Vision screening equipment and methods

Abstract

This article describes a vision screening system for testing a patient's vision. The vision screening system may include a vision screening device configured to perform multiple vision screening tests. For example, the system may be configured to determine or generate a graphical representation for display to a patient through a vision screening device to assess the health of the patient's vision and / or detect abnormal vision behavior. The system may be configured to evaluate image / video data recorded by the vision screening device to determine measurements associated with the patient during the vision screening. The system may be configured to analyze the measurements to generate diagnostic recommendations associated with the patient's vision. The system may also be configured to display recommendations and / or measurements together with additional screening data to a tester performing a vision test.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application is a non-provisional application of and claims priority to U.S. Provisional Application No. 62 / 711,461, filed on July 27, 2018, entitled “VISION SCREENING APPARATUS AND METHODS,” the entire disclosure of which is incorporated herein by reference. Technical Field

[0003] The present application relates to medical devices, and in particular, to vision screening devices configured to determine refractive error, cohesion, visual acuity and / or other vision screening parameters. Background Art

[0004] Vision screening for children and adults typically includes one or more tests to determine various defects associated with the patient's eyes. These tests may include, for example, a refractive error test, a cohesion test, an accommodation test, a visual acuity test, etc. Although one or more of the above tests may be related, each test has a corresponding purpose. For example, a visual acuity test typically relies on having a person read characters printed on a Snellen chart at a given distance. The person's visual acuity depends on the size of the characters on the chart that they can discern. The test typically starts with having a person read the top, largest characters while covering one eye. The person then continues to read each character in each row until they can no longer discern the characters. The process is repeated with the other eye. A person with "normal vision" of 20 / 20 will read about 30 characters on the Snellen chart in each test.

[0005] Although various vision screening devices exist, these devices are often cumbersome and complex to use. As a result, vision screening determinations made using these devices may lack accuracy and consistency. Additionally, while these devices may be designed to perform one of the above tests, such devices are typically not configurable to perform multiple vision screening tests. As a result, these devices lack versatility.

[0006] Various exemplary embodiments of the present invention are directed to overcoming one or more deficiencies associated with known vision screening devices. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The features, characteristics and various advantages of the present invention may be more apparent by studying the following detailed description in conjunction with the accompanying drawings.

[0008] Figure 1 An exemplary environment for vision screening is shown in accordance with some embodiments.

[0009] Figure 2 An exemplary server computing device of an exemplary vision screening device that may be used for vision screening in accordance with some implementations is shown.

[0010] Figure 3 An example server computing device of an exemplary vision screening system that may be used for vision screening in accordance with some implementations is shown.

[0011] Figure 4A A perspective view of an example of a vision screening device according to some implementations is shown.

[0012] Figure 4B Another perspective view of an example of a vision screening device according to some implementations is shown.

[0013] Figure 5 An exemplary spaghetti block diagram is shown in accordance with some implementations.

[0014] Figure 6 An exemplary graphical representation displayed during a vision screening is shown in accordance with some embodiments.

[0015] Figure 7 and 8 An exemplary flow chart for vision screening according to some embodiments is shown.

[0016] In the drawings, the leftmost digit(s) of a reference number identifies the drawing in which the reference number first appears. The use of the same reference number in different drawings indicates similar or identical items or features. The drawings are not drawn to scale. DETAILED DESCRIPTION

[0017] The technology described herein relates in part to a vision screening system. Such an exemplary vision screening system can be configured to perform one or more vision tests on a patient and output the results of the vision test to a user of the device, such as a physician or a physician's assistant. For example, the vision screening system can generate one or more graphical representations, such as text paragraphs or dynamic images, to display to the patient. While the patient is viewing the graphical representation, the system can collect one or more measurements associated with the patient's eyes, such as the diameter of the lens of the eye, the position of the pupil, or the patient's gaze. In this way, the result may include one or more measurements detected throughout the vision screening test. In addition, the system can generate patient-related suggestions and / or diagnoses to display to the tester.

[0018] As is well known, conventional vision screening techniques are typically performed by an individual, such as a physician or other person qualified to perform vision screening tests (e.g., a nurse, technician, etc.). For example, a physician may show a visual, such as a light or a Snellen chart, to a patient, and may observe the eye's response to the visual (e.g., observing how the patient's pupil dilates or contracts, determining the patient's gaze direction, etc.) and / or ask the patient to interact with the visual (e.g., reading letters on a Snellen chart). In these examples, the physician may rely on the patient to provide accurate feedback and / or may rely on their own ability to observe the response of different parts of the eye to the visual. For example, the physician may simply observe the dilation and contraction of the pupil in response to light, or observe the degree to which the eye follows the light as it moves.

[0019] Because these tests rely on patient feedback and / or observation of the individual performing the vision screening test, the results are often unreliable and inaccurate. For example, if the physician is manually monitoring or observing how the patient's pupil tracks the visual object, the test results may not be completely accurate. In addition, there is no record of the patient's responses, so it may not be possible to accurately track the patient's vision quality over time.

[0020] Furthermore, as described herein, conventional systems are generally not configured to perform multiple vision screening tests or record multiple types of measurements, produce different results, etc. For example, a conventional system may be configured to provide only a refraction measurement to a patient, and additional systems or devices may be required to perform additional tests and collect additional information about the patient's eye health. However, the techniques for vision screening described herein help provide more accurate, reliable, and valid vision screening tests for patients and individuals undergoing screening.

[0021] The techniques and systems described herein allow for more effective vision screening while achieving more accurate results. For example, the systems discussed herein are configured to perform multiple dynamic vision screening tests. In some embodiments, the system can be configured to generate different types of graphical representations or vision stimuli to record multiple types of measurements related to a patient's vision. In this way, the system can provide different types of information about a patient's vision and eye health without the need for multiple devices.

[0022] In addition, the system described herein is configured to record different types of vision screening tests to determine more accurate measurements related to the behavior of the patient's eyes. For example, the system described herein can be configured to track the movement of the patient's pupils to determine the pupil behavior and the direction of the patient's gaze in response to a graphic displayed during the vision screening test. In this way, the system can provide accurate, recorded measurements of eye behavior throughout the vision screening test and provide the measurements to the individual undergoing the vision screening. By recording the measurements and generating corresponding video data, the patient's vision health status can be tracked over time to provide more accurate and timely diagnostic recommendations.

[0023] Further, the systems described herein can be configured to provide diagnostic recommendations to individuals undergoing vision screening. For example, by utilizing standard test data and / or machine learning techniques, the system can evaluate the measurements determined by the system to provide recommendations to the individual regarding the patient's vision (e.g., whether the patient passes the test, whether additional screening is needed, etc.). In this way, the systems described herein can provide automated diagnostic recommendations more efficiently and accurately.

[0024] In the example described below, the system can determine or access patient data related to patients participating in vision screening tests. For example, patient data may include data provided by the patient or data accessed from a patient profile. Patient data may include demographic information (e.g., age, race, gender, etc.), physical characteristics of the patient (e.g., height), etc. In the example, patient data may include information determined by the vision screening system. For example, the vision screening system may include a device that can record audio / video data related to the patient at the beginning of the screening, which audio / video data can be used to determine data related to the patient, such as height, the position of the patient's eyes, and the distance of the patient from the screening device, etc. In addition, a user (such as a tester or a person operating a vision screening device) can provide or input information to the system during the vision screening. Further, patient data can be imported into the system from a database that stores patient data locally or remotely.

[0025] In an example, the system can identify a test category associated with the patient based on the patient data, or identify the patient. For example, based on the patient's age, height, or gender, the system can determine a category associated with the patient. Based on the test category, the system can generate an appropriate graphical representation to display to the patient during a vision screening. For example, if the patient data indicates that the patient is a toddler, the system can generate a graphical representation of a toddler for the patient's age, height, gender, etc. for vision screening. The graphical representation can be configured to cause visual or eye fatigue in the patient during a vision screening test. For example, the graphical representation can include light stimulation, augmented or virtual reality displays, depictions, text, etc.

[0026] The system can determine one or more measurements related to the patient's vision, such as measurements related to the patient's eyes. For example, the system can determine the patient's gaze direction, the position of the patient's pupil, accommodation or adjustability associated with the lens, movement of the eye, etc. throughout the vision screening. As an example, a graphical representation including a moving graphic can be displayed to the patient. As the graphic moves, the direction of the patient's gaze can be tracked and used to determine the position of the patient's pupil at different points in time while viewing the graphic.

[0027] In an example, the system may compare the measured value to a known standard or predetermined measured value associated with normal vision health or behavior. For example, a known threshold of normal eye behavior associated with the presented graphical representation and / or a test category associated with the patient may be compared to the determined measured value to determine whether the patient's eyes are functioning according to the known standard. Based on whether the measured value meets the known threshold and / or is within the threshold, the system may generate a diagnostic recommendation associated with the patient. For example, if the measured value meets the known threshold, the system may generate a recommendation indicating that the patient has passed the vision screening. If the measured value does not meet the known threshold, the system may generate a recommendation including an indication that the patient has not passed the screening or a diagnostic indication, or generate a recommendation for additional screening. In an example, the system may also utilize one or more machine learning techniques to generate diagnostic recommendations. The recommendation, together with the measured value, may be presented to the tester through an interface of the device.

[0028] In other examples, the system can also generate audio and / or video data related to vision screening. For example, the system can record the patient during the vision screening, and the video data can be used to determine one or more measurements and / or generate additional video data. As an example, the system can use the patient's video data to generate one or more data points related to the position of the patient's pupil at the time point of the observation graphic representation during the screening. Then, the system can generate additional video data including a graphic representation and one or more vision indicators indicating the position of the pupil in the entire vision screening test. In this way, the tester can watch the video data and / or additional video data at any time after the vision screening is completed. In this way, users such as testers, doctors, etc. can use video data to monitor the patient's vision health and make active diagnostic suggestions.

[0029] Reference below Figure 1-8 It should be understood that although these figures describe exemplary environments and devices that can utilize the claimed technology, these technologies can be equally applied to other environments, devices, etc.

