Topcon has been granted a patent for a method to determine tear film thickness. The method involves reconstructing a full- or hyper-spectral interference pattern from an imaged multi-spectral pattern, allowing for more accurate tear film thickness estimation without time-consuming techniques. GlobalData’s report on Topcon gives a 360-degree view of the company including its patenting strategy. Buy the report here.

According to GlobalData’s company profile on Topcon, eye-tracking wearables was a key innovation area identified from patents. Topcon's grant share as of June 2023 was 1%. Grant share is based on the ratio of number of grants to total number of patents.

Method for measuring tear film thickness using multi-spectral interference pattern

Source: United States Patent and Trademark Office (USPTO). Credit: Topcon Corp

A recently granted patent (Publication Number: US11684253B2) describes a method for measuring the thickness of a layer in a structure using multi-spectral interference patterns. The method involves acquiring a multi-spectral interference pattern of the structure and performing a hyperspectral reconstruction on it to generate a reconstructed full- or hyper-spectral interference pattern. The layer thickness is then estimated based on this reconstructed pattern.

The patent specifically mentions the application of this method to measure the thickness of the tear film in an eye. The multi-spectral interference pattern can be acquired using different types of cameras, such as an RGB camera, a dual color camera, or a narrow-band multi-spectral camera.

The hyperspectral reconstruction of the multi-spectral interference pattern is performed using a machine learning system that is trained to output the full- or hyper-spectral interference pattern based on the input multi-spectral interference pattern. This allows for accurate estimation of the layer thickness.

There are multiple ways to estimate the layer thickness based on the reconstructed interference pattern. One approach involves comparing the pattern with a look-up table, while another involves performing curve-fitting to the pattern. Additionally, a machine learning system can be trained to directly output the layer thickness based on the input interference pattern.

The method also includes the option to display the estimated layer thickness, providing a visual representation of the measurement.

In cases where the acquired multi-spectral interference pattern is out of focus, the method further involves focusing the pattern before performing the hyperspectral reconstruction. This focusing process can be performed by a machine learning system trained to output an in-focus multi-spectral interference pattern based on an input out-of-focus pattern.

Overall, this patented method offers a novel approach to measuring layer thickness in structures using multi-spectral interference patterns. Its application to measuring tear film thickness in the eye could have significant implications for ophthalmology and eye health. The use of machine learning systems enhances the accuracy and efficiency of the measurement process.

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GlobalData Patent Analytics tracks bibliographic data, legal events data, point in time patent ownerships, and backward and forward citations from global patenting offices. Textual analysis and official patent classifications are used to group patents into key thematic areas and link them to specific companies across the world’s largest industries.