Purpose
Vision for a contact lens patient is impacted by the geometric and material properties of the contact lens, the physical properties of the eye and the neural/brain system that interprets the images on the retina. Improved vision requires a contact lens design that is optimized by taking advantage of the properties of the eye and brain components of the visual system. The purpose was to create, from clinically measured data, eye and vision models that capture the natural properties of the visual system suitable for optimization of a presbyopic contact lens system.
Methods
A system of lenses for presbyopia generally consists of a family of lenses designated for progressively higher add needs (i.e. LOW, MID, and HIGH add lenses) along with a fit guide that recommends how to select lenses. The lenses are often fit as disparate pairs to provide the best binocular vision over the range of visual conditions encountered. Therefore, design optimization requires a Binocular Vision Model (BV) that can predict the quality of vision for patients over a wide range of viewing distances and luminance levels. Vision is optimized by minimizing the equation shown nearby by changing the geometry of the contact lenses and the fit guide to best match the target binocular vision (TargetBV) over a wide range of luminance levels, viewing distance, patient ages, and patient sphere prescriptions.<br /> <br /> The Binocular Vision Model allows prediction of the quality of vision by correlating properties of a Retinal Image Model with clinical visual response. The Retinal Image Model depends upon the properties of the eye (Eye Model), properties of the contact lens (Contact Lens Model), and the properties of the tear film (Tear Film Model). Each of these models is developed from a combination of J&J Vision Care data, literature data, design data, and in-vitro measurements.
Results
A contact lens design optimization method was developed which incorporates a Binocular Vision Model developed from a meta-analysis of data from multiple sources. This model-based design optimization approach was used for vision optimization of a new contact lens product.
Conclusions
Optical designs for presbyopic contact lenses developed using the latest physiological and perceptual models provide for potentially improved vision across the full range of viewing conditions and patients.