共同研究者の Melissa Steininger (ボン・ライン・ジーク大学) が、2024年9月15日から18日にかけてイギリス・グラスゴーで開催されたThe 12th International Conference on Affective Computing & Intelligent Interaction (ACII 2024) にて発表しました。これは、当研究室、ボン・ライン・ジーク大学、サイモン・フレーザー大学の共同研究の成果です。
- Melissa Steininger, Monica Perusquia-Hernandez, Alexander Marquardt, Hiromu Otsubo, Marvin Lehnort, Felix Dollack, Kiyoshi Kiyokawa, Ernst Kruijff, Bernhard Riecke,
“Using Skin Conductance to Predict Awe and Perceived Vastness in Virtual Reality,”
(Abstract) Awe is an emotion characterized by the perception of vastness and the need to accommodate this vastness into one’s mental framework. We propose an elicitation scene to induce awe in Virtual Reality (VR), validate it through self-report, and explore the feasibility of using skin conductance to predict self-reported awe and vastness as labeled from the stimuli in VR. Sixty-two participants took part in the study comparing the awe-eliciting space scene and a neutral scene. The space scene was confirmed as more awe-eliciting. A k-nearest neighbor algorithm confirmed high and low-awe score clusters used to label the data. A Random Forest algorithm achieved 65\% accuracy (F1 = 0.56, AUC = 0.73) when predicting the self-reported low and high awe categories from continuous skin conductance data. A similar approach achieved 55% accuracy (F1 = 0.59, AUC = 0.56) when predicting the perception of vastness. These results underscore the potential of skin-conductance-based algorithms to predict awe.
