Awe is a multifaceted emotion often associated with the perception of vastness, that challenges existing mental frameworks. Despite its growing relevance in affective computing and psychological research, awe remains difficult to elicit and measure. This raises the research questions of how awe can be effectively elicited, which factors are associated with the experience of awe, and whether it can reliably be measured using biosensors. For this study, we designed 10 immersive Virtual Reality (VR) scenes with dynamic transitions from narrow to vast environments. These scenes were used to explore how awe relates to environmental features (abstract, human-made, nature), personality traits, and country of origin. We collected skin conductance, respiration, self-reported awe and presence data from participants from Germany, Japan, and Jordan. Our results indicate that self-reported awe varies significantly across countries and scene types. In particular, a scene depicting outer space elicited the strongest awe. Scenes that elicited high selfreported awe also induced a stronger sense of presence. However, we found no evidence that awe ratings are correlated with physiological responses. These findings challenge the assumption that awe is reliably reflected in autonomic arousal and underscore the importance of cultural and perceptual context. Our study offers new insights into how immersive VR can be designed to elicit awe, and suggests that subjective reports - rather than physiological signals - remain the most consistent indicators of emotional impact.

Awe is a complex emotion described as a perception of vastness and a need for accommodation to integrate new, overwhelming experiences. Virtual Reality (VR) has recently gained attention as a convenient means to facilitate experiences of awe. In VR, a first-person perspective might increase awe due to its immersive nature, while a third-person perspective might enhance the perception of vastness. However, the impact of VR perspectives on experiencing awe has not been thoroughly examined. We created two types of VR scenes: one with elements designed to induce high awe, such as a snowy mountain, and a low awe scene without such elements. We compared first-person and third-person perspectives in each scene. Forty-two participants explored the VR scenes, with their physiological responses captured by electrocardiogram (ECG) and face tracking (FT). Subsequently, participants self-reported their experience of awe (AWE-S) and presence (IPQ) within VR. The results revealed that the first-person perspective induced stronger feelings of awe and presence than the third-person perspective. The findings of this study provide useful guidelines for designing VR content that enhances emotional experiences.

Distal facial Electromyography (EMG) can be used to detect smiles and frowns with reasonable accuracy. It capitalises on volume conduction to detect relevant muscle activity, even when the electrodes are not placed directly on the source muscle. The main advantage of this method is to prevent occlusion and obstruction of the facial expression production, whilst allowing EMG measurements. However, measuring EMG distally entails that the exact source of the facial movement is unknown. Therefore, we investigated whether we could identify specific Facial Action Units (AUs) from distal facial EMG after an initial calibration phase with Computer Vision (CV). We compared Support Vector Machines (SVM) and Random Forest (RF) with several types of feature engineering and early fusion of the two modalities. The detection performance for AU6 (Orbicularis Oculi) and AU12 (Zygomaticus Major) was estimated by calculating the agreement with Facial Action Coding System (FACS) certified coders. The best results were achieved using Random Forest. Using a fusion of CV and EMG features resulted in F1 scores of 0.83 for AU6; and the fusion of engineered EMG plus CV returned an F1 score of 0.81 for AU12. Both these results are well above the CV baseline that shows F1 scores of 0.56 and 0.62 for AU6 and AU12 respectively. This demonstrates the potential of distal EMG to detect individual facial movements. It also enables researchers to compare the results measured with this wearable device to psychological research on facial expressions using FACS. Using a wearable enables measurements with higher ecological validity. Finally, we observed that EMG activity starts before the onset of visually perceived movement. Because of this, the agreement between EMG-based methods and FACS coders might be underestimating the ground truth.

Self-tracking aims to increase awareness, decrease undesired behaviors, and ultimately lead towards a healthier lifestyle. However, inappropriate communication of self- tracking results might cause the opposite effect. Subtle self- tracking feedback is an alternative that can be provided with the aid of an artificial agent representing the self. Hence, we propose a wearable pet that reflects the user's affective states through visual and haptic feedback. By eliciting empathy and fostering helping behaviors towards it, users would indirectly help themselves. A wearable prototype was built, and three user studies performed to evaluate the appropriateness of the proposed affective representations. Visual representations using facial and body cues were clear for valence and less clear for arousal. Haptic interoceptive patterns emulating heart-rate levels matched the desired feedback urgency levels with a saturation frequency. The integrated visuo-haptic representations matched to participants own affective experience. From the results, we derived three design guidelines for future robot mirroring wearable systems: physical embodiment, interoceptive feedback, and customization.