Literature DB >> 23612883

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

Chantri Polprasert1, Pratana Kukieattikool, Tanee Demeechai, James A Ritcey, Siwaruk Siwamogsatham.   

Abstract

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.

Entities:  

Mesh:

Year:  2013        PMID: 23612883     DOI: 10.1088/1741-2560/10/3/036012

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  5 in total

1.  Recursive Bayesian Coding for BCIs.

Authors:  Matt Higger; Fernando Quivira; Murat Akcakaya; Mohammad Moghadamfalahi; Hooman Nezamfar; Mujdat Cetin; Deniz Erdogmus
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2016-07-13       Impact factor: 3.802

2.  Optimizing the stimulus presentation paradigm design for the P300-based brain-computer interface using performance prediction.

Authors:  B O Mainsah; G Reeves; L M Collins; C S Throckmorton
Journal:  J Neural Eng       Date:  2017-08       Impact factor: 5.379

3.  An efficient ERP-based brain-computer interface using random set presentation and face familiarity.

Authors:  Seul-Ki Yeom; Siamac Fazli; Klaus-Robert Müller; Seong-Whan Lee
Journal:  PLoS One       Date:  2014-11-10       Impact factor: 3.240

4.  Scenario Screen: A Dynamic and Context Dependent P300 Stimulator Screen Aimed at Wheelchair Navigation Control.

Authors:  Omar Piña-Ramirez; Raquel Valdes-Cristerna; Oscar Yanez-Suarez
Journal:  Comput Math Methods Med       Date:  2018-02-14       Impact factor: 2.238

Review 5.  Brain-Computer Interface Spellers: A Review.

Authors:  Aya Rezeika; Mihaly Benda; Piotr Stawicki; Felix Gembler; Abdul Saboor; Ivan Volosyak
Journal:  Brain Sci       Date:  2018-03-30
  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.