How to Tune Autofocals: A Comparative Study of Advanced Tuning Methods

TL;DR

This paper compares manual, gaze-based, and vergence tuning methods for autofocal glasses in VR, analyzing their performance, usability, and suitability for different user needs and scenarios.

Contribution

It provides a comprehensive evaluation of advanced autofocal tuning methods using VR, highlighting their strengths and weaknesses for practical application.

Findings

Gaze control offers high precision in tuning.

Manual tuning provides stability and predictability.

Different methods suit different user preferences and tasks.

Abstract

This study comprehensively evaluates tuning methods for autofocal glasses using virtual reality (VR), addressing the challenge of presbyopia. With aging, presbyopia diminishes the eye's ability to focus on nearby objects, impacting the quality of life for billions. Autofocals, employing focus-tunable lenses, dynamically adjust optical power for each fixation, promising a more natural visual experience than traditional bifocal or multifocal lenses. Our research contrasts the most common tuning methods - manual, gaze-based, and vergence - within a VR setup to mimic real-world scenarios. Utilizing the XTAL VR headset equipped with eye-tracking, the study replicated autofocal scenarios, measuring performance and usability through psychophysical tasks and NASA TLX surveys. Results show varying strengths and weaknesses across methods, with gaze control excelling in precision but not necessarily comfort and manual control providing stability and predictability. The findings guide the selection of tuning methods based on task requirements and user preferences, highlighting a balance between precision and ease of use.