[0030] Figure 1 An exemplary environment for vision screening according to some embodiments is shown. Figure 1As shown, environment 100 includes a tester 102 who performs a vision screening on a patient 106 via a vision screening device 104 to determine the vision health of the patient 106. As described herein, the vision screening device 104 can perform one or more vision screening tests to determine one or more measurements associated with the patient 106, and provide the measurements to a vision screening system 110 via a network 108 for analysis. In response, the vision screening system 110 can analyze the measurements to diagnose the vision health of the patient 106. It should be understood that although Figure 1 One system, vision screening system 110, is depicted, but environment 100 may include any number of systems configured to operate independently and / or in combination and configured to communicate with each other via network 108. Components of vision screening system 110 may be described in detail below.

[0031] In an example, the vision screening system 110 may include one or more processors 112, one or more network interfaces 114, and a computer-readable medium 116. The computer-readable medium 116 may store one or more functional components executable by the processor 112, such as a patient data component 118, a graphical representation component 120, a measurement data component 122, a threshold data component 124, and / or a diagnostic suggestion component 126. At least some components, modules, or instructions of the computer-readable medium 116 may be described below.

[0032] In an example, the vision screening device 104 may include a fixed or portable device configured to perform one or more vision screening tests on the patient 106. For example, the vision screening device 104 may be configured to perform a visual acuity test, a refractive error test, an accommodation test, a dynamic eye tracking test, and / or any other vision screening test configured to evaluate and / or diagnose the vision health of the patient 106. Due to its fixed or portable nature, the vision screening device 104 may perform vision screening tests in any location, from traditional screening environments (e.g., schools and medical clinics) to remote and / or mobile locations.

[0033] As described herein, the vision screening device 104 and / or the vision screening system 110 may be configured to perform accommodation and refractive error testing on the patient 106. For example, the refractive error and accommodation testing may include displaying visual stimuli, such as lights or graphical representations, configured to induce fatigue to the eyes of the patient 106. In response, the vision screening device 104 may detect the pupil and / or lens of the eye of the patient 106, acquire images and / or video data of the pupil / lens, etc., and may send the vision screening data to the vision screening system 110 via the network 108 for analysis. Alternatively or additionally, the vision screening device 104 may perform the analysis locally.

[0034] In an example, the vision screening device 104 can be configured to perform a visual acuity test and / or a dynamic eye tracking test. For example, the vision screening device 104 and / or the vision screening system 110 can be configured to perform a visual acuity test that includes determining an optotype, determining the distance of the patient 106 from the vision screening device 104, and / or displaying a dynamic optotype to the patient 104. The dynamic eye tracking test can include generating a graphical representation, such as a graphical scene or text, for display to the patient 106, and monitoring the movement of the eye, acquiring images and / or video data of the eye, etc., and the vision screening data can be sent to the vision screening system 110 via the network 108 for analysis. Alternatively or additionally, in some examples, the vision screening device 104 can analyze the vision screening data locally.

[0035] In an example, the patient data component 118 can be configured to store and / or access data related to the patient 106. For example, the patient 106 can provide data, such as patient data 128, when starting a vision screening test. For example, when the vision screening device 104 and / or the vision screening system 110 initiates a vision screening test, the patient 106 can provide or the tester 102 can request patient data 128 about the patient's demographic information, physical characteristics, and preferences. For example, the patient 106 can provide demographic information such as name, age, race, etc. The patient 106 can also provide physical characteristic information such as the height of the patient 106. In these examples, the tester 102 can request data while the screening is ongoing or before the screening begins. In some examples, the tester 102 can be provided with predetermined categories related to the patient 106, such as a predetermined age range (e.g., six to twelve months, one to five years old, etc.), and the patient data 128 can be requested to select an appropriate category related to the patient 106. In other examples, the tester 102 can provide free-form input related to the patient data 128. In other examples, input elements may be provided directly to patient 106 .

[0036] Alternatively or additionally, the vision screening device 104 and / or the vision screening system 110 may determine and / or detect patient data 128 during the vision screening test. For example, the vision screening device 104 may be configured to generate image and / or video data associated with the patient 106 at the start of the vision screening test. For example, the vision screening device 104 may include one or more digital cameras, motion sensors, proximity sensors, or other image capture devices configured to collect image and / or video data of the patient 106, and one or more processors of the vision screening device 104 may analyze the data to determine the patient data 128, such as the height of the patient 106 or the distance of the patient 106 from the screening device. For example, the vision screening device 104 may be equipped with a rangefinder, such as an ultrasonic rangefinder, an infrared rangefinder, and / or any other proximity sensor capable of determining the distance of the patient 106 from the screening device.

[0037] Alternatively or additionally, the vision screening device 104 may be configured to transmit the image / video data to the vision screening system 110 via the network 108 for analysis to determine the patient data 128. For example, the vision screening device 104 may transmit the image / video data to the vision screening system 110, and the patient data component 118 may be configured to analyze the data to determine the patient data 128. Further, the patient data component 118 may be configured to receive, access and / or store patient data 128 associated with the patient 106 and / or other patients. For example, the patient data component 118 may store previous patient information associated with the patient 104 and / or other patients who have used the vision screening system 110. For example, the patient data component 118 may store previous patient preferences, screening history, etc. The patient data component 118 may receive the patient data 128 and / or may access such information via the network 108. For example, the patient data component 118 may access an external database, such as a screening database 130, that stores data associated with the patient 106 and / or other patients. For example, the screening database 130 can be configured to store stored patient data 128 associated with a patient ID. When the tester 102 and / or the patient 106 enters a patient ID, the patient data component 118 can access or receive the stored patient data 128 associated with the patient ID and the patient 106.

[0038] Further, the computer-readable medium 116 can store a graphical representation component 118. The graphical representation component 118 can be configured to generate or determine a graphical representation for display to the patient 106 via the vision screening device 104 during the vision screening process. For example, the graphical representation component 118 can be configured to receive and / or access patient data 128 from the patient data component 118 to determine a graphical representation for generation and / or display to the patient 106. As an example, the graphical representation component 118 can utilize the patient data 128 to determine a test category (e.g., a test category based on age, height, etc.) to which the patient 106 belongs. Based on the patient data 128, the test category, and / or the vision screening to be performed, the graphical representation component 118 can determine an existing graphical representation or generate a graphical representation for display to the patient 106.

[0039] For example, the patient data 128 may indicate that the patient 106 is an infant between the ages of six and twelve months. Based on this information, the graphic representation component 118 may access one or more locally or remotely stored graphic representations associated with a test category of six to twelve months. Alternatively or additionally, the graphic representation component 118 may be configured to generate a graphic representation configured to fatigue the vision of the patient 106. Further, the graphic representation component 118 may be configured to determine a graphic representation for display based on a vision screening test to be performed. In some examples, the graphic representation component 118 may determine a graphic representation for display based on more than one element of the patient data 128 and / or more than one test category. For example, the graphic representation component 118 may be configured to determine a graphic representation for display based on age and gender data.

[0040] The computer readable medium 116 may additionally store a measurement data component 120. The measurement data component 120 may be configured to receive, access, and / or analyze test data collected and / or detected by the vision screening device 104 during the vision screening. For example, the measurement data component 120 may be configured to receive, via the network 108, video data of the patient 106 generated by the vision screening device 104 during the vision screening and when the graphical representation is displayed. The measurement data component 120 may analyze the video data to determine one or more measurements associated with the patient 106, such as the patient's gaze throughout the screening period, the position of the patient's pupil at the point in time when the graphical representation is viewed, the diameter of the pupil, the accommodation of the lens, motion information associated with the eye of the patient 106, and the like. Alternatively or additionally, the measurement data component 120 may be configured to receive and / or access measurement data determined locally by the vision screening device 104.

[0041] Further, the computer-readable medium 116 can be configured to store a threshold data component 124. The threshold data component 124 can be configured to receive, access and / or analyze threshold data associated with standard test results. For example, the threshold data component 124 can be configured to access or receive a third-party database storing test data and / or measurements, or access or receive a series of values ​​indicating a threshold value and in which the test value should be located, which is associated with a patient with normal vision health with similar test conditions. For example, for each test category, standard test data can be accessed or received by the threshold data component 124, and can be used to compare with the measurement data stored by the measurement data component 122. For example, when each graphic is displayed for a toddler, the threshold data associated with the toddler test category can include a standard pupil measurement value, and / or a value (e.g., a standard value range) of a threshold range that the test value should not exceed or be below. For example, when testing the adaptability of the patient 106, the threshold data component 124 can be configured to store information related to the amplitude (e.g., Donder's Table) of adaptability and age.

[0042] Alternatively or additionally, the threshold data component 124 can be configured to utilize one or more machine learning techniques to determine the threshold data associated with each test category and / or graphical representation. For example, the threshold data component 124 can access and / or receive historical vision screening data from the screening database 130, and can utilize the data to train one or more machine learning models to determine the standard test value for each test category. For example, a machine learning component (not shown) of the threshold data component 124 can execute one or more algorithms (e.g., decision trees, artificial neural networks, association rule learning, or any other machine learning algorithm) to train the system to determine one or more thresholds based on historical vision screening data. In an example, the machine learning component can execute any type of supervised learning algorithm (e.g., nearest neighbor, naive Bayes, neural network, unsupervised learning algorithm, semi-supervised learning algorithm, reinforcement learning algorithm, etc.).

[0043] The computer-readable medium 116 may additionally store a diagnostic suggestion component 126. The diagnostic suggestion component 126 may be configured to receive, access and / or analyze measurement data from the measurement data component 122 and / or threshold data from the threshold data component 124 for comparison. For example, the diagnostic suggestion component 126 may utilize learned or otherwise determined threshold data to compare with the measurement data to determine whether the patient 106 exhibits normal vision behavior. For example, if the pupil diameter measurement detected by the vision screening device 104 in response to the graphical representation is within a threshold of a learned or known (e.g., preset) standard value for patients of the same test category (e.g., if the measurement falls within the standard value), the diagnostic suggestion component 126 may generate a recommendation indicating that the patient 106 has passed the vision screening. Alternatively, if the pupil diameter measurement falls outside the standard value range, the diagnostic suggestion component 126 may generate a recommendation indicating that the patient 106 has failed the vision screening test and / or indicating that the patient 106 should undergo additional screening.

[0044] As used herein, network 108 is generally any type of wireless network or other communication network known in the art. Examples of network 108 include the Internet, an intranet, a wide area network (WAN), a local area network (LAN), and a virtual private network (VPN), a cellular network connection, and connections using protocols such as 802.11a, b, g, n, and / or ac. U.S. Patent Application No. 9,237,846, filed on February 17, 2012, describes systems and methods for photorefractive eye screening, the disclosure of which is incorporated herein by reference in its entirety.

