SYSTEMS AND METHODS FOR VIRTUAL REALITY (VR), AUGMENTED REALITY (AR), AND / OR MIXED REALITY (MR) BASED VISUAL FUNCTION ASSESSMENT - Patent application

Abstract

Presented herein are systems and methods for improved virtual reality (VR), augmented reality (AR), and / or mixed reality (MR) based visual function assessment. In various embodiments, the systems and methods described herein utilize eye tracking to display static and / or changing / moving visual stimuli (targets) to a subject and to elicit and record patterns of eye movement to the stimuli, which are correlated with disease or retinal dysfunction. In certain embodiments, the functional vision testing technique automatically performs visibility determinations in real-time during the course of the functional vision test to automatically identify whether the subject is tracking the target in time and space. In some embodiments, the systems and methods align the VR headset optics with the wearer's eyes and / or render a graphical scotoma mask that simulates the effect of a particular patient's scotoma on either the patient's or another individual's visual field.

Description

[Technical field]

[0001] Priority claim This application claims the benefit of U.S. Provisional Patent Application No. 63 / 270,897, filed October 22, 2021, the disclosure of which is incorporated by reference in its entirety herein. [Background technology]

[0002] Current eye-tracking or gaze estimation systems track eye movements to continuously estimate where a subject is looking on a surface or within a volume of space. Head-mounted eye-tracking systems include dedicated camera hardware designed to capture images of one or both of the subject's eyes and a light source (e.g., an infrared illuminator) to illuminate the eyes.

[0003] Eye-tracking systems are primarily used to enhance the player experience in video games by providing an additional element of interactivity. Eye-tracking is not widely used in optometric or ophthalmology practice for functional evaluation of a patient's vision. Current commercially available eye-tracking systems generally lack sensitivity and have poor correlation with retinal anatomy, as is necessary for proper clinical evaluation. For example, current virtual reality (VR) headsets measure the direction of gaze in a headset reference system, independent of the ocular anatomy. Furthermore, the optical quality of VR headsets is limited due to compact lens designs, which introduce aberrations.

[0004] There is a need for improved systems and methods for virtual reality (VR), augmented reality (AR), and / or mixed reality (MR) based visual function assessment. Summary of the Invention

[0005] Presented herein are systems and methods for improved virtual reality (VR), augmented reality (AR), and / or mixed reality (MR) based visual function assessment. In various embodiments, the systems and methods described herein (i) utilize anatomical references to determine the preferred retinal locus (PRL) of the subject's eye, (ii) align the VR headset optics with the wearer's eye, thereby reducing inaccuracies due to aberrations (e.g., chromatic, spherical) near the periphery of the VR headset lens, and / or (iii) render a graphical (e.g., 2D) scotoma mask that simulates the effect of a particular patient's scotoma into the patient's (e.g., the patient's good eye) or another individual's visual field. Furthermore, in various embodiments, the systems and methods described herein utilize eye tracking according to one or more of (i), (ii), and (iii) above to display static and / or changing / moving visual stimuli (targets) to the subject / patient and elicit and record patterns of eye movement in response to the stimuli, which are correlated with disease or retinal dysfunction.

[0006] In some aspects, functional vision tests can be used to diagnose and / or monitor ocular conditions such as geographic atrophy and / or age-related macular degeneration (AMD) (e.g., wet AMD, neovascular AMD, and / or dry AMD). Functional vision tests can provide one or more targets that move and / or change contrast in virtual and / or augmented space. The subject's gaze point can be tracked to determine if it is aligned with one of the targets at any given moment. Time-based parameters can be used to determine if the subject is tracking the target and / or any target to make a visibility determination. Test results (e.g., radial sweep test) can be calculated and / or displayed based on the visibility determination. For example, plots can be generated in contrast sensitivity-spatial frequency space that can be used to diagnose and / or monitor the subject's ocular condition.

[0007] In one aspect, the techniques described herein are used to perform functional vision testing, for example, utilizing a VR / AR / and / or MR device (e.g., headset) (as used below, the term "headset" or "VR headset" refers broadly to head-mounted or face-mounted systems implementing virtual reality, augmented reality, and / or mixed reality functionality). The functional vision testing can include providing one or more targets (e.g., patches, such as contrast-based patches) in a visual and / or augmented scene (e.g., on a virtual chart in the scene). The targets can move over time. A visibility determination can be made to automatically identify whether the subject is tracking one or more targets (e.g., in the scene). The determination can be based, at least in part, on a time-based parameter (e.g., using no other parameters or also using one or more non-time-based parameters). The contrast, spatial location, spatial frequency, and / or direction of movement of the targets can change (e.g., suddenly) throughout the test, for example, upon determining that the subject has been tracking the targets for some time. Test results can be calculated and / or displayed using the visibility determination. The test results may include a metric, such as an area under the curve (AUC) metric, that characterizes the subject's vision. The metric may indicate the presence, severity, and / or progression of the subject's ocular condition.

[0008] In another aspect, the technology described herein utilizes anatomical references to determine the preferred retinal locus (PRL) of the subject's eye via a VR / AR / and / or MR headset with eye tracking capabilities (as used below, the term "headset" or "VR headset" refers broadly to a head-mounted or face-mounted system implementing virtual reality, augmented reality, and / or mixed reality capabilities). For example, in a particular embodiment, two data streams are received, corresponding to gaze direction and gaze origin, respectively. This data can be received from currently existing commercial VR headset systems with gaze tracking capabilities, where the generated data has a headset reference system rather than an anatomical structure reference system of the eye. The gaze origin data (multiple data points) received over time is used to model a sphere or other geometric volume. A stable reference in the anatomical structure of the eye, e.g., the optical axis of the eye in the anatomical structure reference system is then identified, e.g., as a line connecting the center of the modeled sphere and the gaze origin. The PRL relative to the anatomical structure of the retina is then identified using the identified optical axis and gaze direction.

[0009] In yet another aspect, a technique is presented for VR headset adjustment to align the headset optics with the eye, thereby reducing inaccuracies due to aberrations (e.g., chromatic aberration, spherical aberration) near the periphery of the VR headset lens. The optical quality of VR headsets is limited due to compact lens designs (e.g., Fresnel lenses, singlets). Proper headset adjustment to align the headset optics vertically (and / or horizontally) with the eye allows for improved optical quality by reducing or eliminating the effects of aberrations that are generally more common and / or pronounced at the periphery than at the center of the lens. The techniques described herein use eye tracking data to implement a virtual iron sight that provides feedback to the user to adjust headset placement and actively optimize optical alignment.

[0010] In yet another aspect, a technique is presented for rendering a graphic (e.g., 2D) scotoma mask that simulates the effect of a particular patient's scotoma on the visual field. The scotoma mask can simulate the scotoma in its current form or can simulate the estimated appearance of a future scotoma. The technique described herein uses a VR headset with eye-tracking capabilities that provides a gaze data stream. Input is received from a patient suffering from real scotoma and used to define a graphic scotoma mask. The graphic scotoma mask is presented to an individual (which may be the patient or another individual, such as a relative of the patient) as an overlay to a simulated scene (VR) or an actual scene (AR) via a VR headset (the same or a different headset used by the patient to create the mask). The scotoma mask can be used to improve a patient's compliance with treatment, for example, by simulating the effect of future scotoma without treatment, to increase empathy for caregivers who can experience how the patient sees with scotoma through the scotoma mask, and to measure the sensitivity of certain visual function tests during development (e.g., test results of healthy subjects with and without scotoma simulation can be compared).

[0011] In yet another aspect, presented herein is a functional vision testing technique (e.g., optionally using said changing / moving visual stimuli benefiting from one or more of (i), (ii), and (iii) above) that automatically performs visibility determinations using machine learning algorithms in real time during the course of a functional vision test to automatically identify whether a subject is accurately tracking a target in time and space.

[0012] In one aspect, the invention relates to a method for performing a functional vision test (e.g., contrast sensitivity and / or spatial frequency test, e.g., radial sweep test) on a subject using a virtual and / or augmented and / or mixed reality device (e.g., a VR headset with eye tracking capabilities), the method comprising: rendering and displaying to the subject (e.g., on a head mounted display of the VR headset) by a processor of a computing device one or more targets (e.g., two or more, three or more, four or more, or five or more targets) in a virtual and / or augmented scene in the subject's visual field over the course of the functional vision test; automatically performing, by the processor, a visibility determination in real time during the course of the functional vision test to automatically identify whether the subject is tracking (e.g., in time and space) the one or more targets in the virtual and / or augmented scene, the visibility determination being based, at least in part, on time-based parameters; and optionally, calculating and / or displaying test results using the visibility determination.

[0013] In some embodiments, performing the visibility assessment includes determining, by the processor, a subject's point of gaze in real time, and comparing, by the processor, the point of gaze to a current spatial position of one or more targets within the virtual and / or augmented scene using a time-based parameter.

[0014] In some embodiments, performing the visibility determination includes determining, by the processor, in real time, a point of gaze of the subject, and determining, by the processor, whether the point of gaze is aligned with one of the targets in the virtual and / or augmented scene. In some embodiments, performing the visibility determination includes determining, by the processor, in real time, a point of gaze of the subject, and determining, by the processor, using at least one of the time-based parameters, whether the subject is tracking one of the targets in the virtual and / or augmented scene. In some embodiments, the time-based parameters correspond to time periods during which the point of gaze is or is not aligned with one or more of the one or more targets in the virtual and / or augmented scene, respectively.

[0015] In some embodiments, the method includes automatically adjusting (e.g., decreasing) the contrast and / or spatial resolution of one or more of the targets in the virtual and / or augmented scene based on a comparison of the point of gaze to a current spatial location of one or more of the targets in the virtual and / or augmented scene (e.g., based on a determination by the processor that the point of gaze is aligned with one or more of the targets for one (or at least one) predefined threshold time period using one or more of the time-based parameters). In some embodiments, the method includes automatically adjusting (e.g., suddenly) the contrast, spatial location, spatial resolution, and / or direction of movement of one or more targets (e.g., one or more of the one or more targets) in the virtual and / or augmented scene during the test using one or more of the time-based parameters (e.g., lowering the contrast of one of the tracked targets to increase difficulty, suddenly changing the direction of movement of one of the tracked targets to increase difficulty, resetting all targets at high contrast, or stopping the test). In some embodiments, adjusting the contrast, spatial location, spatial resolution, and / or movement direction of the one or more targets includes determining, by the processor, a subject's gaze point in real time and automatically adjusting the contrast and / or spatial resolution of one or more targets (e.g., at least one of the one or more targets) in the virtual and / or augmented scene based at least in part on the subject's gaze point being aligned with the one or more targets according to at least one of the time-based parameters.

[0016] In some embodiments, there are multiple targets displayed in the virtual and / or augmented scene within the subject's field of view, and the time-based parameters include (e.g., consist of) four parameters: (i) a parameter for tracking when the subject's single gaze point (e.g., the gaze point) is on (e.g., aligned with) a particular target among the multiple targets in the virtual and / or augmented scene; (ii) a parameter for tracking when the subject's single gaze point (e.g., the gaze point) is away from (e.g., not aligned with) a particular target among the multiple targets in the virtual and / or augmented scene; (iii) a parameter for tracking when the subject's single gaze point (e.g., the gaze point) is on (e.g., aligned with) any target among the multiple targets in the virtual and / or augmented scene; and (iv) a parameter for tracking when the subject's single gaze point (e.g., the gaze point) is away from (e.g., not aligned with) all of the multiple targets in the virtual and / or augmented scene. In some embodiments, the four parameters account for at least 80% (e.g., at least 90%, e.g., at least 95%, e.g., at least 98%, e.g., 100%) of all significant variables used in the functional visual test (e.g., where the significant variables are those variables that have at least a 5% influence on the outcome of the functional visual test).

[0017] In some embodiments, the time-based parameters are asymmetric (e.g., parameter (i) and parameter (ii) refer to (correspond to) different lengths of time, and / or parameter (iii) and parameter (iv) refer to (correspond to) different lengths of time (e.g., parameter (i) refers to a shorter length of time than parameter (ii) and / or parameter (iii) refers to a shorter length of time than parameter (iv)).

[0018] In some embodiments, (i) at least one of the time-based parameters corresponds to the subject tracking one of the targets (e.g., during which the gaze point is aligned with (e.g., incident on) one of the targets in the virtual and / or augmented scene), (ii) at least one of the time-based parameters corresponds to the subject tracking any of the targets (e.g., during which the gaze point is aligned with (e.g., incident on) any of the targets in the virtual and / or augmented scene), or (iii) both (i) and (ii).

[0019] In some embodiments, the visibility determination is performed using only time-based parameters (i.e., no non-time-based parameters are used to make the visibility determination). In some embodiments, no more than 10 total parameters (e.g., no more than 8 total parameters, no more than 6 total parameters, no more than 5 total parameters, or no more than 4 total parameters) are used to make the visibility determination (e.g., each parameter is a time-based parameter).

[0020] In some embodiments, the one or more targets move and / or change direction of movement within the virtual and / or augmented scene during the functional vision test (e.g., regardless of whether the subject is tracking the target (e.g., as determined by the processor using the subject's point of gaze)). In some embodiments, the one or more targets change contrast within the virtual and / or augmented scene during the functional vision test (e.g., based on determining, in real time, by the processor that the subject is tracking one or more targets) (e.g., changing the contrast and / or spatial resolution of the target only when the subject is tracking the target (e.g., continuously or intermittently) for a predetermined period of time).

[0021] In some embodiments, the functional vision test is a test (e.g., an outcome measure, e.g., a functional endpoint) for one or more ocular conditions selected from the group consisting of diabetic retinopathy (e.g., with or without diabetic macular retinopathy), Stargardt's disease, Leber's hereditary optic neuropathy (LHON), retinitis pigmentosa, glaucoma, inner nuclear layer disease, geographic atrophy, and age-related macular degeneration (AMD) (e.g., intermediate age-related macular degeneration (intermediate AMD), dry age-related macular degeneration (dry AMD), wet age-related macular degeneration (wet AMD), and / or neovascular age-related macular degeneration (neovascular AMD)).

[0022] In some embodiments, the test result is an outcome measure for an ocular condition (e.g., affecting one or both eyes of a subject). In some embodiments, the ocular condition is selected from the group consisting of diabetic retinopathy (e.g., with or without diabetic macular retinopathy), Stargardt's disease, Leber's hereditary optic neuropathy (LHON), retinitis pigmentosa, glaucoma, inner nuclear layer disease, geographic atrophy, and age-related macular degeneration (AMD) (e.g., intermediate age-related macular degeneration (intermediate AMD), dry age-related macular degeneration (dry AMD), wet age-related macular degeneration (wet AMD), and / or neovascular age-related macular degeneration (neovascular AMD)).

[0023] In some embodiments, the test results are indicative of the presence, severity, and / or progression of the subject's ocular condition (e.g., diabetic retinopathy (e.g., with or without diabetic macular retinopathy), Stargardt's disease, Leber's hereditary optic neuropathy (LHON), retinitis pigmentosa, glaucoma, inner nuclear layer disease, geographic atrophy, and age-related macular degeneration (AMD) (e.g., intermediate age-related macular degeneration (intermediate AMD), dry age-related macular degeneration (dry AMD), wet age-related macular degeneration (wet AMD), and / or neovascular age-related macular degeneration (neovascular AMD)).

[0024] In some embodiments, the test results include a metric (e.g., an area under the curve (AUC) metric) that corresponds to the subject's functional vision (e.g., having at least 90% sensitivity at 100% specificity, at least 91% sensitivity at 100% specificity, at least 92% sensitivity at 100% specificity, or at least 92.5% sensitivity at 100% specificity). In some embodiments, the metric is a sparse AUC metric (e.g., when one or more radial sweeps have not been performed and / or are not considered). In some embodiments, the test results include a function of contrast sensitivity (e.g., the inverse of the root mean square (RMS) contrast ratio) and spatial frequency (in cycles per degree, CPD) (e.g., stored as or presented in a plot).

[0025] In some embodiments, each of the one or more targets is a graphically rendered visibility patch (eg, a contrast-based visibility patch) within the virtual and / or augmented scene.

[0026] In some embodiments, the method is performed without the use of artificial intelligence.

[0027] In some embodiments, the method includes simulating, by the processor, a scotoma during functional vision testing (eg, using the methods disclosed herein).

[0028] In one aspect, the invention relates to a packaged pharmaceutical composition or kit comprising a pharma- ceutically acceptable container, a therapeutic agent secured or otherwise sealed within the container, and a label, wherein the therapeutic agent is for an ophthalmic condition (e.g., geographic atrophy and / or age-related macular degeneration (AMD) (e.g., intermediate age-related macular degeneration (intermediate AMD), dry age-related macular degeneration (dry AMD), wet age-related macular degeneration (wet AMD), and / or neovascular age-related macular degeneration (neovascular AMD)), wherein the label comprises a description and / or code identifying that the therapeutic agent is for treatment of an ophthalmic condition, (i) the ophthalmic condition has been diagnosed and / or monitored by a functional vision test performed according to the method of any one of claims 1 to 26, and / or (ii) the efficacy of the therapeutic agent has been established and / or confirmed in a population of subjects (e.g., patients) by a functional vision test performed according to the method of any one of claims 1 to 26.

[0029] In one aspect, the invention relates to a method of treating a subject who has been diagnosed with an ocular condition, who is being or will be monitored for an ocular condition, and / or who has been determined to exhibit worsening severity of an ocular condition (e.g., affecting one or both eyes of the subject) using a functional vision test according to the methods disclosed herein, comprising administering a therapeutically effective amount of a therapeutic agent (e.g., a pharmaceutical compound) to the subject.

[0030] In some embodiments, the ocular condition is selected from the group consisting of diabetic retinopathy (e.g., with or without diabetic macular retinopathy), Stargardt's disease, Leber's hereditary optic neuropathy (LHON), retinitis pigmentosa, glaucoma, inner nuclear layer disease, geographic atrophy, and age-related macular degeneration (AMD) (e.g., intermediate age-related macular degeneration (intermediate AMD), dry age-related macular degeneration (dry AMD), wet age-related macular degeneration (wet AMD), and / or neovascular age-related macular degeneration (neovascular AMD)).

