Measuring Embodiment: Movement Complexity and the Impact of Personal Characteristics
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 mode...
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| Vydáno v: | IEEE transactions on visualization and computer graphics Ročník 30; číslo 8; s. 4588 - 4600 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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IEEE
01.08.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 1077-2626, 1941-0506, 1941-0506 |
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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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| AbstractList | 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. 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.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 | Peck, Tabitha C. Good, Jessica J. |
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37099457$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | Adolescent Adult Age Atmospheric measurements Avatars behavior Behavioral sciences Computer Graphics Effectiveness embodiment Female gender Humans Male Mathematical models Middle Aged Movement - physiology Particle measurements STEM structural equation modeling User-Computer Interface Video Games Virtual environments Virtual Reality Young Adult |
| Title | Measuring Embodiment: Movement Complexity and the Impact of Personal Characteristics |
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