[0045] As described herein, a processor such as processor 112 may be a single processing unit or multiple processing units, and may include a single or multiple computing units or multiple processing cores. Processor 112 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, and / or any device that manipulates signals based on operational instructions. For example, processor 112 may be one or more hardware processors and / or logic circuits of any suitable type that are specifically programmed or configured to perform the algorithms and processes described herein. Processor 112 may be configured to retrieve and execute computer-readable instructions stored in computer-readable medium 116, which may instruct processor 112 to perform the functions described herein.

[0046] The computer-readable medium 116 may include volatile and non-volatile memory and / or removable and non-removable media implemented in any type of technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Such computer-readable media 116 may include, but are not limited to, RAM, ROM, EEPROM, flash memory or other storage technology, optical storage, solid-state storage, magnetic tape, disk storage, RAID storage systems, storage arrays, network attached storage, storage area networks, cloud storage, or any other medium that can be used to store the desired information and can be accessed by a computing device. Depending on the configuration of the electronic negotiation system 110, the computer-readable medium 116 may be a type of computer-readable storage medium and / or may be a tangible, non-transitory medium, to the extent that reference to non-transitory computer-readable media excludes media such as energy, carrier signals, electromagnetic waves, and signals themselves.

[0047] The computer-readable medium 116 may be used to store any number of functional components that may be executed by the processor 112. In many implementations, these functional components include instructions or programs that may be executed by the processor 112, and when the instructions or programs are executed, the instructions or programs specifically configure one or more processors 112 to perform the actions attributed to the service provider and / or the payment service above.

[0048] The network interfaces 114 may enable wired and / or wireless communications between components and / or devices shown in the environment 100, and / or with one or more other remote systems and other networked devices. For example, at least some of the network interfaces 114 may include personal area network components to enable communications in one or more short-range wireless communication channels. In addition, at least some of the network interfaces 114 may include wide area network components to enable communications on a local area network.

[0049] Figure 2 An example of a server computing device 202 of a vision screening device 200 for performing techniques as described herein is shown. As described herein, the server computing device 202 (hereinafter "server") may include one or more servers or other types of computing devices implemented in any manner. For example, in the example of a server, the modules, other functional components, and data may be implemented in a single server, a server cluster, a server farm or data center, a cloud-hosted computing service, a cloud-hosted storage service, etc., although other computer architectures may alternatively or additionally be used.

[0050] In addition, although the accompanying drawings show that the components and data of server 202 exist in a single location, these components and data can alternatively be distributed in different computing devices and different locations in any way. In some examples, as described herein, these components and data can be distributed across user computing devices. These functions can be implemented by one or more server computing devices, wherein the various functions described above are distributed in various ways on different computing devices. Multiple servers 202 can be located together or separately, and, for example, organized as virtual servers, server libraries and / or server farms. Multiple servers 202 can be located together or separately, for example, organized as virtual servers, server libraries and / or server farms.

[0051] In some examples, server 202 may execute Figure 1-8 The server 202 may include a processor 204 operably connected to a network interface 206, a microphone 208, and a computer-readable medium 210. Each processor 204 may be a single processing unit or multiple processing units, and may include a single or multiple computing units or multiple processing cores. The processor 204 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, and / or any device that manipulates signals based on operating instructions. For example, the processor 204 may be one or more hardware processors and / or logic circuits of any suitable type that are specially programmed or configured to perform the algorithms and processes described herein. The processor 204 may be configured to obtain and execute computer-readable instructions stored in the computer-readable medium 210, and the computer-readable instructions may instruct the processor 204 to perform the functions described herein.

[0052] The computer-readable medium 210 may include volatile and non-volatile memory and / or removable and non-removable media implemented with any type of technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Such computer-readable media 210 may include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, optical storage, solid-state storage, tape, disk storage, RAID storage systems, storage arrays, networks of attached storage, storage area networks, cloud storage, or any other medium that can be used to store the desired information and can be accessed by a computing device. Depending on the configuration of the server 202, the computer-readable medium 210 may be a type of computer-readable storage medium and / or may be a tangible non-transitory medium, to the extent that media such as energy, carrier signals, electromagnetic waves, and signals themselves are excluded when referring to non-transitory computer-readable media.

[0053] The computer readable medium 210 may be used to store any number of functional components that may be executed by the processor 204. In many implementations, these functional components include instructions or programs that may be executed by the processor 204, and when the instructions or programs are executed, the instructions or programs specifically configure one or more processors 112 to perform the actions attributed to the service provider and / or payment service above. The functional components stored in the computer readable medium 210 may include an image / video sensor array component 212, a first display unit component 214, a second display unit component 216, a light sensor component 218, a ranging data component 220, a microphone data component 222, and / or a wireless component 224.

[0054] In some examples, the second display unit assembly 216 can be oriented to face the patient, and the first display unit assembly 214 can be oriented to face the individual performing the vision screening test, such as a physician. In other examples, the computer readable medium 210 can include additional components (not shown) capable of adjusting the position of one or more components, such as a mechanical motor assembly.

[0055] In an example, the computer readable medium 210 may include an image / video sensor array assembly 212. The image / video sensor array assembly 212 may be configured to receive and / or access light, image, and / or video data associated with a patient being evaluated during a vision screening. In particular, the image / video sensor array assembly 212 may be configured to capture or generate image and / or video data during a vision screening. For example, as described herein, image data and / or video data may be generated by the image / video sensor array assembly 212 during a vision screening to determine initial patient data, one or more measurements associated with the patient's body and eyes, and the like. The image / video data may be transmitted to the vision screening system via the network interface 206 for processing and analysis.

[0056] In some examples, the image / video sensor array assembly 212 includes, for example, a complementary metal oxide semiconductor (CMOS) sensor array, also known as an active pixel sensor (APS) or a charge coupled device (CCD) sensor. In some examples, the lens is supported by the vision screening device 200 and positioned in front of the image sensor array assembly 212. In further examples, the image / video sensor array assembly 212 has multiple rows of pixels and multiple columns of pixels. For example, the image / video sensor array assembly 212 may include approximately 1280×1024 pixels, approximately 640×480 pixels, approximately 1500×1152 pixels, approximately 2048×1536 pixels, and / or approximately 2560×1920 pixels. The image / video sensor array assembly 212 is capable of capturing approximately 25 frames per second (fps), approximately 30 fps, approximately 35 fps, approximately 40 fps, approximately 50 fps, approximately 75 fps, approximately 100 fps, approximately 150 fps, approximately 200 fps, approximately 225 fps, and / or approximately 250 fps. Note that the above pixel values ​​are exemplary and other values ​​may be greater or less than the examples described herein.

[0057] In an example, the image / video sensor array assembly 212 may include a diode having a light receiving surface and having a substantially uniform length and width. During exposure, the diode converts incident light into an electric charge. The image / video sensor array assembly 212 may operate as a global shutter. For example, substantially all photodiodes may be exposed simultaneously and for substantially the same length of time. Alternatively, the image / video sensor array assembly 212 may be used with a rolling shutter mechanism in which the exposure moves as a wave from one side of the image to the other. In other examples, other mechanisms may operate the image / video sensor array assembly 212. The image / video sensor array assembly 212 may also be configured to capture digital images. Digital images may be captured in various formats, such as JPEG, BITMAP, TIFF, and the like.

[0058] In an example, the computer-readable medium 210 may include a first display unit component 214. The first display unit component 214 may include a graphical user interface configured to display information to a tester and / or receive input from a tester during vision screening. For example, the first display unit component 214 may be configured to receive input about a patient from a tester, such as initial patient information described herein. In addition, the first display unit component 214 may be configured to display information about a vision screening device (e.g., the positioning of various components of the device), the distance between the patient and the device, the characteristics of the environment and / or the focus of the device, the progress of the screening, the option of transmitting data from the device to a vision screening system and / or an external database, one or more measurements and / or diagnostic suggestions generated during vision screening, etc. The first display unit component 214 may, for example, include a liquid crystal display (LCD) or an active matrix organic light emitting display (AMOLED). The first display unit component 214 may also be touch-sensitive to receive input from a tester.

[0059] In an example, the computer-readable medium 210 may include a second display unit component 216. The second display unit component 216 may include one or more components configured to display one or more graphical representations to a patient during a vision screening test. For example, based on the patient data, the second display unit component 216 may be configured to generate a graphical representation for display to the patient and configured to induce eye fatigue. The second display unit component 216 may, for example, include a liquid crystal display (LCD) or an active matrix organic light emitting display (AMOLED).

[0060] The second display unit assembly 216 may also include a light emitting diode (LED) array, which includes one or more visible LEDs and / or one or more near infrared LEDs. In some examples, a beam splitter directs the light emitted from the LED array to the patient. The near infrared LED in the LED array may include a wavelength of about 850 nanometers (nm), and may be configured to capture video and / or image data associated with the patient's eyes. In some examples, the visible LED in the LED array may include a wavelength less than about 630nm. This allows visual stimulation or graphical representation to be displayed to the patient without being seen in the image / video data captured by the image sensor array assembly 212. In some examples, the visible LED may be positioned between the near infrared LEDs in the LED array and may be substantially coplanar with the near infrared LEDs in the LED array.

[0061] In some examples, there may be amber LEDs among the visible LEDs used in the second display unit assembly 216. Amber LEDs may include wavelengths of about 608nm to about 628nm. In an example, the amount of power directed to the LEDs in the LED array may be regulated by one or more components of the device, such as the second display unit assembly 216. For example, in order to minimize pupil constriction and eye fatigue in patients, amber LEDs may be illuminated at low to medium power. For example, 20mA LEDs may be operated between about 2mA and about 10mA. Alternatively, low-brightness amber LEDs may be used, for example, LEDs operating at about 0.5mA. Further, LEDs may be pulse modulated. When present in the second display unit component 216, visible light LEDs other than amber may also be operated at low to medium power.

[0062] In an example, the computer readable medium 210 may include a light sensor assembly 218. As described herein, the vision screening device 200 may record details of each vision screening environment. For example, the light sensor assembly 210 may be configured to record the light intensity of the second display unit assembly 216, the contrast of the second display unit assembly 216, the amount of ambient light, the time of day, and / or the ambient noise level, etc. For example, the recorded data may be additionally used to evaluate a refractive error test.

