A method, system, medium, and product for checking the flexibility of assembly and disassembly.

Abstract

This invention discloses a method, system, medium, and product for examining convergence flexibility, belonging to the field of ophthalmic examination. The method comprises: simultaneously acquiring binocular eye movement trajectory data of the examinee during prism stimulation examination, including fixation on a preset target and alternating reception of base-in and base-out prism stimulation; calculating the actual convergence angle at each moment based on the eye movement trajectory data, and calculating the theoretical convergence angle by combining the target distance and the corresponding prism power, thereby obtaining the convergence angle deviation at each moment; extracting fixation events from the eye movement data, and using the convergence angle deviation within a preset time window before each fixation event and a preset threshold to mark the fusion recovery time; finally, counting the number of complete convergence cycles per unit time based on the fusion recovery time to obtain the convergence flexibility index. By implementing this invention, the problem of existing convergence flexibility examinations relying on subjective feedback and being unable to objectively and automatically determine the fusion recovery time can be solved.

Description

Technical Field

[0001] This invention belongs to the field of ophthalmic examination and relates to a method, system, medium, and product for examining convergence and divergence flexibility. Background Technology

[0002] Convergence-divergence flexibility is an important indicator for assessing the dynamic coordination ability of the binocular visual system. It is widely used in ophthalmology, optometry, and vision training to screen for accommodation-convergence dysfunction and guide visual rehabilitation. Clinical examination typically involves alternating base-in and base-out prisms while the subject fixates on a near target to induce convergence-divergence responses, with the number of convergence-divergence cycles completed per unit time serving as the quantitative indicator.

[0003] In existing technologies, the determination of the fusion recovery time relies on the subject's subjective feeling of "the image changing from diplopia to clear single image" and the examiner records the number of times this is completed. Although this method is simple to operate, it requires the subject to have good language expression and cooperation ability, which is not suitable for children, the elderly or people with cognitive impairment. Moreover, subjective judgment is easily affected by factors such as attention and reaction delay, resulting in poor repeatability and insufficient objectivity of the results, making it difficult to meet the needs of accurate visual function assessment. Summary of the Invention

[0004] This application provides a method, system, medium, and product for checking convergence flexibility, which can solve the problem that the existing technology relies on subjective feedback for checking convergence flexibility and cannot objectively and automatically determine the fusion recovery time.

[0005] To achieve the above objectives, in a first aspect, the present invention provides a method for checking the flexibility of convergence and divergence, comprising: Acquire binocular eye movement trajectory data of the examinee; wherein, the binocular eye movement trajectory data is collected synchronously during the prism stimulation test; the prism stimulation test is the process in which the examinee fixates on a preset target and alternately receives stimulation from a base-in prism and a base-out prism. Based on the eye movement trajectory data, the actual convergence angle at each moment is calculated, and the convergence angle deviation at each moment is calculated based on the actual convergence angle at each moment and the binocular theoretical convergence angle of the prism used at that moment; wherein, the binocular theoretical convergence angle is calculated based on the prism power and the target distance of the prism. Fixation events are extracted from the eye-tracking data, and the fusion recovery time is marked based on the convergence angle deviation within a preset time window before each fixation event and a preset convergence angle deviation threshold. Based on the fusion recovery time of each image, the number of complete convergence-disconvergence cycles per unit time is counted to obtain the convergence-disconvergence flexibility index.

