Detection of eye abnormalities by simultaneously presenting stimuli to both eyes

Abstract

In some embodiments, a wearable device performs a vision test including simultaneously presenting a first eye stimulus to a first eye of a user of the device and a second eye stimulus to a second eye of the user, the first eye stimulus having a display characteristic level greater than the display characteristic level of the second eye stimulus. The display characteristic levels of the first eye stimulus and the second eye stimulus are sequentially increased until feedback information indicates detection of at least one of the first eye stimulus or the second eye stimulus by the user. In response to feedback information indicating such detection by the user, the other stimulus is presented at one or more sequentially increasing display characteristic levels until feedback information indicates detection of the other stimulus. Ocular anomaly information for the user is generated based on the feedback information.

Description

[Technical Field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims the benefit of priority to U.S. Patent Application No. 17 / 816,635, filed August 1, 2022. The contents of the above application are incorporated herein by reference in their entirety. [Background technology]

[0002] background

[0002] Wearable devices can be used to conduct vision tests to determine visual impairments and eye-related conditions by testing the eye's sensitivity to visual stimuli. For example, the wearable device presents visual stimuli on a portion of its display and determines whether the user wearing the wearable device observed the visual stimuli. Each eye is tested to measure each eye's different sensitivity to the visual stimuli. Because movement of one eye generally causes movement of the other eye, visual test stimuli are typically presented to one eye at a time during a vision test to avoid inaccurate test results that are affected by the response of the other eye. Summary of the Invention [Means for solving the problem]

[0003] overview

[0003] Aspects of the present invention relate to a method, apparatus, or system for facilitating ocular abnormality detection. By simultaneously presenting stimuli at different contrast levels (or other different characteristics) to a user's eyes and receiving feedback information from the user indicating detection of the stimuli, the system can determine an ocular abnormality associated with the user's eyes, reducing testing time while maintaining testing accuracy.

[0004]

[0004] While conventional systems for detecting ocular abnormalities may exist, these conventional systems are typically slow, waste valuable computer processing resources, and present only one stimulus to a user's eye at a time when testing for individual conditions specific to each eye. For example, such conventional systems may only be able to test one eye at a time. This may require repeating the test using the same or similar steps for each of the user's eyes, which not only wastes computer processing resources but also increases the test time, potentially resulting in a poor user experience. As described above, particularly when testing individual conditions specific to each eye, conventional systems generally present visual test stimuli to only one eye at a time during a vision test to avoid inaccurate test results that are affected by the response of the other eye (e.g., because eye movement in one eye also moves the other eye).

[0005]

[0005] To solve one or more of the above technical problems, for example, a wearable device can present stimuli to each of the user's eyes simultaneously at different contrast levels, with the contrast levels increasing sequentially, to generate ocular abnormality information based on feedback information.

[0006] In some embodiments, stimuli can be presented simultaneously to a first eye of a user and a second eye of the user, the first eye stimulus having a higher contrast level than the contrast level of the second eye stimulus. The contrast levels of each of the first eye stimulus and the second eye stimulus can be sequentially increased until feedback information indicates detection of at least one of the first eye stimulus or the second eye stimulus by the user. In response to feedback information indicating detection of the first eye stimulus or the second eye stimulus, the other eye stimulus (e.g., an eye stimulus not detected by the user) can be sequentially increased until feedback information indicates detection of the other eye stimulus. Ocular abnormality information can be generated based on the feedback information.

[0007]

[0007] Various other aspects, features, and advantages of the present invention will become apparent from the detailed description of the invention and the accompanying drawings. It should also be understood that both the foregoing general description and the following detailed description are examples only and are not intended to limit the scope of the present invention. As used in this specification and the claims, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Additionally, as used in this specification and the claims, the term "or" means "and / or" unless the context clearly dictates otherwise. Additionally, as used herein, a "portion" refers to some or all (i.e., the entire portion) of a given item (e.g., data) unless the context clearly dictates otherwise. Furthermore, "set" may refer to the singular or plural, so that a "set of items" may refer to one item or multiple items. [Brief explanation of the drawings]

[0008] BRIEF DESCRIPTION OF THE DRAWINGS [Figure 1]

[0008] A system for facilitating visual inspection and collecting feedback information is shown, according to one or more embodiments. [Figure 2A]

[0009] 1 illustrates an exemplary user device used for one or more vision tests, according to one or more embodiments. [Figure 2B] 9 illustrates an exemplary user device used for one or more vision tests, according to one or more embodiments. [Figure 2C] 9 illustrates an exemplary user device used for one or more vision tests, according to one or more embodiments. [Figure 2D] 9 illustrates an exemplary user device used for one or more vision tests, according to one or more embodiments. [Figure 3A]

[0010] 1 illustrates a user's field of view, according to one or more embodiments. [Figure 3B] 1 illustrates a user's field of view, according to one or more embodiments. [Figure 4A]

[0011] 1 illustrates presenting stimuli at one or more locations relative to one or more portions of a user's field of view, according to one or more embodiments. [Figure 4B]

[0011] One or more embodiments illustrate presenting stimuli at one or more locations associated with one or more portions of a user's visual field. [Figure 5]

[0012] 1 is a flowchart illustrating a process for simultaneous visual inspection, according to one or more embodiments. [Figure 6]

[0013] 1 illustrates a predictive model configured to generate ocular anomaly information, according to one or more embodiments. [Figure 7]

[0014] 1 illustrates a system having a testing framework implemented on a computing device and a user device, according to one or more embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0009] Detailed Description

[0015] In the following description, for purposes of explanation, numerous specific details are set forth in order to provide a thorough understanding of embodiments of the present invention. However, those skilled in the art will recognize that embodiments of the present invention may be practiced without these specific details or with equivalent configurations. In other instances, well-known structures and devices are shown in block diagram form in order to avoid unnecessarily obscuring embodiments of the present invention.

[0010]

[0016] FIG. 1 illustrates a system 100 for facilitating visual inspection and collecting feedback information, according to one or more embodiments. As shown in FIG. 1 , the system 100 may include a server 102, a client device 104 (or client devices 104a-104n), or other components. The server 102 may include a stimulus presentation subsystem 123, a feedback collection subsystem 124, a predictive model subsystem 125, or other components. Although not shown, in some embodiments, the client device 104 may also include a stimulus presentation subsystem 123, a feedback collection subsystem 124, a predictive model subsystem 125, or other components. Each client device 104 may include any type of mobile terminal, fixed terminal, or other device. By way of example, the client device 104 may include a user device, a desktop computer, a notebook computer, a tablet computer, a smartphone, a wearable device, or other client device. Users may, for example, utilize one or more client devices 104 to interact with each other, one or more servers, or other components of the system 100. As used herein, "client device," "user device," and "mobile device" may refer to the same device unless the context in which such terms are used dictates otherwise.

[0011]

[0017] It should be noted that while one or more operations are described herein as being performed by particular components of the client device 104, these operations may, in some embodiments, be performed by other components of the client device 104 or other components of the system 100. As an example, while one or more operations are described herein as being performed by components of the client device 104, these operations may, in some embodiments, be performed by components of the server 102. It should also be noted that while one or more operations are described herein as being performed by particular components of the server 102, these operations may, in some embodiments, be performed by other components of the server 102 or other components of the system 100. As an example, while one or more operations are described herein as being performed by components of the server 102, these operations may, in some embodiments, be performed by components of the client device 104. It should be further noted that while some embodiments are described herein with respect to machine learning models, in other embodiments other predictive models (e.g., statistical models or other analytical models) may be used instead of or in addition to machine learning models (e.g., in one or more embodiments, a statistical model replaces the machine learning model, and a non-statistical model replaces the non-machine learning model).

