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Operate P300 speller when performing other task
Journal of Neural Engineering ( IF 4 ) Pub Date : 2020-10-13 , DOI: 10.1088/1741-2552/abb4a6
Yihao Huang 1, 2 , Feng He 1, 2 , Minpeng Xu 1, 2 , Hongzhi Qi 1, 2
Affiliation  

Objective. The P300 speller is a classic brain–computer interface (BCI) paradigm that has the potential to restore impaired motor control function. However, previous studies have confirmed that the letter recognition accuracy (LRA) of the P300 speller is a challenge when performing other tasks. Approach. To address this, we implemented a dynamic stopping strategy (DSS) to maintain the P300 speller LRA when performing multiple tasks simultaneously. Multiple tasks with dynamic workload levels were adopted to simulate the brain’s other thinking activities while operating P300 speller. A Bayes-based DSS offline model was built in single-task (only P300 speller task) and an online P300 speller system was established to test the DSS algorithm feasibility in dual-task. Main results. Online experimental results showed that the P300 speller with DSS could achieve a high LRA (96.9%) under dual-task, which was similar to single-task (98.7%, p = 0.126). Under du...

中文翻译:

执行其他任务时操作 P300 拼写器

客观的。P300 拼写器是一种经典的脑机接口 (BCI) 范例,具有恢复受损运动控制功能的潜力。然而,之前的研究已经证实,P300 拼写器的字母识别准确度 (LRA) 在执行其他任务时是一个挑战。方法。为了解决这个问题,我们实施了动态停止策略 (DSS),以在同时执行多个任务时维护 P300 拼写器 LRA。在操作 P300 拼写器时,采用了具有动态工作量级别的多项任务来模拟大脑的其他思维活动。在单任务(仅P300拼写任务)中建立了基于贝叶斯的DSS离线模型,并建立了在线P300拼写系统,以测试DSS算法在双任务中的可行性。主要结果。在线实验结果表明,使用 DSS 的 P300 拼写器在双任务下可以达到较高的 LRA(96.9%),与单任务相似(98.7%,p = 0.126)。在杜...
更新日期:2020-10-15
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