch Biomed Engn, Guangzhou 510000, Guangdong, Peoples R China
[4] Guangdong Inst Intelligence Sci & Technol, Lab Brain Inspired Comp Syst, Zhuhai 519000, Guangdong, Peoples R China
[5] Guangdong Med Univ, Affiliated Hosp 2, Dept Rehabil, Zhanjiang 524000, Guangdong, Peoples R China
[6] Univ Macau, Dept Elect & Comp Engn, Taipa 999078, Macau, Peoples R China
[7] Univ Leeds, Sch Elect & Elect Engn, Leeds LS2 9JT, England
来源
JOURNAL OF NEURORESTORATOLOGY | 2024年 / 12卷 / 02期
关键词
Brain-computer interface; Steady-state visual evoked potential; System setup; Online adaptive canonical correlation; analysis; USERS WANT OPINIONS; POTENTIAL USERS; EEG; ELECTRODES; PRIORITIES; EMOTIV;
D O I
10.1016/j.jnrt.2024.100122
中图分类号
R74 [神经病学与精神病学];
学科分类号
摘要
The brain-computer interface (BCI) plays an important role in neural restoration. Current BCI systems generally require complex experimental preparation to perform well, but this time-consuming process may hinder their use in clinical applications. To explore the feasibility of simplifying the BCI system setup, a wearable BCI system based on the steady-state visual evoked potential (SSVEP) was developed and evaluated. Fifteen healthy participants were recruited to test the fast-setup system using dry and wet electrodes in a real-life scenario. In this study, the average system setup time for the dry electrode was 38.40 seconds and that for the wet electrode was 103.40 seconds, which are times appreciably shorter than those in previous BCI experiments, enabling a rapid setup of the BCI system. Although the electroencephalogram (EEG) signal quality was low in this fast-setup BCI experiment, the BCI system achieved an information transfer rate of 138.89 bits/min with an eight-channel wet electrode and an information transfer rate of 70.59 bits/min with an eight-channel dry electrode, showing that the overall performance was close to that in traditional experiments. In addition, the results suggest that the solutions of a multi-channel dry electrode or few-channel wet electrode may be suitable for the fast-setup SSEVP-BCI. This fast-setup SSVEP-BCI has the advantages of simple preparation and stable performance and is thus conducive to promoting the use of the BCI in clinical practice. (c) 2024 The Authors. Published by Elsevier Ltd on behalf of Tsinghua University Press. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
引用
收藏
页数:11
相关论文
共 50 条
  • [41] An embedded lightweight SSVEP-BCI electric wheelchair with hybrid stimulator
    Na, Rui
    Hu, Chun
    Sun, Ying
    Wang, Shuai
    Zhang, Shuailei
    Han, Mingzhe
    Yin, Wenhan
    Zhang, Jun
    Chen, Xinlei
    Zheng, Dezhi
    DIGITAL SIGNAL PROCESSING, 2021, 116
  • [42] A high-frequency SSVEP-BCI system based on a 360 Hz refresh rate
    Liu, Ke
    Yao, Zhaolin
    Zheng, Li
    Wei, Qingguo
    Pei, Weihua
    Gao, Xiaorong
    Wang, Yijun
    JOURNAL OF NEURAL ENGINEERING, 2023, 20 (04)
  • [43] Representative-Based Cold Start for Adaptive SSVEP-BCI
    Shi, Nanlin
    Li, Xiang
    Liu, Bingchuan
    Yang, Chen
    Wang, Yijun
    Gao, Xiaorong
    IEEE TRANSACTIONS ON NEURAL SYSTEMS AND REHABILITATION ENGINEERING, 2023, 31 : 1521 - 1531
  • [44] Assisted closed-loop optimization of SSVEP-BCI efficiency
    Fernandez-Vargas, Jacobo
    Pfaff, Hanns U.
    Rodriguez, Francisco B.
    Varona, Pablo
    FRONTIERS IN NEURAL CIRCUITS, 2013, 7
  • [45] An ANFIS Method to Improve SSVEP-BCI Anti-blinking Stability
    Lu Z.
    Zhang X.
    Zhang L.
    Li H.
    Li R.
    Zhendong Ceshi Yu Zhenduan/Journal of Vibration, Measurement and Diagnosis, 2019, 39 (04): : 727 - 732
  • [46] 基于SSVEP-BCI的可穿戴疲劳检测系统
    欧阳元兵
    罗亦鸣
    李宇诗
    王皓
    潘昱杉
    控制与决策, 2024, (07) : 2414 - 2420
  • [47] Optimization of SSVEP-BCI Interface Design - a Study Based on Visual Comfort
    Tong, Mu
    Lin, Yun
    HCI INTERNATIONAL 2024-LATE BREAKING POSTERS, HCII 2024, PT I, 2025, 2319 : 138 - 144
  • [48] Design of a Video Feedback SSVEP-BCI System for Car Control based on Improved MUSIC Method
    Liu, Chang
    Xie, Songyun
    Xie, Xinzhou
    Duan, Xu
    Wang, Wei
    Obermayer, Klaus
    2018 6TH INTERNATIONAL CONFERENCE ON BRAIN-COMPUTER INTERFACE (BCI), 2018, : 69 - 72
  • [49] Development of an Extensible SSVEP-BCI Software Platform and Application to Wheelchair Control
    Waytowich, Nicholas R.
    Krusienski, Dean J.
    2017 8TH INTERNATIONAL IEEE/EMBS CONFERENCE ON NEURAL ENGINEERING (NER), 2017, : 529 - 532
  • [50] An asynchronous SSVEP-BCI based on variance statistics of Multivariate synchronization index
    Zhang, Nannan
    Tang, Jingsheng
    Liu, Yadong
    Zhou, Zongtan
    2017 10TH BIOMEDICAL ENGINEERING INTERNATIONAL CONFERENCE (BMEICON), 2017,