Target Selection With Hybrid Feature for BCI-Based 2-D Cursor Control

被引:89
|
作者
Long, Jinyi [1 ]
Li, Yuanqing [1 ]
Yu, Tianyou [1 ]
Gu, Zhenghui [1 ]
机构
[1] S China Univ Technol, Sch Automat Sci & Engn, Guangzhou 510640, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
Brain-computer interface (BCI); cursor; EEG; hybrid feature; motor imagery; P300; potential; BRAIN-COMPUTER INTERFACES; PROSTHESIS; RHYTHM; TOP;
D O I
10.1109/TBME.2011.2167718
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
To control a cursor on a monitor screen, a user generally needs to perform two tasks sequentially. The first task is to move the cursor to a target on the monitor screen (termed a 2-D cursor movement), and the second task is either to select a target of interest by clicking on it or to reject a target that is not of interest by not clicking on it. In a previous study, we implemented the former function in an EEG-based brain-computer interface system using motor imagery and the P300 potential to control the horizontal and vertical cursor movements, respectively. In this study, the target selection or rejection functionality is implemented using a hybrid feature from motor imagery and the P300 potential. Specifically, to select the target of interest, the user must focus his or her attention on a flashing button to evoke the P300 potential, while simultaneously maintaining an idle state of motor imagery. Otherwise, the user performs left-/right-hand motor imagery without paying attention to any buttons to reject the target. Our data analysis and online experimental results validate the effectiveness of our approach. The proposed hybrid feature is shown to be more effective than the use of either the motor imagery feature or the P300 feature alone. Eleven subjects attended our online experiment, in which a trial involved sequential 2-D cursor movement and target selection. The average duration of each trial and average accuracy of target selection were 18.19 s and 93.99%, respectively, and each target selection or rejection event was performed within 2 s.
引用
收藏
页码:132 / 140
页数:9
相关论文
共 50 条
  • [32] SAR target feature extraction using the 2-D continuous wavelet transform
    Kaplan, LM
    Murenzi, R
    [J]. RADAR SENSOR TECHNOLOGY II, 1997, 3066 : 101 - 112
  • [33] Improving performance in motor imagery BCI-based control applications via virtually embodied feedback
    Choi, Jin Woo
    Huh, Sejoon
    Jo, Sungho
    [J]. COMPUTERS IN BIOLOGY AND MEDICINE, 2020, 127
  • [34] Reconstructing Degree of Forearm Rotation from Imagined movements for BCI-based Robot Hand Control
    Yun, Yong-Deok
    Jeong, Ji-Hoon
    Cho, Jeong-Hyun
    Kim, Dong-Joo
    Lee, Seong-Whan
    [J]. 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2019, : 3014 - 3017
  • [35] Hybrid Traffics Congestion Control Based on 2-D Hurwitz-Schur Stability
    Mao, Pengxuan
    Xiao, Yang
    Qu, Guangzhi
    Woo, Seok
    Kim, Kiseon
    [J]. 11TH INTERNATIONAL CONFERENCE ON CONTROL, AUTOMATION, ROBOTICS AND VISION (ICARCV 2010), 2010, : 61 - 66
  • [36] Hybrid Feature-Based Diffeomorphic Registration for Tumor Tracking in 2-D Liver Ultrasound Images
    Cifor, Amalia
    Risser, Laurent
    Chung, Daniel
    Anderson, Ewan M.
    Schnabel, Julia A.
    [J]. IEEE TRANSACTIONS ON MEDICAL IMAGING, 2013, 32 (09) : 1647 - 1656
  • [37] A high-performance general computer cursor control scheme based on a hybrid BCI combining motor imagery and eye-tracking
    Zhang, Jiakai
    Zhang, Yuqi
    Zhang, Xinlong
    Xu, Boyang
    Zhao, Huanqing
    Sun, Tinghui
    Wang, Ju
    Lu, Shaojie
    Shen, Xiaoyan
    [J]. ISCIENCE, 2024, 27 (06)
  • [38] Correlation-Filter-Based Channel and Feature Selection Framework for Hybrid EEG-fNIRS BCI Applications
    Ali, Muhammad Umair
    Zafar, Amad
    Kallu, Karam Dad
    Masood, Haris
    Mannan, Malik Muhammad Naeem
    Ibrahim, Malik Muhammad
    Kim, Sangil
    Khan, Muhammad Attique
    [J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2024, 28 (06) : 3361 - 3370
  • [39] A performance based feature selection technique for subject independent MI based BCI
    Md. A. Mannan Joadder
    Joshua J. Myszewski
    Mohammad H. Rahman
    Inga Wang
    [J]. Health Information Science and Systems, 7
  • [40] A performance based feature selection technique for subject independent MI based BCI
    Joadder, Md. A. Mannan
    Myszewski, Joshua J.
    Rahman, Mohammad H.
    Wang, Inga
    [J]. HEALTH INFORMATION SCIENCE AND SYSTEMS, 2019, 7 (01):