[0006] Compared to existing technologies, the embodiments of this application have the following beneficial effects: By acquiring binocular eye movement trajectory data, a high temporal resolution physiological signal basis is provided for subsequent objective determination of fusion status; furthermore, by calculating the actual convergence angle at each moment based on the eye movement trajectory data, and combining it with the binocular theoretical convergence angle calculated based on the prism diopter and target distance, the convergence angle deviation at each moment is calculated, enabling the system to quantify the degree of deviation between the current eye position and the theoretically required eye position, thereby establishing a calculable fusion stability criterion; simultaneously, by extracting fixation events from the eye movement trajectory data, and marking the fusion recovery moment based on the convergence angle deviation within a preset time window before each fixation event and a preset convergence angle deviation threshold, fusion recovery is achieved. The automated fusion assessment mechanism, centered on eye position stability, avoids reliance on subjective reports. Furthermore, by statistically analyzing the number of complete convergence-divergence cycles per unit time at each fusion recovery moment to obtain the convergence-divergence flexibility index, an automated mapping from raw physiological signals to clinical quantitative indicators is achieved. The synergistic effect of these features enables the entire scheme to automatically identify fusion recovery events and calculate dynamic convergence-divergence capability based on the objective standard of whether the convergence-divergence angle deviation of both eyes continuously enters the physiological range of fusion (such as the Paum zone) without the need for active feedback from the subject. This solves the fundamental problem of existing technologies where convergence-divergence flexibility testing relies on subjective perception and cannot be objectively and automatically executed, significantly improving the universality, repeatability, and clinical reliability of the test.

[0007] In some embodiments of the first aspect of this application, the theoretical binocular convergence angle is calculated based on the prism power and the target distance, including: Multiply the prism power by the target distance to obtain the product data, and divide the product data by one hundred to obtain the normalized offset. The arctangent function value is calculated for the normalized offset to obtain the monocular deflection angle, and the monocular deflection angle is multiplied by two to obtain the binocular theoretical convergence angle.

[0008] Compared to existing technologies, the above embodiments have the following beneficial effects: by multiplying the prism diopter by the target distance to obtain the product data, and dividing the product data by one hundred to obtain the normalized offset, the optical stimulus parameters are converted into dimensionless geometric proportions, which conform to the physical definition of prism diopter (i.e., 1 prism diopter corresponds to 1 centimeter offset at 1 meter); furthermore, by calculating the arctangent function value of the normalized offset to obtain the monocular deflection angle, and multiplying the monocular deflection angle by two to obtain the binocular theoretical convergence angle, the physiological convergence demand induced by prism stimulation in the binocular visual system is fully restored, ensuring that the calculation of the theoretical convergence angle strictly follows the optical-physiological mapping relationship, thereby providing a benchmark value that conforms to the principles of optometry for the accurate assessment of subsequent convergence angle deviation.

[0009] In some embodiments of the first aspect of this application, calculating the actual convergence angle at each moment based on the eye-tracking trajectory data includes: In the eye-tracking data, the angle between the lines of sight of the two eyes in the horizontal plane is calculated based on the gaze direction vector of the two eyes at each sampling moment, which is used as the actual convergence angle at that moment.

[0010] Compared with the prior art, the above embodiments have the following beneficial effects: by calculating the angle between the lines of sight of the two eyes in the horizontal plane using the gaze direction vector as the actual convergence angle, the key physiological parameters reflecting the state of binocular coordinated movement are directly extracted from the original eye movement signal, ensuring that the calculation of the actual convergence angle has high spatiotemporal accuracy and physiological authenticity, and providing a reliable data basis for determining convergence stability.

[0011] In some embodiments of the first aspect of this application, extracting gaze events from the eye-tracking data includes: A gaze detection algorithm is executed on the eye movement trajectory data to segment the continuous eye movement sequence into discrete gaze events; wherein each gaze event contains the corresponding gaze center coordinates and gaze duration.

[0012] Compared with the prior art, the above embodiments have the following beneficial effects: segmenting the continuous eye movement sequence into discrete fixation events containing the corresponding fixation center coordinates and fixation duration, effectively identifying the period when the subject's visual attention is relatively stable, providing structured event input for subsequent determination of fusion state at meaningful time anchor points, and avoiding misjudgment of fusion recovery during saccades or drift stages.

[0013] In some embodiments of the first aspect of this application, marking the fusion recovery time based on the convergence angle deviation within a preset time window before each gaze event and a preset convergence angle deviation threshold includes: For each gaze event, determine whether the gaze center coordinates are located in the spatial region where the target is located, and whether the gaze duration is greater than or equal to the preset minimum effective gaze duration threshold. If the determination result is true, the corresponding gaze event is determined as a valid gaze event. The fusion recovery time is marked based on the convergence angle deviation within a preset time window before each effective fixation event and the preset convergence angle deviation threshold.