[0012]

[0018] In some embodiments, the system 100 can perform a vision test to detect ocular abnormalities in a user by simultaneously testing the user's left and right eyes. For example, during a vision test, the vision system simultaneously presents corresponding visual stimuli to each eye and measures feedback information to determine whether either eye detects the corresponding stimulus. One of the stimuli is displayed at a greater display characteristic level than the stimulus presented to the other eye, where the display characteristic level may include, for example, a brightness level, a contrast level, a sharpness level, or an opacity level. In some embodiments, a greater display characteristic level may be associated with a lower value. For example, if brightness level is measured in decibels (dB), a lower value such as 5 dB may appear visually brighter to the user as opposed to 10 dB. If the feedback information indicates that neither stimulus is detected, the vision system sequentially increases the display characteristic levels of the stimuli (e.g., until at least one of the stimuli is detected or another criterion is met). The display characteristic levels of the stimuli may be increased in parallel in each step. For example, in each step, a first eye stimulus may be displayed at a greater display characteristic level than a second eye stimulus. As another example, at each step, the first and second eye stimuli may be displayed at increasing display characteristic levels. In response to detection of at least one of the stimuli, the other undetected stimulus may be presented at sequentially increasing display characteristic levels (e.g., until it is detected or other criteria are met). The vision system generates ocular anomaly information for the user based on the display characteristic level at which each eye detected the corresponding stimulus.

[0013]

[0019] While visual testing of a user's eyes individually requires time and resources, testing both eyes simultaneously using one or more of the techniques described herein allows the visual system to perform the visual test more quickly than testing each eye individually. Thus, various implementations of the visual testing techniques described herein can reduce the time and resources spent performing such visual tests.

[0014]

[0020] In some embodiments, the user device 104 communicates with the server 102 by sending and receiving messages over the network 150, and the server 102 may include one or more non-transitory storage media that store program instructions for performing one or more operations, such as generating instructions for a vision test, training a machine learning model, storing or processing ocular anomaly information, or other operations. It should be further noted that while one or more operations are described herein as being performed by a particular component of the system 100, in some embodiments, the operations may be performed by other components of the system 100. For example, operations described in this disclosure as being performed by the server 102 may instead be performed by the user device 104, and program code or data stored on the server 102 may instead be stored on the user device 104 or another client computing device. Similarly, in some embodiments, the server 102 may store program code described as being executed by the user device 104 or perform operations described as being so executed. For example, the server may perform operations described as being performed by the stimulus presentation subsystem 123, the feedback collection subsystem 124, or the predictive model subsystem 125. Additionally, while some embodiments are described herein with respect to machine learning models, other predictive models (e.g., statistical models) may be used instead of or in addition to machine learning models. For example, in one or more embodiments, a statistical model may be used to replace a neural network model to determine ocular abnormalities.

[0015]

[0021] System 100 presents visual stimuli (e.g., shapes, text, or images) on a display of user device 104. Referring to FIGS. 2A and 2B, where user device 204a is a wearable device (e.g., a headset), wearable device 204a may include a housing 243, a left-eye display 241, and a right-eye display 242. Left-eye display 241 and right-eye display 242 may be positioned relative to housing 243 to fit within the user's orbits such that, when wearable device 204a is worn, left-eye display 241 is positioned approximately in front of the user's left eye and right-eye display 242 is positioned in front of the user's right eye. Each of displays 241-242 is configured to present a respective visual stimuli or other image to the user during a vision test.

[0016]

[0022] The wearable device 204a further includes one or more eye-tracking sensors, such as a left eye sensor 244 and a right eye sensor 245. Other embodiments of the wearable device 204a may include a single eye-tracking sensor (e.g., a single eye-tracking sensor 246) or three or more eye-tracking sensors. The sensors may be oriented to face the user's estimated pupil area for gaze tracking or pupil tracking. During a vision test, signals output by the eye-tracking sensors may be processed by the system 100 to detect feedback information including the user's eye response to stimuli presented on the display of the wearable device. Exemplary eye-tracking sensors include a visual spectrum camera, an infrared camera, a photodetector, or an infrared sensor. For example, the eye-tracking sensor may include a camera configured to track pupil movement and determine and track the user's visual axis.

[0017]

[0023] 2C , where the user device is mobile device 204b (e.g., a head-mounted display or other wearable device, a tablet, or other mobile device), the mobile device may include a display that is divided into two portions. That is, the mobile device includes display 250, which may be divided (e.g., by software or hardware) into first display portion 251 and second display portion 252, which may correspond to right-eye and left-eye displays, respectively. In addition, the mobile device may also include one or more eye-tracking sensors, such as eye-tracking sensor 256. As such, the systems and methods described herein are not limited to merely wearable devices, but may also be performed on one or more non-wearable devices.

[0018]

[0024] As yet another example, see FIG. 2D , where the user device is an ophthalmic testing instrument such as refractometer 204c. Refractometer 204c may include housing 264, left eye display 261, and right eye display 262. Left eye display 261 and right eye display 262 may be positioned relative to housing 264 to fit within the user's orbital cavity such that, when refractometer 204c is worn, left eye display 261 is positioned approximately in front of the user's left eye and right eye display 262 is positioned in front of the user's right eye. Each of displays 261-262 is configured to present a respective visual stimulus or other image to the user during a vision test. Refractometer 204c further includes one or more eye-tracking sensors, such as left eye sensor 267 and right eye sensor 268. Other embodiments of refractometer 204c may include a single eye-tracking sensor (e.g., single eye-tracking sensor 266) or three or more eye-tracking sensors.

[0019]

[0025] During or after the operation of a vision test, the system 100 obtains feedback information related to the displayed stimuli, and the feedback information may indicate whether or how the eye responds to one or more stimuli. For example, some embodiments may use the wearable device 104 to collect feedback information including various characteristics associated with the eye. In some embodiments, the feedback information may include an indication of the eye's response to the presentation of dynamic stimuli at a given display location (e.g., the location at which the stimuli are presented). Alternatively, or in addition, the feedback information may include an indication of a lack of response to such stimuli. The response or lack of response may be determined based on one or more eye-related characteristics, such as eye movement, gaze direction, a distance the eye's gaze has moved in the gaze direction, a change in pupil size, user-specific input, etc. In some embodiments, the feedback information may include image data or results based on the image data. For example, some embodiments may obtain an image or a sequence of images (e.g., in video format) of the eye captured during the test operation as the eye responds to the stimuli. The image of the eye may be an image of the retina of the eye, such as an image of the entire retina or a portion thereof, an image of the cornea of ​​the eye, such as an image of the entire cornea or a portion thereof, or another image of the eye.

[0020]

[0026] The system 100 can detect one or more ocular abnormalities of the eye based on feedback information indicating the eye's response to the stimuli and update the associated ocular abnormality information. The ocular abnormality detected by the system 100 can relate to, for example, a visual field defect, a dark adaptation defect, an eye misalignment, or an abnormality in pupil movement or size. For example, some embodiments can use a predictive model to detect a non-responsive visual field region or another ocular abnormality in a portion of the visual field associated with the ocular abnormality. In some embodiments, the region associated with the ocular abnormality can be determined by selecting a location or region of the eye's visual field that does not meet one or more visual acuity criteria. In some embodiments, meeting a set of visual acuity criteria for a visual field location can include determining whether the eye responded to stimuli presented at a display location mapped to the visual field location, where the different stimuli presented can differ in brightness, contrast, color, shape, size, or transparency.

[0021]

[0027] In some embodiments, data used or updated by one or more operations described in this disclosure may be stored in the set of databases 130. In some embodiments, the server 102, the user device 104, or other computing devices associated with the system 100 may access the set of databases to perform one or more operations described in this disclosure. For example, a predictive model used to determine ocular abnormality information may be obtained from the first database 131, which may be used to store the predictive model or parameters of the predictive model. Alternatively or additionally, the set of databases 130 may store feedback information collected by the wearable device 104 or results determined from the feedback information. For example, the second database 132 may be used to store a set of user profiles that includes or links to feedback information corresponding to eye measurement data of users identified by the set of user profiles. Alternatively or additionally, the set of databases 130 may store instructions indicating different types of testing procedures. For example, the third database 133 may store a set of test instructions that cause stimuli to be presented at certain locations on the wearable device 104 and at certain display characteristic levels to test for different types of ocular abnormalities.

[0022]

[0028] According to implementations herein, system 100 tests a user's vision by simultaneously displaying stimuli to both of the user's eyes. During the test, stimuli are presented to each eye simultaneously, with the stimulus presented to one eye displayed at a greater display quality level than the stimulus presented to the other eye. If neither stimulus is detected, the system sequentially increases the display quality level of the stimulus until one is detected. The other undetected stimulus can then be presented at successively increasing display quality levels until it is detected. By testing both eyes simultaneously, system 100 performs the vision test more quickly than testing each eye individually.

