谷歌浏览器插件
订阅小程序
在清言上使用

Driving event-related potential-based speller by localized posterior activities: An offline study

MATHEMATICAL BIOSCIENCES AND ENGINEERING(2020)

引用 4|浏览3
暂无评分
摘要
Multi-sensor recordings are normally used in event-related potential (ERP)-based brain computer interfaces (BCIs), for capturing brain activities widely distributed over the cortical surface. However, this may lead to an increased number of sensors for boosting classification performance, as well as a complicated computational effort for optimizing/reducing sensors, limiting the popularization of mobile/wearable BCIs for the end use. The localization of brain activities may help fix this issue by making useful information concentrated on relatively local brain areas, thus greatly reducing the number of sensors required and computational burden arising from the sensor selection. In the present study, we examined localization of brain activities for an ERP speller, by using novel visual graphic stimuli to induce specific brain responses. Participants were instructed to perform a spelling task under both the graphic stimuli-based and traditional character-flashing-based ERP speller paradigms. Experimental results showed that, compared to character-flashing stimuli, localized brain activities, concentrated over the posterior region, were observed for the graphic stimuli. Classification accuracies and information transfer rates were further evaluated and compared among full- (FS), normal- (NS), and localized- (LS) sensor settings. Effects of PARADIGM, SENSORSETTING, and TRIAL LENGTH were examined by a three-way repeated measure analysis of variance (ANOVA). ANOVA results showed that, the graphic paradigm achieved significantly better performance under LS than those achieved by the traditional paradigm at any of the three sensor settings, indicating that with visual graphic stimuli, localized posterior activities were enough to drive an ERP-based speller to achieve comparable or even better performance, compared to the traditional paradigm using global activities.
更多
查看译文
关键词
mobile/wearable brain computer interface,sensor selection,localized activity,event related potential,P300
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要