METHOD AND/OR SYSTEM FOR TESTING VISUAL FUNCTION

Abstract

A method for performing an eye test includes the steps of: receiving a request from a user to perform the eye test; acquiring predetermined user identification data from the user; presenting or providing at least one test image to the user, the at least one test image including at least one test target contained therein; instructing the user to identify at least one of the at least one test target(s) contained within the at least one test image; acquiring response data associated with the user's attempt(s) to identify the at least one test target(s) contained within the at least one test image; aggregating and/or analysing the acquired user identification data and/or the response data utilising a test algorithm which determines result data; and, presenting or providing the result data to the user.

Claims

1-69. (canceled)

70. A method for performing a visual field test to evaluate a user's monocular peripheral vision at specific loci, without the need for dedicated professional equipment or qualified professional supervision, the method including the steps of: receiving a request from a user to perform the eye test; acquiring predetermined user identification data from the user; presenting or providing at least one test image to the user via at least one display, the at least one test image including at least one test target contained therein; instructing the user to identify at least one of the at least one test target(s) contained within the at least one test image; acquiring response data associated with the user's attempt(s) to identify the at least one test target(s) contained within the at least one test image; aggregating and/or analysing the acquired user identification data and/or the response data utilising a test algorithm which determines result data; and, presenting or providing the result data to the user; wherein the at least one test target(s) is circular and waveform in appearance and the apparent waveform traverses the at least one test target(s).

71. The method as claimed in claim 70, where the at least one test target(s) has at least two graphic segments for alternatingly displaying in at least one graphic segment at least one luminance-configurable colour at a predetermined frequency, and wherein the waveform of the at least one test target(s) is sinusoidal with one or more of peaks or troughs of the waveform defining that at least one graphic segment.

72. The method as claimed in claim 70, wherein the at least one test target(s) has a circular perimeter and the waveform traverses the center and the perimeter of the at least one test target(s).

73. The method as claimed in claim 71, wherein the at least one luminance-configurable colour includes one or more background colour of the at least one graphic segment, and wherein, the at least one luminance-configurable colour is displayed by being faded in and/or out including to and/or from the at least one luminance-configurable colour.

74. The method as claimed in claim 71, wherein the at least one luminance-configurable colour is presented at a predetermined frequency for a predetermined period in one or more intervals.

75. The method as claimed in claim 74, wherein the predetermined frequency is approximately 10 Hz to 110 Hz and the predetermined period is about 0.55 seconds.

76. The method as claimed in claim 74, wherein presentation of the at least one luminance-configurable colour creates a varied contrast during the predetermined period, and wherein, the varied contrast is increasing contrast

77. The method as claimed in claim 71, wherein the luminance of the at least one luminance-configurable colour is a relative luminance (“RL”) determined according by: assigning each Red/Green/Blue (“RGB”) colour component an integer value (“CRGB”) between 0 and 255; converting each component's CRGB integer value to equate with a respective component decimal value (“Co”) from 0.0 to 0.1; if the C.sub.D of a component >0.03928, applying the formula CL=(C.sub.D+0.055/1.055).sup.24 to determine the linear value of the component (“CL”); if the C.sub.D of a component<0.03928, applying the formula C.sub.L=(C.sub.D/12.92) to determine the linear value of the component (“CL”); and, adding the C.sub.L of each component to obtain a relative luminance (“RL”).

78. The method as claimed in claim 71, wherein the relative decibel (“rdB”) of at least two luminance-configurable colours are determined by applying the formula rdB=−2log(RL1−RL2)/(RL1+RL2).

79. The method as claimed in claim 78, wherein the rdB is between the range of about 6 to about 36 dB.

80. The method as claimed in claim 70, further including the steps of: measuring test-local light conditions to acquire corresponding data; processing the test-local light conditions data to determine calibration values; and, calibrating the at least one display according to the one or more determined or predetermined values. wherein, the test-local light conditions are measures via a sensor associated with the at least one display.

81. The method as claimed in claim 70, wherein the at least one test image(s) is/are animated images.

82. The method as claimed in claim 70, wherein the at least one test image(s) is/are divided into up to 80 loci by gridlines that are visible or invisible to the user, wherein the loci comprise at least one test locus and at least one non-test locus, and wherein, the up to 80 loci comprise 52 test loci.

83. The method as claimed in claim 70, wherein the at least one test image(s) includes a focus point positioned within the at least one test image(s), and wherein, the focus point is a moving optical element.

84. The method as claimed in claim 70, wherein an incorrect attempt(s) to identify the at least one test target(s) generates a false positive response data value.