[0031] In some embodiments, the therapeutic agent is an antibody (e.g., a monoclonal antibody) (e.g., an anti-factor D antibody or a vascular endothelial growth factor (VEGF) inhibitor). In some embodiments, the therapeutic agent is a vascular endothelial growth factor (VEGF) inhibitor. In some aspects, the therapeutic agent is ranibizumab, faricimab, brolucizumab, aflibercept, or pegaptanib. In some embodiments, the therapeutic agent includes a vitamin supplement and / or a mineral supplement (e.g., including vitamin C, zinc, vitamin E, copper, or beta-carotene). In some aspects, the therapeutic agent includes a complement inhibitor (e.g., a C3 inhibitor or a C5 inhibitor). In some embodiments, the complement inhibitor includes a peptide, protein, antibody, or aptamer that binds to C3 and / or a biologically active fragment of C3 (e.g., C3b or C3a). In some embodiments, the therapeutic agent is (i) a vitamin and / or mineral supplement selected from the group consisting of vitamin C, zinc, vitamin E, copper, beta-carotene, and combinations thereof, (ii) ranibizumab, (iii) faricimab, (iv) brolucizumab, (v) aflibercept, (vi) pegaptanib, (vii) a complement inhibitor, (viii) a neuroprotective agent, (ix) an anti-inflammatory agent, (x) a free radical scavenger, (xi) an anti-apoptotic agent, (xii) an integrin modulating agent, (xiii) a gene therapy, or (xiv) a cell therapy.

[0032] In one aspect, the present invention relates to a method of determining the therapeutic effectiveness (e.g., benefit) of a therapeutic agent, the method comprising: (i) administering to a subject a functional vision test according to the methods disclosed herein; and (ii) determining the therapeutic effectiveness (e.g., benefit) of the therapeutic agent to the subject based on test results of the functional vision test. In some embodiments, determining the therapeutic effectiveness comprises quantifying quality-adjusted life years (QALYs). In some embodiments, the method comprises determining the cost-effectiveness of the therapeutic agent based at least in part on determining the therapeutic effectiveness based on test results from the functional vision test (e.g., based on quantifying QALYs). In some embodiments, the therapeutic agent is (i) a vitamin and / or mineral supplement selected from the group consisting of vitamin C, zinc, vitamin E, copper, beta-carotene, and combinations thereof, (ii) ranibizumab, (iii) faricimab, (iv) brolucizumab, (v) aflibercept, (vi) pegaptanib, (vii) a complement inhibitor, (viii) a neuroprotective agent, (ix) an anti-inflammatory agent, (x) a free radical scavenger, (xi) an anti-apoptotic agent, (xii) an integrin modulating agent, (xiii) a gene therapy, or (xiv) a cell therapy.

[0033] In one aspect, the present invention relates to the use of (i) a vitamin and / or mineral supplement selected from the group consisting of vitamin C, zinc, vitamin E, copper, beta-carotene and combinations thereof, (ii) ranibizumab, (iii) faricimab, (iv) brolucizumab, (v) aflibercept, (vi) pegaptanib, (vii) a complement inhibitor, (viii) a neuroprotective agent, (ix) an anti-inflammatory agent, (x) a free radical scavenger, (xi) an anti-apoptotic agent, (xii) an integrin modulating agent, (xiii) a gene therapy, or (xiv) a cell therapy, to treat a subject diagnosed with and / or monitored for an ocular condition using the methods disclosed herein.

[0034] In one aspect, the present invention relates to a method for determining the therapeutic efficacy (e.g., benefit) of a therapeutic intervention, comprising: (i) administering a functional vision test according to the methods disclosed herein; and (ii) determining the therapeutic efficacy (e.g., benefit) of the therapeutic intervention (e.g., laser coagulation therapy) to the subject based on the test results of the functional vision test.

[0035] In one aspect, the present invention relates to a method of treating a subject who has been diagnosed with an ocular condition, who has been or will be monitored for an ocular condition, and / or who has been determined to exhibit worsening severity of an ocular condition (e.g., affecting one or both eyes of the subject) using functional vision testing according to the methods disclosed herein, comprising administering a therapeutically effective therapeutic intervention (e.g., laser coagulation therapy) to the subject.

[0036] In one aspect, the invention relates to a method of treating a subject who has been diagnosed with an ocular condition, who has been or will be monitored for an ocular condition, and / or who has been determined to exhibit worsening severity of an ocular condition (e.g., affecting one or both eyes of the subject), comprising administering to the subject a therapeutically effective amount of a therapeutic agent (e.g., a pharmaceutical compound), the efficacy of which has been established or confirmed in a population of subjects using functional vision testing according to the methods disclosed herein. In some embodiments, the ocular condition is selected from the group consisting of diabetic retinopathy (e.g., with or without diabetic macular retinopathy), Stargardt's disease, Leber's hereditary optic neuropathy (LHON), retinitis pigmentosa, glaucoma, inner nuclear layer disease, geographic atrophy, and age-related macular degeneration (AMD) (e.g., intermediate age-related macular degeneration (intermediate AMD), dry age-related macular degeneration (dry AMD), wet age-related macular degeneration (wet AMD), and / or neovascular age-related macular degeneration (neovascular AMD)). In some embodiments, treatment with the therapeutic agent maintains or improves performance on a functional visual test and / or reduces the rate of decline in performance on a functional visual test compared to an appropriate control (e.g., no treatment or sham treatment (e.g., placebo)).

[0037] In one aspect, the invention relates to the use of a therapeutic agent to treat an individual diagnosed with an ocular condition (e.g., geographic atrophy and / or age-related macular degeneration (AMD) (e.g., intermediate age-related macular degeneration (intermediate AMD), dry age-related macular degeneration (dry AMD), wet age-related macular degeneration (wet AMD), and / or neovascular age-related macular degeneration (AMD)), where the therapeutic efficacy of the therapeutic agent has been established or confirmed in a population of subjects using the methods described herein. In some embodiments, the therapeutic agent is (i) a vitamin (ii) ranibizumab, (iii) faricimab, (iv) brolucizumab, (v) aflibercept, (vi) pegaptanib, (vii) complement inhibitors, (viii) neuroprotectants, (ix) anti-inflammatory agents, (x) free radical scavengers, (xi) anti-apoptotic agents, (xii) integrin modulating agents, (xiii) gene therapy, or (xiv) cell therapy.

[0038] In one aspect, the invention relates to a system (e.g., a virtual reality and / or augmented reality and / or mixed reality device (e.g., a VR headset with eye tracking capabilities)) comprising a processor and a memory having instructions stored thereon, the instructions being executable by the processor to perform functional vision testing according to the methods disclosed herein.

[0039] In one aspect, the present invention relates to a method for performing a visual test on a subject using a virtual and / or augmented and / or mixed reality device (e.g., a VR headset with eye tracking capabilities), comprising: rendering and displaying, by a processor, objects in a virtual and / or augmented scene in the subject's field of view via the device (e.g., on a head-mounted display of the VR headset) to the subject, wherein the position of the object remains fixed in the virtual space (e.g., fixed in the virtual and / or augmented scene) when the subject's head turns (e.g., so that the subject can orient the object to a preferred position relative to the subject's gaze point (e.g., a position corresponding to best visual alignment with a region of interest in the object)). In some embodiments, a subject translating the device does not move the object relative to the subject in the virtual space (e.g., the subject cannot move closer to or further away from the object in the virtual space). In some embodiments, the object (e.g., rendered on the head-mounted display of the VR headset) is curved (i.e., not flat) (e.g., a curved test chart) (e.g., to account for reduced peripheral vision due to the quality of one or more lenses of the device). In some embodiments, the object is a virtual test chart (e.g., an eye chart) (e.g., including one or more targets, such as moving targets, for example, for functional vision testing). In some embodiments, the VR headset is a low-cost, off-the-shelf headset.

[0040] In one aspect, the invention provides a system for identifying a preferred retinal trajectory (PRL) (e.g., a location on the retina other than the fovea or macula) relative to a retinal anatomy (e.g., a trajectory in an anatomical structure reference system) for one or both eyes of a subject (e.g., a patient with a macular disease such as macular degeneration, e.g., a patient with central scotoma), comprising: a processor of a computing device; and a memory having stored thereon instructions, which when executed by the processor, cause the processor to receive (e.g., from a VR headset) a first data stream corresponding to a gaze direction of the subject's eye in a headset reference system over time (e.g., independent of actual eye anatomy) (e.g., said gaze direction defines a visual axis), receive (e.g., from the VR headset) a second data stream corresponding to a gaze origin at a nodal point of the subject's eye in the headset reference system over time (e.g., the nodal point corresponds to a center of corneal curvature of the eye), the nodal point moving around the center of rotation of the eye as the eye rotates to change gaze direction, and ... using the data to identify a geometric volume (e.g., a sphere, e.g., a best fit sphere) having a reference point (e.g., a center) corresponding to a center of rotation of the eye and having a surface approximated by nodes, identifying an anatomical reference (e.g., the optical axis of the eye) from the identified geometric volume (e.g., the sphere, e.g., the best fit sphere) (e.g., identifying the optical axis of the eye as a line connecting the center of the sphere and the gaze origin), and using the identified anatomical reference (e.g., the optical axis of the eye) and data from the first data stream to calculate a retinal anatomy (e.g., a trajectory in an anatomical reference system). a preferred retinal trajectory (PRL) relative to the subject's retinal track (e.g., using data from the first data stream to calculate a horizontal angle φ and / or a vertical angle θ between an optical axis and the visual axis of the eye, and using the determined optical axis of the eye and the calculated horizontal angle φ and / or vertical angle θ to determine the PRL) (e.g., and monitoring the PRL (e.g., angles φ, θ) in multiple sessions with the subject over time (e.g., over months or years), e.g., as the disease progresses, to detect PRL changes).

[0041] In certain embodiments, the system includes a virtual reality and / or augmented reality and / or mixed reality headset for generating the first data stream and the second data stream. In certain embodiments, the system includes an eye-tracking camera (e.g., the headset includes the eye-tracking camera). In certain embodiments, the system includes an illumination source (e.g., an infrared illumination source) for illuminating one or both eyes of the subject (e.g., the headset includes the illumination source).

[0042] In certain embodiments, a virtual reality and / or augmented reality and / or mixed reality headset comprises one or more members selected from the group consisting of a head mounted display, one or more lenses, one or more headset processors for generating the first data stream and / or the second data stream (e.g., a processor of a computing device executing instructions is any one or more of: (i) part or all of the one or more headset processors, (ii) distinct from the one or more headset processors, (iii) at least partially co-located with the one or more headset processors, (iv) spatially separated (remote) from the one or more headset processors, and (v) in electrical and / or data communication with the one or more headset processors), one or more mechanisms (e.g., dials, toggles, knobs, or switches) for physically adjusting a position of a display in the headset, one or more mechanisms (e.g., mechanical mechanisms, such as knobs, straps, dials, etc.) for adjusting (e.g., manually adjusting) a horizontal and / or vertical position of the headset relative to the subject's head, a circuit board, and a head support (e.g., straps, mounts, braces, and / or other physical structures for stabilizing the headset on the subject's head).

[0043] In certain embodiments, the instructions, when executed by the processor, cause the processor to display visual stimuli (e.g., one or more static and / or changing / moving graphical targets) to the subject, elicit and record a pattern of eye movement in response to the stimuli using the determined PRL, and correlate the recorded pattern of eye movement with a disease or condition (e.g., retinal dysfunction). In certain embodiments, the instructions, when executed by the processor, cause the processor to identify that the subject may have the disease or condition based at least in part on the pattern of recorded eye movement (e.g., the instructions, when executed by the processor, cause the processor to present a graphical display (e.g., alphanumeric characters) indicating that the subject may have the disease or condition).

[0044] In another aspect, the invention provides a system for facilitating adjustment (e.g., physical adjustment, e.g., manual adjustment by the wearer) of a position of a virtual reality and / or augmented reality and / or mixed reality headset relative to a wearer's head (e.g., to improve / optimize alignment of centers of headset lenses with centers of the wearer's eyes), the system comprising: a virtual reality and / or augmented reality and / or mixed reality headset with one or more mechanisms (e.g., mechanical mechanisms, e.g., knobs, straps, dials, etc.) for adjusting (e.g., manually adjusting) a vertical position of the headset relative to the wearer's head; a processor of a computing device; and a memory having instructions stored thereon, which, when executed by the processor, cause the processor to generate a first data stream corresponding to a position of the wearer's eyes relative to the headset over time (e.g., the first data stream corresponds to a gaze origin at a nodal point of (each of) the wearer's eyes, each of said nodal points corresponding to a center of corneal curvature of the (respective) eye) (e.g., a position of the center of the wearer's eyes relative to the center of one or both respective headset lenses). receiving a virtual camera position (position) linked to a position of the wearer's eye relative to the headset, rendering and displaying virtual iron sights within a real-time (or near real-time) field of view of the headset wearer corresponding to the real-time (or near real-time) position of the virtual camera as the first data stream is received, the iron sights including two concentric rings having fixed positions relative to one another and a third ring having a contrasting color and / or tint relative to the two concentric rings, the third ring having a visually detectable offset relative to the two concentric rings when a center of one or both respective headset lenses is misaligned with a gaze origin (center of corneal curvature) of a respective eye of the wearer, the offset of the third ring relative to the two concentric rings as seen by the wearer within the field of view of the headset prompting (e.g., by the wearer) a physical adjustment of a vertical position of the headset via one or more (e.g., mechanical) mechanisms until said adjustment aligns a center of one or both respective headset lenses with the gaze origin of a respective eye of the wearer;The resulting position of the virtual camera causes the third ring to be fully displayed between the two concentric rings. In certain embodiments, a virtual reality and / or augmented reality and / or mixed reality headset generates the first data stream. In certain embodiments, the system includes an eye-tracking camera (e.g., the headset includes the eye-tracking camera). In certain embodiments, the system includes an illumination source (e.g., an infrared illumination source) for illuminating one or both eyes of the wearer (e.g., the headset includes the illumination source).

[0045] In certain embodiments, a virtual reality and / or augmented reality and / or mixed reality headset comprises one or more members selected from the group consisting of a head mounted display, one or more lenses, one or more mechanisms (e.g., dials, toggles, knobs, or switches) for physically adjusting the position of the display within the headset, a circuit board, and a head support (e.g., straps, mounts, braces, and / or other physical structures for stabilizing the headset on the subject's head).

[0046] In certain embodiments, the instructions, when executed by the processor, cause the processor to display visual stimuli (e.g., one or more static and / or changing / moving graphical targets) to the subject in accordance with the adjustment to align a center of one or both respective headset lenses with the gaze origin of the wearer's respective eye, elicit and record a pattern of eye movement in response to the stimuli, and correlate the recorded pattern of eye movement with a disease or condition (e.g., retinal dysfunction). In certain embodiments, the instructions, when executed by the processor, cause the processor to identify that the subject may have the disease or condition based at least in part on the pattern of recorded eye movement (e.g., the instructions, when executed by the processor, cause the processor to present a graphical display (e.g., alphanumeric characters) indicating that the subject may have the disease or condition).

[0047] In another aspect, the invention provides a system for rendering a graphical (e.g., 2D) scotoma mask simulating the effect of a scotoma on a visual field, said scotoma being afflicted by a particular patient, the system comprising a processor of a computing device and a memory having stored thereon instructions, which when executed by the processor, cause the processor to generate a shape of the simulated scotoma (e.g., a selected default scotoma shape, such as a disk, or a personalized scotoma shape derived from microperimetry of the subject, e.g., Differential light sensitivity (Differential light sensitivity)). receiving input (e.g., from a particular patient suffering from an actual scotoma) to identify one or more visual effect parameters corresponding to values ​​of visual effects caused by a scotoma (e.g., the one or more parameters include one or more elements selected from the group consisting of opacity, saturation, blur, and distortion (e.g., pincushion, barrel, or vortex)); defining a graphical scotoma mask according to the shape of the simulated scotoma and the one or more visual effect parameters; receiving (e.g., from a VR headset) a first data stream corresponding to a point of gaze of a wearer of the VR headset; rendering and displaying in real time (or near real time) to a wearer of the VR headset a virtual and / or augmented scene within the wearer's field of vision, at least a portion of the virtual and / or augmented scene being modified according to the graphical scotoma mask, and the virtual and / or augmented scene tracking the wearer's point of gaze as the point of gaze changes in real time and as the virtual and / or augmented scene is affected by the simulated scotoma (e.g., the wearer may be the patient or the wearer may be a different individual than the patient).

[0048] In certain embodiments, the instructions cause the processor to identify one or more visual effect parameters from a patient by: (i) blocking vision in the patient's healthy eye over a first time period; (ii) displaying a virtual scene to the patient's scotoma-affected eye or enabling observation of an actual visual field by the patient's scotoma-affected eye, the patient having a unilateral scotoma; and (iii) rendering and displaying (e.g., via a VR headset) a virtual and / or augmented scene to only the patient's (one) healthy eye over a second time period, the virtual and / or augmented scene being modified according to a graphical scotoma mask corresponding to a given shape and one or more adjustable visual effect parameters, updating the virtual and / or augmented scene according to feedback from the patient such that the patient can compare the patient's visual field in each eye and adjust the one or more visual effect parameters (and / or scotoma shape) to match the visual field seen by the eye with the actual scotoma with the visual field seen by the eye with the simulated scotoma; and (iv) rendering and displaying (e.g., via a VR headset) the updated virtual and / or augmented scene to the patient's healthy eye in real time (or near real time).

[0049] In certain embodiments, the system includes a virtual reality and / or augmented reality and / or mixed reality headset that generates the first data stream.

[0050] In certain embodiments, the system includes an eye-tracking camera (eg, a headset includes an eye-tracking camera).

[0051] In certain embodiments, the system includes an illumination source (eg, an infrared illumination source) for illuminating one or both of the patient's eyes (eg, a headset includes the illumination source).

[0052] In certain embodiments, the system includes a virtual reality and / or augmented reality and / or mixed reality headset that includes one or more members selected from the group consisting of a head mounted display, one or more lenses, one or more mechanisms (e.g., dials, toggles, knobs, or switches) for physically adjusting the position of the display within the headset, one or more mechanisms (e.g., mechanical mechanisms, such as knobs, straps, dials, etc.) for adjusting (e.g., manually adjusting) the horizontal and / or vertical position of the headset relative to the subject's head, a circuit board, and a head support (e.g., straps, mounts, braces, and / or other physical structures for stabilizing the headset on the subject's head).

