IPD Mismatches & User Comfort in VR Products
A high-impact collaborative research project that evaluates how mismatches between a user's natural interpupillary distance (IPD) and the VR headset settings affect user perception, comfort, usability, and the ability to interact with virtual objects in commercial head-mounted displays.
​
Disclaimer: Due to the confidential nature of this project details have been modified.
Project Overview
Client: Collaboration between York University and a Confidential Industry Partner
My Role: UX Researcher (Behavioural, Quantitative & Qualitative)
Timeline: August 2024 to Current
Skills & Tools: Experimental design, A/B tests, user surveys, user interviews, virtual reality, quantitative analysis (mixed effects and predictive modelling), Unity 3D, Blender, R
​
Summary: This project explores how IPD mismatches in VR headsets affect user perception, comfort, and interaction accuracy. Findings will guide ergonomic design and calibration features for next-generation headsets.
Problem & Objectives
VR users often report discomfort during extended sessions, including eye strain, headaches, or blurred vision. Preliminary research suggested that incorrect IPD calibration (i.e., the distance between the lenses) may be a significant factor. The challenge was to quantify the effects of typical IPD mismatches and identify thresholds where user discomfort becomes noticeable.
Objectives
-
Quantify how different levels of IPD mismatch affect depth perception, interaction accuracy, and comfort.
-
Identify tolerance thresholds for both novice and experienced VR users.
-
Explore whether demographic factors (age, vision correction, prior VR experience) influence sensitivity.
Methods
I collaborated with researchers and product managers to design and execute three confidential studies:​​​
-
Controlled Experiments: Systematically adjusted IPD settings (accurate, ±2 mm, ±4 mm) across custom Unity environments and commercial VR apps.
-
Surveys & Questionnaires: Used the Simulator Sickness Questionnaire (SSQ), demographic questionnaires (age, vision correction, and VR experience), and custom intercept surveys to track comfort, eye strain, and fatigue at each setting.
-
Qualitative Interviews: Follow-up sessions captured subjective experiences of immersion and comfort.
Process
-
Preparation: Calibrated headsets, created survey instruments, designed demographic questionnaire, and authored experiment protocol.
-
Testing: Facilitated 20, 40, and 60 minute VR tasks per IPD condition, balancing custom tasks and real-world VR gameplay.
-
Data Analysis:
-
Quantitative: Mixed effects model to determine significant changes in perception and comfort between test environments. Predictive modelling was used to model user performance according to viewing geometry and environment structure.
-
Qualitative: Conducted thematic coding of interview transcripts to identify recurring complaints and adaptation strategies.
-
Key Findings
Preliminary findings from this ongoing study suggest that experienced VR users can tolerate small IPD mismatches better than novices, highlighting user adaptation while maintaining comfort. Detailed results are confidential.
Impact
-
This research directly informed hardware and software design discussions:
-
Added default calibration prompts during headset setup.
-
Developed visual guides for easier manual IPD adjustment.
-
Proposed warnings if mismatches exceed user comfort thresholds.
-
Anticipated outcomes include reduced early-session complaints, enhanced immersion, and greater long-term adoption for diverse user groups.
-
I presented preliminary findings to design and hardware teams, influencing ergonomic considerations in upcoming headset iterations.
What I learned
-
Challenges: Recruiting a demographically diverse participant pool and controlling for prior VR experience required careful screening and scheduling.
-
Lessons: Even small IPD mismatches measurably affect comfort, reinforcing the need for user-adjustable hardware.
-
Growth: Strengthened my ability to translate statistical insights into design recommendations, balance academic rigor with industry constraints, and collaborate effectively within a large multidisciplinary team.