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JP-2026514270-A - Systems and methods for evaluating visual cognitive function

JP2026514270AJP 2026514270 AJP2026514270 AJP 2026514270AJP-2026514270-A

Abstract

A computer implementation method for evaluating at least one aspect of a user's visual cognitive function, comprising: displaying multiple stimuli on the display screen of a handheld computing device; detecting the user's response or lack of response to the multiple stimuli; determining at least one attribute related to the user's response, each attribute indicating the difficulty level associated with viewing or processing the multiple stimuli; recording at least one attribute; and enabling evaluation of at least one aspect of the user's visual cognitive function. [Selection Diagram] Figure 1A

Inventors

  • ステファニー キャンベル
  • トーマス ウェムス

Assignees

  • オクロ リミテッド

Dates

Publication Date
20260508
Application Date
20231026
Priority Date
20221027

Claims (20)

  1. The steps include displaying multiple stimuli on the screen of a handheld computing device, The steps include detecting at least one response or lack of response from the user to these multiple stimuli, A step of determining at least one attribute related to the user's response, wherein each attribute indicates or relates to the difficulty level related to the perception or processing of multiple stimuli, A computer implementation method for evaluating at least one aspect of a user's visual cognitive function, comprising the step of recording at least one attribute so that at least one aspect of the user's visual cognitive function can be evaluated.
  2. A computer implementation method according to claim 1, i) A step of changing the difficulty level associated with viewing or processing multiple stimuli by changing multiple stimuli, ii) The step of presenting the modified multiple stimuli on the display screen of a handheld computing device, iii) A computer implementation method comprising the step of determining at least one attribute relating to the user's response to the modified set of stimuli.
  3. A computer implementation method according to claim 1 or 2, further comprising the step of evaluating, at least partially, one aspect of a user's visual cognitive function based on at least one attribute.
  4. A computer implementation method according to any one of claims 1, 2, or 3, At least one attribute is, Response time or mean response time; The number of inaccurate responses received from users; Display of the pattern or order of the received responses; The amount of movement of the handheld computing device relative to the user's eyes when a response is received; A computer implementation method in which the distance between the handheld computing device and the user or the user's eyes at the time the response is received is one or more of the following:
  5. A computer implementation method according to any one of claims 1 to 4, wherein detecting a user response includes receiving user input indicating the proposed position of each stimulus on a display screen.
  6. A computer implementation method according to claim 5, wherein at least one attribute includes the accuracy of the proposed position compared to the actual position of the stimulus on the display screen.
  7. A computer implementation method according to claim 5 or 6, further comprising determining whether a user response indicates that the user has seen each stimulus by determining whether the proposed location of the stimulus is within a predetermined range of the actual location of the stimulus on the display screen.
  8. A computer implementation method according to any one of claims 1 to 7, wherein determining at least one attribute is to determine the response time for each response, and this response time is the elapsed time between the display time the stimulus is presented on the display screen and the time when a response from the user is detected.
  9. A computer implementation method according to any one of claims 1 to 8, further comprising adjusting the response time determined considering the learning effect.
  10. A computer implementation method according to claim 9, comprising recording a value indicating the number of evaluations completed by the user or the number of stimuli presented to the user, applying a scaling method to a response time determined to account for learning effects, wherein the scaling method is at least partially based on the aforementioned value.
  11. A computer implementation method according to any one of claims 1 to 10, further comprising comparing at least one determined attribute with stored data, and/or monitoring the at least one determined attribute over a period of time or over a number of evaluations performed by the user.
  12. A computer implementation method according to claim 11, wherein comparing a determined at least one attribute with stored data includes comparing the determined at least one attribute with the user's stored data and/or comparing the determined at least one attribute with an age-specific database containing average data corresponding to age.
  13. A computer implementation method according to any one of claims 1 to 12, wherein determining at least one attribute includes determining an inaccurate response received from a user, each inaccurate response indicating that the user did not see a stimulus or did not see one of several stimuli.
  14. A computer implementation method according to claim 13, further comprising recording at least one of the time of receipt and the position on the display screen of each inaccurate response from a user, and/or determining the accuracy of the responses received from the user based on the number of inaccurate responses received.
  15. A computer implementation method according to any one of claims 1 to 14, wherein determining at least one attribute includes measuring the movement of a handheld computing device when each response from the user is detected, and/or determining the distance between the user or the user's eyes and the display screen each time a response from the user is detected.
  16. A computer implementation method according to any one of claims 1 to 15, wherein determining at least one attribute is to determine the order or pattern in which user responses to multiple stimuli are received, and/or the position of the display screen or device to which the user is looking each time a response from the user is detected, and/or the facial expression of the user while the user is identifying and/or responding to a stimulus.
  17. A computer implementation method according to any one of claims 1 to 16, wherein the plurality of stimuli are stimuli specifically presented for the purpose of evaluating visual cognitive function, and/or display elements or modifications thereof that are typically encountered during normal use of a handheld computing device.
  18. A computer implementation method according to any one of claims 1 to 17, wherein each stimulus has at least one respective visual characteristic, the at least one visual characteristic has a predetermined value selected for evaluating at least one aspect of visual cognitive function, and/or the at least one visual characteristic is one or more of the following: position on a display screen, contrast, color, detail, shape, dimensions, or movement of the stimulus on a display screen.
  19. A computer implementation method according to any one of claims 1 to 18, wherein one or more of a plurality of stimuli are repeatedly presented on a display screen, and a response or lack of response from the user is detected each time the stimuli are presented, and/or the plurality of stimuli are repeatedly presented on the display screen until a threshold is determined for at least one aspect of the user's visual cognitive function, and the method includes comparing at least one attribute related to the user's response to stimuli near the threshold for a predetermined aspect of the visual cognitive function with at least one attribute related to the user's response to stimuli exceeding the threshold for the same aspect of the visual cognitive function.
  20. A computer implementation method according to any one of claims 1 to 19, wherein the display screen consists of a touchscreen, and detecting a user response involves detecting the user's touch point on the touchscreen.