[0023]

[0029] Subsystems 123-125

[0024]

[0030] The vision test may be performed based on operations by stimulus presentation subsystem 123, feedback collection subsystem 124, and predictive model subsystem 125. For example, a user device may receive data from server 102 over network 150 and perform the vision test on the user. In some embodiments, the user device may be a desktop computer, a notebook computer, a tablet computer, a smartphone, a wearable device, an eye test device, or other user device. In this manner, the user device may communicate with server 102 to provide feedback information to one or more of subsystems 123, 124, and 125.

[0025]

[0031] In some embodiments, the stimulus presentation subsystem 123 presents the set of stimuli on the user device. For example, the stimulus presentation subsystem 123 can present the set of stimuli on a user interface of the user device. For example, if the user device is a laptop computer, the stimulus presentation subsystem 123 can present the set of stimuli on the display of the laptop computer. Similarly, if the user device is a mobile device, the stimulus presentation subsystem 123 can present the set of stimuli on the display of the mobile device. As another example, if the user device is a wearable device, the stimulus presentation subsystem 123 can present the set of stimuli on the lenses / display of the wearable device. As yet another example, if the user device is an ophthalmic device (or other eye testing device) such as a refractometer, the stimulus presentation subsystem 123 can present the set of stimuli on one or more lenses of the refractometer. The set of stimuli can be presented at locations according to one or more instructions. For example, testing visual characteristics of the peripheral region of the user's vision includes instructions that cause the stimulus presentation subsystem 123 to display stimuli at respective locations on the user device display that correspond to the peripheral region of the user's visual field. Testing the visual properties of the foveal region includes instructing the stimulus presentation subsystem 123 to display stimuli at respective locations on the user device display that correspond to the foveal region of the user's visual field.

[0026]

[0032] For clarity, with reference to FIG. 3A , a user's field of view may represent a spatial region that the user can see. The user's field of view may include one or more angular segments. Each angular segment may relate to at least a portion of the user's field of view. For example, first angular portion 302 may correspond to the central vision of the user's field of view, while second angular portion 304 a and third angular portion 304 b may correspond to the peripheral vision of the user's field of view. It should be noted that this example is illustrative, and one or more of first angular portion 302, second angular portion 304 a, and third angular portion 304 b may overlap by a threshold number of degrees, or may not overlap in some cases. While FIG. 3A illustrates a user's field of view when the user has both eyes open (e.g., can see with both eyes and does not have an ocular defect or other visual impairment), FIG. 3B illustrates a diagram of one of the user's eyes and the corresponding central and peripheral vision portions. For example, first portion 306 may correspond to the central vision of the user's field of view for the user's eye. The second portion 308a may correspond to a peripheral portion of the user's field of vision relative to the user's eye. Similarly, the third portion 308b may correspond to another peripheral portion of the user's field of vision relative to the user's eye. In some embodiments, the peripheral portion of the user's eye may include a central portion of the user's field of vision, while in other embodiments, the peripheral portion of the user's eye may be separate from a portion of the user's central portion of the user's vision.

[0027]

[0033] As an example, referring to FIG. 4A , where the user device is a wearable device, the stimulus presentation subsystem 123 presents a set of stimuli on the wearable device. A left eye stimulus 402a is presented by a left eye display 404a, and a right eye stimulus 402b is presented by a right eye display 404b. The location of the stimuli on each display and the display quality levels of each stimulus may be specified according to instructions for the type of vision test implemented by the system 100. As an example, as shown in FIG. 4A , testing visual characteristics of the foveal region of the user's vision includes instructions for the stimulus presentation subsystem 123 to display left and right eye stimuli at positions on the display 404 corresponding to the foveal region of the user's visual field. As another example, as shown in FIG. 4B , testing visual characteristics of the peripheral region of the user's vision includes instructions for the stimulus presentation subsystem 123 to display left and right eye stimuli at positions on the display 404 corresponding to the peripheral region of the user's visual field. Some types of vision tests may further include instructions for the stimulus presentation subsystem 123 to present stimuli in addition to those described in the test procedures discussed herein. For example, to test the ability of a user's eyes to adapt to darkness, the stimulus presentation subsystem 123 first whitens the field of view with a bright light before presenting visual stimuli against a dark background.

[0028]

[0034] In some embodiments, the stimulus presentation subsystem 123 may determine the display locations of the stimuli by first determining a location or region of a user's visual field of a user device, such as a wearable device. After determining the location or region of the visual field, some embodiments may then use a display field of view map to determine which display locations of the left-eye display 404a and right-eye display 404b to use when displaying each stimulus during a vision test. For example, some embodiments may determine that a previous series of sensor measurements indicated that a first region of the visual field has not yet been tested and select that first region for testing. Further, the visual field locations of the stimuli may include visual field locations that are mapped or associated with the display locations of the stimuli, the mapping or association between the displays and visual field locations being determined by the display field of view map.

[0029]

[0035] The feedback collection subsystem 124 processes the signals obtained from the eye-tracking sensor to record feedback information indicative of the eye's response to a set of stimuli presented on the user device. The feedback collection subsystem 124 can use any combination of rules, statistical analysis, or trained machine learning models to predict whether the user detected the stimuli based on the signals obtained from the eye-tracking sensor. In some implementations, the feedback collection subsystem 124 combines the eye-tracking data with explicit feedback from the user to predict the detection of the stimuli or update a prediction model.

[0030]

[0036] The predictive model subsystem 125 retrieves feedback information from the feedback collection subsystem 124 and stimulus information, such as the location of the stimuli and the display characteristic levels of the displayed stimuli, from the stimulus presentation subsystem 123. Based on the feedback information and the stimulus information, the predictive model subsystem 125 generates ocular anomaly information for the user. In some embodiments, the predictive model subsystem 125 applies one or more rules or trained machine learning models to the feedback information and the stimulus information, which rules or models are configured to output information indicative of whether an ocular anomaly is present and / or the nature of such an ocular anomaly. The predictive model subsystem 125 can provide the stimulus information, the feedback information, and the output ocular anomaly information to the machine learning model to update parameters of the machine learning model to predict ocular anomalies based on new inputs.

[0031]

[0037] 5 is a flowchart illustrating a process 500 for simultaneous ocular abnormality testing of both eyes of a user, according to some embodiments. The process illustrated in FIG. 5 may be performed by system 100. Other implementations of process 500 may include additional, fewer, or different steps, and the steps may be performed in a different order.

[0032]

[0038] In block 502, the feedback collection subsystem 124 obtains feedback information during the vision test, for example, using one or more eye-tracking sensors that track the eyes of the user of the user device 104. The feedback information relates to whether the user detected a stimulus presented on the display of the user device during the vision test.

[0033]

[0039] In block 504, the stimulus presentation subsystem 123 simultaneously presents a first eye stimulus via a first eye display (or a portion of the user device display within the possible field of view of the first eye) and a second eye stimulus via a second eye display (or a portion of the user device display within the possible field of view of the second eye). The first eye stimulus and the second eye stimulus can be presented at similar corresponding positions on the first and second displays or at different positions. For example, in some types of tests, the first and second stimuli are both displayed in regions of the corresponding displays that correspond to the foveal region of the user's vision (e.g., as shown in FIG. 4A). The foveal region of the user's vision may correspond to a position on the first and second displays that may be approximately central to the first and second displays. For example, as shown in FIG. 4A, the right eye stimulus 402b and the left eye stimulus 402a may be presented at a position that corresponds to the foveal region of the user's vision (e.g., approximately central to the first and second displays, respectively). In other types of tests, both the first and second stimuli are displayed in regions of the corresponding displays that correspond to the peripheral regions of the user's vision, such as above, below, left, or right of the foveal region (e.g., as shown in FIG. 4B ). The peripheral regions of the user's vision may correspond to locations on the first and second displays that may be substantially off-center relative to the first and second displays. For example, as shown in FIG. 4B , the right eye stimulus 402b and the left eye stimulus 402a may be presented at locations that correspond to the peripheral regions of the user's vision (e.g., substantially off-center relative to the first and second displays, respectively). In yet other types of tests, one of the stimuli is presented in the foveal region, while the other is presented in the peripheral region. Furthermore, the first and second eye stimuli can each represent a single stimulus (e.g., a single dot) or multiple stimuli (e.g., multiple dots displayed at different locations on the first eye display or the second eye display).Additionally, while Figures 4A and 4B show "right eye stimuli," "left eye stimuli," "right eye displays," and "left eye displays," it should be noted that such use of the terms "right" and "left" is merely exemplary, and either "right" or "left" can be substituted for "first" or "second" according to one or more embodiments.

