Virtual reality (VR) as a testing bench for consumer optical solutions:
A machine learning approach (GBR) to visual comfort under simulated
progressive addition lenses (PALS) distortions
For decades, manufacturers have attempted to reduce or eliminate the optical
aberrations that appear on the progressive addition lens' surfaces during
manufacturing. Besides every effort made, some of these distortions are
inevitable given how lenses are fabricated, where in fact, astigmatism appears
on the surface and cannot be entirely removed or where non-uniform
magnification becomes inherent to the power change across the lens. Some
presbyopes may refer to certain discomfort when wearing these lenses for the
first time, and a subset of them might never adapt. Developing, prototyping,
testing and purveying those lenses into the market come at a cost, which is
usually reflected in the retail price. This study aims to test the feasibility
of virtual reality for testing customers' satisfaction with these lenses, even
before getting them onto production. VR offers a controlled environment where
different parameters affecting progressive lens comforts, such as distortions,
image displacement or optical blurring, can be analysed separately. In this
study, the focus was set on the distortions and image displacement, not taking
blur into account. Behavioural changes (head and eye movements) were recorded
using the built-in eye tracker. Participants were significantly more displeased
in the presence of highly distorted lens simulations. In addition, a gradient
boosting regressor was fitted to the data, so predictors of discomfort could be
unveiled, and ratings could be predicted without performing additional
measurements