[0063] In an example, the light sensor assembly 218 can be configured to detect the intensity of ambient light surrounding the vision screening device 200. For example, above certain brightness thresholds, the patient's pupil may constrict to a point where pupil detection is unreliable or impossible. In this case, the server computing device 202 in combination with the light sensor assembly 218 can determine that the ambient light is too bright and at least one of the first display unit assembly 214 or the second display unit assembly 216 can communicate to at least one of the tester or the patient using a light block to move to an environment with less ambient light, or adjust the screen environment in some manner.

[0064] In an example, the computer readable medium 210 may also include a rangefinder component 220. The rangefinder component 220, in combination with the server computing device 202, may be configured to determine the distance of the tester from the vision screening device 200. In some examples, the rangefinder component 220 may include an infrared transceiver unit, an ultrasonic transceiver unit, or other distance measuring units known to those skilled in the art. In some examples, the patient may be located approximately 1 meter (m) from the vision screening device 200. However, other distances may also be used for screening, such as 30 inches, 35 inches, 40 inches, or 45 inches.

[0065] The vision screening device 200 and / or the vision screening system can be configured to provide guidance to the tester and / or the patient on how to adjust the relative positioning between the vision screening device 200 and the patient to obtain a focal length that will produce a functional image. In an embodiment where the tester operates the vision screening device 200, the guidance is displayed on the first display unit assembly 214. For example, the first display unit assembly 214 can notify the tester that the patient is too close, too far, or within an appropriate distance. In some examples, the focal length is about 0.2 meters, about 0.3 meters, about 0.4 meters, 0.5 meters, about 0.6 meters, about 0.7 meters, about 0.75 meters, about 0.8 meters, about 0.9 meters, or about 1.0 meters. It is noted that the focal length values ​​described herein are only examples, and other focal lengths may be greater or less than the focal lengths listed herein.

[0066] In a further example, the computer-readable medium 210 may include a microphone assembly 222. The microphone assembly 222 may be configured to receive a patient's response and generate audio data associated with the response. For example, a patient may provide an auditory response as part of a visual acuity test and / or other vision tests described herein. For example, the patient may be asked to read an optotype, such as a letter, displayed on the second display unit assembly 216, and the microphone assembly 222 may be configured to receive the patient's response. In response, the microphone assembly 222 may be configured to generate audio data associated with the response and / or send the audio data to a vision screening system. In conjunction with speech recognition software, the microphone assembly 222 and / or the vision screening system may decode the response to generate audio data, and the audio data may be used in the various vision tests described herein.

[0067] The computer-readable medium 210 may also include a wireless component 224. The wireless component 224 may be configured to receive, access and / or send screening data using a wireless connection to connect to an external database. The wireless connection may include a cellular network connection and a connection using protocols such as 802.11a, b, g and / or ac. In other examples, a wireless connection may be directly implemented between the vision screening device 200 and an external display using one or more wired or wireless protocols (e.g., Bluetooth, Wi-Fi Direct, Radio Frequency Identification (RFID) or Zigbee). Other configurations are also possible. Transmitting data to an external database may enable report printing or further evaluation of the patient's vision test data. For example, the collected data and corresponding test results may be wirelessly transmitted and stored in a remote database accessible to authorized medical professionals.

[0068] Figure 3An example server computing device 302 of a vision screening consultation system 300 for performing techniques as described herein is shown. As described herein, the server computing device 302 (hereinafter "server") may include one or more servers or other types of computing devices that may be implemented in many ways. For example, in the example of a server, the modules, other functional components, and data may be implemented on a single server, a server cluster, a server farm or data center, a cloud-hosted computing service, a cloud-hosted storage service, etc., although other computer architectures may additionally or alternatively be used.

[0069] In addition, although the figures show the components and data of the server 302 as existing in a single location, these components and data can alternatively be distributed in different computing devices and different locations in any manner. In some examples, these components and data can be distributed across user computing devices, as described herein. These functions can be implemented by one or more server computing devices, wherein the various functions described above are distributed in various ways on different computing devices. Multiple servers 202 can be located together or separately, and organized into virtual servers, server libraries and / or server farms, for example.

[0070] In some examples, server 302 may execute Figure 1-8 The server 302 may include a processor 304 operably connected to a network interface 306, a microphone 308, and a computer-readable medium 310. Each processor 304 may be a single processing unit or multiple processing units, and may include a single or multiple computing units or multiple processing cores. The processor 304 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuits, and / or any device that manipulates signals based on operating instructions. For example, the processor 304 may be one or more hardware processors and / or logic circuits of any suitable type that are specifically planned or configured to execute the algorithms and processes described herein. The processor 304 may be configured to obtain and execute computer-readable instructions stored in the computer-readable medium 310, and the computer-readable instructions may instruct the processor 304 to perform the functions described herein.

[0071] The computer-readable medium 310 may include volatile and non-volatile memory and / or removable and non-removable media implemented in any type of technology for storing information, such as computer-readable instructions, data structures, program modules, or other data. Such computer-readable media 310 may include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, optical storage, solid-state storage, tape, disk storage, RAID storage systems, storage arrays, networks of attached storage, storage area networks, cloud storage, or any other medium that can be used to store the desired information and can be accessed by a computing device. Depending on the configuration of the server 302, the computer-readable medium 310 may be a computer-readable storage medium and / or may be a tangible non-transitory medium, to the extent that when mentioned, non-transitory computer-readable media excludes media such as energy, carrier signals, electromagnetic waves, and the signal itself.

[0072] The computer readable medium 310 may be used to store any number of functional components that may be executed by the processor 304. In some implementations, these functional components include instructions or programs that may be executed by the processor 304, and when the instructions or programs are executed, the instructions or programs specifically configure one or more processors 304 to perform the actions above belonging to the automatic negotiation system. The functional components stored in the computer readable medium 310 may include an image / video sensor array data component 312, a first display unit data component 314, a second display unit data component 316, a light sensor data component 318, a range finding data component 320, a microphone data component 322, a patient data component 324, a graphical representation data component 326, a measurement data component 328, a threshold data component 330, a diagnostic suggestion component 332, a video data component 334, a notification component 336, and / or a machine learning component 338.

[0073] In an example, the computer readable medium 310 may include an image / video sensor array component 312. The image / video sensor array component 312 may be configured to receive and / or access light, image, and / or video data associated with a patient being evaluated that is detected and / or generated during a vision screening by a vision screening device (e.g., the image / video sensor array component 212 of the vision screening device 200). For example, as described herein, the image / video sensor array component 212 may detect and / or generate image / video data during a vision screening for determining initial patient data, one or more measurements associated with a patient's body and eyes, and the like. The image / video sensor array data component 312 may be configured to receive, access, and / or store data.

[0074] The computer readable medium 310 may also include a first display unit data component 314, a second display unit data component 316, a light sensor data component 318, a rangefinder data component 320, and / or a microphone data component 322. These components may be configured to receive, access, and / or store data from, for example, at least one of the image / video sensor array component 212, the first display unit component 214, the second display unit component 216, the light sensor component 218, the rangefinder data component 220, and / or the microphone data component 222.

[0075] In an example, the computer-readable medium 310 may also include a patient data component 324. As described herein, the patient data component 324 may be configured to receive, access, store and / or analyze various data associated with the patient to determine the patient data for use by the vision screening system 300. For example, the patient data component 324 may be configured to receive / access patient data indicating demographic information associated with the patient from a vision screening device. For example, the patient data component 324 may be configured to receive patient data input by a tester and indicating various characteristics of the patient (e.g., provided by the patient or otherwise determined) from the vision screening device, as well as the required screening to be performed. In an example, the patient data component 324 may also be configured to receive / access received patient data associated with the patient and / or other patients who have used the vision screening system 300 from a third-party database. In addition, in an example, the patient data component 324 may be configured to receive / access image / video data from the image / video sensor array component 212 and / or the image / video sensor array data component 312 of the vision screening device. The patient data component 324 can be configured to analyze the image / video data to determine certain characteristics associated with the patient, such as age, height, pupil location, etc.

[0076] In an example, the computer-readable medium 310 may also include a graphical representation data component 326. The graphical representation data component 326 may be configured to determine and / or generate one or more graphical representations for display to a patient during a vision screening test. For example, the graphical representation data component 326 may be configured to receive and / or access patient data from the patient data component 324 to determine features and / or test categories associated with the patient (e.g., a young child, an elderly person, myopia, etc.). Using this information, the graphical representation data component 326 may determine the type of graphical representation to be generated for display to the patient. For example, if the patient data indicates that dynamic pupil tracking is being performed on the patient being screened, the system may generate a motion image for display to the patient so as to track the patient's pupil movement during the screening. The graphical representation data component 326 may also be configured to send information to a screening device so that the screening device provides an indication of the graphical representation to the patient.

[0077] In an example, the computer-readable medium 310 may also include a measurement data component 328. For example, the measurement data component 328 may be configured to receive / access image / video data from the image / video sensor array component 212 and / or the image / video sensor array data component 312 of the vision screening device. The measurement data component 328 may also be configured to analyze the image / video data to determine one or more measurements associated with the patient during the entire vision screening and / or in response to the displayed graphical representation. For example, the measurement data component may be configured to analyze the image / video data from the data to determine the position of the patient's pupil and / or lens, the diameter of the pupil and / or lens (e.g., indicating dilation or contraction), the movement of the pupil and / or lens (e.g., indicating cohesion or outward divergence), the patient's gaze, etc. The measurement value may be determined at the time point when the graphical representation is displayed.

[0078] For example, the measurement data component 328 can be configured to receive / access image / video data from the image / video sensor array component 212 and / or the image / video sensor array data component 312 of the vision screening device to determine the patient's gaze direction in response to the displayed graphical representation. For example, the patient's gaze can be determined by illuminating light such as infrared light in the direction of the patient. In response, the patient's cornea can reflect this light, and the reflection can be included or visible in the image or video data. The measurement data component 328 can use the reflection from the light source to the center of the eye (e.g., the origin of the reflection) to determine the flicker or straight line measurement value. In this way, the measurement data component 328 can use this information to determine the position, location and / or movement of the pupil at different time points when the graphical representation is displayed. In other examples, the measurement data component 328 can use the image / video data to determine the position or location of the pupil relative to the outer edge of the eye (e.g., the outline of the eye). The measurement data component 328 can use the measurement value related to the patient's gaze to determine one or more positions of the patient's pupil at a time point when the graphical representation is displayed (e.g., position to time data point).