[0053] In certain embodiments, the instructions, when executed by the processor, cause the processor to display visual stimuli (e.g., one or more static and / or changing / moving graphical targets) to the subject, elicit and record eye movement patterns in response to the stimuli, and correlate the recorded eye movement patterns with a disease or condition (e.g., retinal dysfunction). In certain embodiments, the instructions, when executed by the processor, cause the processor to identify that the wearer may have (or may be at risk for) the disease or condition based at least in part on the recorded eye movement patterns (e.g., the instructions, when executed by the processor, cause the processor to present a graphical display (e.g., alphanumeric characters) indicating that the wearer may have (or may be at risk for) the disease or condition).

[0054] In another aspect, the invention provides a method of identifying a preferred retinal trajectory (PRL) (e.g., a trajectory in an anatomical structure reference system) relative to a retinal anatomy (e.g., a preferred retinal trajectory is a location on the retina other than the fovea or macula) for one or both eyes of a subject (e.g., a patient with a macular disease such as macular degeneration, e.g., a patient with central scotoma), comprising: receiving, by a processor of a computing device, a first data stream (e.g., from a VR headset) corresponding to a gaze direction of the subject's eye in a headset reference system over time (e.g., independent of actual eye anatomy) (e.g., said gaze direction defines a visual axis); receiving, by the processor, a second data stream (e.g., from the VR headset) corresponding to a gaze origin at a nodal point of the subject's eye in the headset reference system over time (e.g., said nodal point corresponds to a center of corneal curvature of the eye), where the nodal point moves around a center of rotation of the eye as the eye rotates to change gaze direction; and receiving, by the processor, a second data stream (e.g., from the VR headset) corresponding to a gaze origin at a nodal point of the subject's eye in the headset reference system over time (e.g., said nodal point corresponds to a center of corneal curvature of the eye), where the nodal point moves around a center of rotation of the eye as the eye rotates to change gaze direction; identifying a geometric volume (e.g., a sphere, e.g., a best fit sphere) having a reference point (e.g., a center) that corresponds to the retinal anatomical structure and having a surface that is approximated by nodes; identifying, by a processor, an anatomical reference (e.g., an optical axis of the eye) from the identified geometric volume (e.g., a sphere, e.g., a best fit sphere) (e.g., identifying the optical axis of the eye as a line connecting the center of the sphere and the gaze origin); and calculating a preferred retinal locus (PRL) (e.g., a line connecting the center of the sphere and the gaze origin) for the retinal anatomy using the identified anatomical reference (e.g., the optical axis of the eye) and data from the first data stream. , a trajectory in an anatomical reference system (e.g., using data from the first data stream to calculate a horizontal angle φ and / or a vertical angle θ between an optical axis and a visual axis of the eye, and determining the PRL using the determined optical axis of the eye and the calculated horizontal angle φ and / or vertical angle θ) (e.g., and monitoring the PRL (e.g., angles φ, θ) in multiple sessions with the subject over time (e.g., over months or years), e.g., as the disease progresses, to detect PRL changes).

[0055] In certain embodiments, the method includes displaying visual stimuli (e.g., one or more static and / or changing / moving graphical targets) to the subject and eliciting and recording (e.g., by a processor) a pattern of eye movement in response to the stimuli using the determined PRL, where the recorded pattern of eye movement is correlated with a disease or condition (e.g., retinal dysfunction). In certain embodiments, the method includes identifying, by a processor, the subject as having the disease or condition (e.g., or alternatively, identifying a subject as at risk for a disease or condition) based at least in part on the pattern of recorded eye movement (e.g., by a processor presenting a graphical representation (e.g., alphanumeric characters) indicating that the subject has (e.g., or alternatively may have) the disease or condition).

[0056] In another aspect, the invention provides a method for facilitating adjustment (e.g., physical adjustment, e.g., manual adjustment by the wearer) of a position of a virtual reality and / or augmented reality and / or mixed reality headset relative to a wearer's head (e.g., to improve / optimize alignment between centers of headset lenses and centers of the wearer's (respective) eyes), comprising: receiving, by a processor of a computing device, a first data stream corresponding to a position of the wearer's eyes relative to the headset over time (e.g., the first data stream corresponds to a gaze origin at a nodal point of (each of) the wearer's eyes, each of said nodal points corresponding to a center of corneal curvature of the (respective) eye) (e.g., a position of the center of the wearer's eye or eyes relative to a center of one or both respective headset lenses), wherein a position of a virtual camera is linked to the position of the wearer's eyes relative to the headset, and the headset comprises one or more mechanisms (e.g., mechanical mechanisms, e.g., knobs, straps, dials, etc.) for adjusting (e.g., manual adjustment) a vertical position of the headset relative to the wearer's head; and rendering and displaying virtual iron sights within the field of view of the headset wearer in real time (or near real time) corresponding to the real time (or near real time) position of the virtual camera as the ream is received, the iron sights including two concentric rings having fixed positions relative to one another and a third ring having a contrasting color and / or tint relative to the two concentric rings, the third ring having a visually detectable offset relative to the two concentric rings when a center of one or both respective headset lenses is misaligned with the gaze origin (center of corneal curvature) of the wearer's respective eye, the offset of the third ring relative to the two concentric rings as seen by the wearer within the field of view of the headset prompting a physical adjustment (e.g., by the wearer) of a vertical position of the headset via one or more (e.g., mechanical) mechanisms until the adjustment aligns the center of one or both respective headset lenses with the gaze origin of the wearer's respective eye, and the resulting position of the virtual camera causes the third ring to be fully displayed between the two concentric rings.Regarding the method,

[0057] In certain embodiments, the method includes checking virtual iron sight alignment during a visual function test.

[0058] In certain embodiments, following the adjustment to align a center of one or both of the respective headset lenses with the gaze origin of the wearer's respective eye, the method includes displaying (e.g., by a processor) a visual stimulus (e.g., one or more static and / or changing / moving graphical targets) to the wearer to elicit and record a pattern of eye movement in response to the stimuli, the recorded pattern of eye movement being correlated with a disease or condition (e.g., retinal dysfunction). In certain embodiments, the method includes identifying, by a processor, that the wearer has (or may have) the disease or condition based at least in part on the pattern of recorded eye movement (e.g., and presenting a graphical indication (e.g., alphanumeric characters) indicating that the wearer has (or may have) the disease or condition).

[0059] In another aspect, the invention provides a method for rendering a graphical (e.g., 2D) scotoma mask simulating the effect of a scotoma on a visual field, said scotoma being afflicted by a particular patient, the method comprising: receiving, by a processor of a computing device, data corresponding to a shape of the simulated scotoma (e.g., a selected default scotoma shape, such as a disk, or a personalized scotoma shape derived from microperimetry of the subject, e.g., a differential light sensitivity (DLS) map); and receiving, by the processor, an input (e.g., from the particular patient afflicted with an actual scotoma) for specifying one or more visual effect parameters corresponding to a value of the visual effect caused by the scotoma (e.g., said one or more parameters include one or more elements selected from the group consisting of opacity, saturation, blurriness, and distortion (e.g., pincushion, barrel, or vortex)). defining, by a processor, a graphical scotoma mask according to a shape of the simulated scotoma and one or more visual effect parameters; receiving, by the processor, a first data stream (e.g., from the VR headset) corresponding to a point of gaze of a wearer of the VR headset; and rendering and displaying in real time (or near real time) a virtual and / or augmented scene within the wearer's field of view to a wearer of the VR headset, wherein at least a portion of the virtual and / or augmented scene is modified according to the graphical scotoma mask such that the virtual and / or augmented scene tracks the wearer's point of gaze as the point of gaze changes in real time and as the virtual and / or augmented scene is affected by the simulated scotoma (e.g., the wearer may be the patient or the wearer may be a different individual than the patient).

[0060] In certain embodiments, the method includes identifying, by a processor, one or more visual effect parameters from a patient input by: (i) blocking vision in the patient's healthy eye over a first time period; (ii) displaying a virtual scene to the patient's scotoma-affected eye or enabling observation of an actual visual field by the patient's scotoma-affected eye, the patient having a unilateral scotoma; and (ii) rendering and displaying a virtual and / or augmented scene (e.g., via a VR headset) to only the patient's (one) healthy eye over a second time period, the virtual and / or augmented scene being modified according to a graphical scotoma mask corresponding to a given shape and one or more adjustable visual effect parameters, updating the virtual and / or augmented scene according to feedback from the patient such that the patient can compare the patient's visual field in each eye and adjust the one or more visual effect parameters (and / or scotoma shape) to match the visual field seen by the eye with the actual scotoma with the visual field seen by the eye having the simulated scotoma; and (iii) rendering and displaying the updated virtual and / or augmented scene to the patient's healthy eye in real time (or near real time).

[0061] In certain embodiments, the method includes displaying (e.g., by a processor) a visual stimulus (e.g., one or more static and / or changing / moving graphical targets) to the wearer to elicit and record a pattern of eye movement in response to the stimuli, and the recorded pattern of eye movement is correlated with a disease or condition (e.g., retinal dysfunction). In certain embodiments, the method includes identifying, by a processor, that the wearer may have (or may be at risk for) the disease or condition (e.g., and presenting a graphical representation (e.g., alphanumeric characters) indicating that the wearer may have (or may be at risk for) the disease or condition) based at least in part on the recorded pattern of eye movement.

[0062] In another aspect, the invention is a system for administering a functional vision test (e.g., contrast sensitivity and / or spatial frequency test, e.g., radial sweep test) to a subject using a virtual reality and / or augmented reality and / or mixed reality device (e.g., a VR headset with eye tracking capabilities), comprising a processor of a computing device and a memory having instructions stored thereon, the instructions, when executed by the processor, causing the processor to: For example, the sweeps all start with a target at a common origin and then radiate outward along a vector in contrast sensitivity function (CSF) space until a functional limit is reached, at which point the invisibility of the target prevents further tracking by the subject and a threshold is recorded) is rendered and displayed to the subject (e.g., via a VR headset), and during the course of a functional vision test, visibility determinations are automatically performed in real time using machine learning algorithms to automatically identify whether the subject is accurately tracking the target in time and space, and the visibility determinations are used to calculate and / or display test results.

[0063] In certain embodiments, the test results include plots of contrast sensitivity (eg, inverse root mean square (RMS) contrast ratio) and spatial frequency (cycles per degree, CPD).

[0064] In certain embodiments, a machine learning algorithm (e.g., the machine learning algorithm includes one or more recombinant neural networks, and / or long-term short-term memory, and / or one or more temporal convolutional networks) is pre-trained from user trials using ground truth established by manual evaluation of video recordings of users who determined whether the subject's eye positions were within individual targets (e.g., culled from hundreds of minutes of observation and annotation).

[0065] In certain embodiments, the machine learning algorithm determines the probability that the subject is (or is not) observing a target (e.g., multiple targets, e.g., 3 or more targets, e.g., individual targets in a visual field of 5 targets) during the course of a functional vision test, for a given time window (e.g., in milliseconds, e.g., <250 ms, <100 ms, <50 ms, <25 ms, etc.), and the appearance of the target presented to the subject is modified (e.g., contrast values ​​and / or spatial frequency values) at least once during the course of the functional vision test upon determining that the subject is (likely) observing a target (e.g., once the algorithm determines that the subject is no longer tracking the target, the modification of the target's appearance is stopped and the final values ​​of contrast and spatial frequency are recorded as the subject's visual / functional threshold for that parameter space, e.g., at which point a new target is presented and the process is repeated, e.g., a new sweep is performed).

[0066] In certain embodiments, the instructions, when executed by the processor, cause the processor to adjust (e.g., during the course of a functional vision test) one or more threshold parameters (e.g., the one or more threshold parameters include one or both of (i) a tolerance for how close or far the subject's actual eye position is from a target, e.g., a center of a circular target, and (ii) a time window for determining visibility using a machine learning algorithm).

[0067] In another aspect, the invention relates to a method for performing a functional vision test (e.g., contrast sensitivity and / or spatial frequency test, e.g., radial sweep test) on a subject using a virtual reality and / or augmented reality and / or mixed reality device (e.g., a VR headset with eye tracking capabilities), the method comprising: rendering and displaying, by a processor of a computing device, to the subject (e.g., via the VR headset) a target (e.g., a moving target, e.g., a target whose spatial frequency and contrast varies in discrete intervals, e.g., along multiple sweep trajectories, e.g., the sweeps all start from the target at a common origin and then radiate outward along a vector in contrast sensitivity function (CSF) space until a functional limit is reached, at which point invisibility of the target prevents further tracking by the subject and a threshold is recorded) over the course of the functional vision test; automatically performing, by the processor, visibility determinations in real time using machine learning algorithms to automatically identify whether the subject is accurately tracking the target in time and space during the course of the functional vision test; and calculating and / or displaying test results using the visibility determinations by the processor.

[0068] In certain embodiments, the test results include plots of contrast sensitivity (eg, inverse root mean square (RMS) contrast ratio) and spatial frequency (cycles per degree, CPD).

[0069] In certain embodiments, a machine learning algorithm (e.g., the machine learning algorithm comprises one or more recombination neural networks, and / or long-term short-term memory, and / or one or more temporal convolutional networks) is pre-trained from user trials using ground truth established by manual evaluation of video recordings of users who determined whether the subject's eye positions were within individual targets (e.g., culled from hundreds of minutes of observation and annotation).

[0070] In certain embodiments, the machine learning algorithm determines the probability that the subject is (or is not) observing a target (e.g., multiple targets, e.g., 3 or more targets, e.g., individual targets in a visual field of 5 targets) during the course of a functional vision test, for a given time window (e.g., in milliseconds, e.g., <250 ms, <100 ms, <50 ms, <25 ms, etc.), and the appearance of the target presented to the subject is modified (e.g., contrast values ​​and / or spatial frequency values) at least once during the course of the functional vision test upon determining that the subject is (likely) observing a target (e.g., once the algorithm determines that the subject is no longer tracking the target, the modification of the target's appearance is stopped and the final values ​​of contrast and spatial frequency are recorded as the subject's visual / functional threshold for that parameter space, e.g., at which point a new target is presented and the process is repeated, e.g., a new sweep is performed).

[0071] In certain embodiments, the method includes adjusting, by the processor (e.g., during the course of a functional vision test), one or more threshold parameters (e.g., the one or more threshold parameters include one or both of (i) a tolerance for how close or far the subject's actual eye position is from a target, e.g., a center of a circular target, and (ii) a time window for determining visibility using a machine learning algorithm).

[0072] In certain embodiments, the method includes features of any of the other methods described herein.

[0073] Any two or more of the features described herein, including in this Summary section, whether or not specifically and explicitly described in separate combinations herein, may be combined to form implementations of the present disclosure.

[0074] At least some of the methods, systems, and techniques described herein may be controlled by executing instructions stored on one or more non-transitory machine-readable storage media on one or more processing devices. Examples of non-transitory machine-readable storage media include read-only memory, optical disk drives, memory disk drives, and random access memories. At least some of the methods, systems, and techniques described herein may be controlled using a computing system consisting of one or more processing devices and a memory that stores instructions executable by the one or more processing devices to perform various control operations.

[0075] definition In order that this disclosure may be more readily understood, certain terms used herein are defined below. Additional definitions for the following terms, as well as other terms, may be found throughout the specification.

[0076] Therapeutic Agent: As used herein, the phrase "therapeutic agent" generally refers to any agent that induces a desired pharmacological effect when administered to an organism. In some aspects, an agent is considered to be a therapeutic agent if it exhibits a statistically significant effect across an appropriate population. In some embodiments, the appropriate population may be a population of model organisms. In some embodiments, the appropriate population may be defined by various criteria, such as a particular age group, sex, genetic background, pre-existing clinical conditions, etc. In some embodiments, a therapeutic agent is a substance that can be used to alleviate, ameliorate, mitigate, inhibit, prevent, delay onset, reduce severity, and / or reduce incidence of one or more symptoms or characteristics of a disease, disorder, and / or condition. In some embodiments, a "therapeutic agent" is a drug that has been approved, or needs to be approved, by a government agency before it can be commercially marketed for administration to humans. In some embodiments, a "therapeutic agent" is a drug that requires a medical prescription for administration to humans.

[0077] Therapeutically effective: As used herein, a therapeutically effective substance [e.g., a therapeutic agent (e.g., a pharmaceutical compound, e.g., a pharmaceutical agent)] is a substance that produces a desired effect for which it is administered. In some embodiments, the term refers to an amount sufficient to treat a disease, disorder, and / or condition when administered to a population suffering from or susceptible to the disease, disorder, and / or condition according to a therapeutic dosing regimen. In some embodiments, a therapeutically effective substance is a substance that, when administered in an appropriate amount, reduces the incidence and / or severity and / or delays the onset of one or more symptoms of a disease, disorder, and / or condition. Those skilled in the art will appreciate that the term "therapeutically effective" does not require that a treatment is actually successful in a particular individual. Rather, a therapeutically effective amount may be an amount that, when administered to a patient in need of such treatment, provides a particular desired pharmacological response in a significant number of subjects. In some embodiments, reference to a therapeutically effective amount may be a reference to an amount measured in one or more specific tissues (e.g., tissues affected by a disease, disorder, or condition) or bodily fluids (e.g., blood, saliva, serum, sweat, tears, urine, etc.). One of skill in the art will appreciate that in some embodiments, a therapeutically effective amount of a particular agent or treatment may be formulated and / or administered in a single dose, in some embodiments, a therapeutically effective agent may be formulated and / or administered in multiple doses, for example, as part of a dosing regimen.

[0078] Treatment: As used herein, the term "treatment" (also "treat" or "treating") refers to any administration of a therapeutic compound or a therapeutic procedure (e.g., surgical intervention) that results in partial or complete alleviation, amelioration, relief, inhibition, delay in onset, reduction in severity, and / or reduction in incidence of one or more symptoms, characteristics, and / or causes of a particular condition (e.g., disease or disorder). In some embodiments, such treatment may be treatment of a subject who does not show signs of the relevant condition (e.g., disease or disorder) and / or a subject who shows only early signs of the condition (e.g., disease or disorder). Alternatively, or in addition, such treatment may be treatment of a subject who shows one or more established signs of the relevant condition (e.g., disease or disorder). In some embodiments, the treatment may be treatment of a subject who has been diagnosed as suffering from the relevant condition (e.g., disease or disorder). In some embodiments, the treatment may be treatment of a subject who is known to have one or more susceptibility factors that are statistically correlated with an increased risk of developing the relevant condition (e.g., disease or disorder).

