Measuring Embodiment: Movement Complexity and the Impact of Personal Characteristics

• Main Authors: Good, J.J (Author), Peck, T.C (Author)
• Format: Article
• Language: English
• Published: IEEE Computer Society 2023
• Subjects: Age; Atmospheric measurement; Atmospheric measurements; Avatar; Avatars; Behavior; Behavioral research; Behavioral science; Behavioral sciences; Embodiment; Environmental technology; Gender; Mathematical models; Particle measurement; Particle measurements; STEM; Structural equation models; Structural Equation Modeling; Virtual environments; Virtual reality
• Online Access: View Fulltext in Publisher; View in Scopus
• Physical Description: 13
• ISBN: 10772626 (ISSN)
• DOI: 10.1109/TVCG.2023.3270725

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. Author