85. The method for performing an eye test as claimed in claim 70, wherein the step of aggregating and/or analysing the acquired user identification data and/or the response data, utilises a test algorithm to optimise the performance and/or accuracy of the eye test, and wherein, the test algorithm includes artificial intelligence and/or machine learning and/or deep learning to optimise the performance and/or accuracy of the test; and wherein, the artificial intelligence and/or machine learning and/or deep learning is adapted to predetermine content and/or parameters of the eye test, including the content and/or parameters of any one or more of the following: the at least one test image(s); the at least one test target(s); the at least one test graphic(s); the at least one test locus; the duration for receipt of response(s); the gridlines that are visible or invisible to the user; the opacity of the at least one test target(s); eye test difficulty; the suitability of the position of the user relative to the display; the focus point; and the focus point location, based on any user identification data and/or the response data to optimise the performance and accuracy of the eye test.

86. The method as claimed in claim 70, further including a blind spot determination test for determining user fixation loss from a focus point.

87. The method as claimed in claim 86, wherein user fixation loss is determined by presenting a graphic at the location of the blind spot so that if fixation loss occurs the graphic becomes visible to the user.

88. The method as claimed in claim 87, wherein user fixation loss is used to calibrate loci parameters including loci number and loci geometry.

89. The method as claimed in claim 86, wherein the blind spot determination test is used to determine optimum user distance from the display and the precise distribution of test loci on the display.

Description

BRIEF DESCRIPTION OF THE DRAWINGS

[0077] In order that the invention may be more clearly understood and put into practical effect there shall now be described in detail preferred eye test methods and/or systems made in accordance preferred embodiments of the present invention, The ensuing description is given by way of non-limitative examples only and is with reference of the accompanying drawings, wherein:

[0078] FIG. 1 is a block diagram of a preferred method and/or system for testing for visual function of a user, made in accordance with a preferred embodiment of the present invention;

[0079] FIG. 2 is a flow diagram which illustrates a preferred method for calibrating a display for an eye test, made in accordance with a preferred embodiment of the present invention and being suitable for use with the preferred method and/or system for testing for visual function shown in FIG. 1;

[0080] FIG. 3 is a block diagram which illustrates a preferred system for calibrating a display for an eye test including a display associated with a user operable device, made in accordance with a preferred embodiment of the present invention and being suitable for use with the preferred method and/or system for testing for visual function shown in FIG. 1 and/or the method for calibrating a display for an eye test shown in FIG. 2;

[0081] FIG. 4 is a block diagram which illustrates a preferred alternative system for calibrating a display for an eye test including an eye test graphic presented on a display associated with a mobile device, made in accordance with a preferred embodiment of the present invention and being suitable for use with the preferred method and/or system for testing for visual function shown in FIG. 1 and/or the method for calibrating a display for an eye test shown in FIG. 2;

[0082] FIG. 5 shows a preferred circular eye test graphic with a sinusoidal waveform traversing the centre and perimeter of the eye test graphic made in accordance with a preferred embodiment of the present invention and being suitable for use with the preferred method and/or system for testing for visual function shown in FIG. 1, and the preferred system for calibrating a display for an eye test of FIG. 3 and/or the preferred alternative system for calibrating a display for an eye test of FIG. 4, as well as the preferred method for calibrating a display for an eye test shown in FIG. 2;

[0083] FIG. 6 shows a preferred test image of a geometric pattern including a preferred eye test graphic made in accordance with a preferred embodiment of the present invention and being suitable for use with the preferred method and/or system for testing for visual function as shown in FIG. 1, and where the focus point is not in the centre of the preferred test image;

[0084] FIG. 7 shows a further preferred test image of a geometric pattern comprising different visual tones defined by the loci of an 8 by 10 grid, and includes a preferred target locus of a different tone to the remaining non-target loci, and also includes a preferred focus point positioned within the grid, the preferred test image also being suitable for use with the preferred method and/or system for testing for visual function shown in FIG. 1;

[0085] FIG. 8 shows yet a further preferred test image of an alternative geometric pattern to that of FIG. 7 comprising two visual tones defined by the loci of an 8 by 10 grid, and also includes a preferred focus point positioned within the grid, the preferred test image also being suitable for use with the preferred method and/or system for testing for visual function shown in FIG. 1;

[0086] FIG. 9 shows still yet a further preferred test image which may be divided into 16 loci by way of a 4 by 4 grid, and which may include a preferred focus point positioned within the grid, the preferred test image also being suitable for use with the preferred method and/or system for testing for visual function shown in FIG. 1; and,

[0087] FIG. 10 shows still yet a further preferred test image, which may be used as part of a test question, as it may appear to a user during a visual function test, the preferred test image also being suitable for use with the preferred method and/or system for testing for visual function shown in FIG. 1.

MODES FOR CARRYING OUT THE INVENTION

[0088] In the following detailed description of the invention, reference is made to the drawings in which like reference numerals refer to like elements throughout, and which are intended to show by way of illustration specific embodiments in which the invention may be practiced. It is to be understood that other embodiments may be utilised and that procedural and/or structural changes may be made without departing from the spirit and scope of the invention.