[0034]

[0040] When presenting the first eye stimulus and the second eye stimulus in block 504, the stimulus presentation subsystem 123 displays the first eye stimulus at a display characteristic level that is higher than the display characteristic level of the second eye stimulus. Exemplary display characteristic levels that can be adjusted by the system 100 include a contrast level (e.g., relative to the background of the user device display), a brightness level, a sharpness level, or a transparency (or opacity) level.

[0035]

[0041] The feedback collection subsystem 124 periodically determines whether the feedback information indicates that the user detected at least one of the stimuli in block 506. For example, if the user's eyes move toward one of the stimuli, the feedback collection subsystem 124 may determine that the user likely observed the stimuli. The system may perform processing on the data generated by the eye tracking sensor to distinguish between eye movements that likely indicate detection of the stimuli and eye movements that are unlikely to indicate detection. For example, if the user's eyes move at least a threshold amount, or if the user's eyes move and remain fixated near the location of one of the stimuli for at least a threshold amount of time, the feedback collection subsystem 124 may classify the eye movement as indicating detection of the stimuli. In other embodiments, the feedback collection subsystem 124 determines that the feedback information indicates detection of the stimuli by applying a trained classifier configured to classify the feedback information as indicating detection of the stimuli or as not indicating detection of the stimuli. In addition to or instead of using feedback from the eye-tracking sensor, system 100 may use explicit feedback from the user (e.g., a button press, hand gesture, or verbal utterance) to determine that the user has observed at least one of the stimuli.

[0036]

[0042] In one use case, if the user device is an eye examination device such as a refractometer, the refractometer may be configured to accept input via one or more buttons. For example, the one or more buttons may be configured to accept explicit user feedback (e.g., via a button press) indicating that the user has observed at least one of the stimuli. As another example, when an ophthalmologist physically views a user's eyes (e.g., during one or more vision tests), the ophthalmologist may determine that at least one of the user's eyes moves in relation to one or more of the presented stimuli. In this manner, the ophthalmologist can use one or more buttons or other input devices to provide feedback information indicating that the user has observed at least one of the stimuli.

[0037]

[0043] If the feedback information does not indicate the detection of a stimulus in block 506, the stimulus presentation subsystem 123 increases the display characteristic level of each stimulus in block 508 and returns to block 504 to simultaneously display the first and second eye stimuli at the increased display characteristic levels. In some implementations, the display characteristic levels of the first and second eye stimuli are increased in parallel in block 508 so that the display characteristic levels of the stimuli increase by the same amount on a linear or logarithmic scale. For example, if the first eye stimulus is initially displayed at a brightness of 24 decibels (dB) and the second eye stimulus is displayed at 28 dB, the system increases the brightness levels of both stimuli by 2 dB to 22 dB and 26 dB, respectively. In each iteration of block 508 in this example, the stimulus presentation subsystem 123 can continue to increase each stimulus by 2 dB. Furthermore, in some implementations, system 100 increases the display characteristic levels simultaneously, while in other implementations, system 100 increases the display characteristic levels at different times (e.g., by first increasing the display characteristic level of the second stimulus and then increasing the display characteristic level of the first stimulus). In some embodiments, each stimulus is displayed sequentially while its display characteristic level is adjusted, e.g., such that the display characteristic level of the stimulus is increased without turning the stimulus off. In other embodiments, one or both stimuli are turned off for a short period of time and then re-displayed at the increased display characteristic level.

[0038]

[0044] If the feedback information indicates that the user detected at least one of the stimuli in block 506, the feedback collection subsystem 124 may store a measurement of the display characteristic level of one or both of the stimuli in block 510. For example, the feedback collection subsystem 124 may store the measurement of the display characteristic level of one or both stimuli in the second database 132. In some embodiments, the feedback collection subsystem 124 may store the measurement of the display characteristic level of the first eye stimulus based on a prediction that a higher display characteristic level of the first eye stimulus means that the first eye stimulus is more likely to be detected than the second eye stimulus. In other implementations, the system 100 applies other rules or models to predict which stimulus is more likely to be observed and stores the display characteristic level of the corresponding stimulus. For example, the system 100 may determine that the first eye stimulus is more likely to be detected if the user's eyes move toward the first eye stimulus, or that the second eye stimulus is more likely to be detected if the user's eyes move toward the second eye stimulus. In another example, the system applies a trained model to predict the observed stimuli based on features such as feedback information, the location of the stimuli relative to the user's eyes, the time each stimulus was displayed, the user's previous visual tests, or other data.

[0039]

[0045] If the user detects at least one of the stimuli, the stimulus presentation subsystem 123 continues to present stimuli other than the stimulus predicted to be detected in block 512. For example, if the first eye stimulus was predicted to be the stimulus to be detected given its high display characteristic level, the system presents the second eye stimulus. If the second eye stimulus was predicted to be the stimulus to be detected (e.g., based on the user's eye movement), the system presents the first eye stimulus. Some implementations of the system stop presenting the detected stimulus in block 512 and present only the other stimulus until feedback information indicates that the user has detected the other stimulus. Other implementations continue to present the detected stimulus below the observed display characteristic level (e.g., so that the user may not see the stimulus presented below the observed display characteristic level). In this way, the system can mitigate any inaccurate feedback information due to simultaneously presenting a stimulus that may already have been detected (e.g., the system can continue to test the other eye that has not yet detected the given stimulus without conflicting feedback information).

[0040]

[0046] In block 514, the feedback collection subsystem 124 determines whether the feedback information indicates that the user detected the other stimulus. The process of determining that the user detected the stimulus may be similar to the process performed with respect to block 506. If the other stimulus is not detected after the threshold time, the stimulus presentation subsystem 123 increases the display characteristic level of the other stimulus in block 516 and returns to block 512 to display the stimulus at the increased display characteristic level.

[0041]

[0047] If the feedback information indicates the detection of the other stimulus at block 514 , the feedback collection subsystem 124 stores a measurement of the detected display characteristic level of the other stimulus at block 518 .

[0042]

[0048] In some embodiments, or after certain test results, system 100 retests the eye corresponding to the stimulus determined to be first detected after the other stimulus is detected in block 520. For example, if system 100 predicts that the first eye stimulus was the stimulus detected in block 506 based on an estimation that a stimulus with a greater display property level is more likely to be detected than the second eye stimulus, stimulus presentation subsystem 123 retests the first eye to confirm that the first eye stimulus was the first detected stimulus. In another example, stimulus presentation subsystem 123 retests the first eye if the second eye detects a stimulus with the same display property level as detected by the first eye to confirm whether the two eyes detected the same stimulus level or whether the second eye (and not the first eye) accidentally observed the first eye stimulus in block 506. If the system decides to retest the eye that first detected the corresponding stimulus, the testing process can proceed in a manner similar to that described above, i.e., the first detected stimulus is again presented at the level at which it was previously determined to be detected, while the second detected stimulus may be turned off or reduced to a display characteristic level below the level at which it was observed. If the first detected stimulus is not detected at that level, the stimulus presentation subsystem 123 sequentially increases the display characteristic level of that stimulus until feedback information indicates that the stimulus has been detected. Once detected, the feedback collection subsystem 124 replaces the stored value of the display characteristic level with the new level at which the user detected the stimulus.

[0043]

[0049] In some embodiments, the feedback collection subsystem 124 can continuously store eye-related characteristic information during one or more steps of the process 500. For example, throughout the vision test or retest, the feedback collection subsystem 124 can store eye-related characteristic information. The eye-related characteristic information can include eye movement, gaze direction, distance the eye's gaze has moved in the gaze direction, changes in pupil size, user-specific input, or other information obtained during the vision test or retest. The feedback collection subsystem 124 can store such eye-related characteristic information in the second database 132 for later retrieval.

