Abstract:
The current study investigated the effectiveness of social robots in facilitating stress management interventions for university students by evaluating their physiological responses. We collected electroencephalogram (EEG) brain activity and Galvanic Skin Responses (GSRs) together with self-reported questionnaires from two groups of students who practiced a deep breathing exercise either with a social robot or a laptop. From GSR signals, we obtained the change in participants\' arousal level throughout the intervention, and from the EEG signals, we extracted the change in their emotional valence using the neurometric of Frontal Alpha Asymmetry (FAA). While subjective perceptions of stress and user experience did not differ significantly between the two groups, the physiological signals revealed differences in their emotional responses as evaluated by the arousal-valence model. The Laptop group tended to show a decrease in arousal level which, in some cases, was accompanied by negative valence indicative of boredom or lack of interest. On the other hand, the Robot group displayed two patterns; some demonstrated a decrease in arousal with positive valence indicative of calmness and relaxation, and others showed an increase in arousal together with positive valence interpreted as excitement. These findings provide interesting insights into the impact of social robots as mental well-being coaches on students\' emotions particularly in the presence of the novelty effect. Additionally, they provide evidence for the efficacy of physiological signals as an objective and reliable measure of user experience in HRI settings.
摘要:
当前的研究通过评估大学生的生理反应来调查社交机器人在促进大学生压力管理干预方面的有效性。我们收集了两组使用社交机器人或笔记本电脑进行深呼吸练习的学生的脑电图(EEG)大脑活动和皮肤电反应(GSR)以及自我报告的问卷。从GSR信号,我们在整个干预过程中获得了参与者觉醒水平的变化,从EEG信号中,我们使用额叶α不对称(FAA)的神经测量法提取了他们的情绪效价变化。虽然对压力和用户体验的主观感知在两组之间没有显着差异,通过唤醒-效价模型评估,生理信号显示出他们的情绪反应存在差异。笔记本电脑组倾向于显示唤醒水平降低,在某些情况下,伴随着负价,表明无聊或缺乏兴趣。另一方面,机器人小组显示了两种模式;一些人表现出唤醒减少,积极的效价表明平静和放松,其他人则表现出觉醒的增加以及被解释为兴奋的正效价。这些发现为社交机器人作为心理健康教练对学生情绪的影响提供了有趣的见解,特别是在存在新奇效应的情况下。此外,它们为生理信号作为HRI设置中用户体验的客观和可靠衡量标准的有效性提供了证据.