HCAILGROMar 6, 2020

DeFINE: Delayed Feedback based Immersive Navigation Environment for Studying Goal-Directed Human Navigation

arXiv:2003.03133v26 citationsHas Code
AI Analysis

This makes virtual environments more accessible to researchers in fields like psychology or neuroscience, but it is incremental as it builds on existing frameworks by adding feedback features.

The paper tackles the problem of high technical expertise required to create immersive virtual environments for studying human navigation by presenting DeFINE, a framework that simplifies creation and administration of navigation tasks via intuitive interfaces, and demonstrates its usability with participant evaluations showing ease of use and low workload.

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.

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