[0014] Compared with the prior art, the above embodiments have the following beneficial effects: by determining whether the coordinates of the gaze center of each gaze event are located in the spatial region where the target is located and whether the gaze duration is greater than or equal to the preset minimum effective gaze duration threshold, if the conditions are met, it is determined as a valid gaze event, effectively eliminating the interference of invalid events such as gaze deviation or momentary gaze on the fusion determination; furthermore, based on the convergence angle deviation within the preset time window before each valid gaze event occurs and the preset convergence angle deviation threshold, the fusion recovery time is marked, ensuring that the determination of fusion recovery is only performed under the premise that the subject is truly gazing at the target and the gaze lasts for a sufficient time, thereby improving the accuracy and clinical significance of fusion recovery time identification.

[0015] In some embodiments of the first aspect of this application, marking the fusion recovery time based on the convergence angle deviation within a preset time window before each effective gaze event and a preset convergence angle deviation threshold includes: For each valid fixation event, determine whether the convergence angle deviation at all times within the preset time window before the event occurs is continuously less than the convergence angle deviation threshold. If the determination result is true, mark the start time of the valid fixation event as the fusion recovery time. The convergence angle deviation threshold is set based on the half-width threshold of the fusion region.

[0016] Compared with the prior art, the above embodiments have the following beneficial effects: For each effective fixation event, it is determined whether the convergence angle deviation at all times within the preset time window before its occurrence is continuously less than the convergence angle deviation threshold. If it is true, the starting time of the effective fixation event is marked as the fusion recovery time, ensuring that the judgment basis is that the eye position is stable in a fusionable state for a period of time, rather than instantaneous fluctuations. The Paum fusion zone refers to the area on the retinas of both eyes where the image of an object point does not fall completely on the anatomically corresponding point (i.e., the corresponding point on the retina) of the two eyes, as long as its positional deviation is within a certain range, the brain can still perceive it as a single image (i.e., without diplopia). The convergence angle deviation threshold is set based on the half-width threshold of the Paum fusion zone, so that the judgment standard is directly anchored to the anatomical-functional boundary of the physiological fusionability of the human eye, thereby ensuring that the marking of the fusion recovery time has a solid physiological basis and individual adaptability.

[0017] In some embodiments of the first aspect of this application, the step of calculating the number of complete convergence / divergence cycles per unit time based on each of the fusion recovery times to obtain a convergence / divergence flexibility index includes: Within a unit time period, the number of pairs of fusion recovery times corresponding to base-in prism stimulation and base-out prism stimulation that satisfy the alternating sequence are counted to obtain the convergence and divergence flexibility index.

[0018] Compared with existing technologies, the above embodiments have the following beneficial effects: by statistically analyzing the paired number of fusion recovery times corresponding to base-inward prism stimulation and base-outward prism stimulation that satisfy the alternating sequence within a unit time period, the convergence-dispersion flexibility index is obtained. This strictly follows the clinical definition of convergence-dispersion flexibility testing, ensuring that the number of cycles counted truly reflects the subject's ability to complete a complete regulation-convergence-fusion closed loop under bidirectional convergence-dispersion stimulation, thereby outputting a quantitative index that meets international standards and enhancing the clinical comparability and diagnostic value of the test results.

