PhysioVaping VR
Designing VR software for scientific study
Project Overview
Timeline
May 2025 -
Dec 2025
Team
Dr. Shu Wei
Roles
VR Design Engineer
Tools
Unity VR
Oculus/Meta VR SDK
Character Creator 4
iClone 8
Skills
VR Development
Interaction Design
Experience Design
Biometrics Integration
Summary
PhysioVaping VR is a research-driven virtual reality experience designed to study how young adults respond to vaping-related cues in realistic social environments.
Built for the Meta Quest Pro, the system immerses participants in everyday scenarios, such as a convenience store or a social gathering, while continuously capturing eye-tracking and physiological data.
The project bridges immersive experience design with behavioral science, using VR as a measurement tool for studying craving, attention, and autonomic responses in real time.
Working alongside Dr. Shu Wei, my work focused on translating experimental goals into an intuitive, comfortable, and immersive VR experience.
Problem Statement
Traditional assessments of nicotine craving and addiction risk rely heavily on self-report, which can be biased and insensitive to real-time cognitive and emotional processes. This study explores whether psychophysiological responses captured during immersive VR cue exposure, including eye gaze, heart rate, and skin conductance, can differentiate young adults who vape from those who do not.
By embedding vaping cues into believable social contexts, the project investigates how attention, arousal, and social pressure interact, and whether these signals can serve as early, non-invasive indicators of nicotine use risk.
Goals & Research Context
The primary goal of PhysioVaping VR is to evaluate the feasibility of VR-based psychophysiological assessment as a research tool for understanding nicotine use behaviors among young adults.
Design Challenges
Create VR environments that feel natural rather than clinical
Balance experimental control with freedom of exploration
Support reliable biometric data capture without disrupting immersion
Design Process
Ideation
Early ideation focused on how vaping appears in everyday life, not as a focal point, but as part of the background of social spaces. Using FigJam, we mapped scene concepts, character behaviors, and environmental cues, iterating on how subtle or overt each vaping element should be.
Special care was taken to design scenes that draw eye gaze, rather than scripted or forced interactions, especially given the sensitivity of biometric measurements.
Early Scene Design Mockups
User Flow
I designed participant flow to support both research constraints and user comfort.
Each VR session follows a clear progression—baseline → cue exposure → reflection—while allowing participants to explore freely within each environment.
The user switches between two scenes, one social and one non-social, each with their unique flows and mechanisms to draw eye gaze and induce vaping-related cues.
User Flow Considerations
Ensure smooth entry and onboarding into VR
Facilitate transitions between scenes and instructions for users
Gated interactions are required for experimental validity
Experimental User Flow | Social Scene User Flow
Interaction Design
Designing interaction for a research-focused VR experience required rethinking traditional UX assumptions.
Learning Curve
Lessening shock of VR space for first-time VR users
Quick onboarding and learning process
Immersion
Logical character and interaction placement
Minimal UI, ambient audio, & idle movement
Intuitiveness
Taking advantage of hand and pose tracking in headset
Interactable items are shown to be interactive
I also created flow charts for each interaction to help implementation and programming.
I implemented a gesture-based menu system linked to the left hand, allowing participants to access objectives with a palm rotation, seamlessly blending the interface with the experience.
Proximity-based character interactions were developed to simulate social realism; virtual characters can be spoken to once interacted with, and dynamic spatial audio was developed to convey ambient social cues.
I incorporated world space UI elements, such as buttons and hover states, and sound effects to signify interactable objects and characters in the space.
Prototyping and Implementation
Design
I designed and outlined interactions and flows through flow charts and sketches.
Taking into account biometrics tracking, room scale, and research aims, I continuously updated the design with researchers and stakeholders involved.
Technical Implementation
Using Unity and Meta VR SDK, I built 3D environments and wrote C# scripts for each flow and interaction of the experience. I worked closely with Dr. Shu Wei in implementation for biometrics data integration.
Iteration
I tested the experience through Quest Pro headset walkthroughs to evaluate spatial layout, scale, and interaction flow. Researcher feedback and UCD design sessions also guided testing.
Validation
User Testing
The experience was iteratively refined through two participatory design focus groups with participants from the target age range. Feedback from these sessions led to specific, testable design changes, including:
Testing-Based Refinements
Context-aware background music, adjusted to better match social settings and emotional tone
Improved facial animation and expression timing to increase perceived realism and peer believability
Repositioning and scaling of interactable UI elements to feel more natural within shared social space
Incorporating direct input from participants strengthened the realism and credibility of the simulation, reinforcing the value of co-design in research tools, particularly when modeling socially sensitive behaviors such as vaping.
Results
Final Design
The current version of PhysioVaping VR represents a polished, study-ready system shaped by iterative testing, researcher feedback, and user-centered design sessions. The experience is now being finalized for deployment in a controlled study.
While outcome data is forthcoming, the project has already demonstrated how immersive design decisions directly impact scientific validity.
The protocol for this study is published on JMIR (Journal of Internet Medical Research).
Lessons Learned
Iterate, iterate, iterate — With each run-through in the Meta Quest headset, new pain points, issues, and bugs were found. Whether that was the physical room being just a little too big compared to the VR scene or technical hiccups leading to further discussion on how to implement biometric sensors intuitively, I learned about working with VR technology and how to design for it step by step.
Design for maximum immersion — In VR, environmental immersion and intuitive interaction are key to providing results for research goals and decreasing discomfort for participants. Most users will not have VR experiences, so I learned to never assume that the user has prior knowledge.
Impact
PhysioVaping VR is intended for dissemination through peer-reviewed digital health and immersive technology venues, with the protocol in process at JMIR, contributing to research on addiction, youth health, and VR-based assessment methods.
More broadly, this project demonstrates how experience design can function as scientific infrastructure, shaping not just how users feel—but how knowledge is produced.