[0079] Subject: As used herein, a "subject" is a human. In some embodiments, the subject is afflicted or may be afflicted with, for example, an ocular related condition (e.g., a disease or disorder) (e.g., one or both eyes). In some embodiments, the subject is susceptible to a condition (e.g., a disease or disorder), such as an ocular condition. In some embodiments, the subject exhibits one or more symptoms or characteristics of a condition (e.g., a disease or disorder). In some embodiments, the subject does not exhibit a symptom or characteristic of a symptom (e.g., a disease or disorder). In some embodiments, the subject is a person having one or more characteristics characteristic of a susceptibility to or risk for a condition (e.g., a disease or disorder). In some embodiments, the subject is a patient. In some embodiments, the subject is an individual to whom, who may be administered, and / or who has been administered a diagnostic and / or therapeutic agent. The subject may be diagnosed with an ocular condition and / or monitored for an ocular condition. The subject's ocular condition can be monitored. The ocular condition can affect one or both eyes of the subject. In some embodiments, the condition is an ocular condition, such as diabetic retinopathy (e.g., with or without diabetic macular retinopathy), Stargardt's disease, Leber's hereditary optic neuropathy (LHON), retinitis pigmentosa, glaucoma, inner nuclear layer disease, geographic atrophy, and age-related macular degeneration (AMD) (e.g., intermediate age-related macular degeneration (intermediate AMD), dry age-related macular degeneration (dry AMD), wet age-related macular degeneration (wet AMD), and / or neovascular age-related macular degeneration (neovascular AMD)). Other ocular conditions that affect vision (e.g., functional vision) are known in the art.

[0080] Administration: As used herein, the term "administration" typically refers to administration of a composition to a subject or system. Those skilled in the art will recognize various routes that may be utilized for administration to a subject, e.g., a human, in the appropriate circumstances. For example, in some embodiments, administration may be ocular, oral, intravenous, parenteral, etc. In some embodiments, administration may include administration that is intermittent (e.g., multiple doses separated in time) and / or periodic (e.g., individual doses separated by a common period of time) administration. In some embodiments, administration may include continuous administration (e.g., perfusion) for at least a selected period of time. [Brief description of the drawings]

[0081] The foregoing and other objects, aspects, features, and advantages of the present disclosure will become more apparent and may be better understood by referring to the following description in conjunction with the accompanying drawings.

[0082] [Figure 1A] 1 is a schematic diagram of a system and method for identifying a preferred retinal trajectory (PRL) relative to a retinal anatomy using a VR headset, according to an exemplary embodiment. [Figure 1B] 1 is a schematic diagram of a system and method for identifying a preferred retinal trajectory (PRL) relative to a retinal anatomy using a VR headset, according to an exemplary embodiment. [Diagram 2] FIG. 1 is a block flow diagram of an exemplary method for determining PRL using a VR headset system, according to an exemplary embodiment. [Figure 3A] An image of the view through a VR headset lens with more pronounced aberrations at the periphery than at the center. [Figure 3B] An image of the view through a VR headset lens with more pronounced aberrations at the periphery than at the center. [Figure 4]FIG. 1 is a block flow diagram of an exemplary method for prompting adjustment of the vertical position of a VR headset to align the centers of one or both of a wearer's eyes with the centers of one or both of a respective VR headset lenses, according to an illustrative embodiment. [Diagram 5] 1 is a schematic diagram illustrating a virtual iron sight used in a method for prompting adjustment of a VR headset to vertically align the eyes and lenses in accordance with an exemplary embodiment. [Figure 6] 1 is a fundus image of a central scotoma of a patient (left) and overlaid differential light sensitivity (DLS) values ​​for use in a system for rendering a graphical scotoma mask according to an exemplary embodiment. [Figure 7] 1 is an image of a scotoma mask overlaid on newsprint to simulate how a patient suffering from scotoma sees newsprint, according to an exemplary embodiment. [Figure 8A] FIG. 1 is a block flow diagram of a method for creating a scotoma mask using input from a patient wearing a VR headset with eye tracking capabilities, according to an exemplary embodiment. In this block diagram, "unilateral" scotoma refers to a scotoma in one eye, with vision in the fellow eye intact. In this flow, the scotoma is present in the right eye, while the left eye is "healthy" and is used as a control for comparison. [Figure 8B] FIG. 8B is a block flow diagram of a method for rendering a dark point mask created via the method of FIG. 8A according to an exemplary embodiment. [Figure 9A] FIG. 1 is a schematic diagram illustrating components of a VR headset with eye-tracking capabilities for use with the systems and methods described herein, according to an exemplary embodiment. [Figure 9B] FIG. 1 is a schematic diagram illustrating components of a VR headset with eye-tracking capabilities for use with the systems and methods described herein, according to an exemplary embodiment. [Figure 9C] FIG. 1 is a schematic diagram illustrating components of a VR headset with eye-tracking capabilities for use with the systems and methods described herein, according to an exemplary embodiment. [Figure 10] 1 is a block flow diagram of a method for identifying a preferred retinal trajectory (PRL) for a retinal anatomical structure according to an exemplary embodiment. [Figure 11] FIG. 1 is a block flow diagram of a method for prompting adjustment of a VR headset position relative to a wearer's head to improve / optimize alignment between the centers of the VR headset lenses and the centers of each of the wearer's eyes, according to an exemplary embodiment. [Figure 12] FIG. 1 is a block flow diagram of a method for rendering a graphical scotoma mask to simulate the effect of a scotoma on a visual field according to an exemplary embodiment. [Figure 13] FIG. 1 is a block diagram of an exemplary cloud computing environment, according to an exemplary embodiment. [Figure 14] FIG. 5 is a schematic diagram illustrating an example of a computing device 500 and a mobile computing device 550 that can be used to perform the methods described herein and / or that can be used in the systems described herein, according to an exemplary embodiment. [Figure 15A] FIG. 1 is a schematic diagram of a neural network implementation for AI-assisted radial sweep functional vision testing including visibility determination to automatically determine whether a subject is looking at a target, according to an exemplary embodiment. [Figure 15B] FIG. 1 is a schematic diagram of a neural network implementation for AI-assisted radial sweep functional vision testing including visibility determination to automatically determine whether a subject is looking at a target, according to an exemplary embodiment. [Figure 16] 1A-1D are graphs showing patch visibility probability (top panel), patch prediction (middle panel), and global visibility (bottom panel) after applying a prediction threshold in an AI-assisted radial sweep functional vision test, according to an exemplary embodiment. [Figure 17]1 is a graph showing the results of using Long Short-Term Memory (LSTM) and Temporal Convolutional Network (TCN) as machine learning algorithm architectures (e.g., 1D convolutional network architectures) in an AI-assisted radial sweep functional vision test, according to an exemplary embodiment. [Figure 18A] FIG. 2 is a schematic diagram of an eye having a gaze point directed at one of multiple targets rendered and displayed on a virtual and / or augmented scene within a subject's field of view according to an exemplary embodiment. [Figure 18B] FIG. 1 is a schematic diagram of multiple targets rendered and displayed on a virtual and / or augmented scene viewable by a subject (e.g., wearing a VR headset with eye tracking) according to an exemplary embodiment. [Figure 19A] FIG. 1 illustrates test results for a radial sweep test, with the shaded areas representing areas not considered by the metric, according to an exemplary embodiment. [Figure 19B] 1 shows the area under contrast sensitivity space of the radial sweep test (denoted as "AUC") metric for multiple eyes with or simulating various scotomata severity (none, mild, or severe), showing highly reproducible and sensitive results, according to an exemplary embodiment. [Figure 19C] 13 illustrates additional calculated AUC metric values ​​and corresponding Receiver Operating Characteristic (ROC) curves for baseline and sparse metrics according to an exemplary embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0083] Eye tracking or gaze estimation systems track eye movements to continuously estimate where a subject is looking on a surface or within a volume of space. Head-mounted eye tracking systems include dedicated camera hardware designed to capture images of one or both of the subject's eyes, and a light source (e.g., infrared illuminators) to illuminate the eyes. Head-mounted systems can enable subjects to view real scenes, fully computer-generated scenes (virtual reality, VR), real scenes with overlaid computer-generated graphical components (augmented reality, AR), and / or mixed reality (MR) scenes that blend VR and AR. The system can also provide the ability to switch between multiple of these modes of operation (real world, VR, AR, and / or MR). Additionally, the system can perform eye tracking while an interactive VR, AR, or MR visual experience is presented to the subject, thereby identifying where the subject is looking at any given time in the presented virtual or augmented scene.

[0084] The systems and methods described herein utilize such VR headset systems (as used below, the terms "headset" or "VR headset" refer broadly to head-mounted or face-mounted systems that implement virtual reality, augmented reality, and / or mixed reality capabilities).

[0085] In various embodiments, the systems and methods described herein (i) utilize anatomical references to determine a preferred retinal locus (PRL) for a subject's eye, (ii) align the VR headset optics with the wearer's eye, thereby reducing inaccuracies due to aberrations (e.g., chromatic, spherical) near the periphery of the VR headset lens, and / or (iii) render a graphical (e.g., 2D) scotoma mask that simulates the effect of a particular patient's scotoma onto the patient's (e.g., the patient's good eye) or another individual's visual field.

[0086] 1A and 1B are schematic diagrams of a system and method for identifying a preferred retinal locus (PRL) relative to the retinal anatomy using a VR headset, according to an exemplary embodiment. Existing VR headsets use a retinal locus (PRL) that is based on the ocular anatomy (RS). A ) regardless of the Headset Reference System (RS H The techniques described herein measure and provide the direction of gaze within an RS H A stable reference for the ocular anatomy in the headset reference system is determined to determine the preferred retinal locus (PRL) relative to the retinal anatomy. In this example, the anatomical reference is the optical axis of the eye.

[0087] VR headsets with eye tracking are based on the Headset Reference System (RS H ) provides gaze direction and gaze origin data streams. Anatomically, the gaze origin at a given time corresponds to a nodal point of the eye, which is the center of corneal curvature. When the eye rotates to change gaze direction, the nodal points move around the eye's center of rotation. The eye's center of rotation is determined from a sufficient number of different nodal points positions. For example, these points approximate the shape of the eye over time, which can be modeled, for example, as a sphere on which all the nodal points reside. The optical axis of the eye is then determined from the center of rotation and the nodal points.

[0088] Thus, a first stream of data in headset reference coordinates (a coordinate system independent of the actual eye anatomy) is received from the VR headset corresponding to the gaze direction of the subject's eye over time, said gaze direction defining the visual axis. A second stream of data in the headset reference coordinate system is received from the VR headset corresponding to the gaze origin at nodal points of the subject's eye that change over time. Each nodal point corresponds to the corneal curvature center of the eye measured at a given time point. Then, using data from the second data stream, a geometric volume is modeled / defined (e.g., a sphere, e.g., a best fit sphere) with a center corresponding to the eye's center of rotation and with a surface approximated by the nodal points. The optical axis of the eye is then identified from the modeled sphere, the optical axis being the line connecting the center of the sphere and the gaze origin. The optical axis thus identified and the data from the first stream (visual axis / gaze direction) are then used to identify a preferred retinal locus (PRL) relative to the retinal anatomy (e.g., in the eye's coordinate system). For example, data from the first stream is used to calculate a horizontal angle φ and / or a vertical angle θ between the optical axis and the visual axis of the eye, and the PRL is determined using the determined optical axis of the eye and the calculated horizontal angle φ and / or vertical angle θ. In certain embodiments, the method is used to monitor the PRL (e.g., angles φ, θ) over time, e.g., obtained over multiple sessions performed at regular checkups to monitor PRL changes as a disease or condition progresses.

[0089] 2 is a block flow diagram of a particular exemplary method for determining PRL using a VR headset system, according to an exemplary embodiment. In a first step, the built-in eye tracking system of the VR headset is calibrated. For example, the vertical and / or horizontal position of the lenses is adjusted using virtual iron sights, which are described in more detail herein below. Next, an eye tracking data stream is collected over time while the subject is wearing and gazes into the VR headset. The eye tracking data for this example is represented in the block diagram of FIG. 2 as gaze_origin . t and gaze_direction tThen, the system selects all gaze_origins that satisfy the indicated criteria to improve the data quality. t The system then filters out the remaining gaze_origin t Fit a sphere to the data points and determine sphere_center and sphere_radius. The quality of the gaze tracking data points is determined by fitting sphere_radius to sphere_center and gaze_origin t is evaluated by comparing it to the distance between t The system returns an error. t The data points that exceed a given threshold are filtered, and a cleaned up data stream is generated. The previously identified sphere_center and sphere_radius are then used to filter the filtered gaze_origin. t It is refined by fitting a new sphere to the data points. Then, the error t The smallest gaze_origin t and gaze_direction t Select a reference data point from the gaze_origin in Figure 2. r( Optical axis) and gaze_direction r (visual axis). The system then calculates the horizontal and vertical angles φ, θ between the optical axis and the visual axis. The system can monitor changes in these angles over time, e.g., obtained over multiple sessions at regular checkups, to monitor the patient's PRL changes, which may indicate, for example, disease progression and / or benefit obtained from a prescribed treatment, surgery, and / or therapy.

[0090] 3A and 3B are images of the field of view through a VR headset lens with more pronounced aberrations at the periphery than at the center. The optical quality of commercially available VR headsets (even professional systems) is limited by compact lens design, as seen for example with the use of Fresnel lenses and singlets. Compared to Fresnel lenses, singlets are generally thicker, heavier, and more curved. However, both types usually have more pronounced aberrations, such as chromatic and / or spherical aberrations, at the periphery of the lens than at the center of the lens. This can result in inaccurate measurements when performing functional vision tests using VR systems.

[0091] Thus, certain embodiments of the systems and methods described herein implement virtual iron sights that trigger headset adjustments by the wearer (or by an assistant to the wearer looking at a screen displaying the virtual image seen by the headset wearer) and allow interactive feedback to the wearer of the VR system to align the headset optics to the eyes in real time, allowing for improved optical quality and more accurate measurements from functional vision testing.

[0092] FIG. 4 is a block flow diagram of an exemplary method for prompting adjustment of the vertical position of a VR headset such that the position of the center of one or both of the wearer's eyes is aligned with the center of one or both of the respective VR headset lenses, according to an exemplary embodiment. The system measures the eye position relative to the VR headset over time, e.g., gaze_origin corresponding to a nodal point of the eye or of each of the wearer's eyes, a nodal point corresponding to the corneal curvature center of each eye. The position of the virtual camera is then associated with the position of the wearer's eyes relative to the VR headset. The system then dynamically positions (and repositions) the virtual camera position based on the eye position in real time. The subject repositions the VR headset by physically adjusting a toggle, strap, dial, switch, knob, dial, or other mechanism (e.g., manual or electronic) while observing real-time feedback via the virtual iron sights. The gaze_origin continues to be tracked in real time, and the virtual camera is dynamically repositioned as the subject repositions the VR headset. The subject continues to reposition the headset as prompted by the virtual iron sights until alignment of the virtual iron sights is achieved, indicating alignment of the centers of the wearer's eye (or eyes) with the respective lens(es) of the VR headset.

[0093] In one example, a virtual iron sight presented in real time within the headset wearer's field of view includes two concentric rings with fixed positions relative to each other and a third ring with a contrasting color to the concentric rings. The third ring has a visually detectable offset relative to the two concentric rings when the center of one or both headset lenses is misaligned with the gaze origin of the wearer's respective eye. The offset prompts the wearer to physically adjust the headset, thereby adjusting the vertical position of the headset, until the adjustment aligns the center of the lens with the gaze origin of the wearer's respective eye. The resulting virtual camera position causes the third ring to be displayed perfectly between the two concentric rings. The system can then freeze the virtual camera position when the rings are aligned. The alignment can then be checked periodically during the visual function test to ensure that the alignment continues to be maintained.

[0094] FIG. 5 is a schematic diagram illustrating a virtual iron sight used in a method for prompting adjustment of a VR headset to vertically align the eyes and lenses, according to an exemplary embodiment. In this example, a top view of a head wearing a VR headset shows that the headset is positioned too low on the wearer's head, causing a vertical misalignment between the center of the eyes and the center of the respective lenses of the VR headset. Two concentric rings with a fixed spacing between the rings are displayed in blue, and a third ring is displayed in gold. On the right side, a side view of the virtual scene is shown, with the virtual camera linked to the position of the eyes relative to the VR headset. In the top example, the headset is positioned too low, with the gold ring lower than it should be between the two blue rings for an optimal vertical position. In the bottom example, the headset is optimally positioned. The headset has been adjusted to fit higher on the wearer's face so that the center of the lens coincides with the center of the eye. Thus, the gold ring appears to the wearer to fit perfectly between the two concentric blue rings, indicating that alignment has been achieved.

[0095] Virtual iron sights other than the rings shown in FIG. 5 can be used so long as they indicate a graphic offset to the cue adjustment of the headset on the wearer's head / face. The system can be calibrated before use so that the position of the virtual camera is precisely linked to the position of the wearer's eyes relative to the VR headset and / or so that the offsets presented to the wearer of the VR headset during adjustment precisely indicate the relative displacement between the center of the VR headset lenses and the center of the wearer's eyes. The illustrated example shows a vertical alignment. In other embodiments, the system displays a view of the virtual iron sight to depict an offset to indicate to the wearer that a physical adjustment of the headset is required to achieve proper horizontal alignment of the eyes with the respective lenses, for example, in addition to or instead of the vertical alignment shown in FIG. 5. In certain embodiments, there can be multiple virtual iron sights.

[0096] In certain embodiments, the systems and methods presented herein visually simulate the effect of a scotoma on the visual field of a VR headset wearer, for example during functional vision testing. A real scotoma is a blind spot or distortion that affects the patient's visual field. Types of scotoma include (i) scintillating scotoma, which causes blurred vision in a portion of the visual field and may have a bright "aura" appearance, (ii) central scotoma, which is a blind spot directly in the line of sight, and (iii) paracentral scotoma, which causes relative or total vision loss within 10 degrees of fixation and is not directly in the line of sight. Patient-reported scotoma characteristics include blurring, distortion, and / or absence or missing of objects in the visual field. An operator of the system for scotoma simulation described herein can independently adjust each of these characteristics to optimize the appearance of the scotoma, as informed / explained by the patient.

