用生理信号和对话分析医疗团队协作中的关键决策时刻。
Physiological and Semantic Patterns in Medical Teams Using an Intelligent Tutoring System
- 结合生理同步与对话语义，捕捉团队协作中的认知状态变化。
- 高生理同步时语义相似度降低，表明探索性语言使用增多。
- 成功团队在共同发现时出现同步高峰，适合人机协作研究者参考。
有效协作需要团队通过社会共享学习调节（SSRL）管理复杂的认知与情绪状态。生理同步（即生理信号的纵向对齐）可反映这些状态，但单独解读困难。本研究分析了四组医疗双人团队在智能辅导系统中诊断虚拟患者案例时的生理与对话动态。对话中的语义转变与短暂的生理同步峰值相关。我们对话语片段进行SSRL编码，并利用句嵌入计算余弦相似度。结果显示，激活先验知识时的语义相似度显著低于简单任务执行阶段。高生理同步与低语义相似度相关，表明此时为探索性、多样的语言表达。定性分析证实这些同步高峰是“关键节点”：成功团队在共同发现时同步，失败团队则在共同困惑时同步。该研究推进了以人为本的人工智能，展示了如何融合生物信号与对话理解来解析问题解决中的关键时刻。
原文摘要 · Abstract (English)
Effective collaboration requires teams to manage complex cognitive and emotional states through Socially Shared Regulation of Learning (SSRL). Physiological synchrony (i.e., longitudinal alignment in physiological signals) can indicate these states, but is hard to interpret on its own. We investigate the physiological and conversational dynamics of four medical dyads diagnosing a virtual patient case using an intelligent tutoring system. Semantic shifts in dialogue were correlated with transient physiological synchrony peaks. We also coded utterance segments for SSRL and derived cosine similarity using sentence embeddings. The results showed that activating prior knowledge featured significantly lower semantic similarity than simpler task execution. High physiological synchrony was associated with lower semantic similarity, suggesting that such moments involve exploratory and varied language use. Qualitative analysis triangulated these synchrony peaks as ``pivotal moments'': successful teams synchronized during shared discovery, while unsuccessful teams peaked during shared uncertainty. This research advances human-centered AI by demonstrating how biological signals can be fused with dialogues to understand critical moments in problem solving.
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