[0079] In an example, the computer-readable medium 310 may also include a threshold data component 330. The threshold data component 330 may be configured to receive, access and / or analyze threshold data associated with standard test results. For example, the threshold data component 330 may be configured to access data from a third-party database storing test data and / or measurements, or to access or receive a series of values ​​indicating a threshold value in which the test value should be located, which is associated with a patient with normal vision health having similar test conditions. For example, for each test category, standard test data may be accessed or received by the threshold data component 330, and the standard test data may be compared with the measurement data stored by the measurement data component 328. For example, when each graphical representation is displayed for an elderly person, the threshold data associated with the elderly test category may include a standard pupil measurement value, and / or a threshold value that the test value should not exceed or fall below (e.g., a standard value range, such as the Donder's Table values ​​described herein).

[0080] Additionally or alternatively, the threshold data component 330 can be configured to utilize one or more machine learning techniques to determine threshold data associated with each test category and / or graphical representation. For example, the threshold data component 330 can be configured to utilize one or more trained machine learning models of the machine learning component 338 to determine the threshold data. For example, the machine learning component 338 can be configured to access and / or receive historical vision screening data from a database (e.g., from a screening database storing historical screening data), and can utilize the data to train one or more machine learning models to determine standard test measurements for each test category. For example, the machine learning component 338 can execute one or more algorithms (e.g., decision trees, artificial neural networks, association rule learning, or any other machine learning algorithm) to train the system based on historical vision screening data to determine one or more thresholds. In response, the threshold data component 330 can be configured to utilize the trained model to determine one or more thresholds and / or standard values ​​for the vision screening system 300.

[0081] The computer-readable medium 310 may additionally store a diagnostic suggestion component 332. The diagnostic suggestion component 332 may be configured to receive, access and / or analyze measurement data from the measurement data component 328 and / or threshold data from the threshold data component 330 for comparison. For example, the diagnostic suggestion component 332 may utilize threshold data learned or otherwise determined to compare with the measurement data to determine whether the patient exhibits normal vision behavior (e.g., has passed or failed a vision screening), whether further screening is required, etc. For example, if the pupil diameter measurement detected by the vision screening device in response to the displayed graphical representation is within a threshold of a standard range learned or known (e.g., preset) for patients of the same test category (e.g., the measurement is within a standard value range), then the diagnostic suggestion component 332 may generate a recommendation indicating that the patient has passed the vision screening. Alternatively, if the pupil diameter measurement falls outside the standard value range, then the diagnostic suggestion component 332 may generate a recommendation indicating that the patient has failed the vision screening test and / or indicating that the patient should undergo additional screening. In other examples, if the patient's pupil movement data (e.g., measurements indicating the position of the pupil during screening or the direction of the patient's gaze) indicates that the patient's eye movement exceeds a known threshold (e.g., measurements associated with gaze at the leftmost, rightmost, uppermost, and / or lowermost corners of the patient's gaze, the patient's gaze experiences oscillations or saccades, etc.), the diagnostic recommendation component 332 can generate a recommendation instructing the patient to undergo further screening.

[0082] In an example, the computer-readable medium 310 may also include a video data component 334. The video data component 334 may be configured to generate and / or store video data associated with vision screening. For example, the video data component 334 may be configured to receive / access video data and / or receive / access measurement data of the measurement data component 328 from the image / video sensor array component 212 and / or the image / video sensor array data component 312 of the vision screening device. The video data component 334 may be configured to receive and / or access measurement data and / or analyze video data to determine one or more data points associated with the patient, such as the direction of the patient's gaze or the position of the patient's pupil during the vision screening. The video data component 334 may be configured to utilize the data points to generate video data including a graphical representation, and one or more vision indicators indicating the position of the pupil during the entire vision screening. For example, the vision indicator may include one or more symbols overlaid on the graphical representation and indicating the position of the pupil when the graphical representation is displayed to the patient.

[0083] For example, as described herein, the measurement data component 328 can be configured to determine one or more measurements related to the patient's gaze direction during screening. For example, the measurement data component 328 can be configured to determine the position of one or two pupils of the patient at a point in time. In some examples, as described herein, the measurement data component 328 and / or the video data component 334 can be configured to analyze the image / video data component to determine the location or position of the patient's pupil when the graphical representation is displayed. For example, using the patient's gaze visible in the video / image data, the measurement data component 328 and / or the video data component 334 can determine the position or position of one or two pupils during each frame of the graphical representation being displayed. In this way, the measurement data component 328 and / or the video data component 334 can determine the data of the position of the patient's eyes relative to the graphical representation being displayed relative to time. In addition, the video data component 334 can use these data points to generate video data including the graphical representation and one or more vision indicators overlaid on the graphical representation and indicating the position of the pupil on each frame of the graphical representation.

[0084] The video data component 334 can also be configured to provide the generated video data to the vision screening device for display to the tester. In some examples, the video data component 334 can be configured to store the video data for later access by the tester, physician, etc. In this way, the patient's vision health can be monitored at any time, and more accurate and timely diagnostic recommendations can be determined.

[0085] In an example, the computer-readable medium 310 may also include a notification component 336. For example, the notification component 336 may be configured to receive and / or access diagnostic advice from the diagnostic advice component 332, and provide an indication of the diagnostic advice to a user (e.g., a tester or a physician) performing a vision screening. For example, the notification component 336 may be configured to send a signal to the vision screening device via at least one of the first display unit component 214 and / or the second display unit component 316 so as to display a user interface indicating the diagnostic advice, such as whether the patient has passed the vision screening, whether the vision screening has not passed, and / or a suggestion for further treatment. Additionally or alternatively, the notification component 336 may be configured to receive and / or access measurement data from the measurement data component 328 to provide the measurement data to the tester together with the diagnostic advice or in place of the diagnostic advice. For example, the notification component 336 may be configured to send a signal to the vision screening device so as to display an indication of one or more measurement values ​​through the user interface.

[0086] In an example, the computer-readable medium 310 may also include one or more machine learning components 338. For example, as described herein, the machine learning component 338 may be configured to execute one or more algorithms (e.g., decision trees, artificial neural networks, association rule learning, or any other machine learning algorithm) to train the vision screening system 300. In an example, the machine learning component 338 may execute any type of supervised learning algorithm (e.g., nearest neighbor classification, Bayesian classification, neural networks, unsupervised learning algorithms, semi-supervised learning algorithms, reinforcement learning algorithms, etc.). As described herein, the trained model of the machine learning component 338 may be used by one or more components of the vision screening system 300 (e.g., threshold data component 330 or diagnostic suggestion component 332) to determine various values ​​and / or analyze data to determine suggestions, etc.

[0087] Figure 4A and 4B A perspective view of an example of a vision screening device 400 according to some embodiments is shown. For example, the vision screening device 400 includes the above reference Figure 1-3 The vision screening device 400 may include some or all of the components described above for the vision screening device of FIG. The vision screening device 400 may include a housing 402, a first display unit 404, a second display unit 406, and / or a rangefinder 408. Other embodiments may include more or fewer components.

[0088] In an example, the housing 402 can be configured to provide support for the components of the vision screening device 400 and be configured in one or more aspects to facilitate handheld or mobile operation. In some examples, the vision screening device 400 can also be mounted on a surface such as a tripod. In some configurations, the first display unit 404 can be configured to face a user operating the vision screening device 400, such as a tester or a physician, so that the tester can manipulate various control interfaces and view test results (e.g., diagnostic recommendations). Although the first display unit 404 is shown to be oriented at a certain angle relative to the tester, the first display unit 404 can have other orientations in different embodiments.

[0089] In other examples, the second display unit 406 can be positioned on the opposite end of the housing 402 so that the second display unit 406 faces the patient or the person being evaluated during typical operation during vision screening. As described herein, the second display unit 406 may include a display and one or more LEDs or LED arrays configured to display a graphical representation to the patient during vision screening. The image sensor array is located inside the housing 402 and behind the second display unit 406, or adjacent to it. In an example, light propagating from the patient's pupil passes through the second display unit 406, and the light is received by the image sensor array at the second display unit 406. Alternatively or additionally, the image sensor array can be positioned adjacent to the second display unit 406 so that light does not need to pass through the second display unit 406 to reach the image sensor array device.

[0090] In some examples, the housing 402 may include a third display unit (not shown). For example, the third display unit may be configured on the opposite end of the housing and be located near the second display unit facing the patient. In this way, each of the second display unit 406 and the third display unit may be configured to display the same or different graphical representations to monitor how each eye works together. In other examples, an enhanced or virtual reality experience machine 410 may be provided to the patient. The experience machine 410 may be configured to display graphical representations to the patient without physical limitations or display limitations for the display unit. In other examples, a larger monitor such as a computer monitor or projection screen 412 may be utilized to display graphical representations to the patient. The projection screen 412 may be located at any distance from the patient to cause the desired eye fatigue to perform vision screening. In these examples, the ambient light in the surrounding screening environment may be controlled to allow the use of a computer monitor or projection screen 412 during vision screening.

[0091] In an example, the rangefinder 408 can be configured to determine the distance from the vision screening device 400 to the patient. For example, the rangefinder 408 can be configured to determine the distance from the patient's face to the second display unit 406. As discussed herein, the rangefinder 408 can be configured to determine the patient's distance at the beginning of a test and / or dynamically determine the patient's distance throughout various vision screenings.

[0092] Figure 5 and 6 An exemplary graphical representation for display during a vision screening test is shown. For example, according to some implementations, Figure 5 shows an example spaghetti block diagram, Figure 6 An example graphical scene according to some embodiments is shown. As described herein, an exemplary vision screening device (e.g., Figure 4A and 4BThe vision screening device described in the present invention can be configured to perform one or more vision tests on a patient, and can be configured to output the results of these tests to the tester. In addition to the exemplary vision tests described herein, the vision screening device / system can be configured to test cohesion and visual efficiency using binocular gaze tracking during reading. For example, it is understood that almost all elementary and high school learning revolves around students' reading ability. Some studies have shown that 10% of children between the ages of nine and thirteen suffer from moderate or even obvious cohesion deficiency. Unfortunately, cohesion deficiency can be difficult to assess, and many children are misdiagnosed as ADHD when they actually have cohesion deficiency or vision problems when reading. This may be due to abnormal working of the eyes when focusing on near vision activities. For example, during routine screenings, it may be difficult for a physician or school employee who manages vision screening to accurately track a child's gaze.