[0097] The impact of scotoma on affected patients' vision has been difficult to explain or demonstrate in the past. The systems and methods described herein allow for a better understanding of how scotoma affects a patient's vision by allowing for the simulation of the impact of scotoma for viewing with a VR headset. This more accurate demonstration can be used, for example, to simulate the predicted appearance of the visual field due to scotoma over time if no intervention is performed, thereby helping to inform the patient of the importance of treatment options and / or increase patient compliance with prescribed treatments, surgeries, and / or therapeutic agents. The ability to simulate the impact of scotoma can also allow the patient's family and / or caregivers to experience how the patient sees the world, thereby increasing empathy for the patient and the ability to determine activities (e.g., driving) that are safe for the patient. A "simulated scotoma" may also allow for the measurement of the sensitivity of certain visual function tests during development. For example, test results of healthy subjects performed both with and without scotoma simulation can be compared, and the results can be used, for example, to indicate the sensitivity of functional tests for the identification of scotoma.

[0098] The shape of the simulated scotoma can be derived from microperimetry, e.g., a discriminative light sensitivity (DLS) map. Figure 6 is a fundus image of a patient's central scotoma (left) and overlaid DLS values. Effects caused by scotoma often reported by affected patients include decreased opacity and saturation, and increased blurring and distortion (e.g., pincushion, barrel, vortex). These effects can be simulated in a VR headset, and the intensity of these effects can be individually adjusted in creating the simulated scotoma. For example, if a subject has one normal eye and one eye affected by a scotoma, a virtual scene can be presented to the subject and feedback from the subject can be solicited by allowing vision of the scene with one eye at a time. Feedback from the subject is then used to construct the simulated scotoma (graphic mask). The graphic mask can be rendered and displayed in real time to the wearer of the VR headset, who can look around the virtual scene affected by the overlaid graphic scotoma mask. The simulated scotoma follows the gaze point of the wearer of the VR headset in real time.

[0099] For example, FIG. 7 is an image of a scotoma mask overlaid on newsprint to simulate how a patient suffering from scotoma sees newsprint, according to an exemplary embodiment.

[0100] FIG. 8A is a block flow diagram of a method for creating a scotoma mask with input from a patient wearing a VR headset with eye tracking capabilities, according to an exemplary embodiment. In this block diagram, a "unilateral" scotoma refers to a scotoma in one eye, while the vision of the other eye is unimpaired. For this flow, the scotoma is present in the right eye, while the left eye is "healthy" and used as a comparison control. A simulated scotoma is shown only on the side of the healthy eye. The impaired (left) eye is virtually covered, while the right eye is uncovered and can see a virtual (or augmented / mixed) scene affected by the virtual scotoma mask with unadjusted parameters. The healthy (right) eye is then virtually covered and the impaired (left) eye is exposed (affected by a real scotoma). The patient compares the real scotoma with the simulated scotoma, and the operator adjusts the intensity of the effect based on the patient's feedback. This process is repeated with each eye successively covered so that the patient can compare his or her vision using each eye, and the intensity of the visual effect of the virtual scotoma continues to be adjusted until the visual field using the healthy eye approaches the visual field using the impaired eye. Then, if the appearance of the simulated and real scotoma is sufficiently similar, the parameter set (effect strength) is stored. The scotoma mask can then be presented to the family, for example, to show how the patient would see the virtual (or augmented / mixed) scene. A simulation of the progression of the scotoma mask can also be performed to demonstrate to the patient what the effect of the scotoma would be over a certain period of time if left untreated.

[0101] Figure 8B is a block flow diagram of a method for rendering a scotoma mask created via the method of Figure 8A according to an exemplary embodiment. In this example, either a default scotoma shape or a personalized scotoma base is loaded. The personalized scotoma base can be determined, for example, from microperimetry (e.g., DLS map). A predefined set of parameters is then applied. The resulting simulated scotoma can then be refined, for example, via the workflow shown in Figure 8A.

[0102] FIG. 10 illustrates an exemplary method 1000 for identifying a preferred retinal locus (PRL) relative to the retinal anatomy of one or both eyes of a subject (e.g., a patient). In the method 1000, data received in a data stream over time in a headset reference system (e.g., coordinates corresponding to the virtual space of a VR headset) is oriented (e.g., by transforming to an anatomical reference system where coordinates correspond to a physical space) relative to the subject's retinal anatomy to identify the PRL relative to the subject's retinal anatomy. In step 1002, a processor receives a first data stream corresponding to the gaze direction of the eye over time. The first data stream is oriented in the headset reference system (e.g., a virtual coordinate system independent of the actual eye anatomy). In step 1004, a processor receives a second data stream corresponding to the gaze origin at the nodal point of the eye over time. The second data stream is also oriented in the headset reference system. Both the first data stream and the second data stream can be received from a device or system monitoring the subject's eyes, such as a VR headset (embodiments of which are described in detail below).

[0103] The nodal points may move about the eye's center of rotation as the eye rotates to change gaze direction, for example as determined by a VR headset, such that a set of temporally resolved nodal points is determined as the subject's gaze changes direction over time. The nodal points may correspond to the eye's corneal center of curvature.

[0104] In step 1006, the processor identifies a geometric volume using the second data stream. The geometric volume has a reference point (e.g., center) corresponding to the center of rotation of the eye and a surface that is approximated by nodes. The geometric volume may be, for example, a sphere, such as a best-fit sphere. In step 1008, an anatomical reference (e.g., the optical axis of the eye) is identified by the processor from the identified geometric volume. In some embodiments where the anatomical reference is the optical axis of the eye, the optical axis of the eye can be considered as a line connecting the center of the geometric volume (e.g., sphere) and the gaze origin.

[0105] In step 1010, a preferred retinal trajectory (PRL) is determined for the retinal anatomy using the anatomical reference and data from the first data stream. The identified PRL can thus be oriented with respect to an anatomical reference system that can use coordinates corresponding to physical space (e.g., with a position corresponding to the eye as the origin). For example, data from the first data stream can be used to calculate a horizontal and / or vertical angle between the optical axis and the visual axis of the eye, and thus the identified optical axis and the calculated horizontal angle can be used to identify the PRL. The PRL can be monitored (e.g., over multiple sessions conducted over a longer period such as weeks or months or years) to detect changes in the PRL that may indicate disease progression.

[0106] FIG. 11 illustrates an exemplary method 1100 for facilitating adjustment of a VR headset position relative to a wearer's head. In step 1102, a processor receives a first data stream (over time) corresponding to a position of a wearer's eyes relative to a headset, where a position of a virtual camera is linked to the position of the wearer's eyes relative to the headset. For example, the first data stream can correspond to a gaze origin at a nodal point of one or both of the wearer's eyes, such as the center of corneal curvature of the (respective) eye. For example, each nodal point can correspond to a position of the center of one or both of the wearer's eyes relative to the center of one or both respective headset lenses. The headset may include one or more adjustment mechanisms for adjusting the position of the headset relative to the wearer's head (e.g., vertical and / or horizontal position).

[0107] In step 1104, when the first data stream is received, the virtual iron sights are rendered and displayed in the field of view of the headset wearer in real time (or near real time) corresponding to the real time (or near real time) position of the virtual camera. In a particular embodiment, as in method 1100, the virtual iron sights include two concentric rings (e.g., may be circular or have another similar shape such as a regular polygon) having fixed positions relative to each other, and a third ring (e.g., may be circular or have another similar shape such as a regular polygon) having a contrasting color and / or shade (e.g., hue, saturation, or luminance) from the two concentric rings. The third ring generally has a visually detectable offset relative to the two concentric rings when the center of one or both headset lenses is misaligned with the line of sight origin of the wearer's eye (e.g., the center of corneal curvature).

[0108] In optional step 1106, the wearer is prompted to adjust the headset based at least in part on the offset of the third ring relative to the other two present. In certain embodiments, the prompt is visually identified by the wearer in that the third ring appears to have an offset relative to the other two (e.g., not concentric with the other two). In certain embodiments, the prompt may further include some type of notification, such as an additional visual and / or audio notification. In optional step 1108, the wearer (or another, e.g., a doctor, optometrist, or other healthcare provider) may adjust the VR headset (e.g., by one or more adjustment mechanisms) until the third ring is aligned (e.g., concentric) with the other two rings. The alignment may be determined, for example, by an adjustment that causes the position of the virtual camera to appear completely between the two concentric rings (e.g., whether or not a portion of the third ring may be weakly occluded by one or both of the concentric rings, if there is no portion visually detectable by the wearer as outside the two concentric rings).

[0109] FIG. 12 illustrates an exemplary method 1200 for rendering a graphical (e.g., 2D) scotoma mask that simulates the effect of a scotoma on a visual field. In step 1202, data corresponding to a shape of the simulated scotoma is received by the processor. The data can correspond to a selected default scotoma shape, such as a disk, or a personalized scotoma shape derived from microperimetry of the subject (e.g., a differential light sensitivity (DLS) map). In step 1204, input is received by the processor to identify one or more visual effect parameters corresponding to values ​​of visual effects caused by the scotoma. For example, the input can be from a particular patient suffering from an actual scotoma (e.g., who may be the patient for whom the scotoma mask is being simulated, e.g., if the scotoma mask is used to simulate disease progression). The one or more visual effect parameters can include one or more of opacity, saturation, blur, and distortion (e.g., pincushion, barrel, or vortex). In step 1206, a graphical scotoma mask is defined by the processor according to the shape of the simulated scotoma and the one or more visual effect parameters.

[0110] In step 1208, a first data stream is received by the processor, for example from a VR headset, the first data stream corresponding to a gaze point of a wearer of the VR headset. In step 1210, a virtual and / or augmented scene is rendered by the processor and displayed in real time (or near real time) within the wearer's field of view. At least a portion of the virtual and / or augmented scene is modified according to the graphic scotoma mask. The scene can follow the wearer's gaze point as the gaze point changes in real time. The virtual and / or augmented scene can be affected by a simulated scotoma using a graphic scotoma mask that follows the wearer's gaze point. The wearer may be a different individual than the patient, for example, if the wearer wants to understand how scotoma is affecting a particular patient's vision (e.g., if the wearer is a physician, optometrist, or other healthcare provider), or if the physician, optometrist, or other healthcare provider wants to convey to the wearer an understanding of how scotoma may affect the wearer's vision based on patients with similar diseases and / or disease progressions.

[0111] VR / AR / MR device (e.g., headset) components The following is a description of an exemplary VR headset system for use in various embodiments described herein. Commercially available virtual reality (VR), augmented reality (AR), and / or mixed reality (MR) systems feature head-mounted and / or face-mounted hardware and eye-tracking software and can be used as components of the systems and methods described herein. As used herein, the term "headset" or "VR headset" refers broadly to such head- or face-mounted systems that implement virtual reality, augmented reality, and / or mixed reality functionality. For example, in certain embodiments, two data streams corresponding to gaze direction and gaze origin, respectively, are received from a commercially available VR headset system with eye-tracking capabilities, and the generated data has a headset reference system rather than an anatomical structure reference system of the eye.

[0112] An example of a professional-grade VR headset system with eye-tracking capabilities that can be used with the systems and methods described herein is the VIVE Pro Eye Office VR system manufactured by HTC Corporation (headquartered in Xindian, New Taipei City, New Taipei Province), as described at https: / / business.vive.com / us / product / vive-pro-eye-office / and in U.S. Pat. No. 10,990,170, entitled "Eye-tracking method, electronic device, and non-transitory computer-readable storage medium," and U.S. Pat. No. 10,705,604, entitled "Eye-tracking apparatus and light source control method therefor," the text of each of which is incorporated herein by reference.

[0113] 9A illustrates an example system 900 capable of performing methods described herein. The example system 900 includes a memory 902 having stored therein instructions that, when executed by a processor 904, perform one or more methods described herein. Optionally, the system 900 can include a VR headset 910, for example, from which first and second data streams corresponding to a gaze direction and gaze origin are transmitted to and received by the processor 904 for use in executing the instructions stored in the memory 902.

[0114] FIG. 9B shows a detailed block diagram of components that may be included in the VR headset 910, for example, when the VR headset 910 is a VIVE Pro Eye Office VR system. The components may include one or more of: (i) a camera 912 for tracking the subject / patient's eye; (ii) one or more illumination sources LS1, LS2, ... LSN for illuminating the subject-patient's eye and providing a signal to the camera 912 for tracking the eye; (iii) one or more optical systems 916, such as lenses, reflectors, or other light directing components, for directing light interacting with the eye (e.g., reflected from the eye) to the camera 912; (iv) a display 920 for displaying images to the subject / patient; (v) one or more headset processors 914 for processing data from the camera 912, for the display 920, or from and / or for other components in the VR headset 910; (vi) one or more adjustment and / or head support mechanisms 922 for physically adjusting (e.g., orienting and / or aligning) the VR headset on the subject / patient (e.g., relative to the subject / patient's eye and / or for comfort during use). In general, the VR headset 910 is a wearable device that can be worn over one or both eyes of the subject / patient at a time. For example, the VIVE Pro Eye Office VR system is worn over both eyes, while other available VR headsets may have a "monocular" style that is worn over one eye at a time.

[0115] The display 920 may also be used to provide one or more simulated images to the subject / patient based on, for example, the subject's / patient's ocular function determined by the methods described herein. For example, in certain embodiments, the display 920 may be used to provide the subject / patient with a simulated disease progression with an integrated or overlaid scotoma mask generated by the processor 904 using instructions stored in the memory 902.

[0116] The processor 904 that executes the instructions may be one of the headset processors 914. The memory 902 and processor 904 may be housed in the VR headset 910, or may be housed separately, for example on a server or other computing device that is in communication (e.g., wireless communication) with the VR headset 910. One or more of the headset processors 914 may be used to send data streams to the processor 902, for example wirelessly.

[0117] The VR headset 910 may also include one or more adjustment and / or head support mechanisms 922. The adjustment mechanism 922 may include one or more mechanical mechanisms, such as knobs, straps, dials, etc. The adjustment mechanism 922 may be used to adjust the horizontal and / or vertical position of the headset (e.g., its components, such as the display 920) relative to the subject / patient's head. For example, the VIVE Pro Eye Office VR system includes a mechanism for adjusting the interpupillary distance (IPD) to a particular subject / patient using the system by an "IPD knob." IPD adjustment may include first determining a physical IPD measurement, for example, manually by the subject / patient or with assistance from a doctor, optometrist, or other healthcare provider. As another example, the VIVE Pro Eye Office VR system includes a lens distance adjustment button that can be pressed by the subject / patient to further adjust the lens distance or closer to their face. Such adjustments may be used to account for the subject / patient's anatomy or other factors, such as glasses or other visual aids. The user may be prompted to make adjustments to one or more of the adjustment mechanisms 922 based on methods disclosed herein, such as example method 1100, that use eye tracking (e.g., in combination with virtual iron sights (alignment assistance)) to determine whether the VR headset 910 is properly aligned and / or oriented.

[0118] To help secure the VR headset and / or provide comfort to the user during use, various head support mechanisms can be used to "fit" the VR headset to the subject's / patient's head. The head support mechanism 922 can include one or more physical structures such as straps, mounts, braces, padding, etc. The physical structures can be adjustable (e.g., hook-and-loop or elastic straps) or compliant (e.g., foam padding) or both (e.g., adjustable straps with padding). For example, the VIVE Pro Eye Office VR system includes interchangeable face cushions that provide flexible support around the subject's / patient's eyes for comfort, a head pad, an adjustment dial, and a center strap that collectively secure the system to the subject's / patient's head, the adjustment dial being part of the head pad located on the back of the head, and the center strap covering the top of the head. The adjustment dial can adjust the tension of the center strap, which also has a hook-and-loop fastener for easy attachment and removal from the head.

[0119] Further details regarding certain exemplary adjustment and / or head support mechanisms that may be included in embodiments of a VR headset, such as the VR headset 910 shown in Figures 9A-9C, are provided in the VIVE Pro Eye User Guide for the VIVE Pro Eye Office VR System. Other adjustment and / or head support schemes may be used. Furthermore, in certain embodiments, a particular mechanism (e.g., structure) may function as both an adjustment mechanism and a head support mechanism. For example, a strap may be used to secure the VR headset to a wearer and may be used to adjust the physical position of the VR headset relative to the wearer's eyes.

[0120] FIG. 9C shows a schematic diagram of a method for tracking a subject / patient's eye 901 using an exemplary VR headset 910. Illumination sources (light sources) LS1, LS2, ..., LSN provide light to the eye 901. The light is received by a reflector 916 from the eye 901 after illumination and reflected towards a camera 912 where it is detected and processed using a headset processor 914, which is part of the controller, which references a look-up table 918. Optionally, a display 920 simultaneously displays images to the subject / patient, for example to encourage eye movement or a specific focus of the subject / patient, for example to orient or track the eye 901. One or more optical systems 916 (e.g., lenses) can be used to focus or direct the light from the display 920 to the subject / patient. The display 920 can be considered part of the one or more optical systems 916, for example, a "lens" of the VR headset 910 can include the display 920 (or a part thereof).

[0121] In the exemplary VR headset 910, the illumination sources LS1, LS2, ..., LSN project multiple light beams onto the eye 901 on a target area. The light reflecting device 916 receives and reflects the display image IMG of the eye 901 to the camera 912. A controller having a headset processor 914 is coupled to the camera 912 and the illumination sources LS1, LS2, ..., LSN. The headset processor 914 receives the display image IMG and analyzes the contrast ratio of the display image IMG. The headset processor 914 further generates a command signal DS as a result of the analysis, and controls the on or off state of each illumination source LS1, LS2, ..., LSN by the command signal DS. The lookup table 918 is configured to store the relationship between the on / off state of the illumination sources LS1, LS2, ..., LSN and the visual field information of the eye. The lookup table 918 may be implemented as any suitable form of memory that would be apparent to a person skilled in the art. The lookup table 918 may be external to the controller along with the headset processor 914 or may be coupled to the controller. Alternatively, the lookup table 918 may be embedded in the controller along with the headset processor 914. Further details of additional embodiments of how such lookup tables 918 and controllers may be used to control components of a VR headset 910 and track a subject's / patient's eye 901 can be found in U.S. Patent No. 10,705,604.

[0122] Eye Conditions / Disorders and Functional Vision Testing Below is a description of various eye conditions / disorders for which functional testing may be beneficial. The systems and methods described herein may be implemented in functional testing using a VR headset. For example, the systems and methods described herein utilize eye tracking implementing the techniques described herein to display static and / or changing / moving visual stimuli (targets) to a subject / patient to elicit and record patterns of eye movement in response to the stimuli, said patterns of eye movement being correlated to a disease or condition, such as retinal dysfunction. Examples of such diseases or conditions include age-related macular degeneration (AMD), more specifically "dry" or "wet" AMD, as well as diabetic macular edema, venous or arterial occlusion, and inherited retinal diseases. Functional vision testing enabled by the systems and methods described herein may also help identify and / or monitor cataracts, glaucoma, optic neuritis, diabetic retinopathy, and uncorrected myopia. Optical functional abnormalities that can be identified and / or monitored by the systems and methods described herein may also result from (and may be indicative of) multiple sclerosis, schizophrenia, or other neurological disorders.

