DeFINE: Delayed Feedback based Immersive Navigation Environment for Studying Goal-Directed Human Navigation
| Autor: | Allen Cheung, Ville Kyrki, Kshitij Tiwari, Naohide Yamamoto |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
Computer Science - Machine Learning Computer science Computer Science - Artificial Intelligence Computer Science - Human-Computer Interaction Experimental and Cognitive Psychology Virtual reality Data type 050105 experimental psychology Task (project management) Human-Computer Interaction (cs.HC) Machine Learning (cs.LG) Computer graphics 03 medical and health sciences Computer Science - Robotics 0302 clinical medicine Software Arts and Humanities (miscellaneous) Human–computer interaction Developmental and Educational Psychology 0501 psychology and cognitive sciences General Psychology Graphical user interface business.industry 05 social sciences Usability Workload Artificial Intelligence (cs.AI) Psychology (miscellaneous) business Robotics (cs.RO) 030217 neurology & neurosurgery |
| Popis: | With the advent of consumer-grade products for presenting an immersive virtual environment (VE), there is a growing interest in utilizing VEs for testing human navigation behavior. However, preparing a VE still requires a high level of technical expertise in computer graphics and virtual reality, posing a significant hurdle to embracing the emerging technology. To address this issue, this paper presents Delayed Feedback based Immersive Navigation Environment (DeFINE), a framework that allows for easy creation and administration of navigation tasks within customizable VEs via intuitive graphical user interfaces and simple settings files. Importantly, DeFINE has a built-in capability to provide performance feedback to participants during an experiment, a feature that is critically missing in other similar frameworks. To show the usability of DeFINE from both experimentalists' and participants' perspectives, a demonstration was made in which participants navigated to a hidden goal location with feedback that differentially weighted speed and accuracy of their responses. In addition, the participants evaluated DeFINE in terms of its ease of use, required workload, and proneness to induce cybersickness. The demonstration exemplified typical experimental manipulations DeFINE accommodates and what types of data it can collect for characterizing participants' task performance. With its out-of-the-box functionality and potential customizability due to open-source licensing, DeFINE makes VEs more accessible to many researchers. 43 pages, 10 figures, 5 tables, Submitted to Behavioral Research Methods |
| Databáze: | OpenAIRE |
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