[0093] The vision screening system described herein can be configured to track the patient's pupil during the reading activity and display the results on the first display 404 for the tester to view. As part of the vision test, Figure 5 As shown, the vision screening system can also be configured to display a spaghetti-type box diagram and an indicator (e.g., determined measurements, video data, and / or generated suggestions) indicating whether the patient suffers from dyslexia, fusion, and / or cohesion problems. In these examples, the vision screening device can be configured as a binocular eye tracking device (which can include virtual reality goggles 410 or other virtual reality display components), which can, for example, display a graphical representation of a test for cohesion problems for a patient of the test type through goggles 410, such as age-appropriate text (e.g., the kind of text that the patient can read), or display a target and determine whether the eyes are tilted inward as indicated by normal behavior when the target moves toward or away from the subject. In such an example, the vision screening device can be connected internally or externally to a laptop computer, a computer screen, or an e-reader, and the vision screening device can enable real-time analysis of vision test data. In particular, the vision screening device can track the patient's eyes while the patient reads age-appropriate reading material, and compare such eye movements with typical eye movements of other patients at that grade level (e.g., known values ​​and / or threshold data).

[0094] In another example embodiment, the vision screening device can be configured to provide a patient with a virtual reality eye examination. For example, it is understood that most current vision screening devices cannot effectively screen patients with smaller pupil diameters, eyes with higher accommodation (e.g., the eyes of a child) in environments with higher ambient light, etc. Because most known devices use static (as opposed to dynamic) vision tests, these devices are not configured to test correction, reading cohesion, and / or memory and cognitive decline.

[0095] The technology described herein provides a vision screening system that can be configured to use eye tracking and algorithms and normative data to run a test sequence in a virtual reality environment. Figure 5 As shown, the process will allow the tester to view the spaghetti diagram, and the system can analyze the patient's eye behavior to determine the efficiency of the patient's eyes and use this information for vision therapy or corrective actions. For example, the system can be configured to record the behavior and generate video data of the patient's eyes while the patient is reading the spaghetti diagram. The video data (e.g., eye tracking data and / or other test data obtained using a vision screening device) can be analyzed to determine one or more measurements related to the patient's eyes for comparison with known or standard measurements (e.g., thresholds associated with normal eye behavior) to determine whether the patient's eyes behave in the same or similar manner as patients with similar characteristics (e.g., patients of the same age, height, etc.). In this way, the measurements can indicate how each eye of the patient responds to stimuli in a binocular and monocular manner.

[0096] For example, the vision screening system can be configured to determine measurements associated with the range of motion of each eye when the patient reads the text of a spaghetti diagram (e.g., the gaze of each eye can move the entire range of motion in four cardinal directions). In some examples, the system may determine measurements associated with smooth tracking, or determine whether one or both eyes can smoothly follow a target displayed in a graphical representation (e.g., reading the text of a spaghetti diagram). In this example, the system can determine measurements indicating whether the eye has a stutter or a saccade (e.g., whether the eye jumps back and forth during movement). In a further example, the system can be configured to determine measurements associated with binocular tracking of the eye, which indicates whether the eyes track the text of the spaghetti diagram together or whether one eye lags behind the other eye (e.g., whether the movement of each eye indicates that the eye is tracking in unison). As described herein, the system can be configured to determine measurements associated with one or both eyes to prevent either eye from affecting the results of the other eye (e.g., one eye can help correct the defects of the other eye).

[0097] In some examples, the vision screening device can be configured to output an interactive movie script or command response application to the tester via the second display 406. Such a movie script or other video can be three minutes or less in length and have the following Figure 6 Such an exemplary vision test may force the patient's eyes to move dynamically, and the vision screening device may generate video data of the patient's eyes during the test to determine eye-related measurements while the scene is displayed.

[0098] For example, the eye can be forced to look spatially to the extremes to remove some of the existing accommodation limitations. In this way, the device can track the eye under dynamic conditions through gaze tracking, so that confirmation can be confirmed without manual procedures. In addition, the device can simulate potential corrections so that the tester can have a more complete understanding of the characteristics of the patient's eyes. Figure 6 In the example scenario shown, as part of such a dynamic test, the vision screening device can move the bat 602 or point 604 while tracking the patient's pupil. Such a test can evaluate the person's close and long-distance focus. In addition, the device can test color recognition by requesting the patient to read and / or identify the symbol 606 shown on the wall of the building. In addition, the device can test cohesion and / or saccades by requesting the patient to read the text 608 shown on the fence. In addition, the device can test pupil reaction by showing a dim scene (e.g., a night scene). The device can evaluate refractive error while presenting a dynamic scene to the patient through the second display 406. In any such example, the virtual reality vision test provided by the device not only evaluates refractive error, but also evaluates insufficient cohesion, stimulus tracking, etc. As a result of these tests, the system can track the improvement or deterioration of vision or cognitive problems.

[0099] In a further example, the vision screening system can be configured to measure eccentric light refraction by adaptability and pupil control using a tinted medium or other such medium. For example, it should be understood that when a patient (especially a child) is tested for eccentric light refraction using known equipment, the patient's eyes tend to adapt and focus on near-point objects. As a result, light refraction readings using such equipment are often inaccurate because such eye focusing causes the lens in the eye to change shape. In contrast, it should be understood that the most accurate light refraction readings can be obtained when the eye is in a relaxed state. This relaxed state can correspond to a condition in which the patient's pupil diameter is relatively high / maximized.

[0100] Thus, an exemplary vision test described herein may include relaxing a patient's eyes by presenting the patient with darkened media or glasses, e-tint (electronic tint) glasses, or a dark tinted barrier that removes focus / eliminates viewpoints. By having the patient wear glasses made of a dark but IR transparent material, experiments have shown that pupil diameter increases by more than 20%. In other examples, the system described herein may be configured to monitor the patient's pupil diameter. Once the desired (e.g., enlarged) pupil diameter is observed, the device and / or system may mark the corresponding optical refraction data as captured when the pupil diameter is above the desired diameter threshold. Because such data may be more reliable / accurate, the system may use this data to generate screening results or for other purposes. In such an example, the system may be used to monitor the dynamics of the pupil (e.g., diameter) to determine when to accept substantially continuously captured optical refraction data.

[0101] In a further example, the system described herein can be configured to output a relaxing stimulus (e.g., a graphic representation of a calm beach / seascape, a rabbit graphic, etc.) via a second display 406, an experience machine 410, etc. When the patient views the stimulus, his / her pupil will dilate as a natural response of the patient feeling happy and / or relaxed. This dilation will eliminate at least some of the adaptation, so that more reliable and accurate light refraction data can be obtained. Yet another alternative example includes placing a substantially opaque cover around the face of the person being evaluated and beyond the range of one or more sensors of the device to eliminate the effects of ambient light when capturing light refraction data.

[0102] In another example, the vision screening system can be configured to accurately measure the refraction of eccentric light even when the patient accommodates during vision testing. For example, it is understood that the lens of a child's eye is generally very flexible, typically providing more than 10 diopters of accommodation for a child. Therefore, when a child is being tested for refractive error, the shape of the lens of the child's eye may change significantly when the child focuses on a target of visual stimulation. Therefore, most known devices cannot be configured to accurately determine, for example, whether a child has normal vision, or whether the child is farsighted and is accommodating.

[0103] In this way, the technology described herein can be configured to provide different focused and blurred (e.g., unclear) images to the patient via the second display 406. Such blurred images or other such unclear stimuli may relax the patient's eyes. The device and / or system may also capture a series of refractive error measurements during the process. In particular, the device can capture refractive error measurements when various focused and blurred images are presented to the patient. Therefore, due to some measurements corresponding to the pre-adapted state of the patient's eye lens and other measurements corresponding to the post-adapted condition of the patient's eye lens, the measurements will have large value differences. The system can use one or more algorithms, machine learning techniques, neural networks, lookup tables, and / or other components to analyze the refractive error measurement data to more accurately determine, for example, suitable eye protection recommendations for the patient.

[0104] In some such examples, the device may output a stimulus via a second display 406 that may cause the patient to gaze far or near so that the eyes enter two states. The device may also capture a series of refractive error measurements in the process. In particular, the device may capture refractive error measurements when the patient's eyes are in the corresponding state and when the eyes transition between the two states. The device may use one or more algorithms, machine learning techniques, neural networks, lookup tables, and / or other components to analyze such refractive error measurement data to more accurately determine, for example, appropriate eye protection recommendations for the patient. In any of these examples, the device may include an eccentric optical refractor configured to present a video or other such stimulus to relax each eye of the patient so that corresponding optical refraction readings may be obtained in a relaxed and adapted state of the eye.

[0105] In yet another example, the vision screening device may include a visual acuity system configured to use eye tracking and DLP projection to determine the ability of the patient to identify characters at a specific distance. For example, it should be understood that visual acuity screening may be time-consuming and inaccurate in certain environments. In addition, known vision screening devices are generally not suitable for accurately testing visual acuity. In this way, the system described herein may be configured to project a graphical representation including a visual acuity motion stimulus test on a projection surface and / or onto a fixed surface such as a building wall or screen, such as a projector screen 412. The projected image may provide dynamic (e.g., lateral) stimulation, and when the patient observes such stimulation, the speed, direction, lateral movement and other performance indicators of the eye may be tracked and / or otherwise determined by the device / system. As described herein, the device may be configured to record these parameters and / or compare the rate of change of these parameters with empirical data or known standards. In some examples, this dynamic stimulus test facilitated by the system replaces the classic Snellen eye chart, because the visual acuity assessment based on the Snellen eye chart is relatively subjective. Additionally, as part of such dynamic stimulation testing, the device can be configured to flash an optotype to the patient so that the patient can confirm the target Snellen visual equivalent.