[0123] In macular degeneration, the macula, a spot near the center of the retina, is damaged. As the disease progresses, patients may experience a central scotoma. The scotoma may appear as a blurry or smudged spot, or may be a blind spot (e.g., which may progress to a gray or black spot). The size of the scotoma may increase as the disease progresses. The remainder of the retina may remain undamaged, and the patient may compensate for the scotoma by moving their gaze to see more clearly things around the central scotoma, around the direct line of sight. The patient is using peripheral vision, and the rod cells are taught to perform a function that once was performed to damage the cone cells. In this way, the preferred retinal locus (PRL) is the retinal region that acts as a pseudofovea to compensate for the lesioned fovea (the region in the center of the macula). The location of the PRL (relative to the anatomy of the retina) is important as it may indicate a retinal disease or condition, such as macular degeneration, and changes in the PRL over time can be tracked to monitor the progression of the disease or condition. Functional tests performed using the systems and methods described herein can be used to identify the location of the PRL relative to the retinal anatomical structures, as well as to identify abnormalities that may or may not be directly related to the PRL.

[0124] Functional tests that may be performed include, for example, fixation stability tests, tracking stimuli moving in and out of the scotoma, contrast sensitivity tests (pellets, flicker targets), and serial search (maze) tasks.

[0125] In one example of fixation stability testing, a subject wearing a VR headset with eye tracking fixates on a single target (e.g., a single point) presented on a display that is stationary in virtual space. The test can incorporate low contrast, high contrast, different shapes and sizes of targets, and other variations. A heat map is generated that shows where the subject was looking over the length of the test. The system can then measure a bivariate contour ellipse area (BCEA) with the results compared to known parameters in a healthy population. PRL determination may also be part of a functional test, for example, with changes in PRL monitored over time.

[0126] Another example of a functional vision test includes a contrast sensitivity test, such as the "Gradiate" test as described in Mooney, S.W. et al., "Gradiate: A radial sweep method for measuring detailed contrast sensitivity function from eye movements," Journal of Vision, 20(13):17 (2020) (https: / / doi.org / 10.1167 / jov.20.13.17), the text of which is incorporated herein by reference.

[0127] Herein, improvements to the contrast sensitivity functional vision test are presented, where a machine learning model determines the probability that a subject observed or did not observe an individual target for a given time window (in milliseconds), which may be applied to other functional vision tests.

[0128] In developing this improvement, it is now noted that it would be beneficial to have an objective classification of whether the subject was truly tracking the target during the contrast sensitivity test, or whether the subject was looking elsewhere, or otherwise moving the eyes randomly. A precise and rapid feedback loop was developed in the test that gradually reduced the visibility of the target. An artificial intelligence (AI)-based visibility determination algorithm was created to determine whether the subject was accurately tracking the target in time and space during the course of the contrast sensitivity functional vision test.

[0129] The AI ​​system was developed by having the user track the targets over a number of trials (sample data), then a "ground truth" was established by manually assessing the video recordings after the test and annotating whether the subject's eye position was within each individual target. The ground truth dataset included hundreds of minutes of observations and annotations. The resulting AI model provided the probability that the subject did or did not observe an individual target (e.g., a field of five targets) for a given time window (in milliseconds). For functional testing, if the AI ​​feedback indicated that the subject was looking at a target, the system would change the target's appearance accordingly until the AI ​​determined that the subject was no longer tracking the target. The final values ​​of contrast and spatial frequency were recorded as the subject's visual / functional threshold for that parameter space. The subject then moved to a different target (e.g., a different sweep in a radial sweep test) and the process was repeated.

[0130] A variety of architectures were tested, including recombination neural networks, long and short-term memory, temporal convolutional networks, etc. Several threshold parameters can be adjusted to alter and improve performance. These include the time window for the AI ​​judgement (e.g., increase or decrease), and the tolerance on how close or far in space the subject's actual eye position is located from the center of the circular target.

[0131] 15A-15B are schematic diagrams of a neural network implementation for an AI-assisted radial sweep functional vision test, including a visibility judgment that automatically determines whether the subject is looking at the target. An example of an exemplary AI network architecture and the target field and visibility judgment output (visibility detection) of the AI ​​are shown. In some embodiments, a deep recurrent neural network (DRNN) architecture is used. The input to the DRNN may be 10 consecutive data points (including the coordinates of the gaze point and one patch). The DRNN may be three concatenated recurrent neural networks (RNNs). FIG. 15A shows the basic structure of the RNN. The DRNN may use an aggregation that takes the output of the 10th frame (e.g., 32 scalars). A fully connected network (e.g., two layers) can be used to map the hidden DRNN state to a visibility probability. The final output may be the visibility probability of one patch. The network may be trained with about 2 minutes of data (e.g., comparison with ground truth and backpropagation). Patch visibility prediction may be performed already on evaluation data (e.g., about 45 seconds) after very short training (e.g., about 120 seconds). Figure 15B is a schematic diagram of visibility detection using a machine learning algorithm.

[0132] FIG. 16 is a graph showing patch visibility probability, patch prediction, and global visibility after applying a prediction threshold in an AI-assisted radial sweep functional vision test, according to an exemplary embodiment. The graph shows patch visibility output for a set of five targets (indicated in the legend), with time shown on the x-axis. The "Patch Prediction" graph shows the "ground truth" (blue line, manual validation) compared to the prediction before applying the prediction threshold (yellow line), and "Global Visibility after Applying Prediction Threshold" is a plot of the ground truth against the prediction after applying the prediction threshold. FIG. 17 is a graph showing performance results using long short-term memory (LSTM) and temporal convolutional networks (TCN) as machine learning algorithm architectures in an AI-assisted radial sweep functional vision test, according to an exemplary embodiment.

[0133] Contrast sensitivity testing was performed using an HTC Vive Pro Eye headset. An exemplary still frame from the visual task used in the test is shown below: Five targets move in a random pattern around the subject's visual field. As the subject tracks the targets, their contrast decreases (they become more difficult to see). The subject is instructed to follow them until they can no longer see them. Once all five targets are no longer visible, a new set of targets appears and the subject repeats the task (there are a total of three "runs" accounting for a total of 15 targets).

[0134] Functional vision tests, such as contrast sensitivity and / or spatial frequency tests (e.g., radial sweep tests), can be used to test the function of a subject's eye. A subject may be suffering from an eye condition, at risk for an eye condition, or unsure whether they have an eye condition. Such eye conditions can be, for example, age-related macular degeneration (AMD) and / or related (e.g., associated) conditions. Examples of such conditions include dry age-related macular degeneration (dry AMD), wet age-related macular degeneration (wet AMD), neovascular age-related macular degeneration (AMD), and geographic atrophy. Functional vision tests can be used to diagnose and / or monitor a subject's eye condition. For example, functional vision tests can be used to generate test results that indicate the presence, severity, and / or progression of a subject's eye condition, such as AMD or a related (e.g., associated) condition (e.g., geographic atrophy). Functional vision tests can be performed using virtual reality and / or augmented reality and / or mixed reality devices (e.g., VR headsets with eye tracking capabilities). In some embodiments, an eye condition is simulated using such a device, for example, to demonstrate to the subject what it is like to have an eye condition and / or what may happen due to the progression of an eye condition the subject may already have. In some embodiments, such a device can be used to simulate a scotoma while a functional vision test is being performed. A functional vision test can be used to assess the quality of vision of a subject (e.g., the subject's visual acuity).

[0135] Functional eye testing generally involves rendering and displaying to the subject on one or more targets in a virtual and / or augmented scene in the subject's field of view. The one or more targets may be visibility patches, such as contrast-based visibility patches. FIGS. 18A-B show examples of contrast-based visibility patches on charts of virtual and / or augmented scenes that may be rendered, for example, by a VR headset. The one or more targets may be two or more, three or more, four or more, or five or more targets. The targets may move continuously during the test. The target(s) may change contrast during the test, for example, upon a determination that the subject has been tracking the target(s) for a sufficient amount of time. In some embodiments, the targets may change direction of movement during the test. Such abrupt changes in direction may make the test more reliable in determining visibility by reducing the likelihood of determining that the subject is actually tracking a moving target when in fact the subject was simply following a known path seen previously. In some embodiments, the abrupt change in the target's direction of movement may be initiated (e.g., as soon as the target is seen) based on a determination that the subject has tracked the target in less than one second (e.g., using one or more time-based parameters). The adjustment (e.g., abrupt adjustment) of the contrast, spatial location, spatial resolution, and / or direction of movement may be made automatically using one or more time-based parameters. Such adjustments may include lowering the contrast of the tracked targets to increase difficulty, abruptly changing the direction of movement of the tracked targets to increase difficulty, resetting all targets at high contrast, and / or stopping the functional vision test. For example, if the subject has not tracked any target for a significant period of time (e.g., at least 5 seconds), the test may be stopped or all targets may have their contrast reset. The former case may occur if the subject is not engaged in the test, and the latter case may occur if the subject can no longer see the targets because all contrasts are too low.During testing, the contrast and / or spatial resolution of one or more targets may be automatically adjusted (e.g., decreased) within the virtual and / or augmented scene based on a comparison of the point of gaze to a current spatial location of the one or more targets within the virtual and / or augmented scene. For example, the automatic adjustment may be based on a determination that the point of gaze is aligned with the one or more targets for one (or at least one) predetermined threshold period of time using one or more time-based parameters.

[0136] The functional vision test may include automatically performing visibility determinations in real time to automatically identify whether the subject is tracking one or more targets (e.g., in time and space) in the virtual and / or augmented scene. Tracking may be determined by comparing the spatial location of the target with the subject's gaze point. The gaze point may be determined, for example, using a VR headset. The gaze point determination may be performed in real time. In some embodiments, tracking is considered to occur when the gaze point is aligned with the target for a period of time. A gaze point may be considered to be aligned with a target if it coincides with the target or, in some embodiments, is at least locally close to the target [e.g., within an area slightly larger (e.g., 10% larger) than the target]. FIG. 18A is a schematic diagram representing a subject's eye, with a line extending from the eye toward the virtual and / or augmented scene representing the gaze point of the eye that is aligned with (specifically incident in this case) the target (in this case, the contrast-based visibility patch).

[0137] The visibility determination can be made using one or more time-based parameters, preferably multiple time-based parameters. The use of appropriate time-based parameters can simplify the process of determining whether the alignment between the gaze point and the target (e.g., tracking of the target) is intentional because the subject is observing and / or tracking the target, or is accidental. For example, the Gradiate test described by Mooney et al. uses many parameters (more than 10 parameters), including non-time-based parameters, to make a visibility determination that may make the test (i) unreliable or unreliable (e.g., due to the complexity of making a visibility determination using so many different parameters). In contrast, in some embodiments, the functional vision test disclosed herein uses a total of 10 or fewer parameters. In some embodiments, time-based parameters are used and artificial intelligence need not be used (e.g., is not used). Thus, the visibility determination may be made in a different manner than described for the Gradiate test. The time-based parameters can correspond to a time period during which the gaze point is aligned or not aligned with one or more targets in the virtual and / or augmented scene. For example, in some embodiments, four time-based parameters are used: a first time-based parameter may be for tracking when the subject's gaze point is on a particular target in the virtual and / or augmented scene; a second time-based parameter may be for tracking when the subject's gaze point moves away from a particular target in the virtual and / or augmented scene; a third time-based parameter may be for tracking when the subject's gaze point is on any of multiple targets in the virtual and / or augmented scene; and a fourth time-based parameter may be for tracking when the subject's gaze point moves away from all of multiple targets in the virtual and / or augmented scene.

[0138] This paragraph describes an illustrative (non-limiting) example of using a set of four time-based parameters to make visibility determinations. The parameters can have units of seconds (e.g., fractions thereof). Each target moves around and has an evidence counter associated with it (minimum 0%, maximum 100%). When the subject's gaze is aligned with (e.g., incident on or in close proximity to) a particular target, its associated evidence counter is filled at a particular rate. A first time-based parameter governs when the evidence counter is filled. The first time-based parameter can be 0.5s to fill up to 100% to track a particular target. That is, for 0.5s of the gaze being aligned with a particular target, the evidence counter goes from 0% to 100%. When the gaze is somewhere else and no longer on that particular target, the evidence counter is depleted at a particular rate. A second time-based parameter governs when the evidence counter is emptied. The second time-based parameter can be emptied from 1s to 0% to not track a particular target. That is, if the gaze point for 1s is not aligned with a particular target, the evidence counter empties from 100% to 0%. Each evidence counter can increase while the subject looks at the corresponding target and decrease while the subject looks somewhere else. In general, the (visibility) evidence for all targets [e.g., all five targets (e.g., all five visibility patches)], independently at any time, can be anywhere between 0% and 100%, depending on where the subject's gaze point is currently and where it has been recently. Thus, one counter may be increasing while the other counter is decreasing. If the tracking evidence corresponding to a particular target reaches 100%, the system assumes that the target is being seen by the subject (i.e., there is conscious awareness and the gaze point did not just accidentally cover the target). The appearance (contrast and / or spatial frequency) of that target is consequently altered to make the task more difficult.If the target is not being tracked (e.g., it is no longer visible) (all of the local evidence is decreasing), the global evidence is also slowly decreasing towards 0% at a constant rate. A third time-based parameter governs when the global evidence counter is empty. The third time-based parameter may be empty from 6s to 0% for not tracking any target. That is, for 6s of fixation point not aligned with any target in the virtual and / or augmented scene, the global evidence counter is empty from 100% to 0%. Similarly, if the local evidence is increasing, the global evidence is also increasing. A fourth time-based parameter governs when the global evidence counter is filled. The fourth time-based parameter may be 4s to fill up to 100% for tracking any of the targets. That is, for 4s of fixation point aligned with any target in the virtual and / or augmented scene, the evidence counter is filled from 0% to 100%. In some embodiments, if the global evidence counter is at 0%, the system assumes that the patch can no longer be seen and 5 new patches with high contrast are shown. The contrast and / or spatial resolution of any particular one of the targets (e.g., contrast-based visibility patches) may be automatically reduced when an evidence counter is met (e.g., when the subject's gaze point is aligned with a particular gaze point for 0.5 s longer than when the subject's gaze point is not aligned with the particular gaze point). Targets may suddenly change direction of movement while the subject is tracking them, e.g., to increase the reliability of visibility judgments.

[0139] The time-based parameters may correspond to periods of, for example, milliseconds or seconds, such as periods of, for example, 100 ms or less, 250 ms or less, 500 ms or less, 750 ms or less, 1 s or less, 2 s or less, 4 s or less, 6 s or less, 8 s or less, or 10 s or less (e.g., each parameter corresponds to an independent period). For example, the above examples used parameters corresponding to periods of 500 ms, 1 s, 4 s, and 6 s.

[0140] In some embodiments, the four time-based parameters account for at least 80% (e.g., at least 90%, e.g., at least 95%, e.g., at least 98%, e.g., 100%) of all significant variables used in the functional visual test (e.g., where the significant variables are variables that have at least 5% impact on the outcome of the functional visual test). In some embodiments, the visibility determination is performed (e.g., only the four time-based parameters) using only time-based parameters (i.e., no non-time-based parameters are used to perform the visibility determination). In some embodiments, no more than 10 parameters in total (e.g., no more than 8 parameters in total, no more than 6 parameters in total, no more than 5 parameters in total, or no more than 4 parameters in total) are used to perform the visibility determination, preferably each parameter being a time-based parameter.

[0141] The at least one time-based parameter used for the visibility determination may, for example, correspond to a subject tracking a target whose gaze point is aligned with (e.g., incident on) the target in the virtual and / or augmented scene. The at least one time-based parameter used for the visibility determination may, for example, correspond to a subject not tracking a target whose gaze point is not aligned with (e.g., incident on) the target in the virtual and / or augmented scene. A combination of these two different types of time-based parameters may be used.

[0142] The time-based parameters may be asymmetric, for example, as described in the previous example of the set of four time-based parameters. For example, a parameter for tracking when the gaze point is on the target (e.g., aligned with the target) can refer to (e.g., corresponds to) a different time length than a parameter for tracking when the gaze point is away from the target (e.g., not aligned with the target) (e.g., 0.5s vs. 1s for the corresponding parameters in the previous example). The "on" parameter can refer to a shorter time length than the "off" parameter. As another example, a parameter for tracking when the gaze point is on any of the multiple targets (e.g., aligned with any of the targets) can refer to (e.g., corresponds to) a different time length than a parameter for tracking when the gaze point is away from (e.g., not aligned with) all targets (e.g., 4s vs. 6s for the corresponding parameters in the previous example). The "on" parameter can refer to a shorter time length than the "off" parameter.

[0143] Performing the visibility determination may include determining a subject's point of gaze in real time and comparing the point of gaze to a current spatial location of one or more targets in the virtual and / or augmented scene. Such a comparison may use time-based parameters. Performing the visibility determination may include determining a subject's point of gaze in real time and determining whether the point of gaze is aligned with a target in the virtual and / or augmented scene. Performing the visibility determination may include, for example, determining a subject's point of gaze in real time using at least one of the time-based parameters and determining whether the subject is tracking a target in the virtual and / or augmented scene.

[0144] A visibility determination may mean that the subject was able to see (e.g., over a period of time) one or more targets (e.g., be able to track one or more moving targets). A radial sweep test may include making one or more visibility determinations. The visibility determinations may be made, for example, using a processor in the VR headset or a processor in communication with the VR headset.