[0089] Unless specifically stated otherwise as apparent from the following discussion, it is to be appreciated that throughout the description, discussions utilising terms such as “processing”, “computing”, “calculating”, “acquiring”, “transmitting”, “aggregating”, “receiving”, “retrieving”, “identifying”, “determining”, “analysing”, “manipulating” and/or “displaying”, or the like, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system's registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices.

[0090] Discussions and direct or indirect reference regarding any apparatus for performing the operations of the invention are provided herein. This apparatus may be specially constructed for the required purposes, or it may comprise a general-purpose computer selectively activated or reconfigured by a computer program stored in the computer. Such a computer program may be stored in a computer readable storage medium, such as, but is not limited to, any type of disk including floppy disks, optical disks, CD-ROMs, and magnetic-optical disks, read-only memories (ROMs), random access memories (RAMS), erasable programmable read-only memory (EPROMs), electrically erasable programmable read-only memory (EEPROMs), magnetic or optical cards, or any type of media suitable for storing electronic instructions, and each coupled to a computer system bus.

[0091] The software modules, applications, or any engines and displays or any GUIs presented or discussed directly or indirectly herein are not inherently related to any particular computer or other apparatus. Various general-purpose systems may be used with programs in accordance with the teachings herein, or it may prove convenient to construct more specialised apparatus to perform the required method steps, The required structure for a variety of these systems will appear from the description below. In addition, the present invention is not described with reference to any particular programming language. It will be appreciated that a variety of programming languages may be used to implement the teachings of the invention as described herein.

[0092] Although separate modules, applications or any engines (e.g. module(s)/application(s) and database(systorage device(s) are described including with reference to one or more network server, each for effecting specific preferred aspects (or combinations thereof) of the method and/or system, it should be appreciated that any number of modules/applications/engines/databases/storage devices for performing any one, or any suitable combination of, aspects of method and/or system, could be provided (wherever required) in accordance with the present invention. A person skilled in the relevant art will appreciate many such module(s)/application(s)/engine(s) and databases(s)/storage devices, embodiments, modifications, variations and alternatives therefor, and as such the present invention should not be construed as limited to any of the examples provided herein and/or described with reference to the drawings.

[0093] A machine-readable medium includes any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer). For example, a machine-readable medium includes read only memory (“ROM”); random access memory (“RAM”); magnetic disk storage media; optical storage media; flash memory devices; electrical, optical, acoustical or other form of propagated signals (eg., carrier waves, infrared signals, digital signals, etc.); etc.

[0094] In FIG. 1 of the drawings there is shown a block diagram of a preferred method and/or system 10 (hereinafter generally referred to as “method 10” for simplicity) for enabling a user 11n to perform a preferred visual function test by way of a user operable device 12n, Method 10 is suitable for use over a communications network(s) 80n, such as, for example, the Internet, as shown. It should be understood however, that method 10 of the present invention is not limited to that use only.

[0095] The term “user operable device 12n” refers to any suitable type of computing device or software application, etc., capable of transmitting, receiving, capturing, conveying and/or displaying data as described herein, including, but not limited to, a mobile or cellular phone, a smart phone, an App, a smart watch or other wearable electronic device, an augmented reality device, a connected Internet of Things (“loT”) device; a Personal Digital Assistant (FDA), and/or any other suitable computing device, including a server, personal, desktop, tablet, notebook computer or any combination thereof or combination of sub-components thereof.

[0096] To start the preferred visual function test (hereinafter simply referred to as “test”), method 10 commences at block 14, whereat a user 11n may request the performance of the test via a user operable device 12n. At block 15 a display 13n (see, for example, FIGS. 3 and 4) associated with the user operable device 12n can be calibrated according to the preferred method for calibrating a display 15A of FIG. 2, using preferred system 15B of FIG. 3, or the alternative preferred system of 15C of FIG. 4, or any other suitable system (not shown). The steps of method 15A for calibrating a display in FIG. 2 can be performed on a suitable combination of the display 13n of a user operable device 12n such as in FIG. 3 or 4, and preferably includes measuring test-local light conditions 15(i), including those light conditions local to the display 13A, to acquire test-local light conditions data 15(ii), processing the acquired test-local light conditions data 15(iii) to determine display calibration values 15(iv) and then calibrating the display using one or more pre-determined values and/or the values determined during the display values determination step 15(v) of the method for calibrating a display 15A, thus allowing for the display 13n to be preferably appropriately calibrated for the test according to method 10. Calibrating the display 13n provides more consistent results as between separate tests and within individual tests to promote overall test accuracy.

