Literature DB >> 32746042

Doubling the Speed of N200 Speller via Dual-Directional Motion Encoding.

Dingkun Liu, Chang Liu, Jingjing Chen, Dan Zhang, Bo Hong.   

Abstract

OBJECTIVE: Motion-onset visual evoked potentials (mVEPs)-based spellers, also known as N200 spellers, have been successfully implemented, avoiding flashing stimuli that are common in visual brain-computer interface (BCI). However, their information transfer rates (ITRs), typically below 50 bits/min, are lower than other visual BCI spellers. In this study, we sought to improve the speed of N200 speller to a level above the well-known P300 spellers. APPROACH: Based on our finding of the spatio-temporal asymmetry of N200 response elicited by leftward and rightward visual motion, a novel dual-directional N200 speller was implemented. By presenting visual stimuli moving in two different directions simultaneously, the new paradigm reduced the stimuli presentation time by half, while ensuring separable N200 features between two visual motion directions. Furthermore, a probability-based dynamic stopping algorithm was also proposed to shorten the decision time for each output further. Both offline and online tests were conducted to evaluate the performance in ten participants. MAIN
RESULTS: Offline results revealed contralateral dominant temporal and spatial patterns in N200 responses when subjects attended to stimuli moving leftward or rightward. In online experiments, the dual-directional paradigm achieved an average ITR of 79.8 bits/min, with the highest ITR of 124.8 bits/min. Compared with the traditional uni-directional N200 speller, the median gain on the ITR was 202%. SIGNIFICANCE: The proposed dual-directional paradigm managed to double the speed of the N200 speller. Together with its non-flashing characteristics, this dual-directional N200 speller is promising to be a competent candidate for fast and reliable BCI applications.

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Year:  2020        PMID: 32746042     DOI: 10.1109/TBME.2020.3005518

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  2 in total

1.  Ten-Hour Stable Noninvasive Brain-Computer Interface Realized by Semidry Hydrogel-Based Electrodes.

Authors:  Junchen Liu; Sen Lin; Wenzheng Li; Yanzhen Zhao; Dingkun Liu; Zhaofeng He; Dong Wang; Ming Lei; Bo Hong; Hui Wu
Journal:  Research (Wash D C)       Date:  2022-03-10

2.  A novel brain-computer interface based on audio-assisted visual evoked EEG and spatial-temporal attention CNN.

Authors:  Guijun Chen; Xueying Zhang; Jing Zhang; Fenglian Li; Shufei Duan
Journal:  Front Neurorobot       Date:  2022-09-30       Impact factor: 3.493

  2 in total

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