[0044]

[0050] In block 522, the system 100 generates ocular anomaly information based on the feedback information. For example, the feedback collection subsystem 124 can use stored measurements of the respective display characteristic levels of the stimuli detected by the first and second eyes to generate the ocular anomaly information. Depending on the location of the stimuli and the level at which the user detected them, the feedback collection subsystem 124 determines characteristics of the user's vision, such as light sensitivity, distortion, or other aberrations associated with one or more of the user's eyes. The system 100 can determine one or more defective visual field portions of the user's visual field (e.g., automatic determination based on feedback associated with the stimuli displayed to the user or other feedback). As an example, the defective visual field portion can be a visual field portion of the user's visual field that does not meet one or more visual criteria (e.g., whether or to what extent the user perceives one or more stimuli, the degree of light sensitivity, distortion, or other aberrations, or other criteria). In some embodiments, the defective visual field portion can be a portion of the user's visual field that matches a visual field defect pattern, such as an area of ​​reduced luminosity, an area of ​​high or low optical aberrations, an area of ​​reduced luminance, or other defective visual field portion.

[0045]

[0051] In some embodiments, the predictive model subsystem 125 can train or configure one or more predictive models to facilitate one or more embodiments described herein. In some embodiments, such models can be used to determine or generate ocular anomaly information. For example, the predictive model can use feedback information, eye characteristic information, or other information to generate ocular anomaly information for one or more eyes of a user. By way of example, such a model can be trained or configured to perform the aforementioned functions by mapping input data and output data to each other in a nonlinear relationship based on learning (e.g., deep learning). Additionally, one or more pre-trained predictive models can be stored in the first database 131. For example, the first database 131 can store multiple pre-trained predictive learning models configured to generate predictions related to a set of entities related to a first entity.

[0046]

[0052] In some embodiments, the predictive model may include one or more neural networks or other machine learning models. As an example, a neural network may be based on a large collection of neural units (or artificial neurons). A neural network may roughly mimic the way a biological brain functions (e.g., with a large cluster of biological neurons connected by axons). Each neural unit of a neural network may be connected to many other neural units of the neural network. Such connections may be constraining or inhibitory in their influence on the activation state of the connected neural units. In some embodiments, an individual neural unit may have a sum function that combines the values ​​of all its inputs together. In some embodiments, each connection (or the neural unit itself) may have a threshold function such that a signal must exceed a threshold before propagating to other neural units. These neural network systems may be self-learning and trained rather than explicitly programmed, and may exhibit significantly superior performance in certain areas of problem solving compared to traditional computer programs. In some embodiments, a neural network may include multiple layers (e.g., signal paths traverse from an earlier layer to a later layer). In some embodiments, backpropagation techniques may be utilized by neural networks, where forward stimuli are used to reset the weights of "forward" neural units. In some embodiments, stimuli and inhibitions for neural networks may be more flexible, with connections interacting in a more chaotic and complex manner.

[0047]

[0053] As an example, with reference to FIG. 6 , the machine learning model 602 can take in input 604 and provide output 606. In one use case, the output 606 can be fed back to the machine learning model 602 as input to train the machine learning model 602 (e.g., alone or in combination with a user's indication of the accuracy of the output 606, a label associated with the input, or other reference feedback information). In another use case, the machine learning model 602 can update its configuration (e.g., weights, biases, or other parameters) based on its evaluation of its prediction (e.g., the output 606) and reference feedback information (e.g., a user's indication of accuracy, a reference label, or other information). In another use case, if the machine learning model 602 is a neural network, the connection weights can be adjusted to accommodate the discrepancy between the neural network's prediction and the reference feedback. In a further use case, one or more neurons (or nodes) of the neural network can require their errors to be sent back to them through the neural network (e.g., backpropagating errors) to facilitate the update process. The connection weight updates can reflect the magnitude of the backpropagated errors, for example, after a forward pass is completed. In this way, for example, the machine learning model 602 may be trained to generate better predictions.

[0048]

[0054] As an example, if the predictive model includes a neural network, the neural network may include one or more input layers, hidden layers, and output layers. The input layer and output layer may each include one or more nodes, and the hidden layer may each include multiple nodes. If the overall neural network includes multiple parts trained for different purposes, there may or may not be an input layer or output layer between the different parts. The neural network may also include different input layers for receiving different input data. Furthermore, in different examples, data may be input to the input layer in different formats and input to individual nodes of the input layer of the neural network in different dimensional formats. In a neural network, nodes in layers other than the output layer are connected to nodes in the subsequent layer by links, for example, to transmit output signals or information from the current layer to the subsequent layer. The number of links may correspond to the number of nodes included in the subsequent layer. For example, in an adjacent fully connected layer, each node in the current layer may have an individual link to each node in the subsequent layer, and in some examples, such a fully connected layer may be later pruned or minimized during training or optimization. In a recurrent structure, a node in a layer may be reinput to the same node or layer at a later time, while in a bidirectional structure, forward and backward connections may be provided. Links, also referred to as connections or connection weights, refer to the hardware-implemented connections or corresponding "connection weights" provided by those connections in a neural network. During training and implementation, such connections and connection weights may be selectively implemented, removed, and modified, thereby generating or obtaining a resultant neural network that can be trained and correspondingly implemented for a trained purpose, such as any of the exemplary recognition purposes listed above.

[0049]

[0055] In some embodiments, the machine learning model 602 may be trained based on information stored in the database 130. For example, the machine learning model 602 may be trained based on feedback information, eye-related characteristic information, or a combination thereof, stored in the second database 132 to generate predictions related to ocular abnormalities present in one or more eyes of a user. For example, the machine learning model 602 may take as input 604 feedback information, such as one or more measurements obtained during a vision test, and generate as output 606 ocular abnormality information related to (or associated with) the feedback information. In some embodiments, the machine learning model 602 may take as input 604 eye-related characteristic information, such as eye movement information of one or more eyes, and generate as output 606 ocular abnormality information related to (or associated with) the eye-related characteristic information. In some embodiments, the output 606 may be fed back to the machine learning model 602 to update one or more configurations (e.g., weights, biases, or other parameters) based on its evaluation of its predictions (e.g., output 606) and reference feedback information (e.g., user indication of accuracy, reference labels, or other information).

[0050]

[0056] Referring again to FIG. 1 as an example, in some embodiments, the predictive model subsystem 125 can provide training data to the predictive model to train the predictive model. For example, in some embodiments, the predictive model subsystem 125 can obtain a predictive model (e.g., a machine learning model) from the first database 131. In such a case, the predictive model subsystem 125 can train a selected predictive model based on feedback information, characteristic information related to the eye, or a combination thereof, stored in the second database 132 to generate predictions related to ocular abnormalities present in one or more eyes of the user. Once the predictive model is trained, the predictive model subsystem 125 can use the predictive model to detect the presence of an ocular abnormality. For example, in some embodiments, the predictive model subsystem 125 can provide eye-tracking data, other feedback information, or a visual field map of the eye to a predictive model (or one or more pre-trained predictive models) trained to detect one or more ocular abnormalities associated with the eye. The predictive model can perform operations to determine an abnormal boundary of the ocular abnormality, such as the shape of a defect area (e.g., a blind spot or other visual defect) in the peripheral region of the eye. Some embodiments may then use the predicted anomaly boundary to determine future field locations for testing. For example, the predictive model subsystem 125 may determine whether the anomaly boundary overlaps with a stimulus boundary of the first display region and present a subsequent stimulus on an adjacent region of the first display region. Some embodiments may then perform additional measurements to update the anomaly boundary of the ocular anomaly based on additional feedback information collected after the presentation of the second stimulus.

[0051]

[0057] The simultaneous visual testing process described with respect to Figure 5 can improve the speed of visual testing. For example, by presenting at least some of the stimuli to the left and right eyes simultaneously, the system presents the stimuli less often and waits for feedback from the user indicating whether the user detected the stimuli. Thus, the visual testing systems described in implementations herein may consume fewer computational, time, or other resources associated with such visual testing.