[0097] Preferred system 15B of FIG. 3 includes a display 13n for displaying the visual function test, display 13n being preferably in communication with a user operable device 12n via a communication network 80n, such as a cellular network (not shown). System 15B preferably utilises a data acquisition device/module 12n(i) for acquiring test-local light conditions 13A data, and a data processing device/module 12n(ii) to process the acquired test-local light conditions 13A data and to determine the calibration values, and also to calibrate the display 13n. In an alternative preferred system 15C, shown in FIG. 4, a test target 3n displayed on display 13n forms part of the test-local light conditions 13A, and mobile device 12n (user operable device 12n) is used to measure 15(i) and acquire test-local light conditions data 15(ii), process the test-local light conditions data 15(iii), determine display calibration values 15(iv), and calibrate the display 15(v). In either preferred system 156 or 15C, the display 13n may be calibrated manually on the display 13n following instructions 12A for manual calibration obtained from the data processing and calibration device/module 12n(ii) or mobile device 12n of the respective systems 15A or 15B. In an embodiment, the instructions for manual calibration 12A may be presented on display 13n and so that user 11n can calibrate by toggling appropriate display controls (not shown) themselves.

[0098] User 11n is then preferably prompted or otherwise, at block 16, to provide predetermined user 11n details (hereinafter simply referred to as “user data”). Preferred user data may include, but is not limited to, the user's 11n name, gender, age, contact telephone number, location, etc. The user data provided at block 16, of method 10, is then captured and stored on a data storage device(s) or module(s) 17n which is preferably part of a data and analysis module(s) 50, which is hosted or otherwise provided by one or more network server(s) (not shown). The preferred process of capturing and storing user data on data storage device(s) or module(s) 17n, is represented by block 51 within preferred data and storage module(s) 50.

[0099] At block 18 the user 11n is prompted to perform a blind spot determination test. The blind spot determination test, or a suitable adaptation thereof, is used to determine the location of the user's 11n blind spot—this information can be used to determine if the user 11n is suitably distanced from the display 13n, and also used to more precisely map the test loci on the display 13n. Once the blind spot is determined it can be employed during the eye test according to method 10 to determine user fixation loss from focus point 2n by presenting a graphic (not shown) at the location of an initially determined blind spot (not shown) so that if user 11n looks away from focus point 2n the graphic becomes visible to the user 11n and the user 11n is thereby alerted that they have lost fixation on focus point 2n. In the event that user 11n has lost fixation due to, for example, moving away from or closer to the display 13n during the test, the blind spot test can be performed again to determine the user's 11n new location in reference to the display 13n and used to calibrate the loci 1n parameters, including the number of loci 1n as well as loci 1n geometry, or any other parameters, to suit the new location of the user 11n in reference to display 13n.

[0100] An instruction page(s) or GUI(s) (not shown), which can include an animation, video or voice recording to provide instructions on how to take the test is then preferably presented to user 11n, at block 19, which preferably includes instructing user 11n to conduct the test monocularly, wherein user 11n is instructed to keep one eye covered at a time during the whole or part of the test. At this point of preferred method 10, i.e. at block 19, user 11n may also be instructed to take the test undisturbed, in a sufficiently darkened room, and informed of the duration of the test which may take approximately 15 to 20 minutes, or any other suitable time as required or desired. Method 10 then continues at block 20, whereat a general question screen(s) or GUI(s) (not shown) is preferably displayed to the user 11n, which can provide further instruction or additional information, including providing a list of test questions, and which also allows user 11n to initiate the presentation of the test questions, at block 22, in order to continue the preferred test of method 10.

[0101] After initiating the presentation of the test questions, at block 22, a series of test questions in the form of timed tasks are presented to user 11n iteratively. In a preferred embodiment of method 10 of the present invention, one or more test image(s) 23n of geometric pattern(s) comprising at least two different visual tones defined by sectors 1n (hereinafter referred to as “loci 1n”), arranged within a preferred 8 by 10 grid (examples of which are shown in, for example, FIGS. 7 and 8) may be presented to user 11n with at least one test target 3n (as best shown in, for example, FIG. 7) disposed therein. The one or more test target(s) 3n may be one or more loci 1n (i.e. test loci 3n) and may have a tonal value different to other non-target loci 1n. The tonal value of the one or more test loci 3n may correlate to a test difficulty level of one of a number of difficulty levels, such as, for example, four preferred levels of difficulty. In further preferred embodiments, any visual value of any loci 1n, test target 3n, or test image 23n may be assigned a correlated test difficulty level.

[0102] In one embodiment of preferred method 10, the test may involve presenting still or animated images 23n (as will be described in further detail below with reference to, for example, FIGS. 6 to 10) of common objects, virtual scenes of daily life, or other suitable images, that are preferably formed composite with the aforementioned grid-based patterns (not shown), along with respective test targets 3n (examples of which are shown in FIGS. 6 to 10) to be identified and selected by user 11n. The common objects or virtual scenes preferably include, but are not limited to, objects and scenes such as: a street scene (such as, for example, that depicted in FIG. 10; faces in a crowd; hidden objects; camouflaged animals; a cutlery drawer; persons or objects in a crowded room; shadowy furniture; a newspaper; and/or, any other test image 23n determined to be suitable. Test targets 3n to be identified and selected within test images 23n preferably include, but are not limited to: symbol(s)/letter(s); an object(s) or part(s) of an object(s); a graphic; a moving, animated, vibrating or spinning object(s); and/or, any other test target 3n determined to be suitable. For example, referring to FIG. 10, test targets 3n could be a bollard 3n, a shop sign 3n, flag 3n, or a bus 3n. One practical preferred embodiment of preferred method 10, may also involve hazard perception driving videos, traffic light changes, locating vehicles and associated objects on a road, and similar. It will be appreciated that the type of test image(s) 23n used, and the test target(s) 3n to be identified therein, is/are not limited, and new test images 23n and test targets 3n may be deemed suitable by, for example, testing their ability to generate accurate test results.