Description

This invention relates to a computer implementation method and system for evaluating at least one aspect of a user's visual function. Assessment of visual cognitive function is essential for understanding the health status and disease progression of a patient's eyes, vision, and cognitive systems, and for determining whether visual correction, medical intervention, or lifestyle intervention is necessary. Visual cognitive function is defined as the ability to acquire, interpret, and process visual information. Therefore, visual cognitive function may be affected by declines in the associated visual system or cognitive function related to specific activities. Accurate assessment of visual and cognitive function is crucial for the early detection and prompt initiation of treatment for eye and brain diseases. This is particularly challenging in children, the elderly, and patients with visual and/or cognitive impairments, where visual acuity test results are inherently more variable. If vision loss goes undetected, it can sometimes lead to blindness. This can have significant impacts on individuals, society, and the economy. Measuring visual cognitive function and visual function is fraught with difficulties due to the limitations of conventional test charts, leading to inherent variability and inaccuracy. Variability in testing stems from variations in the lighting of printed charts and differences in how the test is administered (e.g., the level of encouragement given to the patient). Large, distinct difficulty levels on visual acuity charts impair measurement accuracy, further increasing variability in results and hindering the identification of subtle or early changes in visual state. Common clinical visual function tests (such as the Snerlen visual acuity chart) rely on letter recognition. For children and individuals with learning disabilities or cognitive impairments, identifying and verbalizing all rows of letters and symbols is difficult, resulting in inaccurate results. Initially, when large stimuli such as letters and symbols are presented, most users can easily distinguish them and maintain high motivation. However, as traditional vision tests progress to smaller letters and symbols, users find them harder to see and lose confidence. When users become distracted, lower levels are recorded, making it difficult for clinicians to determine whether this is due to distraction or an underlying visual problem. When a patient reads a standard eye chart, the results are recorded as if they "correctly" read as many letters/symbols as possible, meaning there are two possible outcomes for identifying each letter/symbol: correct or incorrect. However, clinicians often report that patients with early-stage vision problems or impaired vision can often identify the symbols on the eye chart, but at a slower pace or with greater difficulty. Unfortunately, conventional eye charts and scoring methods lose this subtle and nuanced information about "difficulty," resulting in the failure to capture small changes in visual acuity. Embodiments of the present invention will be described below with reference only to the accompanying drawings, where similar reference numerals relate to similar elements. Figure 1A is an explanatory diagram of the display screen of a handheld computing device that performs visual evaluation according to one embodiment of the present invention.Figure 1B is an explanatory diagram of the display screen of a handheld computing device that performs visual evaluation according to another embodiment of the present invention.Figure 2 is a block diagram showing a handheld computing device according to an embodiment of the present invention.Figure 3 is a flowchart showing a computer implementation method according to an embodiment of the present invention.Figure 4 is a flowchart showing a part of a computer implementation method according to another embodiment of the present invention. Currently, visual acuity is typically measured as a threshold determined by difficulty level. For example, in traditional visual acuity charts, the smallest line of letters/symbols the patient can identify may be used as the lower limit of visual ability. However, it is becoming increasingly recognized that visual acuity tests may not always detect early signs of vision loss. Traditional visual acuity thresholds are often too coarse and likely miss subtle vision declines experienced by patients. Visual acuity refers to the central part of the retina and macula, specifically the area called the "fovea" (or "cone cells"), which is finely tuned for seeing details. Subtle vision loss can occur near the cone cells and therefore may be "missed" by conventional visual acuity tests that focus on the details of the central part of vision. Because a broad area of the macula is used for visual stabilization during image detection and recognition, partial defects in the surrounding macula may preferentially affect image localization and