[0052]

[0058] Aspects of process 500 may be implemented by a vision system 700, an embodiment of which is shown in Figure 7. In some embodiments, with reference to Figure 7, system 100 may include vision system 700 including a vision inspection framework 702. Vision inspection framework 702 may be implemented on an image processor 704 and a wearable device 706 for attachment to a subject. Image processor 704 may be contained entirely within an external image processor or other computer, while in other examples, all or a portion of image processor 704 may be implemented within wearable device 706.

[0053]

[0059] The image processing device 704 may include a memory 708 that stores instructions 710 that, when executed by a processor 712, perform the inspection and / or visualization modes described herein, and may include instructions for collecting feedback information from the wearable device 706. In some embodiments, the wearable device 706 may capture real-time visual field image data as raw data, processed data, or preprocessed data. In some embodiments, the wearable device display of the wearable device 706 may be positioned in front of the eye and may present stimuli such as text, images, or other objects, and the eye's response may be used to generate or update a visual field map for the eye.

[0054]

[0060] The wearable device 706 may be communicatively connected to the image processing device 704 via a wired or wireless link. The link may be via Universal Serial Bus (USB), IEEE 1394 (Firewire), Ethernet, or other wired communication protocol devices. The wireless connection may be via any suitable wireless communication protocol, such as Wi-Fi, NFC, iBeacon, Bluetooth, Bluetooth low energy, etc.

[0055]

[0061] In various embodiments, the image processing device 704 may have a controller operably connected to a database 720 via a link connected to input / output (I / O) circuitry 724. Additional databases may be linked to the controller in known manner. The controller may include a program memory, a processor 712 (which may be referred to as a microcontroller or microprocessor), a random access memory (RAM), and I / O circuitry 724, all of which may be interconnected via an address / data bus. While only one microprocessor is described, it should be understood that the controller may include multiple microprocessors. Similarly, the controller's memory may include multiple RAMs and multiple program memories. The RAM and program memory may be implemented as semiconductor memory, magnetically readable memory, and / or optically readable memory. A link may operably connect the controller to the capture device via the I / O circuitry 724.

[0056]

[0062] The program memory and / or RAM may store various applications (i.e., machine-readable instructions) for execution by the microprocessor. For example, an operating system may generally control the operation of the vision system 700, including the operation of the wearable device 706 and / or image processor 704, and in some embodiments may provide a user interface to the device for implementing the processes described herein. The program memory and / or RAM may also store various subroutines for accessing specific functions of the image processor 704 described herein. By way of example and not limitation, the subroutines may include, among other things, obtaining high-resolution images of the field of view from the eyewear device, enhancing and / or correcting the images, and providing the enhanced and / or corrected images for presentation to the subject by the wearable device 706.

[0057]

[0063] In addition to the above, the image processing device 704 may include other hardware resources. The device may include or be connected to various types of I / O hardware, such as an electronic display 750 and input devices 751, which may include devices such as a keypad, keyboard, etc. In some embodiments, the electronic display 750 may be touch-sensitive and may cooperate with a software keyboard routine as one of the software routines for accepting user input. The image processing device 704 may advantageously communicate with a wider network (not shown) by any of several known networking devices and techniques (e.g., by a computer network such as an intranet, the Internet, etc.). For example, the device may be connected to a database of ocular abnormality data.

[0058]

[0064] The method operations presented in this disclosure are intended to be illustrative and non-limiting. It is contemplated that the operations or descriptions of FIG. 5 may be used with any other embodiment of the present disclosure. Additionally, the operations and descriptions described with respect to FIG. 5 may be performed in alternate orders or in parallel to further the objectives of the present disclosure. For example, each of these operations may be performed in any order, in parallel, or simultaneously to reduce lag or increase the speed of a computer system or method. In some embodiments, the method may be accomplished with one or more additional operations not described and / or without one or more of the operations discussed. Furthermore, the order in which the process operations of the method are illustrated (and described below) is not intended to be limiting.

[0059]

[0065] In some embodiments, the operations described in this disclosure may be implemented by one or more processing devices (e.g., digital processors, analog processors, digital circuits designed to process information, analog circuits designed to process information, state machines, and / or other mechanisms for electronically processing information). A processing device may include one or more devices that perform some or all of the operations of the methods in response to instructions stored electronically on a non-transitory machine-readable medium, such as an electronic storage medium. A processing device may include one or more devices configured with hardware, firmware, and / or software specifically designed to perform one or more of the operations of the methods. It should be noted that any of the devices or apparatus discussed with respect to, for example, FIG. 1, 2A-2D, or 7, may be used to perform one or more of the operations of FIG. 5.

[0060]

[0066] It should be noted that features and limitations described in any embodiment may be applied to any other embodiment herein, and that flowcharts or examples relating to one embodiment may be combined in any suitable manner with any other embodiment, performed in a different order, or performed in parallel. In addition, the systems and methods described herein may be performed in real time. It should also be noted that the systems and / or methods described above may be applied to or used in accordance with other systems and / or methods.

[0061]

[0067] In some embodiments, the various computer systems and subsystems illustrated in FIGS. 1, 2A-2D, or 7 may include one or more computing devices programmed to perform the functions described herein. A computing device may include one or more electronic storage areas (e.g., set of databases 130), one or more physical processors programmed with one or more computer program instructions, and / or other components. A computing device may include communications lines or ports to enable information exchange with a set of networks (e.g., network 150) or other computing platforms via wired or wireless techniques. A network may include the Internet, a cellular network, a mobile voice or data network (e.g., a 5G or LTE network), a cable network, a public switched telephone network, or other types of communications networks or combinations of communications networks. Network 150 may include one or more communications paths, such as Ethernet, satellite paths, fiber optic paths, cable paths, paths supporting Internet communications (e.g., IPTV), free-space connections (e.g., for broadcast or other wireless signals), Wi-Fi, Bluetooth, near-field communication, or any other suitable wired or wireless communications paths or combinations of such paths. A computing device may include additional communication paths linking multiple hardware, software, and / or firmware components operating together. For example, a computing device may be implemented by a cloud of computing platforms operating together as a computing device.

[0062]

[0068] Each of these devices described in this disclosure may also include electronic storage. Electronic storage may include non-transitory storage media that electronically store information. The storage media of electronic storage may include one or both of: (i) system storage provided integrally (e.g., substantially non-removably) with the server or client device; or (ii) removable storage that may be removably connected to the server or client device, for example, via a port (e.g., a USB port, a FireWire port, etc.) or a drive (e.g., a disk drive, etc.). Electronic storage may include one or more of optically readable storage media (e.g., optical disks, etc.), magnetically readable storage media (e.g., magnetic tape, magnetic hard drives, floppy drives, etc.), charge-based storage media (e.g., EEPROM, RAM, etc.), solid-state storage media (e.g., flash drives, etc.), and / or other electronically readable storage media. Electronic storage may include one or more virtual storage resources (e.g., cloud storage, virtual private networks, and / or other virtual storage resources). The electronic storage may store software algorithms, information determined by a processor, information obtained from a server, information obtained from a client device, or other information that enables the functionality described herein.

[0063]

[0069] A processor may be programmed to provide information processing functionality in a computing device. As such, a processor may include one or more of a digital processor, an analog processor, a digital circuit designed to process information, an analog circuit designed to process information, a state machine, and / or other mechanisms for electronically processing information. In some embodiments, a processor may include multiple processing units. These processing units may be physically located within the same device, or a processor may represent the processing functions of multiple devices working in conjunction. A processor may be programmed to execute computer program instructions to perform the functions described herein of subsystems 123-125 or other subsystems. A processor may be programmed to execute computer program instructions by software, hardware, firmware, or any combination of software, hardware, or firmware, and / or other mechanisms for configuring processing capabilities on the processor.

[0064]

[0070] It should be understood that the description of the functionality provided by the different subsystems 123-125 described herein is for illustrative purposes and is not intended to be limiting, as any of the subsystems 123-125 may provide more or less functionality than described. For example, one or more of the subsystems 123-125 may be eliminated, with some or all of its functionality provided by another of the subsystems 123-125. As another example, additional subsystems may be programmed to perform some or all of the functionality attributed herein to one of the subsystems 123-125.

