Faculty of Humanities, AGH University of Science and Technology, 30-059 Kraków, Poland.
Department of Computer Science, College of Science, Utah State University, Logan, UT 84322, USA.
Sensors (Basel). 2024 Jun 21;24(13):4032. doi: 10.3390/s24134032.
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.
本研究通过评估生理反应，考察了社交机器人在促进大学生压力管理干预方面的有效性。我们从两组学生那里收集了脑电图（EEG）脑活动和皮肤电反应（GSR），以及他们在练习深呼吸练习时使用社交机器人或笔记本电脑的自我报告问卷。从 GSR 信号中，我们获得了参与者在整个干预过程中唤醒水平的变化，从 EEG 信号中，我们使用额前阿尔法不对称性（FAA）的神经测量法提取了他们情绪效价的变化。虽然两组学生在压力的主观感知和用户体验方面没有显著差异，但生理信号揭示了他们在情绪反应方面的差异，这些差异是通过唤醒-效价模型评估的。笔记本电脑组倾向于表现出唤醒水平的降低，在某些情况下，伴随着负面效价，表明无聊或缺乏兴趣。另一方面，机器人组表现出两种模式；一些人表现出唤醒水平降低，同时伴随着积极的效价，表明平静和放松，另一些人则表现出唤醒水平升高，同时伴随着积极的效价，这被解释为兴奋。这些发现为社交机器人作为学生情绪的心理健康教练的影响提供了有趣的见解，特别是在新奇效应的存在下。此外，它们为生理信号作为 HRI 环境中用户体验的客观可靠测量提供了证据。
