Mood induction through imitation of full‐body movements with different affective intentions

Abstract

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.

EMOKINE: A software package and computational framework for scaling up the creation of highly controlled emotional full-body movement datasets

“…A series of computational validations and an observer experiment confirmed the validity of the EMOKINE pilot dataset and the creation procedure. Besides these validations provided here, the dataset has been shown to be useful to assess research questions in health psychology, for example, about how dance breaks during work hours may improve mood and motivation (Schmidt et al, 2023). Datasets created following the EMOKINE suite may be particularly useful for addressing questions about which kinematic features drive high emotion recognition and/or misclassifications.…”

“…Each sequence was performed six times to express a different emotional intention at each repetition, namely, anger, contentment, fear, joy, neutrality, sadness; i.e., 9 sequences × 6 emotions = 54 emotional dance movement stimuli. In addition, for each sequence, the dancer did a seventh repetition of the sequence, during which she explained the movements while doing them, like an instruction video for a dance class; yielding nine explanation videos (used elsewhere; Schmidt et al, 2023), yet the videos are provided here as part of the full EMOKINE dataset). Therefore, the total number of stimuli in the EMOKINE dataset is 63 (see Fig.…”

“…The EMOKINE pilot dataset is available for download online, and a selection of stimuli has been used in published work (Schmidt et al, 2023). However, please note that this dataset was created to enable the development of the EMOKINE software and contains portrayals from only one dancer.…”

“…The seventh time she explained the movements, as for a dance class instruction. The latter stimuli were included in a different experiment (Schmidt et al, 2023), but are also included in the present dataset for sake of completeness…”