[0103] More specifically, a given timed task (of a test question, presented to user 11n, at block 22) may require user 11n attempting to correctly select a test target 3n located in one of any suitable number of loci I n, e.g. in one of 52 of 80 numbered loci 1n as shown, for example, FIG. 7 or 8, defined by preferred gridlines, which can be visible or invisible to the user 11n, as is illustrated by way of the exemplary test images 23n shown in FIGS. 7 to 9. The test may be grouped for scoring based on which loci 1n is being tested. Each locus 1n may be tested by a number of test questions of varying levels of difficulty and duration, resulting in a number of response data values being generated per locus in. The relative difficulty of each timed task may be predetermined by any suitable predefined test, data or analysis, such as, for example, a suitable Item Response Theory (“RT”) analysis, such as, for example, a Rasch analysis or Partial Credit model analysis, performed on sample evaluation among a cohort of healthy controls and Glaucoma patients of different severity levels by an IRT analysis module 53n (see, FIG. 1).

[0104] Test questions, presented at block 22, of preferred method 10, may involve specific peripheral vision testing in which a predefined focal point 2n, such as, for example, a still or spinning star 2n, may be presented as an initial focus starting point during the test, as shown in, for example, FIGS. 6 to 10. The focal point (hereinafter simply referred to as “star 2n”), may be located anywhere on the test image 23n, including at a suitable intersection of gridlines, such as, for example, at the centre of the image 23n as shown in, for example, FIGS. 7 to 10, or at another suitable location as shown in FIG. 6. Users' 11n may be asked to make selections while focusing their vision on star 2n, or may be asked to focus on star 2n initially, and then subsequently be permitted to move their eyes and/or head to complete a given timed task.

[0105] A test target 3n within a test image 23n, presented as part of a test question, at block 22, of preferred method 10, may be selected or otherwise identified, or in a preferred form of the test only the presence or absence of a test target 3n identified, by the user 11n, for example: utilising a mouse, or other GUI pointing device (not shown), to click or otherwise select a potential test target 3n; touching a touchscreen; or answering or otherwise replying to a task question either verbally or by way of a gesture, etc. A given test question may have multiple test targets 3n per image 23n. Test targets 3n are preferably vetted for repeated test takers (i.e. users 11n) to avoid repetition so that users 11n do not habitually learn the correct test target 3n locations and generate erroneous results.

[0106] Test targets 3n, and test images 23n, can be sourced from a pool of prior test images 23n stored on the network server(s) (not shown) which hosts or otherwise maintains/provides data and analysis module(s) 50, or they may be obtained from other suitable data source(s) 60n, including, for example, external data source(s) 60n readily accessible over the internet (communications network(s) 80n). Test target 3n and/or test image 23n opacity, dimensions and other characteristics may be predetermined, altered and/or adjusted as required or desired.

[0107] A suitable test question (and its test image 23n, with test targets 3n contained therein) may appear to user 11n, at block 22, of preferred method 10, in the format as shown in any one of FIGS. 6 to 10.

[0108] The completion of the test questions (presented at block 22) is rated on Pass 26 (block 26) or Fail 24 (block 24) gradings, as shown in FIG. 1. The gradings are preferably measured by two parameters: the correct completion of the timed task, and, completion of the timed task in the allocated time. A Pass (at block 26) is achieved when both parameters are satisfied, that is, when user 11n finds the requested test target 3n object(s) in allocated time, and user 11n Fails (at block 24) a test question when they are unable to correctly identify the test target 3n object(s) in the allocated time.

[0109] The test of preferred method 10, continues for a predetermined number of iterations (as indicated by block 30), until all the test questions are completed by user 11n and a result can be generated to be selectively provided to user 11n. Following each test question, the response value (i.e. Pass or Fail, at blocks 26 or 24) and the time taken to select a target (i.e. the response time), both of which can be referred to as response data, is/are sent/captured by data and analysis module(s) 50, as is indicated by block 28.

[0110] Following the capture/acquisition of user 11n response data at block 28, all obtained response data is consolidated/aggregated, at block 52, with the preferred user data that was captured/acquired/stored at block 51, and thereafter, the consolidated/aggregated data is analysed against a population database (stored on the network server(s) (not shown) associated with data and analysis module(s) 50) that has been validated and vetted/calibrated against a cohort of glaucoma patients of various levels of visual function, and/or any other suitable cohort, and/or any data acquired from any prior eye tests. This step/stage being preferably accomplished by a test algorithm module(s) 53n, and optionally an IRT analysis module(s) 53n, an eye locus performance map module(s) 53n, and/or an artificial intelligence module(s) 53n (which may be separate or consolidated module(s) 53n) associated with, or of, data and analysis module(s) 50. This analysis and specifically the test algorithm of the module(s) 53n may be based on a suitable algorithm or test as required or desired.

