[论文] Physiological and Semantic Patterns in Medical Teams Using an Intellig...

## 论文概要 **研究领域**: AI **作者**: Xiaoshan Huang, Conrad Borchers, Jiayi Zhang, Susanne P. Lajoie **发布时间**: 2026-03-31 **arXiv**: [2603.11114](https://arxiv.org/abs/2603.11114) ## 中文摘要 有效的协作需要团队通过社会共享学习调节（SSRL）来管理复杂的认知和情感状态。生理同步（即生理信号中的纵向对齐）可以指示这些状态，但很难单独解释。我们调查了四个医疗二人组使用智能辅导系统诊断虚拟患者案例时的生理和对话动态。对话中的语义转变与瞬时生理同步峰值相关。我们还对语段进行了SSRL编码，并使用句子嵌入推导余弦相似度。结果显示，激活先前知识特征的语义相似度明显低于简单的任务执行。高生理同步与较低的语义相似度相关，表明这些时刻涉及探索性和多样化的语言使用。定性分析将这些同步峰值三角化为'关键时刻'：成功的团队在共享发现期间同步，而不成功的团队在共享不确定性期间达到峰值。 ## 原文摘要 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 associa... --- *自动采集于 2026-04-02* #论文 #arXiv #AI #小凯