Passive eye condition detection during independent content presentation
AssigneeHeru Inc.
InventorMohamed ABOU SHOUSHA
Life of this patent
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Abstract
In some embodiments, a head-mounted device and related method may use a presenting application to present content to an eye while a testing application sandboxed from the presenting application generates one or more eye condition indications. Some embodiments may do so while preserving computer resources by using a hierarchical arrangement of machine learning models.
Claims20
A head-mounted device for passive eye condition detection via a sandboxed application during content presentation independent of the sandboxed application, the head-mounted device comprising:
- one or more inward-facing sensors and an inward-facing display;
- one or more processors and non-transitory media storing instructions that, when executed by the one or more processors, perform operations comprising:
- in connection with a presenting application presenting image content to a user of the head-mounted device via the inward-facing display, obtaining, via the one or more inward-facing sensors, eye-related feedback data comprising (i) eye response data corresponding to eye responses to the presentation of the image content and (ii) reflected image content data corresponding to reflections off an eye while the image content is being presented;
- providing the eye-related feedback data to a sandboxed vision testing application that is sandboxed from the presenting application;
- generating, via the sandboxed vision testing application, a sequence of reconstructed images that approximate the image content based on the reflected image content data, wherein the image content stored in memory and used by the presenting application is not accessible to the sandboxed vision testing application;
- generating, based on the sequence of reconstructed images, a set of expected eye measurements representing an expected response of the eye to the sequence of reconstructed images expected for a healthy eye;
- and
- generating an eye condition indication by using a machine learning model to compare the set of expected eye measurements with the eye-related feedback data.
A method comprising:
- obtaining, via one or more sensors of a head-mounted device, eye-related feedback data corresponding to (i) eye responses to a presentation of image content and (i) reflections off an eye while the image content is being presented to a user by an inward-facing display of the head-mounted device using a first application;
- providing the eye-related feedback data to a second application that is sandboxed from the first application;
- generating, by the second application, an eye condition indication by providing the eye-related feedback data to a machine learning model, wherein:
- the second application generates simulated input data based on the eye-related feedback data;
- and
- generating the eye condition indication comprises generating the eye condition indication based on the simulated input data.
One or more non-transitory machine-readable media storing program instructions that, when executed by one or more processors, causes the one or more processors to perform operations comprising:
- in connection with a first application presenting image content to a user via an inward-facing display of a head-mounted device, obtaining, via one or more sensors of the head-mounted device measuring reflections off an eye of the user, feedback data while the image content is being presented;
- providing to the feedback data to a second application that is sandboxed with respect to the first application, generating, via the second application, an eye condition indication by using a machine learning model based on the feedback data.
Dependencies are inferred from the claim text.