[0111] The test algorithm(s) of modules) 53n assess a user's 11n visual function relating to glaucoma for each of the loci 1n of the test image 23n, such as, for example, the loci 1n of the test images 23n shown in FIGS. 7 to 9. A staircase method is preferably used in the test algorithm of module(s) 53n, where the difficulty level of subsequent test questions is based on the time taken to select a target and/or success of previous test questions and optionally compared to predetermined control values, such as, for example, an age-matched cohort sample. When sufficient response data per loci 1n is acquired (at blocks 28 & 52), that response data can be used to generate a map per eye locus, as is indicated by way of block 54. Preferably, two global summary scores for each eye may also be produced: a mean ability and a variation between loci scores. The map per eye locus and global summary scores, generated at block 54, may then be provided to user 11n, and/or may be stored (e.g. in data storage device(s) or module(s) 17n, or externally in, for example, an associated cloud (not shown)) for future access/retrieval purposes.

[0112] The reliability of the test of preferred method 10, of the present invention, may be monitored by the test algorithm module(s) 53n, including the or its artificial intelligence module 53n, and/or any another suitable module(s) 53n, such that, for example: false positives may be recorded by the number of incorrect answers; false negatives may be tested by evaluating question tests of lower difficulty than a predetermined difficulty for one or more particular loci 1n, etc. Fixation loss/reversion to binocularity may also be preferably tested by evaluating test question response times/items in test questions which are of higher difficulty than a predetermined difficultly level for one or more particular loci 1n, e.g. in the one or more loci 1n of the exemplary test images 23n shown in FIGS. 7 to 9.

[0113] According to preferred method 10 the test target 3n may include or may preferably be in the form of a test graphic 3A as shown in FIG. 5, where the graphic preferably has a circular perimeter 3A(i) and includes a sinusoidal waveform 3A(ii) traversing the center 3A(iii) and the circular perimeter 3A(i). The peaks 3A(iv) and troughs 3A(v) of the sinusoidal waveform 3A(ii) preferably define luminance-configured graphic segments where the luminance is a relative luminance RL which has preferably been determined by he following mathematical steps:

[0114] assigning each Red/Green/Blue (“RGB”) colour component an integer value (“CRGB”) between 0 and 255;

[0115] converting each component's CRGB integer value to equate with a respective component decimal value (“C.sub.D”) from 0.0 to 0.1;

[0116] if the C.sub.D of a component>0.03928, applying the formula C.sub.L=(CD+0.055/1.055).sup.24 to determine the linear value of the component (“C.sub.L”);

[0117] if the C.sub.D of a component<0.03928, applying the formula C.sub.L=(C.sub.D/12.92) to determine the linear value of the component (“C.sub.L”);

[0118] adding the C.sub.L of each component to obtain a relative luminance (“RL”).

[0119] In preferred method 10 one or more luminance of the one or more luminance-configured colours of one or more graphic segments defining one or more sinusoid peaks 3A(iv) and/or troughs 3A(v) may be configured with a relative decibel valued (rdB) colour using the following formula: rdB=−2log(RL1−RL2)/(RL1+RL2), to obtain rdB resembling standard automated penmen)/range, being 30 to 46 dB. One or more luminance-configured colours defining one or more sinusoid peaks 3A(iv) and/or troughs 3A(v) wherein the luminance has been configured with an RL or rdB value, can be assigned to one or more difficulty levels of the eye test according to method 10.

[0120] A luminance-configurable colour in preferable embodiment of eye test graphic 3A (best shown in FIG. 5), can be displayed by cyclically fading (or transitioning) the luminance-configurable colour in or out (or both) in a given graphic segment defining a sinusoid peak 3A(iv) or trough 3A(v), and/or fading to and/or from (or both) another luminance-configurable colour defining a peak 3A(iv) or trough 3A(v). A display cycle from one luminance-configurable colour to another and back can be made at a frequency selected from preferred frequency range of approximately 10 Hz to 110 Hz, for a preferable display period of about (155 seconds.

[0121] In the preferred embodiment of eye test graphic 3A the display cycle may involve a peak 3A(iv) having a first luminance-configurable colour transitioning (or fading) to a trough 3A(v) and back to the peak 3A(iv) in the same graphic segment, there being two or more graphic segments and in each adjacent graphic segment the opposite of a peak 3A(vi) or trough 3A(v) being displayed, thus forming sinusoidal waveform 3A(ii) where each peak 3A(iv) transitions to a trough 3A(v) and back in an undulating display cycle. It should be appreciated that a display cycle may start at any point between the transition from/to a peak 3A(iv) or a trough 3A(v).

