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Thesis
The NEVRland platform: an immersive virtual reality experimentation platform for research in neuroergonomics
Master of Science (M.S.), Drexel University
Jun 2025
DOI:
https://doi.org/10.17918/00011097
Abstract
Neuroergonomics research utilizes continuous metrics of the brain, body, behavior, and environment to develop a wholistic understanding of the brain at work in the complex, naturalistic context of everyday life. Though the development of increasingly mobile neurophysiological monitoring devices has enabled real-world experiments, researchers must accept a tradeoff of experimental control when bringing investigations out of the lab environment. Researchers have historically mitigated this tradeoff by employing immersive virtual technologies that create the illusion of naturalistic interactions and scenarios from within lab settings. Literature on human subject research suggests that the more immersive the technology used in an experiment is, the more accessible naturalistic experimental paradigms are to the researcher without sacrificing experimental control. Conveniently, modern head-mounted display (HMD) based virtual reality (VR) systems have become nearly synonymous with immersion, reliably evoking presence and embodiment. Immersive HMD-VR paradigms are accordingly being adopted in neuroergonomics research to take advantage of the naturalistic illusions they enable. Although research-specific platforms have been developed, they vary in the level of immersion, visual realism, coverage of cognitive domains, system transparency, or accessibility they offer. The alternative to these platforms is to design a custom VR environment compatible with neuroergonomics research using modern video game engines, which still requires a significant amount of technical expertise specific to programming and VR design. As a solution to the technological barrier posed by VR development for neuroergonomics research, this thesis proposes NEVRland: an accessible, reliable, plug-and-play platform designed to naturalistically simulate the real-world execution of any computer-based visual cognitive task through a photorealistic immersive virtual environment (NE short for neuroergonomics, VR for virtual reality). The NEVRland platform aims to enable more valid immersive VR paradigms for neuroergonomics research, which is currently achieved by utilizing pre-existing, robustly validated cognitive tasks already familiar to researchers from within the immersive environment. The default environment of the NEVRland platform emulates a generic behavioral experimentation room to support research where the visual task presentation medium is manipulated as an independent variable, as well as to serve as a control setting where needed. The default NEVRland environment is a one-to-one digital twin of a conventional lab setup: the original cognitive-task software is projected onto a virtual desktop monitor that appears before the participant inside the headset. Standard input devices (i.e. mouse, keyboard, or response pad) are visually replicated and animated in real time, closing the visual-haptic loop and preserving familiar task mechanics; optional hand-tracking overlays deepen the sense of embodiment. Comprehensive session logging, implemented via C++ extensions to Unreal's Blueprint architecture, records every interaction for subsequent analysis. As NEVRland is built in Unreal Engine on the cross-platform OpenXR runtime, the default digital twin is only a starting point. The same task can be transplanted into any fully realized 3-D scene from a serene beach at sunrise to a bustling surgical operating room, letting researchers examine cognition in richly contextual, ecologically valid settings while retaining experimental control. To assess NEVRland's feasibility, we implemented a high-precision flicker-timing benchmark on a standard desktop paired with a Meta Quest 2 HMD for the visual stimulus presentation event and duration timing. The test assessed whether rendering a photorealistic VR scene would divert enough hardware resources to degrade the timing accuracy of the external cognitive-task program. Results indicate that NEVRland's default environment can run concurrently with the task software without measurable loss in stimulus-onset or duration fidelity. Future work will broaden validation to diverse cognitive paradigms and pair NEVRland with simultaneous neural and physiological recordings to establish end-to-end performance for neuroergonomics research.
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Details
- Title
- The NEVRland platform
- Creators
- Callan Moira Powell
- Contributors
- Hasan Ayaz (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Master of Science (M.S.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- xii, 62 pages
- Resource Type
- Thesis
- Language
- English
- Academic Unit
- School of Biomedical Engineering, Science, and Health Systems (1997-2026); Drexel University
- Other Identifier
- 991022061354604721