Context-aware Adaptive Visualizations for Critical Decision Making
This addresses the need for more responsive and personalized visualization tools in critical decision-making scenarios, representing a novel application rather than an incremental improvement.
The paper tackled the problem of static InfoVis dashboards by developing Symbiotik, a system that uses neurophysiological signals and reinforcement learning to adapt visualizations in real-time based on users' mental workload, resulting in improved task performance and engagement as demonstrated in a study with 120 participants.
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.