[0122] During each display period, the luminance-configurable colours may be displayed to vary in contrast and preferably so that initial display cycles have less contrast and increase to having higher contrast in latter display cycles. In an alternative preferred method 10 contrast may increase across a number of periods.

[0123] It will be appreciated that the shape of the eye test graphic 3A does not need to be circular, and sinusoidal waveform 3A(ii) may traverse the graphic 3A other than by from the perimeter 3A(i) to the center 3A(iii). To remove any doubt, reference to a peak also refers to the whole of a positive part of a waveform cycle, and reference to a trough also refers to the whole of a negative part of a cycle.

[0124] Referring to FIG. 6, the test target 3n includes the eye test graphic 3A as presented within a test image 23n of an array of forms, the tonality of eye test graphic 3A having being adjusted to show a lighter tonal value.

[0125] Artificial intelligence in the form of one or more artificial intelligence algorithm(s), module(s) or application(s) (hereinafter collectively referred to as artificial intelligence module(s) 53n) which use machine or deep learning (as shown in FIG. 1) in association, or combination with, various other software and/or hardware module(s) or application(s) (e.g. module(s) 53n) is preferably adapted to analyse any/all acquired/consolidated/aggregated user data, response data, result data and map of eye performance data collected and/or otherwise acquired/aggregated, etc., by data and analysis module(s) 50, and/or data sources 60n, either periodically or live (or substantially in real-time), and/or during the test, of preferred method 10, being conducted, and/or after each or any step of preferred method 10, and is also preferably adapted to optimise the performance of the test and improve test accuracy. Artificial intelligence module(s) 53n may also preferably be used to monitor change over time of the test(s) to determine if an individual's 11n vision and/or level of glaucoma has worsened over time. This change over time may be represented and/or conveyed to the user 11n by any suitable means, but is preferably conveyed graphically by any suitable means by way of method 10. Thus, a user 11n may repeat the test over a period of time and be able to see whether their vision has worsened since their first of subsequent test(s) in accordance with method 10.

[0126] The artificial intelligence module(s) 53n is also adapted to directly interact with the data module(s) 53n, test algorithm module(s) 53n, IRT algorithm module(s) 53n, and map of eye locus performance module(s) 54 and/or one or more aspects of any one or more of the mentioned rnodule(s) 53n, other suitable modules which may be added as part of the method 10, as well as the instructions from the non-transitory computer readable medium of the present invention, and/or of any suitable system that may be deployed in accordance with the present invention.

[0127] Artificial intelligence module(s) 53n is also preferably specifically adapted to predetermine and/or generate any content and parameters of the test, including, but not limited to: the test images 23n; test targets 3n (within test images 23n); test graphic(s) 3A; test duration; loci 1n, gridline numbers, etc.; test target 3n opacity; difficulty of the test; focal point 2n; and focal point 2n location, based on any data available to artificial intelligence module(s) 53n resulting from any part or stage of preferred method 10, etc., any instructions of/for a non-transitory computer readable medium, and/or any part of any preferred practical system of the present invention.

[0128] Artificial intelligence module(s) 53n is also preferably adapted to select suitable test images 23n and test targets 3n including test graphic(s) 3A (within test images 23n), as required or desired, based on comparing/vetting their suitability against, for example, previously selected test images 23n and test targets 3n, test graphic(s) 3A, etc.

[0129] Preferred method 10 of the present invention, may be performed wholly or partially using one or more computing devices (i.e. network server(s)—not shown) executing a set of instructions of the method 10, which may be sourced and then executed from a non-transitory computer readable medium (not shown) associated with the one or more computing device(s) (i.e. network server(s)—not shown) which store or otherwise contains/provides the instructions.

[0130] Preferred method 10 of the present invention may be performed wholly or partially by a system (e.g. shown in FIG. 1) which includes one or more eye test module(s) or application(s) 50; one or more algorithm module(s) or application(s) 53n; one or more data module(s) 17n/52n/53n; one or more IRT analysis algorithm module(s) 53n; one or more eye locus performance map module(s) or application(s) 53n/54; and one or more artificial intelligence and/or machine learning and/or deep learning module(s) or application(s) 53n, and/or any other module(s)/application(s) deemed suitable.

[0131] It will be appreciated the method 10 may be performed by a system that includes distributing one or more aforementioned module(s)/application(s) 50/53n across such a system, including one or more network server(s) and/or computing device(s) and/or computing mean(s) (not shown), and one or more user operable devices 12n, that are all preferably operable over communications network(s) 80n.

