用脑电波实时调节仪表盘，提升决策效率与专注度。
Context-aware Adaptive Visualizations for Critical Decision Making
- 通过脑电信号监测认知负荷，动态调整可视化界面。
- 120人实验表明任务表现和参与度显著提升。
- 适合需要高注意力的实时决策场景，如医疗或交通监控。
有效决策常依赖复杂视觉数据的及时洞察。尽管信息可视化（InfoVis）仪表盘可支持这一过程，但通常无法实时适应用户的认知状态。我们提出Symbiotik，一种基于神经生理信号估计心理工作量（MWL）并利用强化学习（RL）动态调整可视化界面的智能自适应系统。通过包含120名参与者和三种可视化类型的研究，我们验证了该方法能显著提升任务表现与用户参与度。Symbiotik提供了可扩展的实时自适应架构，以及神经适应性用户界面的验证方法。
原文摘要 · Abstract (English)
Effective decision-making often relies on timely insights from complex visual data. While Information Visualization (InfoVis) dashboards can support this process, they rarely adapt to users' cognitive state, and less so in real time. We present Symbiotik, an intelligent, context-aware adaptive visualization system that leverages neurophysiological signals to estimate mental workload (MWL) and dynamically adapt visual dashboards using reinforcement learning (RL). Through a user study with 120 participants and three visualization types, we demonstrate that our approach improves task performance and engagement. Symbiotik offers a scalable, real-time adaptation architecture, and a validated methodology for neuroadaptive user interfaces.
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