Theories of human emotion, including some emotion embodiment theories, suggest that our moods and affective states are reflected in the movements of our bodies. We used the reverse process for mood regulation; modulate body movements to regulate mood. Dancing is a type of full-body movement characterized by affective expressivity and, hence, offers the possibility to express different affective states through the same movement sequences. We tested whether the repeated imitation of a dancer performing two simple full-body dance movement sequences with different affective expressivity (happy or sad) could change mood states. Computer-based systems, using avatars as dance models to imitate, offer a series of advantages such as independence from physical contact and location. Therefore, we compared mood induction effects in two conditions: participants were asked to imitate dance movements from one of the two avatars showing: (a) videos of a human dancer model or (b) videos of a robot dancer model. The mood induction was successful for both happy and sad imitations, regardless of condition (human vs. robot avatar dance model). Moreover, the magnitude of happy mood induction and how much participants liked the task predicted work-related motivation after the mood induction. We conclude that mood regulation through dance movements is possible and beneficial in the work context.

中文翻译：

---

通过模仿不同情感意图的全身动作进行情绪感应

人类情感理论，包括一些情感体现理论，表明我们的情绪和情感状态反映在我们身体的运动中。我们用相反的过程来调节情绪；调节身体动作来调节情绪。舞蹈是一种以情感表达为特征的全身运动，因此提供了通过相同的动作序列表达不同情感状态的可能性。我们测试了重复模仿舞者表演两个具有不同情感表达（快乐或悲伤）的简单全身舞蹈动作序列是否可以改变情绪状态。基于计算机的系统使用化身作为模仿的舞蹈模型，具有一系列优点，例如独立于身体接触和位置。因此，我们比较了两种条件下的情绪诱导效果：参与者被要求模仿两个化身之一的舞蹈动作，其中显示：（a）人类舞者模型的视频或（b）机器人舞者模型的视频。无论条件如何（人类与机器人化身舞蹈模型），情绪感应对于快乐和悲伤的模仿都是成功的。此外，快乐情绪诱导的程度以及参与者对任务的喜爱程度预测了情绪诱导后与工作相关的动机。我们的结论是，通过舞蹈动作调节情绪是可能的，并且在工作环境中是有益的。