Name
Abstract | ||
|---|---|---|
Different rendering styles induce different levels of agency and user behaviors in virtual reality environments. We applied an electroencephalogram-based approach to investigate how the rendering style of the users’ hands affects behavioral and cognitive responses. To this end, we introduced prediction errors due to cognitive conflicts during a 3-D object selection task by manipulating the selection distance of the target object. The results showed that, for participants with high behavioral inhibition scores, the amplitude of the negative event-related potential at approximately 50–250 ms correlated with the realism of the virtual hands. Concurring with the uncanny valley theory, these findings suggest that the more realistic the representation of the user’s hand is, the more sensitive the user becomes toward subtle errors, such as tracking inaccuracies. |
Year | Venue | Field |
|---|---|---|
2018 | IEEE Access | Mean squared prediction error,Virtual reality,Task analysis,Uncanny valley,Visualization,Computer science,Human–computer interaction,Cognition,Rendering (computer graphics),Visual appearance,Distributed computing |
DocType | Volume | Citations |
Journal | 6 | 0 |
PageRank | References | Authors |
0.34 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Avinash Kumar Singh | 1 | 31 | 13.77 |
| Hsiang-Ting Chen | 2 | 88 | 8.49 |
| Yu-Feng Cheng | 3 | 0 | 0.34 |
| Jung-Tai King | 4 | 52 | 9.83 |
| Li-Wei Ko | 5 | 519 | 58.70 |
| Klaus Gramann | 6 | 168 | 19.01 |
| Chin-Teng Lin | 7 | 3840 | 392.55 |