[0106] In an example, the appearance and / or other characteristics of the stimulus can be scaled by distance projection on a surface such as a projection screen 412. For example, a visual acuity test can be performed at 4 feet, or a more strenuous visual field test can be performed at 8 feet. When the device projects lateral stimuli within such a range, this wider projection may place more strain on the eyes in the eye's field of vision. In such a test, the device can track eye indicators such as speed, direction, velocity, glances, etc. The device can also be operated to perform such visual acuity tests in different dedicated operating modes that are adjusted based on the patient's age (e.g., "child" mode, "adult" mode, "elderly" mode, or other modes) and / or based on the tester's skills (e.g., "optometrist" mode, "streamline" mode, etc.). In addition, the vision screening device can automatically scale the test by measuring the wall or surface distance.

[0107] In any of the examples described herein, the vision screening device can include a DLP projection unit on one side and an eye tracker for each eye on the other side. In addition, in some examples, an additional computing device such as an iPad, a mobile phone, a tablet computer, a laptop computer, or other such processor or device can be used with and / or in place of the vision screening device. Such additional devices are configured to track eyes through software and / or by using an associated image capture device (e.g., a camera). Therefore, the various systems described herein can be implemented in a single unit or in separate devices or components.

[0108] Furthermore, it should be understood that in examples, the vision screening device and / or vision screening system can be configured to perform a variety of vision screening tests on a patient. These tests may include, for example, but not limited to:

[0109] Accommodation test - having the patient look far and near to measure the ability of each eye to accommodate

[0110] Color test - standard color blindness test

[0111] Target tracking efficiency test - binocular dynamic tracking target

[0112] Eye tracking reading test-spaghetti vision box diagram

[0113] Reading and indicators

[0114] · Eyespots / 100 words: This measures how often the eyes stop for every 100 words

[0115] Regression / 100 words: This measures how often the eyes move backward without rereading (ie, involuntary backward movement)

[0116] Directional Attack Percentage: This measures the tendency to perceive content in a left-to-right manner. This metric measures the ratio between forward and backward glances (Ratio of viewpoints to regressions %)

[0117] Average recognition range: This measures the number of words contained in a single viewpoint (viewpoint / total words)

[0118] Average duration of viewpoint: Determine the average viewpoint time

[0119] Words / minute rate w comprehension - instant words / minute

[0120] Convergence - the ability to converge with optical power at near / read range

[0121] Cohesion deficiency test - close-up binocular fusion test

[0122] Dynamic Cover Test - refracts and then covers the weaker eye to determine phoria or strabismus

[0123] Depth perception test - can propagate objects near and far

[0124] Visual acuity - Snellen or Lea notation

[0125] Figure 7 and 8 Various flow charts of example processes for vision screening as described herein are shown. Processes 700 and 800 are shown as a collection of blocks in a logical flow chart, which represent a sequence of operations that can be implemented in hardware, software, or a combination thereof. In the case of software, a block represents a computer executable instruction stored on one or more computer-readable storage media, and when the computer executable instruction is executed by a processor, the computer executable instruction performs the operation. Typically, computer executable instructions include routines, programs, objects, components, data structures, etc. that perform specific functions or implement specific abstract data types. The order in which the operations are described is not intended to be interpreted as a limitation, and any number of the described boxes may be combined in any order and / or in parallel to implement the process. In some embodiments, one or more blocks of the process may be omitted entirely. In addition, processes 700 and 800 may be combined in whole or in part with each other or with other processes in whole or in part.

[0126] Figure 7 An example process 700 for vision screening according to some implementations is shown. In some examples, the operations described below can be performed by a system including a local computing device and / or a remote computing device in communication with the local computing device (eg, in a distributed configuration).

[0127] At operation 702, the system may determine patient data associated with a patient participating in a vision screening test. As described herein, a patient evaluated by a vision screening system may provide information to the system. In some examples, the patient may manually input such information via one or more touch screens or other input devices of a vision screening device. In another example, a physician or other user of the device may manually input such information via such an input device. Additionally or alternatively, the system may receive and / or access patient-related data from a database of the system storing information associated with the patient. The system may analyze the received and / or accessed data to determine one or more characteristics associated with the patient, such as demographic information, physical characteristics of the patient, and the like. Further, in some examples, the system may generate image or video data associated with the patient, and the image / video data may be analyzed to determine features associated with the patient.

[0128] At operation 704, the system may identify a test category associated with the patient. For example, the system may determine the category to which the patient belongs based at least in part on the patient data. The test categories may include, but are not limited to, age categories, gender categories, physical characteristic categories (e.g., height, pupil distance, etc.).

[0129] At operation 706, the system may generate a graphical representation for display to the patient, the graphical representation configured to cause visual fatigue. For example, as described herein, based at least in part on the patient data and / or the test category, the system may determine and / or generate a graphical representation configured to cause fatigue on the patient's vision or eyes. For example, if the system determines that the patient is a teenager, the system may determine the graphical representation from pre-generated graphical representations, or the system may generate a graphical representation that will fatigue the patient's vision in order to perform the desired vision screening. As an example, if the system wants to test the behavior of the patient's eyes while reading, the graphical representation may include a piece of text. As another example, if the system wants to test the movement limits of the patient's eyes, the graphical representation may include a dynamic video.

[0130] At operation 708, the system may determine one or more measurements associated with the patient's eye in response to the graphical representation. For example, as described herein, the system may be configured to record image / video data of the patient during a vision screening. The system may then analyze the image / video data to determine one or more measurements associated with the patient's eye. The measurements may include, but are not limited to, measurements associated with the patient's gaze, the position of the pupil, the diameter of the pupil, the diameter of the lens, motion data, and the like.

[0131] At operation 710, the system may compare one or more measured values ​​to one or more standard values. For example, the system may be configured to receive, access, and / or determine known standard values ​​that indicate values ​​of known standard behavior for the screened patient. The system may then compare the one or more determined measured values ​​to the standard values ​​to determine whether the patient exhibits normal vision behavior. As described herein, the standard values ​​may be received and / or accessed from the data and / or may be determined using historical screening data and / or one or more machine learning techniques.

[0132] At operation 712, the system can determine whether the one or more values ​​meet a threshold value associated with the test category. As described in operation 710, the system can be configured to compare one or more measurements associated with the patient with one or more standard values. The system can also be configured to receive, access or determine a threshold range in which one or more measurements should be. Based on the comparison, the system can determine whether one or more measurements are within a threshold range of normal behavior. In some examples, known values ​​and / or thresholds can be associated with test categories. For example, a standard value can be associated with each test category associated with each age range (e.g., a standard value for a young child can be different from a standard value for an adult).

[0133] At operation 714, the system may generate a diagnostic suggestion related to the patient. For example, as described in operation 712, the system may determine whether one or more measurements meet a threshold of standard behavior. Based on this determination, the system may generate a suggestion indicating whether the patient has passed or failed a vision screening and / or whether the patient needs additional screening. As described herein, the system may also generate suggestions using historical screening data and / or one or more machine learning techniques. For example, based on historical patient data, the system may train one or more machine learning models. Then, the system may use the trained model to determine whether the patient's measurements exceed a determined learning threshold associated with normal vision behavior. Alternatively or additionally, the system may compare the patient's measurements with previous screening behaviors, and generate suggestions based on the similarity of the measurements with the measurements of previous similar screenings (e.g., if the patient's measurements are similar to the measurements of the previous screenings, the system may generate substantially similar suggestions). The system may provide suggestions and one or more measurements, video data, etc. to a user (e.g., a tester or physician performing screening and / or operating a screening device) for viewing.

[0134] Figure 8 An example process 800 for vision screening according to some implementations is shown. In some examples, the operations described below can be performed by a system including a local computing device and / or a remote computing device in communication with the local computing device (eg, in a distributed configuration).

[0135] In operation 802, the system can generate a graphical representation based on the patient data, which is configured to cause visual fatigue during the vision screening test. As described herein, the system can be configured to receive patient data from a patient (e.g., a patient evaluated by a vision screening system). In some examples, the system can also receive and / or access patient-related data from a database of the system storing information related to the patient. The system can analyze the received and / or accessed data to determine one or more features related to the patient, such as demographic information, the patient's physical characteristics, etc. Further, in some examples, the system can generate images or video data related to the patient, and the image / video data can be analyzed to determine features related to the patient. Based at least in part on the patient data, the system can then determine and / or generate a graphical representation configured to cause fatigue in the patient's vision or eyes during the vision screening test.

[0136] At operation 804, the system may display a graphical representation to the patient during the vision screening test. As described herein, the system may be configured to display the graphical representation to the patient in a variety of ways. For example, the system may be configured to display the graphical representation to the patient via a display unit of a vision screening device in communication with the system. The system may also be configured to display the graphical representation to the patient via a virtual reality or augmented reality experience machine, or by projection onto an external surface (e.g., a projector screen or wall).

[0137] At operation 806, the system may determine one or more measurements associated with the patient's eye. For example, as described herein, the system may be configured to record image / video data of the patient during a vision screening. The system may then analyze the image / video data to determine one or more measurements associated with the patient's eye in response to the graphical representation. The measurements may include, but are not limited to, measurements associated with the patient's gaze, the position of the pupil, the diameter of the pupil, the diameter of the lens, motion data, and the like.

[0138] At operation 808, the system may compare one or more measured values ​​with one or more standard values ​​to determine a difference. For example, the system may be configured to receive, access and / or determine a known standard value indicating a value of a known standard behavior of the screened patient. The system may then compare one or more determined measured values ​​with a standard value or a value of a threshold range to determine whether the patient exhibits normal visual behavior. As described herein, standard values ​​and threshold ranges may be received and / or accessed from a database and / or may be determined using historical screening data and / or one or more machine learning techniques. For example, the system may be configured to compare one or more measured values ​​associated with the patient with one or more standard values ​​to determine a difference (e.g., to determine whether one or more measured values ​​are within a threshold range of normal behavior).

[0139] At operation 810, the system may generate a diagnostic suggestion related to the patient based at least in part on determining whether the difference meets a threshold. For example, as described in operation 808, the system may determine whether one or more measurements meet a threshold of standard behavior (e.g., whether the difference between the measurement and the standard value is within a threshold range). Based on this determination, the system may generate a suggestion indicating whether the patient has passed or failed the vision screening and / or whether the patient needs additional screening. As described herein, the system may also generate suggestions using historical screening data and / or one or more machine learning techniques. The system may provide suggestions and one or more measurements, video data, etc. to a user (e.g., a tester or physician performing a screening and / or operating a screening device) for review.

