Measuring Embodiment: Movement Complexity and the Impact of Personal Characteristics

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Abstract

A user's personal experiences and characteristics may impact the strength of an embodiment illusion and affect resulting behavioral changes in unknown ways. This paper presents a novel re-analysis of two fully-immersive embodiment user-studies (n = 189 and n = 99) using structural equation modeling, to test the effects of personal characteristics on subjective embodiment. Results demonstrate that individual characteristics (gender, participation in science, technology, engineering or math - Experiment 1, age, video gaming experience - Experiment 2) predicted differing self-reported experiences of embodiment Results also indicate that increased self-reported embodiment predicts environmental response, in this case faster and more accurate responses within the virtual environment. Importantly, head-tracking data is shown to be an effective objective measure for predicting embodiment, without requiring researchers to utilize additional equipment.

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Peck, T. C., & Good, J. J. (2024). Measuring Embodiment: Movement Complexity and the Impact of Personal Characteristics. IEEE Transactions on Visualization and Computer Graphics, 30(8), 4588–4600. https://doi.org/10.1109/TVCG.2023.3270725

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