Personalized optics-free vision correction

Patent metadata

Field	Value
Publication number	US-11222615-B2
Application number	US-201916541214-A
Country	US
Kind code	B2
Filing date	Aug 15, 2019
Priority date	Aug 15, 2019
Publication date	Jan 11, 2022
Grant date	Jan 11, 2022

Abstract

A user profile associated with a first user is received. A user prescription associated with the first user is received. A historical interaction of the first user with a display is received. A global vision model is received. One or more display sets to be used on the display is determined based on at least the user profile, the user prescription, the global vision model, and the historical interaction.

First claim

What is claimed is:

1. A computer-implemented method, the method comprising the steps of:
receiving, by one or more computer processors, a user eye prescription associated with the first user;
receiving, by one or more computer processors, a personal vision model of the first user, wherein the personal vision model is a machine learning model that models relationships between the user eye prescription and display settings on a display;
receiving, by one or more computer processors, a global vision model, wherein the global vision model is a machine learning model that models relationships between two or more users eye prescription and display settings on a display;
determining, by one or more computer processors, one or more display settings to be used on a display based on at least the user eye prescription, the global vision model, and the personal vision model;
displaying, by one or more computer processors, one or more visual representations on the display using the one or more determined display settings;
receiving, by one or more computer processors, user feedback to the display, wherein the user feedback is eye fatigue of the user;
updating, by one or more computer processors, the display settings based on the user feedback; and
updating, by one or more computer processors, the personal vision model based on the user feedback.

2. The computer-implemented method of claim 1 , wherein the one or more display settings is selected from the group consisting of zoom level, contrast, distortion, color tune, brightness, and sharpness.

3. The computer-implemented method of claim 1 , wherein the user prescription is selected from the group consisting of OD (oculus dexter, right eye), OS (oculus sinister, left eye), SPH (Sphere), CYL (cylinder), PD (pupillary distance), Axis, Add, and Prism.

4. The computer-implemented method of claim 1 , wherein the eye fatigue is pupil size.

5. The computer-implemented method of claim 1 , wherein the eye fatigue is facial expressions.

6. The computer-implemented method of claim 1 , wherein the eye fatigue is a change of position or distance of the user from the display.

7. The computer-implemented method of claim 1 , further comprising:
receiving, by one or more computer processors, an eye gaze of the first user; and
modifying, by one or more computer processors, a subsection of the one or more visual representations on the display based on the eye gaze using the one or more determined display settings.

8. A computer program product, the computer program product comprising:
one or more computer readable storage media; and
program instructions stored on the one or more computer readable storage media, the program instructions comprising:
program instructions to receive a user eye prescription associated with the first user;
program instructions to receive a personal vision model of the first user, wherein the personal vision model is a machine learning model that models relationships between the user eye prescription and display settings on a display;
program instructions to receive a global vision model, wherein the global vision model is a machine learning model that models relationships between two or more users eye prescription and display settings on a display;
program instructions to determine one or more display settings to be used on a display based on at least the user eye prescription, the global vision model, and the personal vision model;
program instructions to display one or more visual representations on the display using the one or more determined display settings;
program instructions to receive user feedback to the display, wherein the user feedback is eye fatigue of the user;

program instructions to receive update the display settings based on the user feedback; and
program instructions to updated the personal vision model based on the user feedback.

9. The computer program product of claim 8 , wherein the one or more display settings is selected from the group consisting of zoom level, contrast, distortion, color tune, brightness, and sharpness.

10. The computer program product of claim 8 , wherein the user prescription is selected from the group consisting of OD (oculus dexter, right eye), OS (oculus sinister, left eye), SPH (Sphere), CYL (cylinder), PD (pupillary distance), Axis, Add, and Prism.

11. The computer program product of claim 8 , further comprising program instructions, stored on the one or more computer readable storage media, to:
program instructions to receive an eye gaze of the first user; and
program instructions to modify a subsection of the one or more visual representations on the display based on the eye gaze using the one or more determined display settings.

12. A computer system, the computer system comprising:
one or more computer processors;
one or more computer readable storage media; and
program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more computer processors, the program instructions comprising:
program instructions to receive a user eye prescription associated with the first user;
program instructions to receive a personal vision model of the first user, wherein the personal vision model is a machine learning model that models relationships between the user eye prescription and display settings on a display;
program instructions to receive a global vision model, wherein the global vision model is a machine learning model that models relationships between two or more users eye prescription and display settings on a display;
program instructions to determine one or more display settings to be used on a display based on at least the user eye prescription, the global vision model, and the personal vision model;
program instructions to display one or more visual representations on the display using the one or more determined display settings;
program instructions to receive user feedback to the display, wherein the user feedback is eye fatigue of the user;
program instructions to receive update the display settings based on the user feedback; and
program instructions to updated the personal vision model based on the user feedback.

13. The computer system of claim 12 , wherein the one or more display settings is selected from the group consisting of zoom level, contrast, distortion, color tune, brightness, and sharpness.

14. The computer system of claim 12 , further comprising program instructions, stored on the one or more computer readable storage media for execution by the at least one of the one or more computer processors, to:
program instructions to receive an eye gaze of the first user; and
program instructions to modify a subsection of the one or more visual representations on the display based on the eye gaze using the one or more determined display settings.

Assignees

• IBM

Inventors

• Shafieibavani Elaheh
• Zhong Peter
• Garnavi Rahil
• Raghib Michael

Classifications

• G09G2320/0626

  for control of overall brightness · CPC title

• G09G2340/0407

  Resolution change, inclusive of the use of different resolutions for different screen areas · CPC title

• G09G2320/0666

  for control of colour parameters, e.g. colour temperature · CPC title

• G09G2354/00

  Aspects of interface with display user · CPC title

• G09G5/37 Primary

  Details of the operation on graphic patterns (G09G5/38 takes precedence) · CPC title