使用动作单元探索情绪处理中面部模仿的时间动态
Exploring the Temporal Dynamics of Facial Mimicry in Emotion Processing Using Action Units
AI总结：
本研究基于面部动作单元和动态时间规整分析情绪处理中面部模仿的时间动态，发现特定情绪引发更强模仿且人格特质起次要作用，为情感计算及个性化虚拟智能体设计提供了重要启示。
摘要：
面部模仿——即对他人表情的自动、无意识模仿——对情绪理解至关重要。本研究使用视频中的面部动作单元和参与者的反应，探讨模仿在不同情绪间的差异。采用动态时间规整量化了参与者与刺激物面部表情之间的时间对齐，揭示了显著的情绪差异。事后检验表明，“恐惧”的模仿程度大于“快乐”，而“愤怒”的模仿程度较“恐惧”有所降低。模仿与外向性和宜人性等人格特质的相关性显著，展现出微妙却紧密的联系。这些发现表明特定情绪会引发更强的模仿，而人格特质在情绪对齐中起次要作用。值得注意的是，我们的结果突显了与人格相关的模仿机制如何超越人际传播，延伸至情感计算应用，例如远程人际交互和人-虚拟智能体场景。来自时间性面部模仿的洞察——例如设计自适应镜像用户表情的数字智能体——使开发者能够创建具有共情能力、个性化的系统，从而增强情感共鸣与用户参与度。
英文摘要：
Facial mimicry - the automatic, unconscious imitation of others' expressions - is vital for emotional understanding. This study investigates how mimicry differs across emotions using Face Action Units from videos and participants' responses. Dynamic Time Warping quantified the temporal alignment between participants' and stimuli's facial expressions, revealing significant emotional variations. Post-hoc tests indicated greater mimicry for 'Fear' than 'Happy' and reduced mimicry for 'Anger' compared to 'Fear'. The mimicry correlations with personality traits like Extraversion and Agreeableness were significant, showcasing subtle yet meaningful connections. These findings suggest specific emotions evoke stronger mimicry, with personality traits playing a secondary role in emotional alignment. Notably, our results highlight how personality-linked mimicry mechanisms extend beyond interpersonal communication to affective computing applications, such as remote human-human interactions and human-virtual-agent scenarios. Insights from temporal facial mimicry - e.g., designing digital agents that adaptively mirror user expressions - enable developers to create empathetic, personalized systems, enhancing emotional resonance and user engagement.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