[0132] It will be appreciated that the one or more network server(s) (not shown) associated with data and analysis module(s) 50 is/are preferably configured to communicate with user operable devices 12n, and data source(s) 60n, via any suitable communications connection(s) or network(s) 80n. Data source(s) 60n may be configured to transmit and receive data to/from network server(s) (now shown) associated with data and analysis module(s) 50, via one or more communicates network(s) 80n. User operable devices 12n may be configured to transmit, receive capture and/or display data, including test question data from/to the network server(s) (not shown) associated with data and analysis rnodule(s) 50 via one or more communications network(s) 80n. Each user operable device 12n and data source(s) 60n provider, may communicate with the network server(s) (not shown) associated with data and analysis module(s) 50 via the same or a different communications network(s) 80n. Suitable communications network(s) 80n include, but are not limited to: a Local Area Network (LAN); a Personal Area Network (PAN), as for example an Intranet; a Wide Area Network (WAN), as for example the Internet; a Virtual Private Network (VPN); a Wireless Application Protocol (WAP) network, or any other suitable telecommunication network, such as, for example, a GSM, 3G, 4G, 5G, etc., network; Bluetooth network; and/or any suitable WiFi network (wireless network). The network server(s) (now shown) associated with data and analysis module(s) 50, data source(s) 60n providers, and/or user operable device(s) 12n, may include various types of hardware and/or software necessary for communicating with one another via the one or more network(s) 80n, and/or additional computers, hardware, software, such as, for example, routers, switches, access points and/or cellular towers, etc. (not shown), each of which would be deemed appropriate by persons skilled in the relevant art.

[0133] For security purposes, various levels or security, including hardware and/or software, such as, for example, application programming interfaces (or “APIs”), firewalls, tokens, two-step authentication (not shown), etc., may be used to prevent the unauthorized access to, for example, the network server(s) (now shown) associated with data and analysis module(s) 50, and/or data source(s) 60n. Similarly, the network server(s) (not shown) associated with data and analysis module(s) 50 may utilise security (e.g. hardware and/or software—not shown) to validate access by user operable devices 12n. It is also preferred that the network server(s) (not shown) associated with data and analysis module(s) 50 performs validation functions to ensure the integrity of data transmitted between data source(s) 60n and/or user operable devices 12n. A person skilled in the relevant art will appreciate such technologies and the many options available to achieve a desired level of security and/or data validation, and as such a detailed discussion of same will not be provided. Accordingly, the present invention should be construed as including within its scope any suitable security and/or data validation technologies as would be deemed appropriate by a person skilled in the relevant art.

[0134] Communication and data transfer between the network server(s) (now shown) associated with data and analysis module(s) 50, data source(s) 60n and/or user operable devices 12n, may be achieved utilising any suitable communication, software architectural style, and/or data transfer protocol, such as, for example, FTP, Hypertext Transfer Protocol (HTTP), Representational State Transfer (REST); Simple Object Access Protocol (SOAP); Electronic Mail (hereinafter simply referred to as “e-mail”), Unstructured Supplementary Service Data (USSD), voice, Voice over IP (VoIP), Transfer Control Protocol/Internet Protocol (hereinafter simply referred to as “TCP/IP”), Short Message Service (hereinafter simply referred to as “SMS”), Multimedia Message Service (hereinafter simply referred to as “MMS”), any suitable Internet based message service, any combination of the preceding protocols and/or technologies, and/or any other suitable protocol or communication technology that allows delivery of data and/or communication/data transfer between network server(s) (not shown) associated with data and analysis module(s) 50, data source(s) 60n and/or user operable devices 12n, in accordance with preferred method 10 of the present invention. Similarly, any suitable data transfer or file format may be used in accordance with preferred method 10 of the present invention, including (but not limited to): text; a delimited file format, such as, for example, a CSV (Comma-Separated Values) file format; a RESTful web services format; a JavaScript Object Notation (JSON) data transfer format; a PDF (Portable Document Format) form at; and/or, an XML (Extensible Mark-Up Language) file format.

[0135] It will be appreciated that the illustrated invention provides an easy, objective method and/or system 10 for detecting glaucoma that is reflective of real-world visual function and which can be taken by an individual 11n on a user operable device 12n in an individual's 11n home or at another convenient location.

[0136] While this invention has been described in connection with specific embodiments thereof, it will be understood that it is capable of further modification. The present invention is intended to cover any variations, uses or adaptations of the invention following in general, the principles of the invention and including such departures from the present disclosure as come within known or customary practice within the art to which the invention pertains and as may be applied to the essential features hereinbefore set forth.

[0137] As the present invention may be embodied in several forms without departing from the spirit of the essential characteristics of the invention, it should be understood that the above described embodiments are not to limit the present invention unless otherwise specified, but rather should be construed broadly within the spirit and scope of the invention as defined in the attached claims. Various modifications and equivalent arrangements are intended to be included within the spirit and scope of the invention. Therefore, the specific embodiments are to be understood to be illustrative of the many ways in which the principles of the present invention may be practiced.

[0138] Where the terms “comprise”, “comprises”, “comprised” or “comprising” are used in this specification, they are to be interpreted as specifying the presence of the stated features, integers, steps or components referred to, but not to preclude the presence or addition of one or more other features, integers, steps, components to be grouped therewith.