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P300-Based Brain-Computer Interface Speller Performance Estimation with Classifier-Based Latency Estimation

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关于第一个被动脑电脑接口竞赛的回顾跨会话工作量估计.

Raphaëlle N Roy^1,2, Marcel F Hinss¹, Ludovic Darmet¹

¹ISAE-SUPAERO, Université de Toulouse, Toulouse, France.

Frontiers in neuroergonomics

|January 18, 2024

概括

在被动脑计算机接口 (BCI) 中的数据共享是有限的. 一项竞赛解决了跨会期工作负载估计的挑战,突出了大脑信号变化的难度和里曼几何方法的有效性.

关键词:

这是一个EEGEEGEEGEEGEEGEEGEEG.里曼的几何学里曼的几何学基准测试 (benchmarking) 是一种比较的方法.跨会期的变化率的跨会期的变化.数据集数据集数据集估计估计估计的估计.一个被动的大脑-计算机接口.工作负载的工作负载.

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科学领域:

神经科学是一个神经科学.
计算机科学计算机科学
人与计算机的交互

背景情况:

在脑计算机接口 (BCI) 研究中,数据共享是有限的,特别是对于被动BCI.
大脑信号的变化,特别是跨会话的变化,对BCI发展构成重大挑战.
需要标准化实践和协作努力来解决BCI的变化.

研究的目的:

建立良好的研究实践,促进社区在被动BCI的跨会期估计中的合作.
举办第一个被动BCI竞赛,专注于跨会话工作负载估计.
为了促进进一步的研究,公开提供相关数据集.

主要方法:

在第三届国际神经机能学会议上组织了第一个被动BCI比赛.
从15名志愿者收集了脑电图 (EEG) 数据,他们在3个会议中执行了多属性任务电池-II (MATB-II).
在Zenodo上公开提供培训和测试数据集以及支持代码.

主要成果:

十一支球队参加了比赛,使用里曼几何学方法的最佳管道实现了超过机会但低于60%的精度.
四个团队使用的深度学习方法,在机会级别进行,表明潜在的过拟合.
结果强调了被动BCI跨会期估计的重大挑战.

结论:

该竞赛成功地突出了在被动BCI中跨会话工作负载估计的挑战.
里曼几何学方法在BCI应用中证明了其稳定性和有效性.
该倡议是迈向合作努力的关键第一步,以克服BCI变异性并促进可重复的研究.