[0145] The test results can be calculated and / or displayed using the visibility determination. In some embodiments, the test results include a function of contrast sensitivity (e.g., inverse root mean square (RMS)) and spatial frequency (in cycles per degree, CPD) (e.g., stored as a plot or presented in a plot). The test results from the functional vision test can be an outcome measure of an ocular condition (e.g., affecting one or both eyes of the subject). The functional vision test can be a test of an ocular condition, such as AMD or a related (e.g., associated) condition (e.g., geographic atrophy). The test can be an outcome measure and / or a functional endpoint. The label of the packaged pharmaceutical composition or kit can include a label including a description and / or code identifying a therapeutic agent for the treatment of the ocular condition, the ocular condition being monitored and / or diagnosed by the functional vision test. In some aspects, the subject's ocular condition is diagnosed by a method other than functional vision testing, such as imaging (e.g., optical coherence tomography and / or fundus autofluorescence), and subsequently monitored by functional vision testing. The label may indicate that the subject (e.g., patient) should be prescribed a therapeutic agent if progression of the ocular condition is observed using the test results from the functional vision testing. The test results may include (e.g., may be) a metric corresponding to the subject's functional vision, such as, for example, an area under the curve (AUC) metric. The AUC metric may be a "sparse" AUC metric, e.g., one or more radial sweeps have not been performed and / or have not been taken into account. In some embodiments, the metric (e.g., AUC metric) has a sensitivity of at least 90% with 100% specificity, a sensitivity of at least 91% with 100% specificity, a sensitivity of at least 92% with 100% specificity, or a sensitivity of at least 92.5% with 100% specificity. In some embodiments, the metric (e.g., the AUC metric) has a sensitivity of at least 90%, at least 91%, at least 92%, or at least 92.5%. The test results may be calculated, for example, using a processor within the VR headset or a processor in communication with the VR headset.The test results may be displayed, for example, using a processor within the VR headset or a processor in communication with the VR headset.

[0146] Functional vision testing can be used to diagnose and / or monitor subjects with ocular conditions. Subjects can be treated with a therapeutic agent (e.g., by administering a therapeutically effective amount of a therapeutic agent) based on diagnosis and / or monitoring. For example, subjects can be determined to have a worsening severity of an ocular condition that is an indication for treatment, e.g., administration of a therapeutically effective amount of a therapeutic agent. The ocular condition can be, for example, diabetic retinopathy (e.g., with or without diabetic macular retinopathy), Stargardt's disease, Leber's hereditary optic neuropathy (LHON), retinitis pigmentosa, glaucoma, inner nuclear layer disease, geographic atrophy, and age-related macular degeneration (AMD) (e.g., dry age-related macular degeneration (dry AMD), wet age-related macular degeneration (wet AMD) and / or neovascular age-related macular degeneration (neovascular AMD)). Diagnosis and / or monitoring (e.g., determining severity of deterioration) (e.g., progressive deterioration) (e.g., poor progression) of an ocular condition can use the functional vision tests disclosed herein. In some embodiments, the therapeutic efficacy of a therapeutic agent administered to a subject is determined using a functional vision test disclosed herein, e.g., from test results from a functional vision test. The therapeutic efficacy can be determined for a particular subject. In some embodiments, the functional vision test can be used with a population of subjects to determine the therapeutic efficacy of a candidate therapeutic agent and / or therapeutic intervention (e.g., in a clinical trial, e.g., to establish whether the endpoints of the trial have been met).

[0147] The therapeutic agent can be (i) a vitamin and / or mineral supplement selected from the group consisting of vitamin C, zinc, vitamin E, copper, beta-carotene, and combinations thereof, (ii) ranibizumab, (iii) faricimab, (iv) brolucizumab, (v) aflibercept, or (vi) pegaptanib, (vii) a complement inhibitor, (viii) a neuroprotectant, (ix) an anti-inflammatory agent, (x) a free radical scavenger, (xi) an anti-apoptotic agent, (xii) an integrin modulating agent, (xiii) a gene therapy, or (xiv) a cell therapy. The therapeutic intervention can be laser coagulation therapy.

[0148] In some embodiments, the therapeutic agent comprises a complement inhibitor (e.g., a C3 inhibitor or a C5 inhibitor). In some embodiments, the complement inhibitor comprises a peptide, protein, antibody, aptamer, or small molecule that binds to and inhibits the activity of a complement component or a biologically active fragment thereof (or a complex comprising two or more complement components or biologically active fragments thereof). In some embodiments, the complement component or a biologically active fragment thereof is C3, C3a, C3b, C4, C4a, C4b, C5, C5a, C5b, C1, C1q, factor B, or factor D. In some embodiments, the complement inhibitor comprises a nucleic acid, e.g., an siRNA or an antisense oligonucleotide, that inhibits expression of a complement component (e.g., C3, C5, factor B, factor D, or C1).

[0149] In some embodiments, the therapeutic agent is a gene therapy, which may genetically modify cells within the eye to inhibit expression of a pathogenic gene product, correct a mutation in a gene, deliver a functional copy of a gene to a cell that has a dysfunctional copy of such a gene, or cause the cell to express a beneficial nucleic acid or protein.

[0150] In some embodiments, the therapeutic agent is a cell therapy. The cells can include, for example, stem cells (e.g., induced pluripotent stem cells), stem cell-derived cells, retinal pigment epithelial cells, or photoreceptor cells. The cells can replace cells lost to disease or support or complement the function of remaining cells.

[0151] Below is an illustrative (non-limiting) example of a functional vision test using the visibility assessment described above as an example using four specific time-based parameters. To test the usefulness of the functional vision test, scotoma of various severity (mild or severe) was simulated while running the test as well as a test repetition without simulated scotoma, and the test results were compared. Simulated mild or severe scotoma was designed from published microperimetric maps of real patients. Two severity levels (0.2 and 0.6) from the range 0-1.0 were selected. The scotoma was the same size and shape, and the input settings were adjustable for both opacity and blur, based on literature reports of vision loss in geographic atrophy (GA).

[0152] Performance of the contrast sensitivity test was evaluated in a group of adult subjects using simulated mild or severe scotoma. Some of the subjects had refractive errors and used regular corrective lenses during the test. Otherwise, the subjects reported no history of significant vision problems. Each subject's performance in tracking individual targets mapping to contrast spatial frequency space was fitted by a curve for each eye. The area under the curve (AUC) was determined as a metric of the subject's performance for each task by each eye. Figures 19A-19C plot the results of the test. The test showed repeatability and sensitivity, and was able to distinguish between mild and more severe simulated losses. Figure 19A shows the test results of a functional vision test. A "sparse" AUC metric was used to determine performance (see Figure 19C) by intentionally not considering radial sweeps in sensitivity-frequency space that fall into the shaded region. Logistic regression with L1 regularization revealed low sensitivity sweeps that were excluded from the AUC metric used, as shown by the shaded region in Figure 19A. In some embodiments, the AUC metric includes less than 75% (e.g., less than 50%) of the total (e.g., possible) sweeps (e.g., 6 sweeps out of 15). Such a metric can indicate improved sensitivity and can allow for reduced test time. However, it should be noted that some alternative radial sweep metrics do not or only show limited improvement in sensitivity.

[0153] FIG. 19B shows the progression of the AUC metric across different sessions for data from 20 eyes. The first session used no simulated scotoma, the second session used mild simulated scotoma, the third session used severe simulated scotoma, and the fourth session used no simulated scotoma (second time). Comparing the performance of the 20 eyes during the first and fourth sessions (both without simulated scotoma) demonstrated a high degree of reproducibility (shown in the right panel of FIG. 19B). Furthermore, high sensitivity is shown by well-separated box-and-whisker plots for mild and severe simulated scotoma. A receiver operating characteristic plot of the AUC metric was created as shown in FIG. 19C. The left panel of FIG. 19C shows an exemplary ROC plot that is useful for understanding the ROC plots in the center and right panels. Referring to the center and right panels, it can be seen that for both AUC metrics, the separation threshold points are higher for normal and severe scotoma separation than for normal and moderate scotoma separation. Furthermore, the separator threshold point is higher for the sparse AUC metric than for the baseline AUC metric (radial sweep is not considered). The sensitivity at 100% specificity for the sparse AUC metric was 92.5%, but only 90% for the baseline AUC metric, indicating an improvement in the sensitivity of the sparse metric.

[0154] Separating head direction and virtual objects In some embodiments, it is important to separate the object (e.g., a test chart such as an eye chart) from the subject's head pose, e.g., to enable the use of low-cost off-the-shelf VR headsets with low-quality optics (e.g., Fresnel lenses). In some embodiments, the subject can align their central visual field with a particular target (e.g., a contrast-based visibility patch) by rotating their head (and associated headset) to, e.g., align their best vision with the particular target. Allowing such reorientation can increase the reliability of the overall test, e.g., because the test results do not depend on the target spatial location on the virtual and / or augmented scene chart. The subject has the opportunity to increase the perceived optical quality on the test chart (e.g., its borders) simply by rotating their head (e.g., toward the borders of the chart).

[0155] In some embodiments, the method includes rendering and displaying to the subject an object in a virtual and / or augmented scene in the subject's field of view via a virtual reality and / or augmented reality and / or mixed reality device (e.g., a VR headset with eye tracking capabilities). The position of the object may remain fixed in the virtual space (e.g., fixed in the virtual and / or augmented scene) when the subject's head turns. Such an object may remain fixed when the subject reorients his / her head so that the subject can orient the object to a preferred location relative to the subject's gaze point. For example, the subject may orient the object to a location corresponding to the alignment of best vision with the object's region of interest (e.g., a target in a test chart). In some embodiments, a subject translating the device does not move the object relative to the subject in the virtual space. For example, in some embodiments, the subject cannot move closer to or further away from the object (e.g., a chart) in the virtual space. In some embodiments, the object (e.g., when rendered on a head mounted display of a VR headset) is curved (i.e., not flat) to account for reduced peripheral vision due to, for example, the quality of one or more lenses of the device. In some embodiments, the object is a virtual test chart (e.g., an eye chart), e.g., a test chart including one or more targets (e.g., moving targets and / or targets of varying contrast) for functional vision testing. The test chart may be curved (e.g., like a curved piece of paper). The object may be a target that is rendered and displayed as part of the functional vision test. Such a method may, for example, enable the use of low-cost, commercially available VR headsets for vision testing, as it allows the subject to accommodate their inferior optics (e.g., compromising the periphery of the subject's visual field). Such a method may be used during functional vision testing.

[0156] Uses of the methods disclosed herein, including ocular conditions and treatments thereof Disclosed herein are, among other things, methods for performing visual tests (e.g., functional visual tests) (with or without artificial intelligence), simulating scotoma, determining PRL, calibrating a VR headset, and displaying objects (e.g., charts) at fixed positions within a virtual and / or augmented scene (e.g., relative to the subject's head orientation), as well as systems for performing those methods. Any of these methods and / or systems may be used with subjects who have or may have an ocular condition. The ocular condition may be monitored and / or diagnosed using the methods and / or systems. For example, determining the presence, severity, and / or progression of an ocular condition may use any of the methods and / or systems disclosed herein. The ocular condition may be any ocular condition described herein, including, for example, diabetic retinopathy (e.g., with or without diabetic macular retinopathy), Stargardt's disease, Leber's hereditary optic neuropathy (LHON), retinitis pigmentosa, glaucoma, inner nuclear layer disease, geographic atrophy, or age-related macular degeneration (AMD) (e.g., dry age-related macular degeneration (dry AMD), wet age-related macular degeneration (wet AMD), and / or neovascular age-related macular degeneration (neovascular AMD)). One of skill in the art will recognize that other ocular conditions may benefit from applying the methods or systems disclosed herein. The systems and / or methods disclosed herein, such as functional vision tests (with or without artificial intelligence), can be used to determine the therapeutic efficacy (e.g., benefit) of a therapeutic agent and / or therapeutic intervention. Determining therapeutic efficacy may include quantifying quality-adjusted life years (QALYs). Alternatively or additionally, determining the cost-effectiveness of the therapeutic agent and / or therapeutic intervention may be based, at least in part, on determining therapeutic effectiveness based on test results from a method disclosed herein, such as a functional vision test. The cost-effectiveness may be based on a quantification of QALYs. The subject may be treated with a therapeutic agent and / or therapeutic intervention that has been established or confirmed to be therapeutically effective in a population of subjects using the systems and / or methods disclosed herein (e.g., functional vision tests).Treatment with such therapeutic agents and / or therapeutic interventions may maintain or improve performance on a functional visual test and / or reduce the rate of decline in performance on a functional visual test compared to an appropriate control (e.g., no treatment or sham treatment (e.g., placebo)).

[0157] Thus, the methods disclosed herein, such as functional vision tests, can be used as tests (e.g., outcome measures or functional endpoints) for ocular conditions. The tests can inform and / or dictate whether, how (e.g., how much), and / or when (e.g., how often) a treatment, such as a therapeutic agent and / or therapeutic intervention for an ocular condition, is administered. The therapeutic agent and / or therapeutic intervention can then be administered in a therapeutically effective amount. The progression of the ocular condition (e.g., progression of the severity of the ocular condition) can be monitored before and / or after administration of the therapeutic agent and / or therapeutic intervention. The progression can inform and / or dictate further administration of the therapeutic agent and / or therapeutic intervention. The methods disclosed herein can be used to evaluate the therapeutic effectiveness of the therapeutic agent and / or therapeutic intervention for an ocular condition. The subject having the ocular condition can then be treated with the therapeutic intervention and / or therapeutic agent.

[0158] A subject may be treated (e.g., with a therapeutic agent and / or therapeutic intervention) after being diagnosed with an ocular condition using the methods and / or systems disclosed herein, after the subject's ocular condition is monitored using the methods and / or systems disclosed herein, while the subject's ocular condition is monitored using the methods and / or systems disclosed herein, or after the subject is determined to exhibit a worsening severity of an ocular condition using the methods and / or systems disclosed herein. The methods and / or systems may preferably be functional vision tests. The methods and / or systems disclosed herein may be used to diagnose and / or monitor ocular conditions. The therapeutic intervention may be laser coagulation therapy.

[0159] The therapeutic agent administered to treat the ocular condition after diagnosis and / or monitoring and / or determining the severity of the deterioration or during diagnosis can be, for example, (i) a vitamin supplement and / or a mineral supplement selected from the group consisting of vitamin C, zinc, vitamin E, copper, beta-carotene, and combinations thereof, (ii) ranibizumab, (iii) faricimab, (iv) brolucizumab, (v) aflibercept, (vi) pegaptanib, (vii) a complement inhibitor, (viii) a neuroprotectant, (ix) an anti-inflammatory agent, (x) a free radical scavenger, (xi) an anti-apoptotic agent, (xii) an integrin modulating agent, (xiii) a gene therapy, or (xiv) a cell therapy. In some aspects, the therapeutic agent comprises a complement inhibitor. In some embodiments, the complement inhibitor comprises a peptide, protein, antibody, aptamer, or small molecule that binds to and inhibits the activity of a complement component or biologically active fragment thereof (or a complex comprising two or more complement components or biologically active fragments thereof). In some embodiments, the complement component or biologically active fragment thereof is C3, C3a, C3b, C4, C4a, C4b, C5, C5a, C5b, C1, C1q, factor B, or factor D. In some embodiments, the complement inhibitor comprises a nucleic acid, e.g., an siRNA or an antisense oligonucleotide, that inhibits expression of a complement component (e.g., C3, C5, factor B, factor D, or C1). In some aspects, the therapeutic agent is a gene therapy. Gene therapy may inhibit expression of a pathogenic gene product, correct a mutation in a gene, deliver a functional copy of a gene to a cell that has a dysfunctional copy of such a gene, or genetically modify cells in the eye to cause the cells to express a beneficial nucleic acid or protein. In some aspects, the therapeutic agent is a cell therapy. The cells may include, for example, stem cells (e.g., induced pluripotent stem cells), stem cell-derived cells, retinal pigment epithelial cells, or photoreceptor cells. The cells may replace cells lost to disease or support or complement the function of remaining cells.

[0160] Network environment, computing devices, and software for use with various embodiments As shown in FIG. 13, an implementation of a network environment 400 for use in providing the systems and methods described herein is shown and described. Briefly, referring now to FIG. 13, a block diagram of an exemplary cloud computing environment 400 is shown and described. The cloud computing environment 400 can include one or more resource providers 402a, 402b, 402c (collectively 402). Each resource provider 402 can include computing resources. In some implementations, the computing resources can include any hardware and / or software used to process data. For example, the computing resources can include hardware and / or software capable of executing algorithms, computer programs, and / or computer applications. In some implementations, exemplary computing resources can include application servers and / or databases with storage and retrieval capabilities. Each resource provider 402 can be connected to any other resource provider 402 in the cloud computing environment 400. In some implementations, the resource providers 402 can be connected via a computer network 408. Each resource provider 402 can be connected to one or more computing devices 404 a , 404 b , 404 c (collectively 404 ) via a computer network 408 .

[0161] The cloud computing environment 400 may include a resource manager 406. The resource manager 406 may be connected to the resource providers 402 and the computing devices 404 via a computer network 408. In some implementations, the resource manager 406 may facilitate the provision of computing resources by one or more resource providers 402 to one or more computing devices 404. The resource manager 406 may receive a request for a computing resource from a particular computing device 404. The resource manager 406 may identify one or more resource providers 402 that can provide the computing resource requested by the computing device 404. The resource manager 406 may select a resource provider 402 to provide the computing resource. The resource manager 406 may facilitate a connection between the resource provider 402 and the particular computing device 404. In some implementations, the resource manager 406 may establish a connection between a particular resource provider 402 and a particular computing device 404. In some implementations, the resource manager 406 may redirect the particular computing device 404 to a particular resource provider 402 that has the requested computing resource.

[0162] 14 illustrates an example of a computing device 500 and a mobile computing device 550 that can be used to implement the techniques described in this disclosure. The computing device 500 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The mobile computing device 550 is intended to represent various forms of mobile devices, such as personal digital assistants, mobile phones, smartphones, and other similar computing devices. The components illustrated herein, their connections and relationships, and their functions are exemplary only and are not meant to be limiting.

[0163] The computing device 500 includes a processor 502, a memory 504, a storage device 506, a high-speed interface 508 connecting to the memory 504 and a number of high-speed expansion ports 510, and a low-speed interface 512 connecting to a low-speed expansion port 514 and the storage device 506. Each of the processor 502, memory 504, storage device 506, high-speed interface 508, high-speed expansion port 510, and low-speed interface 512 are interconnected using various buses and may be implemented on a common motherboard or in other suitable manners. The processor 502 is capable of processing instructions for execution within the computing device 500, including instructions stored in the memory 504 or storage device 506 for displaying graphical information for a GUI on an external input / output device, such as a display 516 coupled to the high-speed interface 508. In other implementations, multiple processors and / or multiple buses may be used, along with multiple memories and memory types, as desired. Also, multiple computing devices may be connected, with each device providing a portion of the required operations (e.g., as a bank of servers, a group of blade servers, or a multi-processor system). Thus, when the term is used herein where functions are described as being performed by a "processor," this encompasses embodiments in which the functions are performed by any number of processors (one or more) in any number of computing device (one or more). Further, when a function is described as being performed by a "processor," this encompasses embodiments in which the function is performed by any number of processors (one or more) in any number of computing device (one or more) (e.g., in a distributed computing system).