[0065]

[0071] With respect to the components of the computing devices described in this disclosure, each of these devices can receive content and data via input / output (hereinafter "I / O") paths. Each of these devices may also include a processor and / or control circuitry for sending and receiving commands, requests, and other suitable data using the I / O paths. The control circuitry may include any suitable processing, storage, and / or input / output circuitry. Additionally, some or all of the computing devices described in this disclosure may include a user input interface and / or a user output interface (e.g., a display) for use in receiving and displaying data. In some embodiments, a display such as a touchscreen may also function as a user input interface. It should be noted that in some embodiments, one or more devices described in this disclosure may not have a user input interface or a display, but may instead use another device (e.g., a dedicated display device such as a computer screen and / or a dedicated input device such as a remote control, mouse, voice input, etc.) to receive and display content. Additionally, one or more devices described in this disclosure may execute an application (or another suitable program) that performs one or more operations described in this disclosure.

[0066]

[0072] While the present invention has been described in detail for purposes of illustration, based on what are presently considered to be the most practical and preferred embodiments, it should be understood that these details are for that purpose only and that the invention is not limited to the disclosed embodiments, but on the contrary, is intended to cover modifications and equivalent arrangements included within the scope of the appended claims. For example, it should be understood that the present invention contemplates that, to the extent possible, one or more features of any embodiment can be combined with one or more features of any other embodiment.

[0067]

[0073] As used throughout this application, the words "can" and "may" are used in an permissive sense (i.e., meaning that they may), rather than a mandatory sense (i.e., meaning that they must). Words such as "include," "including," and "includes" mean including, but not limited to. As used throughout this application, the singular forms "a," "an," and "the" include plural references unless the context clearly dictates otherwise. Thus, for example, reference to "an element" or "a element" includes a combination of two or more elements, regardless of the use of other terms and phrases for one or more elements, such as "one or more." The word "or" is non-exclusive (i.e., encompasses both "and" and "or") unless the context clearly dictates otherwise. Terms expressing conditional relations (e.g., "in response to X, Y," "when X, Y," "if X, Y," "if X, Y," etc.) encompass causal relations in which the antecedent condition is a necessary causal condition, a sufficient causal condition, or a contributory causal condition of the outcome (e.g., "state X occurs when condition Y holds" is a generic term for "X occurs only because of Y" and "X occurs because of Y and Z"). Such conditional relations are not limited to outcomes that immediately follow from the antecedent holding; some outcomes may be delayed, and in conditional statements, the antecedent condition is related to the outcome (e.g., the antecedent condition is related to the likelihood of the outcome occurring). A statement in which multiple attributes or functions are mapped to multiple objects (e.g., one or more processors perform steps / operations A, B, C, and D) encompasses both all attributes or functions being mapped to all such objects, and a subset of attributes or functions being mapped to a subset of attributes or functions (e.g., both the case where all processors perform each of steps / operations A through D, and the case where processor 1 performs step / operation A, processor 2 performs step / operation B and part of step / operation C, and processor 3 performs part of step / operation C and step / operation D), unless otherwise indicated.Additionally, unless otherwise indicated, a statement that a value or action is "based on" another condition or value encompasses both cases where the condition or value is the only factor and cases where the condition or value is one factor among multiple factors.

[0068]

[0074] Unless the context clearly indicates otherwise, a statement that "each" instance of a set has a certain property should not be read to exclude instances where some otherwise identical or similar member of the larger set does not have the property (i.e., "each" does not necessarily mean "each and every"). Limitations on the order of recited steps should not be read as limitations on the claim unless expressly specified (e.g., by express language such as "perform X after performing Y"), in contrast to language used for claim readability rather than specifying an order and which could be improperly asserted to imply an order limitation (e.g., "perform X on items; perform Y on Xed items"). Language referring to "at least Z of A, B, and C" (e.g., "at least Z of A, B, or C") refers to at least Z of the recited categories (A, B, and C) and does not require at least Z units in each category. Unless the context clearly indicates otherwise, it will be understood that throughout this specification, descriptions utilizing terms such as "processing," "computing," "calculating," "determining," etc., refer to the actions or processes of a particular piece of equipment, such as a special-purpose computer or similar special-purpose electronic processing / computing device. Furthermore, unless otherwise indicated, updating an item may include creating an item or modifying an existing time. Thus, updating a record may include creating a record or modifying the value of a value that has already been created.

[0069]

[0075] The present technique will be more fully understood with reference to the following enumerated embodiments: 1. A method comprising: simultaneously presenting a first eye stimulus for a first eye of a user of a user device (e.g., on a first display / display portion for the first eye) and a second eye stimulus for a second eye of the user (e.g., on a second display / display portion for the second eye) by a user device, wherein the first eye stimulus and the second eye stimulus are each associated with a display characteristic level; sequentially increasing the display characteristic levels of the first eye stimulus and the second eye stimulus until feedback information indicates detection of at least one of the first eye stimulus or the second eye stimulus by the user; in response to feedback information indicating detection of the first eye stimulus by the user, presenting the second eye stimulus at one or more sequentially increasing display characteristic levels (e.g., until feedback information indicates detection of at least the second eye stimulus); and generating ocular abnormality information based on the feedback information. 2. The method of embodiment 1, wherein the first eye stimulus has a display characteristic level that is greater than the display characteristic level of the second eye stimulus. 3. The method of embodiment 1 or 2, wherein the feedback information comprises signals obtained from one or more sensors. 4. The method of embodiment 3, wherein the one or more sensors include one or more eye-tracking sensors. 5. The method of any one of embodiments 1 to 4, wherein feedback information is obtained during a user's visual inspection. 6. The method of any one of embodiments 1 to 5, wherein the first eye stimulus is presented by a first display of the user device and the second eye stimulus is presented by a second display of the user device. 7. The method of any one of embodiments 1 to 6, wherein the first eye stimulus is identified as being detected by the user based on a determined probability. 8. The method of any one of embodiments 1 to 7, wherein the feedback information includes explicit input from the user to confirm detection of the first ocular stimulus or the second ocular stimulus. 9. The method according to any one of embodiments 1 to 8, wherein the display characteristic level comprises a contrast level, a brightness level, a sharpness level, or an opacity level. 10. A method according to any one of embodiments 1 to 9, wherein a first eye stimulus is presented at a first position on a first eye display and a second eye stimulus is presented at a second position on a second eye display corresponding to the first position. 11. The method of embodiment 10, wherein the first location corresponds to the foveal region of the user's vision. 12. The method of embodiment 10, wherein the first location corresponds to a peripheral region of the user's vision. 13. A method according to any one of embodiments 1 to 9, wherein a first eye stimulus is presented at a first position on a first eye display and a second eye stimulus is presented at a second position on a second eye display that does not correspond to the first position. 14. The method of embodiment 13, wherein the first position is one of a peripheral region or a foveal region of the user's vision, and the second position is a position corresponding to the other of the peripheral region or the foveal region of the user's vision. 15. The method of any one of embodiments 1 to 14, wherein increasing the display characteristic level of the first eye stimulus and the display characteristic level of the second eye stimulus comprises increasing the display characteristic level of the first eye stimulus and the display characteristic level of the second eye stimulus at different times. 16. The method of any one of embodiments 1-15, wherein presenting the second eye stimulus at one or more sequentially increasing display characteristic levels comprises presenting the second eye stimulus without the first eye stimulus. 17. A method according to any one of embodiments 1 to 16, wherein presenting the second eye stimulus at one or more sequentially increasing display characteristic levels includes presenting the second eye stimulus while the first eye stimulus is being presented at a display characteristic level below the display characteristic level at which feedback information indicated detection of the first eye stimulus or the second eye stimulus. 18. The method of any one of embodiments 1-17, wherein increasing the display characteristic levels of the first eye stimulus and the second eye stimulus comprises increasing the display characteristic levels by the same amount. 19. The method of any one of embodiments 1 to 18, wherein the user device is at least one of a wearable device, a smartphone, a tablet, a computer, or other eye testing equipment. 20. A method according to any one of embodiments 1 to 19, wherein simultaneous presentation of a first eye stimulus and a second eye stimulus is performed at an initial point in time, a display characteristic level of the first eye stimulus and a sequential increase in the display characteristic level are performed in parallel, and during the parallel sequential increase in the display characteristic level, a user detects a given stimulus of the first eye stimulus or the second eye stimulus at a first point in time, and a display characteristic level for the detected given stimulus at the first point in time is stored. 21. A method according to any one of embodiments 1 to 20, further comprising, after the first time point, continuing to present the other stimulus not detected by the user at one or more sequentially increasing display characteristic levels while the detected given stimulus is no longer presented to the user. 22. The method of embodiment 20 or 21, further comprising, in response to feedback information indicating that the user has detected the other stimulus at a second time point, storing the display characteristic level of the other detected stimulus at the second time point. 23. The method of any one of embodiments 20 to 22, further comprising identifying the first ocular stimulus or the second ocular stimulus as the detected given stimulus based on a determined probability that the first ocular stimulus or the second ocular stimulus was detected at the first time point. 24. The method of any one of embodiments 1 to 23, wherein the first ocular stimulus is identified as the detected given stimulus based on a rule that assigns a greater probability of detection to the first ocular stimulus than to the second ocular stimulus. 25. The method of embodiment 23, further comprising identifying a direction of eye movement based on data obtained from one or more eye tracking sensors, and determining a probability that the first eye stimulus or the second eye stimulus was detected at the first time point based on the identified direction of eye movement at the first time point. 26. The method of any one of embodiments 20 to 22, further comprising, in response to the stored measurements of the display characteristic levels of the first eye stimulus and the second eye stimulus being the same, re-examining the eye corresponding to the detected given stimulus by presenting the detected given stimulus at a third time point. 27. A tangible, non-transitory, machine-readable medium storing instructions that, when executed by a data processing device, cause the data processing device to perform operations including those described in any one of embodiments 1 to 26. 28. A system including one or more processors and a memory storing instructions that, when executed by the processors, cause the processors to perform operations including any one of embodiments 1 to 26.

