New stimulation pattern design to improve P300-based matrix speller performance at high flash rate

被引:12
|
作者
Polprasert, Chantri [1 ]
Kukieattikool, Pratana [1 ]
Demeechai, Tanee [1 ]
Ritcey, James A. [2 ]
Siwamogsatham, Siwaruk [1 ]
机构
[1] Natl Elect & Comp Technol Ctr, Klong Luang Dist 12120, Pathumthani, Thailand
[2] Univ Washington, Dept Elect Engn, Seattle, WA 98195 USA
关键词
P300; SPELLER; BRAIN; BCI; INTERVAL;
D O I
10.1088/1741-2560/10/3/036012
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Objective. We propose a new stimulation pattern design for the P300-based matrix speller aimed at increasing the minimum target-to-target interval (TTI). Approach. Inspired by the simplicity and strong performance of the conventional row-column (RC) stimulation, the proposed stimulation is obtained by modifying the RC stimulation through alternating row and column flashes which are selected based on the proposed design rules. The second flash of the double-flash components is then delayed for a number of flashing instants to increase the minimum TTI. The trade-off inherited in this approach is the reduced randomness within the stimulation pattern. Main results. We test the proposed stimulation pattern and compare its performance in terms of selection accuracy, raw and practical bit rates with the conventional RC flashing paradigm over several flash rates. By increasing the minimum TTI within the stimulation sequence, the proposed stimulation has more event-related potentials that can be identified compared to that of the conventional RC stimulations, as the flash rate increases. This leads to significant performance improvement in terms of the letter selection accuracy, the raw and practical bit rates over the conventional RC stimulation. Significance. These studies demonstrate that significant performance improvement over the RC stimulation is obtained without additional testing or training samples to compensate for low P300 amplitude at high flash rate. We show that our proposed stimulation is more robust to reduced signal strength due to the increased flash rate than the RC stimulation.
引用
收藏
页数:11
相关论文
共 8 条
  • [1] A P300-Based Speller Design Using a MINMAX Riemannian Geometry Scheme and Convolutional Neural Network
    Aghili, Seyedeh Nadia
    Erfanian, Abbas
    [J]. IEEE ACCESS, 2023, 11 : 98633 - 98652
  • [2] P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation
    Khan, Nazmun N.
    Sweet, Taylor
    Harvey, Chase A.
    Warschausky, Seth
    Huggins, Jane E.
    Thompson, David E.
    [J]. JOVE-JOURNAL OF VISUALIZED EXPERIMENTS, 2023, (199):
  • [3] New Visual Stimulation Paradigm for P300-Based Brain-Computer Interfaces
    Wilaiprasitporn, Theerawit
    Yagi, Tohru
    [J]. 2014 7TH BIOMEDICAL ENGINEERING INTERNATIONAL CONFERENCE (BMEICON), 2014,
  • [4] P300-based Brain-Computer Interface Memory Game to Improve Motivation and Performance
    Angeloni, C.
    Salter, D.
    Corbit, V.
    Lorence, T.
    Yu, Y-C.
    Gabel, L. A.
    [J]. 2012 38TH ANNUAL NORTHEAST BIOENGINEERING CONFERENCE (NEBEC), 2012, : 35 - +
  • [5] Relationship between the spatial pattern of P300 and performance of a P300-based brain-computer interface in amyotrophic lateral sclerosis
    Sugata, Hisato
    Hirata, Masayuki
    Kageyama, Yu
    Kishima, Haruhiko
    Sawada, Jinichi
    Yoshimine, Toshiki
    [J]. BRAIN-COMPUTER INTERFACES, 2016, 3 (01) : 1 - 8
  • [6] Optimizing the stimulus presentation paradigm design for the P300-based brain-computer interface using performance prediction
    Mainsah, B. O.
    Reeves, G.
    Collins, L. M.
    Throckmorton, C. S.
    [J]. JOURNAL OF NEURAL ENGINEERING, 2017, 14 (04)
  • [7] Applying dynamic data collection to improve dry electrode system performance for a P300-based brain-computer interface
    Clements, J. M.
    Sellers, E. W.
    Ryan, D. B.
    Caves, K.
    Collins, L. M.
    Throckmorton, C. S.
    [J]. JOURNAL OF NEURAL ENGINEERING, 2016, 13 (06)
  • [8] Convolutional Neural Network Architecture and Input Volume Matrix Design for ERP Classifications in a Tactile P300-based Brain-Computer Interface
    Kodama, Takumi
    Makino, Shoji
    [J]. 2017 39TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC), 2017, : 3814 - 3817