[0164] The memory 504 stores information within the computing device 500. In some implementations, the memory 504 is a volatile memory unit. In some implementations, the memory 504 is a non-volatile memory unit. The memory 504 may also be another form of computer-readable medium, such as a magnetic or optical disk.

[0165] The storage device 506 can provide mass storage for the computing device 500. In some implementations, the storage device 506 can be or include a computer-readable medium such as a floppy disk device, a hard disk device, an optical disk device, or a tape device, a flash memory or other similar solid-state memory device, or an array of devices including devices in a storage area network or other configuration. The instructions can be stored on an information carrier. The instructions, when executed by one or more processing devices (e.g., the processor 502), perform one or more methods as described above. The instructions can also be stored by one or more storage devices, such as a computer or machine-readable medium (e.g., the memory 504, the storage device 506, or a memory on the processor 502).

[0166] The high-speed interface 508 manages the bandwidth-intensive operations of the computing device 500, and the low-speed interface 512 manages the less bandwidth-intensive operations. Such an allocation of functions is merely an example. In some implementations, the high-speed interface 508 is coupled to the memory 504, the display 516 (e.g., via a graphics processor or accelerator), and a high-speed expansion port 510 that can accept various expansion cards (not shown). In this embodiment, the low-speed interface 512 is coupled to the storage device 506 and the low-speed expansion port 514. The low-speed expansion port 514, which can include various communication ports (e.g., USB, Bluetooth, Ethernet, wireless Ethernet), can be coupled, for example, via a network adapter, to one or more input / output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router.

[0167] Computing device 500 may be implemented in a number of different forms, as shown. For example, it may be implemented as a standard server 520, or multiple times in a group of such servers. It may also be implemented in a personal computer, such as a laptop computer 522. It may also be implemented as part of a rack server system 524. Alternatively, components from computing device 500 may be combined with other components in a mobile device (not shown), such as mobile computing device 550. Each such device may include one or more of computing device 500 and mobile computing device 550, and the entire system may be made up of multiple computing devices in communication with each other.

[0168] The mobile computing device 550 includes, among other things, a processor 552, a memory 564, input / output devices such as a display 554, a communication interface 566, and a transceiver 568. The mobile computing device 550 may also include a storage device, such as a microdrive or other device, to provide additional storage. Each of the processor 552, memory 564, display 554, communication interface 566, and transceiver 568 are interconnected using various buses, and some of the components may be mounted on a common motherboard or in other manners as desired.

[0169] The processor 552 can execute instructions within the mobile computing device 550, including instructions stored in the memory 564. The processor 552 may be implemented as a chipset of chips including multiple separate analog and digital processors. The processor 552 can provide coordination of other components of the mobile computing device 550, such as control of a user interface, applications run by the mobile computing device 550, and wireless communication by the mobile computing device 550.

[0170] The processor 552 can communicate with a user via a control interface 558 and a display interface 556 coupled to a display 554. The display 554 can be, for example, a thin-film-transistor liquid crystal display (TFT) display or an organic light emitting diode (OLED) display, or other suitable display technology. The display interface 556 can include appropriate circuitry for driving the display 554 to present graphics and other information to the user. The control interface 558 can receive commands from the user and convert them for submission to the processor 552. Additionally, an external interface 562 can provide communication with the processor 552 to enable short-range communication between the mobile computing device 550 and other devices. The external interface 562 can provide, for example, wired communication in some implementations or wireless communication in other implementations, and multiple interfaces can also be used.

[0171] The memory 564 stores information within the mobile computing device 550. The memory 564 may be implemented as one or more of a computer readable medium, a volatile memory unit, or a non-volatile memory unit. An expansion memory 574 may also be provided and connected to the mobile computing device 550 via an expansion interface 572, which may include, for example, a Single In Line Memory Module (SIMM) card interface. The expansion memory 574 may provide additional storage space for the mobile computing device 550 or may store applications or other information for the mobile computing device 550. In particular, the expansion memory 574 may include instructions for performing or supplementing the processes described above, and may also include secure information. Thus, for example, the expansion memory 574 may be provided as a security module for the mobile computing device 550 and may be programmed with instructions that enable secure use of the mobile computing device 550. Additionally, secure applications may be provided via a SIMM card along with additional information, such as placing specific information on the SIMM card in an unhackable manner.

[0172] The memory may include, for example, flash memory and / or non-volatile random access memory (NVRAM) memory, as described below. In some implementations, the instructions are stored on an information carrier. In some implementations, the instructions, when executed by one or more processing devices (e.g., processor 552), perform one or more methods, such as those described above. The instructions may also be stored by one or more storage devices, such as one or more computer- or machine-readable media (e.g., memory 564, expansion memory 574, or memory on processor 552). In some implementations, the instructions may be received in a propagated signal, for example via transceiver 568 or external interface 562.

[0173] The mobile computing device 550 may communicate wirelessly via a communication interface 566, which may include digital signal processing circuitry as necessary. The communication interface 566 may provide for communication under various modes or protocols, such as Global System for Mobile communications (GSM) voice, Short Message Service (SMS), Enhanced Messaging Service (EMS), or Multimedia Messaging Service (MMS), code division multiple access (CDMA), time division multiple access (TDMA), Personal Digital Cellular (PDC), Wideband Code Division Multiple Access (WCDMA), CDMA2000, or General Packet Radio Service (GPRS), among others. Such communication may occur via a transceiver 568, for example, using radio frequencies. Additionally, short-range communication may occur, such as using Bluetooth, Wi-Fi, or other such transceivers (not shown). Additionally, a GPS (Global Positioning System) receiver module 570 can provide additional navigation- and location-related radio data to the mobile computing device 550 for use as appropriate by applications executing on the mobile computing device 550.

[0174] The mobile computing device 550 can also communicate audibly using a voice codec 560, which can receive voice information from a user and convert it into usable digital information. The voice codec 560 can also generate sounds audible to the user, such as through a speaker in a handset of the mobile computing device 550. Such sounds can include sounds from a voice call, can include recorded sounds (e.g., voice messages, music files, etc.), and can also include sounds generated by applications running on the mobile computing device 550.

[0175] The mobile computing device 550 can be implemented in a number of different forms, as shown in the figure, including as a mobile phone 580, as part of a smartphone 582, a personal digital assistant, or other similar mobile device.

[0176] Various implementations of the systems and techniques described herein may be realized in digital electronic circuitry, integrated circuits, specially designed ASICs (application-specific integrated circuits), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include implementation in one or more computer programs executable and / or interpretable on a programmable system including at least one programmable processor, which may be special-purpose or general-purpose, coupled to receive data and instructions from, and transmit data and instructions to, a storage system, at least one input device, and at least one output device.

[0177] These computer programs (also referred to as programs, software, software applications or codes) contain machine instructions for a programmable processor and may be implemented in a high-level procedural and / or object-oriented programming language and / or in an assembly / machine language. As used herein, the terms machine-readable medium and computer-readable medium refer to any computer program product, apparatus and / or device (e.g., magnetic disk, optical disk, memory, programmable logic device (PLD)) used to provide machine instructions and / or data to a programmable processor, including a machine-readable medium that receives machine instructions as a machine-readable signal. The term machine-readable signal refers to any signal used to provide machine instructions and / or data to a programmable processor.

[0178] A computer program may include software implementing machine learning techniques, e.g., artificial neural networks (ANNs), convolutional neural networks (CNNs), random forests, decision trees, support vector machines, etc., to determine one or more output values ​​for a given input. In some embodiments, a machine learning module implementing machine learning techniques is trained, e.g., using a curated and / or manually annotated dataset. Such training may be used to determine various parameters of the machine learning algorithm implemented by the machine learning module, such as weights associated with layers in a neural network. In some embodiments, once a machine learning module has been trained, e.g., to accomplish a particular task, the values ​​of the determined parameters are fixed (e.g., immutable, static) and the machine learning module is used to process new data (e.g., different from the training data) and accomplish that trained task without further updating its parameters (e.g., the machine learning module does not receive feedback and / or updates). In some embodiments, the machine learning module may receive feedback, e.g., based on user reviews of accuracy, and such feedback may be used as additional training data, e.g., to dynamically update the machine learning module. In some embodiments, the trained machine learning module is a classification algorithm with adjustable and / or fixed (e.g., locked) parameters, e.g., a random forest classifier. In some embodiments, two or more machine learning modules can be combined and implemented as a single module and / or a single software application. In some embodiments, two or more machine learning modules can also be implemented separately, e.g., as separate software applications. The machine learning modules can be software and / or hardware.For example, the machine learning module may be implemented entirely as software, or certain functions of the ANN module may be performed via dedicated hardware (e.g., via an application specific integrated circuit (ASIC), field programmable gate array (FPGA), etc.).

[0179] As used herein, terms such as “image,” “video,” “video stream,” and the like refer to image data (e.g., pixel intensity values, pixel color component values ​​(e.g., RGB, etc.)) used to render a displayed graphical image or a series of graphical images (e.g., a video). In certain embodiments, image data received from a camera or other digital image recording device is processed as two-dimensional (2D) data. In other embodiments, the received image data is transformed or mapped to a three-dimensional (and / or two- and one-half dimensional) location of a model. In other embodiments, the received image data is received as three-dimensional (3D) or two- and one-half dimensional data (e.g., no transformation or mapping is required).

[0180] To provide for user interaction, the systems and techniques described herein can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user, and a keyboard and pointing device (e.g., a mouse or trackball) by which the user can provide input to the computer. Other types of devices can also be used to provide for user interaction. For example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback), and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0181] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or includes middleware components (e.g., an application server), or includes front-end components (e.g., a client computer having a graphical user interface or web browser through which a user can interact with an implementation of the systems and techniques described herein), or includes any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0182] A computing system may include clients and servers. Clients and servers are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0183] In some implementations, the software modules described herein may be separated, combined, or incorporated into single or combined modules. The modules shown in the figures are not intended to limit the systems described herein to the software architectures shown therein.

[0184] Elements of different embodiments described herein can be combined to form other embodiments not specifically described above. Elements can be removed from the processes, computer programs, databases, etc. described herein without adversely affecting their operation. Furthermore, the logic flows depicted in the figures do not require the particular order shown, or sequential order, to achieve desirable results. Various separate elements can be combined into one or more individual elements to perform the functions described herein. In some implementations, the structures, functions, and apparatus of the systems and methods described herein may be combined into one or more individual elements.

[0185] The systems, architectures, devices, methods, and processes of the claimed inventions are intended to encompass variations and adaptations developed using information from the embodiments described herein. Adaptations and / or modifications of the systems, architectures, devices, methods, and processes described herein may be implemented as contemplated by this specification.

[0186] Throughout this specification, when articles, devices, systems, and architectures are described as having, including, or comprising certain components, or processes and methods are described as having, including, or comprising certain steps, it is further contemplated that there are articles, devices, systems, and architectures of the invention that consist essentially of, or consist of, the recited components, and there are processes and methods of the invention that consist essentially of, or consist of, the recited processing steps.

[0187] It should be understood that the steps or order for performing certain operations is not critical so long as the invention remains operable. Moreover, two or more steps or operations may be conducted simultaneously.

[0188] The reference herein to any publication, for example in the Background section, is not an admission that the publication serves as prior art with respect to any of the claims presented herein. The Background section is presented for clarity and is not meant to be a description of prior art with respect to any claim.

[0189] Headings are provided for the convenience of the reader, and the presence and / or placement of headings is not intended to limit the scope of the subject matter described herein.

Claims

1. 1. A method for performing functional vision testing on a subject using a virtual reality and / or augmented reality and / or mixed reality device, comprising: displaying, by a processor of a computing device, one or more targets within a virtual and / or augmented scene within the subject's visual field, rendered to the subject throughout the course of the functional vision test; automatically performing, by the processor, a visibility determination in real time during the course of the functional vision test to automatically identify whether the subject is tracking the one or more targets within the virtual and / or augmented scene, the visibility determination being based, at least in part, on a time-based parameter; and Optionally, calculating and / or displaying test results using said visibility determination, by said processor; A method comprising:

2. performing the visibility determination, determining, by the processor, a point of gaze of the subject in real time; comparing, by the processor, the point of regard to a current spatial position of the one or more targets within the virtual and / or augmented scene using the time-based parameters; The method of claim 1 , comprising:

3. performing the visibility determination, determining, by the processor, a point of gaze of the subject in real time; determining, by the processor, whether the point of regard is aligned with one of the targets in the virtual and / or augmented scene; The method of claim 1 , comprising:

4. performing the visibility determination, determining, by the processor, a point of gaze of the subject in real time; determining, by the processor, whether the subject is tracking one of the targets in the virtual and / or augmented scene using at least one of the time-based parameters; The method of claim 1 , comprising:

5. The method of claim 2 , wherein the time-based parameters each correspond to a period during which the point of gaze is aligned or not aligned with one or more of the one or more targets in the virtual and / or augmented scene.

6. 3. The method of claim 2, comprising automatically adjusting the contrast and / or spatial resolution of one or more of the targets in the virtual and / or augmented scene based on the comparison between the point of gaze and the current spatial position of one or more of the targets in the virtual and / or augmented scene.

7. 2. The method of claim 1, wherein there are multiple targets displayed in the virtual and / or augmented scene within the field of view of the subject, and the time-based parameters include four parameters: (i) a parameter for tracking when the subject's point of gaze is on a specific target among the multiple targets in the virtual and / or augmented scene; (ii) a parameter for tracking when the subject's point of gaze is away from a specific target among the multiple targets in the virtual and / or augmented scene; (iii) a parameter for tracking when the subject's point of gaze is on any target among the multiple targets in the virtual and / or augmented scene; and (iv) a parameter for tracking when the subject's point of gaze is away from all of the multiple targets in the virtual and / or augmented scene.

8. 8. The method of claim 7, wherein the four parameters account for at least 80% of all significant variables used in the functional visual testing.

9. The method of claim 1 , wherein the time-based parameter is asymmetric.

10. 2. The method of claim 1, wherein (i) at least one of the time-based parameters corresponds to the subject tracking one of the targets, (ii) at least one of the time-based parameters corresponds to the subject tracking any of the targets, or (iii) both (i) and (ii).

11. 2. The method of claim 1, comprising automatically adjusting contrast, spatial position, spatial resolution, and / or direction of movement of the one or more targets in the virtual and / or augmented scene during the test using one or more of the time-based parameters.

12. Adjusting the contrast, spatial position, spatial resolution, and / or direction of movement of the one or more targets may include: determining, by the processor, a point of gaze of the subject in real time; automatically adjusting the contrast and / or spatial resolution of the one or more targets in the virtual and / or augmented scene based at least in part on the subject's point of gaze being aligned with the one or more targets according to at least one of the time-based parameters; The method of claim 11 , comprising:

13. The method of claim 1 , wherein the visibility determination is performed using only the time-based parameters.

14. The method of claim 1 , wherein a total of 10 or fewer parameters are used to perform the visibility determination.

15. The method of claim 1 , wherein the one or more targets move and / or change direction of movement within the virtual and / or augmented scene during the functional vision test.

16. The method of claim 1 , wherein the one or more targets vary contrast within the virtual and / or augmented scene during the functional vision test.

17. 2. The method of claim 1, wherein the functional vision test is a test for one or more ocular conditions selected from the group consisting of diabetic retinopathy, Stargardt's disease, Leber's hereditary optic neuropathy (LHON), retinitis pigmentosa, glaucoma, inner nuclear layer disease, geographic atrophy, and age-related macular degeneration (AMD).

18. 10. The method of claim 1, wherein the test result is an outcome measure for an ocular condition.

19. 19. The method of claim 18, wherein the ocular condition is selected from the group consisting of diabetic retinopathy, Stargardt's disease, Leber's hereditary optic neuropathy (LHON), retinitis pigmentosa, glaucoma, inner nuclear layer disease, geographic atrophy, and age-related macular degeneration (AMD).

20. 10. The method of claim 1, wherein the test results indicate the presence, severity, and / or progression of an ocular condition in the subject.

21. The method of claim 1 , wherein the test results include a metric corresponding to the subject's functional vision.

22. 22. The method of claim 21, wherein the metric is a sparse AUC metric.

23. The method of claim 1 , wherein each of the one or more targets is a graphically rendered visibility patch within the virtual and / or augmented scene.

24. The method of claim 1 , wherein the method is performed without the use of artificial intelligence.

25. The method of claim 1 , wherein the test results include a function of contrast sensitivity and spatial frequency (in cycles per degree, CPD).

26. The method of claim 1 , further comprising simulating, by the processor, a scotoma during the functional vision test.

27. 27. Use of (i) a vitamin and / or mineral supplement selected from the group consisting of vitamin C, zinc, vitamin E, copper, beta-carotene, and combinations thereof, (ii) ranibizumab, (iii) faricimab, (iv) brolucizumab, (v) aflibercept, (vi) pegaptanib, (vii) a complement inhibitor, (viii) a neuroprotective agent, (ix) an anti-inflammatory agent, (x) a free radical scavenger, (xi) an anti-apoptotic agent, (xii) an integrin modulating agent, (xiii) a gene therapy, or (xiv) a cell therapy to treat a subject diagnosed with and / or monitored for an ocular condition using the method of any one of claims 1 to 26.

28. 27. Use of a therapeutic agent to treat an individual diagnosed with an ocular condition, wherein the therapeutic efficacy of the therapeutic agent has been established or confirmed in a population of subjects using the method of any one of claims 1 to 26.

29. 29. The use of claim 28, wherein the therapeutic agent comprises (i) a vitamin and / or mineral supplement selected from the group consisting of vitamin C, zinc, vitamin E, copper, beta-carotene, and combinations thereof, (ii) ranibizumab, (iii) faricimab, (iv) brolucizumab, (v) aflibercept, (vi) pegaptanib, (vii) a complement inhibitor, (viii) a neuroprotective agent, (ix) an anti-inflammatory agent, (x) a free radical scavenger, (xi) an anti-apoptotic agent, (xii) an integrin modulating agent, (xiii) a gene therapy, or (xiv) a cell therapy.

30. The use described in claim 28, wherein the eye condition is geographic atrophy and / or age-related macular degeneration (AMD).

31. 27. A system comprising a processor and a memory having instructions stored thereon, the instructions being executable by the processor to perform the method of any one of claims 1 to 26.

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