用脑机接口引导注意力转移，有效缓解晕船
Alleviating Seasickness through Brain-Computer Interface-based Attention Shift
- 通过呼吸计数等任务，用AI脑机接口实现持续注意力转移
- 81.39%参与者报告干预有效，脑电图显示θ波增、β波减
- 无需药物、便携实用，适合海员与游客使用
晕船严重影响乘客舒适度和海上人员作业效率。尽管注意力转移被认为可缓解运动病症状，但其在航海环境中的有效性尚未得到严格验证。本研究开发了一种基于人工智能的脑机接口（BCI），通过呼吸计数等任务实现持续且实际的注意力转移。43名参与者完成了包含真实反馈、静息及伪反馈三个阶段的真实航海实验。结果显示，81.39%的参与者认为该干预有效。脑电分析表明，该系统能有效调节运动病相关的脑电特征，如总频带功率下降，θ相对功率上升，β相对功率下降。此外，注意力聚焦指标θ/β比值在真实反馈阶段显著降低，进一步证实了BCI转移注意力的效果。研究表明，这是一种新颖的非药物、便携且有效的晕船干预方式，为脑机接口开辟了全新应用领域。
原文摘要 · Abstract (English)
Seasickness poses a widespread problem that adversely impacts both passenger comfort and the operational efficiency of maritime crews. Although attention shift has been proposed as a potential method to alleviate symptoms of motion sickness, its efficacy remains to be rigorously validated, especially in maritime environments. In this study, we develop an AI-driven brain-computer interface (BCI) to realize sustained and practical attention shift by incorporating tasks such as breath counting. Forty-three participants completed a real-world nautical experiment consisting of a real-feedback session, a resting session, and a pseudo-feedback session. Notably, 81.39\% of the participants reported that the BCI intervention was effective. EEG analysis revealed that the proposed system can effectively regulate motion sickness EEG signatures, such as an decrease in total band power, along with an increase in theta relative power and a decrease in beta relative power. Furthermore, an indicator of attentional focus, the theta/beta ratio, exhibited a significant reduction during the real-feedback session, providing further evidence to support the effectiveness of the BCI in shifting attention. Collectively, this study presents a novel nonpharmacological, portable, and effective approach for seasickness intervention, which has the potential to open up a brand-new application domain for BCIs.
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