US 12,093,871 B2
Ocular system to optimize learning
David Zakariaie, Austin, TX (US); Kathryn McNeil, Austin, TX (US); Alexander Rowe, Austin, TX (US); Joseph Brown, Austin, TX (US); Patricia Herrmann, Austin, TX (US); Jared Bowden, Austin, TX (US); Taumer Anabtawi, Austin, TX (US); Andrew R. Sommerlot, Austin, TX (US); Seth Weisberg, Austin, TX (US); and Veronica Choi, Austin, TX (US)
Assigned to Senseye, Inc., Austin, TX (US)
Filed by Senseye, Inc., Austin, TX (US)
Filed on Mar. 30, 2023, as Appl. No. 18/128,987.
Application 18/128,987 is a division of application No. 17/247,636, filed on Dec. 18, 2020, granted, now 11,640,572.
Claims priority of provisional application 62/950,918, filed on Dec. 19, 2019.
Prior Publication US 2023/0306341 A1, Sep. 28, 2023
Int. Cl. G06K 9/62 (2022.01); A61B 3/00 (2006.01); A61B 3/11 (2006.01); A61B 3/113 (2006.01); A61B 3/14 (2006.01); A61B 5/00 (2006.01); A61B 5/11 (2006.01); A61B 5/16 (2006.01); G06N 3/045 (2023.01); G06N 3/08 (2023.01); G06Q 10/0635 (2023.01); G06Q 10/0639 (2023.01); G06Q 10/10 (2023.01); G06T 7/73 (2017.01); G06V 10/143 (2022.01); G06V 10/44 (2022.01); G06V 10/764 (2022.01); G06V 20/40 (2022.01); G06V 40/18 (2022.01); G06V 40/19 (2022.01); G16H 15/00 (2018.01); G16H 30/20 (2018.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01); G06N 3/088 (2023.01); G16H 50/30 (2018.01)
CPC G06Q 10/0635 (2013.01) [A61B 3/0025 (2013.01); A61B 3/0041 (2013.01); A61B 3/0091 (2013.01); A61B 3/112 (2013.01); A61B 3/113 (2013.01); A61B 3/145 (2013.01); A61B 5/1103 (2013.01); A61B 5/161 (2013.01); A61B 5/163 (2017.08); A61B 5/165 (2013.01); A61B 5/4845 (2013.01); A61B 5/4863 (2013.01); A61B 5/6898 (2013.01); A61B 5/7246 (2013.01); G06N 3/045 (2023.01); G06N 3/08 (2013.01); G06Q 10/06398 (2013.01); G06Q 10/10 (2013.01); G06T 7/73 (2017.01); G06V 10/143 (2022.01); G06V 10/454 (2022.01); G06V 10/764 (2022.01); G06V 20/46 (2022.01); G06V 40/18 (2022.01); G06V 40/19 (2022.01); G06V 40/193 (2022.01); G16H 15/00 (2018.01); G16H 30/20 (2018.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01); A61B 5/7267 (2013.01); A61B 2503/20 (2013.01); G06N 3/088 (2013.01); G06T 2207/10016 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30041 (2013.01); G16H 50/30 (2018.01)] 4 Claims
OG exemplary drawing
 
1. A method to measure a cognitive load based upon ocular information of a subject, the method comprising the steps of:
providing a video camera configured to record a close-up view of at least one eye of the subject;
providing a computing device electronically connected to the video camera and the electronic display;
recording, via the video camera, the ocular information of the at least one eye of the subject;
processing, via the computing device, the ocular information to identify changes in ocular signals of the subject through the use of convolutional neural networks;
evaluating, via the computing device, the changes in ocular signals from the convolutional neural networks by a machine learning algorithm;
determining, via the machine learning algorithm, the cognitive load for the subject; and
displaying, to the subject and/or to a supervisor, the cognitive load for the subject.