Abstract
Graceful interaction is a form of interaction that incorporates quality movement that can invoke the emotional appeal of users engaged with it. However method of evaluation of the quality graceful interaction has not been discussed. As we argue that graceful interaction can evoke emotion, we explore the use of possible instruments to evaluate graceful interaction based on the valence–arousal model. To measure emotional response of arousal the response is using verbal and non-verbal instruments. The former is based on self-report emotions and the later through autonomic measures of emotion via bio-physical measures of skin conductance. We conducted an experiment with six participants who were given the tasks to perform movement tasks in virtual fitting using three different virtual fitting room (VFR) applications available on e-commerce fashion retailing websites. The selection of the VFR applications was based on the presence of two identified graceful interaction design elements, which are tempo and sequence as prescribed by the graceful interaction design model. While performing the tasks, each participant’s physiology measure of emotional response was recorded using the tool BioGraph Infiniti. Upon completion, the participants were requested to report their emotional response in an instrument constructed based on the valence arousal model. Finally each participant was also interviewed to state the VFR applications they preferred. The analysis of each type emotional response were made and the findings showed the congruence between the verbally expressed emotional response and physiology measure of emotional response in performing graceful interaction tasks. This suggests that the evaluation of graceful interaction can be made by the use of verbally and non-verbally expressed emotional respond instruments.
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Wan Adnan, W.A., Noor, N.L.M., Saman, F.M., Zailani, S.N., Hashim, W.N.W. (2014). Evaluation of Graceful Movement in Virtual Fitting through Expressed Emotional Response and Emotion Expressed via Physiology Measures. In: Kurosu, M. (eds) Human-Computer Interaction. Advanced Interaction Modalities and Techniques. HCI 2014. Lecture Notes in Computer Science, vol 8511. Springer, Cham. https://doi.org/10.1007/978-3-319-07230-2_75
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DOI: https://doi.org/10.1007/978-3-319-07230-2_75
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