Claims

1. one or more eye-tracking sensors; a first eye display and a second eye display; One or more processors executing computer program instructions that, when executed, obtaining feedback information during the vision test by the one or more eye-tracking sensors relating to whether a user of the headset detected the presented stimuli; At an initial time point during the visual test, simultaneously presenting a first eye stimulus and a second eye stimulus at a corresponding position of the first eye display and the corresponding position of the second eye display, respectively, wherein the first eye stimulus presented at the initial time point has a contrast greater than a contrast of the second eye stimulus presented at the initial time point; sequentially increasing the contrast of the first eye stimulus and the contrast of the second eye stimulus in parallel until the feedback information indicates that the user has detected at least one of the first eye stimulus or the second eye stimulus, wherein when both the first eye stimulus and the second eye stimulus are presented to the user simultaneously, the contrast of the first eye stimulus remains greater than the contrast of the second eye stimulus throughout the visual test; Responsive to the feedback information indicating that the user's eye detected a given stimulus, the first eye stimulus or the second eye stimulus, at a first time point, storing the measurement of the contrast of the detected given stimulus at the first time point; While the detected given stimulus is not being presented at the corresponding position of the individual display for the detected given stimulus, continuing to present the other of the first eye stimulus or the second eye stimulus at the corresponding position of the individual display for the other stimulus at one or more sequentially increasing contrasts; responsive to the feedback information indicating that the user detected the other stimulus at a second time point, storing the measurement of the contrast of the other detected stimulus at the second time point; generating ocular abnormality information based on the stored measurements; and one or more processors that cause operations including: A headset for detecting ocular abnormalities, including:

2. 2. The headset of claim 1, wherein increasing the contrast of the first eye stimulus and the contrast of the second eye stimulus in parallel comprises simultaneously increasing the contrast of the first eye stimulus and the contrast of the second eye stimulus.

3. 2. The headset of claim 1, wherein increasing the contrast of the first eye stimulus and the contrast of the second eye stimulus in parallel comprises increasing the contrast of the first eye stimulus and the contrast of the second eye stimulus by the same amount but at different times.

4. The computer program instructions: identifying the first ocular stimulus or the second ocular stimulus as the detected given stimulus based on a determined probability that the first ocular stimulus or the second ocular stimulus was detected at the first time point; The headset of claim 1 , further causing an operation including:

5. obtaining feedback information during the visual test via one or more sensors relating to whether a user of the user device detected the presented stimulus; simultaneously presenting a first eye stimulus via a first display of the user device and a second eye stimulus via a second display of the user device during the vision test, the first eye stimulus having a greater contrast than the second eye stimulus; sequentially increasing the contrast of the first eye stimulus and the second eye stimulus until the feedback information indicates detection of at least one of the first eye stimulus or the second eye stimulus by the user; responsive to the feedback information indicating detection of the first eye stimulus by the user, continuing to present the second eye stimulus at sequentially increasing contrasts via the second display until the feedback information indicates detection of the second eye stimulus by the user; generating ocular abnormality information based on the feedback information; A method comprising:

6. 6. The method of claim 5, wherein increasing the contrast of the first eye stimulus and the contrast of the second eye stimulus comprises increasing the contrast of the first eye stimulus and the contrast of the second eye stimulus at different times.

7. 6. The method of claim 5, wherein the first eye stimulus and the second eye stimulus are displayed on the first display and second display, respectively, at locations corresponding to a foveal region of the user's vision.

8. 6. The method of claim 5, wherein the first eye stimulus and the second eye stimulus are displayed on the first display and the second display, respectively, at locations corresponding to peripheral regions of the user's vision.

9. 6. The method of claim 5, wherein one of the first eye stimulus and the second eye stimulus is displayed on the corresponding first display or second display at a position corresponding to a foveal region of the user's vision, and the other of the first eye stimulus and the second eye stimulus is displayed on the corresponding first display or second display at a position corresponding to a peripheral region of the user's vision.

10. 6. The method of claim 5, wherein increasing the contrast of the first eye stimulus and the contrast of the second eye stimulus comprises simultaneously increasing the contrast of the first eye stimulus and the contrast of the second eye stimulus.

11. identifying the first eye stimulus as detected by the user further based on the determined probability; The method of claim 5 further comprising:

12. When executed by one or more processors: simultaneously presenting, by a user device, a first eye stimulus for a first eye of a user of the user device and a second eye stimulus for a second eye of the user, the first eye stimulus having a display characteristic level greater than a display characteristic level of the second eye stimulus; Sequentially increasing the display characteristic levels of the first eye stimulus and the second eye stimulus until feedback information indicates detection of at least one of the first eye stimulus or the second eye stimulus by the user; responsive to the feedback information indicating detection of the first eye stimulus by the user, presenting the second eye stimulus at one or more sequentially increasing display characteristic levels until the feedback information indicates detection of at least the second eye stimulus; generating ocular abnormality information based on the feedback information; A non-transitory computer-readable medium storing executable instructions that cause operations to be performed.

13. The non-transitory computer-readable medium of claim 12 , wherein the feedback information comprises signals obtained from one or more eye-tracking sensors.

14. 13. The non-transitory computer-readable medium of claim 12, wherein the feedback information comprises explicit input from the user to confirm detection of the first eye stimulus or the second eye stimulus.

15. The non-transitory computer-readable medium of claim 12 , wherein the display characteristic level comprises a contrast level, a brightness level, a sharpness level, or an opacity level.

16. 13. The non-transitory computer-readable medium of claim 12, wherein the first eye stimulus is presented at a first position on a first eye display and the second eye stimulus is presented at a second position on a second eye display corresponding to the first position.

17. 13. The non-transitory computer-readable medium of claim 12, wherein the first eye stimulus is presented at a first position on a first eye display and the second eye stimulus is presented at a second position on a second eye display that does not correspond to the first position.

18. 13. The non-transitory computer-readable medium of claim 12, wherein presenting the second eye stimulus at the one or more sequentially increasing display characteristic levels comprises presenting the second eye stimulus without the first eye stimulus.

19. 13. The non-transitory computer-readable medium of claim 12, wherein presenting the second eye stimulus at the one or more sequentially increasing display characteristic levels comprises presenting the second eye stimulus while the first eye stimulus is presented at a display characteristic level below the display characteristic level at which the feedback information indicated detection of the first eye stimulus or the second eye stimulus.

20. 13. The non-transitory computer-readable medium of claim 12, wherein increasing the display characteristic levels of the first eye stimulus and the second eye stimulus comprises increasing the display characteristic levels by the same amount.

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