	US 12,236,796 B2
	Predictive virtual training systems, apparatuses, interfaces, and methods for implementing same
Jonathan Josephson, Austin, TX (US); and Robert William Strozier, Houston, TX (US)
Assigned to Quantum Interface LLC, Austin, TX (US)
Filed by Quantum Interface, LLC, Austin, TX (US)
Filed on Dec. 6, 2021, as Appl. No. 17/542,812.
Application 17/542,812 is a continuation of application No. PCT/US2020/037807, filed on Jun. 15, 2020.
Claims priority of provisional application 62/861,971, filed on Jun. 14, 2019.
Prior Publication US 2022/0270509 A1, Aug. 25, 2022
Int. Cl. G09B 19/00 (2006.01); G06F 3/01 (2006.01); G06T 19/00 (2011.01); G09B 5/06 (2006.01)

CPC G09B 19/003 (2013.01) [G06F 3/011 (2013.01); G06T 19/00 (2013.01); G09B 5/065 (2013.01); G06F 3/012 (2013.01); G06F 3/013 (2013.01)]

20 Claims

1. A method implemented on an electronic device comprising a process coupled to or associated with a motion sensor, an input device, a display device and an output device, the method comprising:

loading a pre-existing virtual reality (VR) training program comprising a plurality of routines, tasks, or combinations thereof or an augmented reality/mixed reality/extended reality (AR/MR/XR) training program comprising a plurality of routines, tasks, or combinations thereof;

gathering information about:

(a) training program features, attributes, properties, characteristics, or combinations thereof,

(b) routine features, attributes, properties, characteristics, or combinations thereof,

(d) program equipment features, attributes, properties, characteristics, or combinations thereof associated with equipment used in the pre-existing training program, routines, and tasks;

analyzing the gathered information;

creating content from the analyzed and/or gathered information, the content comprising program content, routine content, task content, and equipment content;

generating hot spots or interactive areas from the created content, the hot spots or interactive areas comprise:

(a) program content hot spots or interactive areas associated with one, some, or all of the program features, attributes, properties, or characteristics,

(b) routine content hot spots or interactive areas associated with one, some, or all of the routine features, attributes, properties, or characteristics,

(c) task content hot spots or interactive areas associated with one, some, or all of the task features, attributes, properties, or characteristics, and

(d) equipment hot spots or interactive areas associated with one, some, or all of the equipment features, attributes, properties, or characteristics,

wherein the hot spots or interactive areas comprise documents, images, videos, tutorials, expert analyses, interact with experts, simulations, or any combination thereof and are represented as selectable objects, lists, menus, icons, or any combination thereof;

populating the pre-existing VR training program or the pre-existing VR/AR/MR training program with the generated hot spots or interactive areas at locations within the pre-existing VR training program or the pre-existing VR/AR/MR training program, the locations are associated with some or all of the features, devices, and/or attributes associated with or forming a part of the pre-existing VR training program or the pre-existing VR/AR/MR training program;

capturing trainer performance data as a trainer performs the pre-existing VR training program or the pre-existing VR/AR/MR training program, the trainer performance data comprising trainer program competency data, trainer routine competency data, trainer task competency data, trainer hot spot or interact area interaction data, trainer equipment interaction data, or any combination thereof;

capturing trainee performance data as a trainee performs the generated training program, the trainee performance data includes trainee program competency data, trainee routine competency data, trainee task competency data, trainee hot spot or interact area interaction data, equipment interaction data, or any combination thereof;

comparing the trainer performance data and the trainee performance data;

determining differences between the trainer performance data and the trainee performance data;

testing the differences between the trainer performance data and the trainee performance data, if each of the differences exceeds one or more minimum difference criteria, then:

displaying the differences; and

for each of the routines or tasks having differences that exceeds one or more minimum difference criteria, repeating:

the trainee capturing step,

the comparing step,

the determining differences step;

the testing step;

until each of the differences is less than or equal to the one or more minimum difference criteria; and

indicating successful completion of the training program.