MONITORING OPHTHALMIC CONDITIONS USING A HEADSET

1 . A system for monitoring an ophthalmic condition, comprising:

a headset configured to be worn by a user, the headset including a display and an ophthalmic testing unit comprising one or more sensors to obtain sensor information indicating a physiological measurement of an eye of the user; and

a device including a processor configured by instructions stored in memory to:

receive surgical information, from a data structure, corresponding to a first time in which a physiological measurement of the eye is obtained;

receive sensor information, from the headset, corresponding to a second time in which a physiological measurement is obtained; and

generate an ophthalmic score based on a comparison between the surgical information and the sensor information.

2 . The system of claim 1 , wherein the processor is further configured by instructions stored in memory to:

trigger an alert based on the ophthalmic score exceeding a range.

3 . The system of claim 1 , wherein the processor is further configured by instructions stored in memory to:

trigger an alert based on the ophthalmic score, the alert includes outputting a message to at least one of the device or the headset.

4 . The system of claim 1 , wherein the processor is further configured by instructions stored in memory to:

generate a recommendation based on the ophthalmic score.

5 . The system of claim 1 , wherein the device is a mobile device in communication with the headset.

6 . The system of claim 1 , wherein the headset is at least one of a virtual reality (VR), augmented reality (AR), or mixed reality (MR) headset.

7 . The system of claim 1 , wherein the second time occurs after the first time with the ophthalmic score representing a post-surgical evaluation.

8 . The system of claim 1 , wherein the processor is further configured by instructions stored in memory to:

receive updated sensor information from the headset; and

update the ophthalmic score based on the updated sensor information.

9 . The system of claim 1 , wherein the processor is further configured by instructions stored in memory to:

invoke a machine learning model to determine, based on the sensor information, recovery of the eye.

10 . The system of claim 1 , wherein the processor is further configured by instructions stored in memory to:

invoke a machine learning model to determine, based on the sensor information, a symptom of the ophthalmic condition.

11 . The system of claim 1 , wherein the physiological measurement comprises a measure of at least one of visual acuity, drooping eye lids, blink pattern, blood vessels, inflammatory cells, intraocular pressure (IOP), muscle movement, corneal curvature, or pupil response.

12 . The system of claim 1 , wherein the headset exercises the eye before obtaining the sensor information.

13 . The system of claim 1 , wherein the ophthalmic testing unit includes a pupil detector, a beam splitter, and an illuminator.

14 . The system of claim 1 , wherein the ophthalmic testing unit measures blink frequencies, intervals between blinks, and length of blinks.

15 . A method for monitoring an ophthalmic condition, comprising:

receiving surgical information, from a data structure, corresponding to a first time in which a physiological measurement of an eye of a user is obtained;

receiving sensor information, from a headset worn by a user, corresponding to a second time in which a physiological measurement of the eye is obtained, wherein the headset includes a display and an ophthalmic testing unit comprising one or more sensors to obtain the sensor information indicating the physiological measurement of the eye; and

generating an ophthalmic score based on a comparison between the surgical information and the sensor information.

16 . The method of claim 15 , further comprising:

triggering a first alert based on the ophthalmic score falling below a lower threshold and a second alert based on the ophthalmic score exceeding an upper threshold.

17 . The method of claim 15 , further comprising:

receiving, periodically, updated sensor information from the headset; and

updating the ophthalmic score based on the updated sensor information.

18 . The method of claim 15 , further comprising:

invoking a machine learning model to determine, based on the sensor information, a symptom of the ophthalmic condition.

19 . The method of claim 15 , further comprising:

triggering an alert based on the ophthalmic score, wherein the alert includes displaying a message to a device in communication with the headset.

20 . The method of claim 15 , further comprising:

configuring the headset to exercise the eye before obtaining sensor information.