Department of Computing, Xi'an Jiaotong-Liverpool University, Suzhou 215123, China.
Center for Ubiquitous Computing, University of Oulu, 90570 Oulu, Finland.
Sensors (Basel). 2021 Feb 2;21(3):990. doi: 10.3390/s21030990.
Research from psychology has suggested that body movement may directly activate emotional experiences. Movement-based emotion regulation is the most readily available but often underutilized strategy for emotion regulation. This research aims to investigate the emotional effects of movement-based interaction and its sensory feedback mechanisms. To this end, we developed a smart clothing prototype, E-motionWear, which reacts to four movements (elbow flexion/extension, shoulder flexion/extension, open and closed arms, neck flexion/extension), fabric-based detection sensors, and three-movement feedback mechanisms (audio, visual and vibrotactile). An experiment was conducted using a combined qualitative and quantitative approach to collect participants' objective and subjective emotional feelings. Results indicate that there was no interaction effect between movement and feedback mechanism on the final emotional results. Participants preferred vibrotactile and audio feedback rather than visual feedback when performing these four kinds of upper body movements. Shoulder flexion/extension and open-closed arm movements were more effective for improving positive emotion than elbow flexion/extension movements. Participants thought that the E-motionWear prototype were comfortable to wear and brought them new emotional experiences. From these results, a set of guidelines were derived that can help frame the design and use of smart clothing to support users' emotional regulation.
心理学研究表明，身体运动可能会直接激活情绪体验。基于运动的情绪调节是最容易获得但经常未被充分利用的情绪调节策略。本研究旨在探讨基于运动的交互及其感觉反馈机制的情绪效果。为此，我们开发了一种智能服装原型 E-motionWear，它可以对四种运动（肘部弯曲/伸展、肩部弯曲/伸展、手臂张开/闭合、颈部弯曲/伸展）、基于织物的检测传感器和三种运动反馈机制（音频、视觉和触觉反馈）做出反应。我们采用定性和定量相结合的方法进行实验，收集参与者的客观和主观情绪感受。结果表明，运动和反馈机制对最终的情绪结果没有交互作用。参与者在进行这四种上肢运动时更喜欢触觉反馈和音频反馈，而不是视觉反馈。与肘部弯曲/伸展运动相比，肩部弯曲/伸展和手臂张开/闭合运动更能有效改善积极情绪。参与者认为 E-motionWear 原型穿着舒适，并为他们带来了新的情感体验。根据这些结果，得出了一套准则，可以帮助设计和使用智能服装来支持用户的情绪调节。