[0140] At operation 812, the system may generate first video data associated with at least one of the graphical representation or the patient during the vision screening test. For example, the vision screening device may be configured to record (e.g., generate video data) the graphical representation being displayed and / or the patient during the vision screening test. Based on the video data, the system may determine measurements associated with the patient's eye, such as measurements associated with the pupil, lens, etc., at a point in time during the screening and in response to the graphical representation being displayed.

[0141] At operation 814, the system may determine a plurality of positions of the patient's pupil during the vision screening test based at least in part on the one or more measurements. For example, as described in operation 812, the system may generate video data associated with the patient and / or the graphical representation during the vision test. The system may use the video data to determine the position of the patient's pupil throughout the vision screening and at the point in time when the graphical representation is displayed. For example, the position of the pupil may indicate movement of the patient's eye during the vision screening test, such as when the patient is being displayed a video clip.

[0142] At operation 816, the system may generate second video data that includes the first video data associated with the graphical representation and a plurality of visual indicators indicating the positions of the pupil. For example, the system may be configured to generate a second video that includes the graphical representation and one or more indicators of the position of the patient's pupil during a vision screening test and / or in response to displaying the graphical representation. For example, the video may include a graphical representation, such as a video clip displayed to the patient, and one or more points indicating the position of the patient's pupil while the video is being played. The video may be used to determine whether the patient's eyes exhibit normal behavior in response to the video clip (e.g., whether the eyes track the displayed object correctly, whether the movement is normal, etc.).

[0143] At operation 818, the system may provide the one or more measurements and the second video data to a user. For example, as described herein, the system may be configured to provide the one or more measurements and / or the second video data to a user (e.g., a tester or physician performing the screening and / or operating the screening device). For example, the system may be configured so that the one or more measurements and / or the second video data are displayed to the user via a display unit of the screening device.

[0144] It should be noted that the "embodiment" appearing in this document does not limit the described elements to a single embodiment; all described elements can be combined in any number of ways in any embodiment. In addition, for the purpose of interpreting this specification, unless otherwise stated, the use of "or" herein means "and / or". Unless otherwise stated, the use of "one" or "one" herein means "one or more". The use of "include", "include", "contain", "have" is interchangeable and is not intended to be limiting. In addition, unless otherwise stated, the use of terms such as "first", "second", "third", "upper", "lower", etc. does not indicate any spatial, sequential or hierarchical order or importance, but is used to distinguish one element from another element. It should be understood that, for example, in the case of "A and / or B" and "at least one of A and B", the use of the terms "and / or" and "at least one" is intended to include selecting only the first listed option (A), or selecting only the second listed option (B), or selecting two options (A and B). As another example, in the case of "A, B, and / or C" and "at least one of A, B, and C," such language is intended to include selecting only the first listed option (A), or only the second listed option (B), or only the third listed option (C), or only the first and second listed options (A and B), or only the first and third listed options (A and C), or only the second and third listed options (B and C), or all three options (A and B and C). This applies to many of the listed items, as will be readily appreciated by persons of ordinary skill in this and related arts.

[0145] It should also be understood by those skilled in the art that any block diagram, step or subprocess herein represents a conceptual view of an illustrative system that embodies the principles of this subject. Similarly, it is understood that any flow chart, flow chart, state transition diagram, pseudocode, etc. represent various processes that can be substantially represented in a computer-readable medium and thus performed by a computer or processor, whether or not such a computer or processor is explicitly displayed. The order of describing the method is not intended to be interpreted as a limitation, and any number of described method blocks can be deleted, moved, added, subdivided, combined and / or modified in any order to implement the method, or an alternative combination or subcombination. Moreover, although steps, subprocesses or blocks are sometimes shown as being executed in series, some steps, subprocesses or blocks can be executed in parallel or at different times, as can be recognized by a person of ordinary skill in the art. In addition, any specific numbers mentioned herein are exemplary only; alternative implementations may adopt different values ​​or ranges. In addition, the methods and implementations described herein may be implemented in any suitable hardware, software, firmware, or a combination thereof. For example, the methods and embodiments described herein may utilize multiple user interfaces, including but not limited to any or all user interfaces presented through a device terminal (e.g., a keypad, a touch screen, etc.), software installed on a user device (e.g., a mobile application, a messaging service, etc.), a tablet computer, or a web interface. In addition, these user interfaces are typically, but not always, supported by an Internet cloud service.

[0146] The foregoing is merely an illustration of the principles of the present invention, and those skilled in the art may make various modifications without departing from the scope of the present invention. The above embodiments are provided for illustration and not limitation. In addition to those explicitly described herein, the present invention may also take many forms. Therefore, it is emphasized that the present invention is not limited to the explicitly disclosed methods, systems and devices, but is intended to include variations and modifications within the spirit of the appended claims.

[0147] As another example, changes can be made to the device or process constraints (e.g., size, configuration, components, order of process steps, etc.) to further optimize the provided structures, apparatus, and methods, as shown and described herein. Regardless, the structures and apparatus described herein and the related methods have many applications. Therefore, the disclosed subject matter should not be limited to any single example described herein, but should be interpreted in accordance with the breadth and scope of the appended claims.

Claims

1. A system comprising: Memory: one or more processors; as well as One or more computer executable instructions stored in the memory and executable by the one or more processors to perform the following operations, including: Identify patient data associated with patients who participate in vision screening tests; identifying a test category associated with the patient based at least in part on the patient data; generating a graphical representation for display to the patient based at least in part on at least one of the patient data or the test category, the graphical representation comprising at least one object configured to induce a change in an eye of the patient; determining one or more measurements associated with the eye of the patient in response to the graphical representation; generating first video data during the vision screening test, the first video data including the graphical representation being displayed and the patient; determining, based on the first video data, a plurality of positions of the patient's pupil throughout the vision screening test and at points in time when the graphical representation is displayed to the patient; generating second video data including the graphical representation included in the first video data and visual indicators indicating a plurality of positions of the pupil when the graphical representation is displayed to the patient; displaying, via a display unit, the second video data including the graphical representation and the visual indicator; comparing the one or more measured values ​​to one or more preset values; determining whether one or more values ​​satisfy a threshold based at least in part on the comparing; and Based at least in part on determining whether the difference satisfies the threshold, a diagnostic recommendation associated with the patient is generated.

2. The system of claim 1, wherein: The one or more measurements include at least one of a velocity or a position of a pupil of the eye, and wherein the one or more measurements are determined based at least in part on the first video data.

3. The system of claim 2, wherein: The change in the patient's eye includes at least one of a first movement of the pupil from near a leftmost position of the pupil to near a rightmost position of the pupil or a second movement of the pupil from near a topmost position of the pupil to near a bottommost position of the pupil.

4. The system of claim 1, wherein: The one or more measurements include at least one of a shape of a lens of the eye, a diameter of a pupil of the eye, or a cohesion of the pupil, and wherein the one or more measurements are determined at least in part based on the video data.

5. The system of claim 4, further comprising displaying the one or more measurements together with the diagnostic suggestion to a user.

6. A system comprising: Memory: one or more processors; as well as One or more computer executable instructions stored in the memory and executable by the one or more processors to perform the following operations, including: generating a graphical representation comprising at least one object configured to induce a change in an eye of a patient; displaying said graphical representation to said patient during a vision screening test; determining one or more measurements associated with the eye of the patient during the vision screening test; generating first video data during the vision screening test, the first video data including the graphical representation being displayed and the patient; determining, based on the first video data, a plurality of positions of the patient's pupil throughout the vision screening test and at points in time when the graphical representation is displayed to the patient; generating second video data including the graphical representation included in the first video data and visual indicators indicating a plurality of positions of the pupil when the graphical representation is displayed to the patient; displaying, via a display unit, the second video data including the graphical representation and the visual indicator; comparing the one or more measured values ​​to one or more preset values; and Based at least in part on the comparison, a diagnostic recommendation associated with the patient is generated.

7. The system of claim 6, further comprising: receiving patient data associated with the patient; and The graphical representation is determined based at least in part on the patient data.

8. The system of claim 6, wherein: Generating the diagnostic suggestion includes: determining whether the one or more measurements satisfy a threshold based at least in part on the comparing; and The diagnostic recommendation is generated based at least in part on determining whether the one or more measurements satisfy the threshold.

9. The system of claim 6, wherein: The change in the patient's eye includes at least one of a first movement of the pupil of the eye from near the leftmost position of the pupil to near the rightmost position of the pupil or a second movement of the pupil from near the topmost position of the pupil to near the bottommost position of the pupil.

10. The system of claim 6, wherein: The one or more measurements include at least one of a velocity of a pupil of the eye, a position of the pupil, a shape of a lens of the eye, a diameter of the pupil, or a cohesion of the pupil, and wherein the one or more measurements are determined at least in part based on the video data.

11. A method performed by a system, comprising: generating a graphical representation including at least one object based at least in part on the patient data, the object being configured To induce changes in a patient's eyes during vision screening tests; displaying the graphical representation to the patient during the vision screening test; generating first video data during the vision screening test, the first video data including the graphical representation being displayed and the patient; determining one or more eye measurements associated with the eye of the patient; determining, based on the first video data, a plurality of positions of the patient's pupil throughout the vision screening test and at points in time when the graphical representation is displayed to the patient; generating second video data including the graphical representation included in the first video data and visual indicators indicating a plurality of positions of the pupil when the graphical representation is displayed to the patient; displaying, via a display unit, the second video data including the graphical representation and the visual indicator; comparing the one or more measured values ​​to one or more predetermined values ​​to determine a difference; and A determination is made as to whether the difference satisfies a threshold.

12. The method of claim 11, further comprising generating a diagnostic recommendation associated with the patient based at least in part on the determining whether the difference satisfies the threshold.

13. The method of claim 11, wherein: The change in the patient's eye includes at least one of a first movement of the pupil of the eye from near the leftmost position of the pupil to near the rightmost position of the pupil or a second movement of the pupil from near the topmost position of the pupil to near the bottommost position of the pupil.

14. The method of claim 11, wherein: The one or more measurements include at least one of a velocity of the pupil, a speed of the pupil, a movement of the pupil, a shape of the patient's lens, a diameter of the pupil, or a cohesion of the pupil, and wherein the one or more measurements are determined at least in part based on the video data.

Images