| Abstract |
| This study examined affective representation by analyzing physiological responses measured using wearable devices and affective ratings in response to emotional videos. To achieve this aim, a published dataset was reanalyzed using multidimensional scaling to demonstrate affective representation in two dimensions. Cross-participant classification was also conducted to identify the consistency of emotional responses across participants. The accuracy and misclassification in each emotional condition were described by exploring the confusion matrix derived from the classification analysis. Multidimensional scaling revealed that the represented objects, namely, emotional videos, were positioned along the rated valence and arousal vectors, supporting the core affect theory (Russell, 1980). Vector fittings of physiological responses also showed the associations between heart rate acceleration and low arousal, increased heart rate variability and negative and high arousal, and increased electrodermal activity and negative and low arousal. Using the data of behavioral and physiological responses across participants, the classification results revealed that emotional videos were more accurately classified than the chance level of classification. The confusion matrix showed that awe, enthusiasm, and liking, which were categorized as positive, low arousal emotions in this study, were less accurately classified than the other emotions and were misclassified for each other. Through multivariate analyses, this study confirms the core affect theory using physiological responses measured through wearable devices and affective ratings in response to emotional videos. |
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| Key Words |
| Classification, Multidimensional Scaling, Naturalistic Stimuli, Physiological Responses, Wearable Devices, 분류분석, 다차원척도법, 자연주의 자극, 생리적 반응, 웨어러블 기구 |
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