[0019] Secondly, the present invention also provides a system for checking the flexibility of convergence and divergence, comprising: a data acquisition module, a calculation module, a marking module, and an output module; The data acquisition module is used to acquire binocular eye movement trajectory data of the examinee; wherein the binocular eye movement trajectory data is collected synchronously during the prism stimulation test; the prism stimulation test is a process in which the examinee fixates on a preset target and alternately receives stimulation from a base-in prism and a base-out prism. The calculation module is used to calculate the actual convergence angle at each moment based on the eye movement trajectory data, and to calculate the convergence angle deviation at each moment based on the actual convergence angle at each moment and the binocular theoretical convergence angle of the prism used at that moment; wherein, the binocular theoretical convergence angle is calculated based on the prism power and the target distance of the prism. The marking module is used to extract gaze events from the eye movement trajectory data and mark the fusion recovery time based on the convergence angle deviation within a preset time window before each gaze event and a preset convergence angle deviation threshold. The output module is used to count the number of complete convergence-disconvergence cycles per unit time based on each of the fusion recovery times, and obtain the convergence-disconvergence flexibility index.

[0020] Compared to existing technologies, the above embodiments of this application have the following beneficial effects: By acquiring binocular eye movement trajectory data, a high temporal resolution physiological signal basis is provided for subsequent objective determination of fusion status; furthermore, by calculating the actual convergence angle at each moment based on the eye movement trajectory data, and combining it with the binocular theoretical convergence angle calculated based on the prism diopter and target distance, the convergence angle deviation at each moment is calculated, enabling the system to quantify the degree of deviation between the current eye position and the theoretically required eye position, thereby establishing a calculable fusion stability criterion; simultaneously, by extracting fixation events from the eye movement trajectory data, and marking the fusion recovery time based on the convergence angle deviation within a preset time window before each fixation event and a preset convergence angle deviation threshold, fusion recovery is achieved. An automated fusion assessment mechanism based on eye position stability was developed, avoiding reliance on subjective reports. Furthermore, by statistically analyzing the number of complete convergence-divergence cycles per unit time at each fusion recovery moment, a convergence-divergence flexibility index was obtained, completing the automated mapping from raw physiological signals to clinical quantitative indicators. The synergistic effect of these features enables the entire scheme to automatically identify fusion recovery events and calculate dynamic convergence-divergence capability based on the objective standard of whether the convergence-divergence angle deviation of both eyes continuously enters the physiological range of fusion (such as the Paum zone), without requiring active feedback from the subject. This solves the fundamental problem of existing technologies where convergence-divergence flexibility testing relies on subjective perception and cannot be objectively and automatically executed, significantly improving the universality, repeatability, and clinical reliability of the test.

[0021] Thirdly, the present invention also provides a computer program product, including a computer program or instructions, characterized in that, when the computer program or instructions are executed, they implement any one of the aggregation and dispersal flexibility checking methods of the present invention.

[0022] Fourthly, embodiments of this application also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements any one of the aggregation and dispersal flexibility checking methods of the present invention. Attached Figure Description

[0023] Figure 1 This is a flowchart illustrating a method for checking the flexibility of convergence and divergence provided in some embodiments of the present invention.

[0024] Figure 2 This is a schematic diagram of the structure of a system for checking the flexibility of convergence and divergence provided in some embodiments of the present invention. Detailed Implementation

[0025] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0026] Example 1: Please refer to Figure 1 To address the problem that existing technologies rely on subjective feedback for convergence flexibility checks and cannot objectively and automatically determine the fusion recovery time, an embodiment of the present invention provides a method for checking convergence flexibility, comprising steps S1 to S4: Step S1: Acquire binocular eye movement trajectory data of the examinee; wherein, the binocular eye movement trajectory data is collected synchronously during the prism stimulation test; the prism stimulation test is the process in which the examinee fixates on a preset target and alternately receives stimulation from a base-in prism and a base-out prism.

[0027] Step S2: Calculate the actual convergence angle at each moment based on the eye movement trajectory data, and calculate the convergence angle deviation at each moment based on the actual convergence angle at each moment and the binocular theoretical convergence angle of the prism used at that moment; wherein, the binocular theoretical convergence angle is calculated based on the prism diopter and the target distance.

[0028] Furthermore, the theoretical convergence angle of the two eyes is calculated based on the prism diopter and the target distance, and can be implemented through the following preferred embodiments, including steps S21-S22, as follows: S21: Multiply the prism diopter by the target distance to obtain the product data, and divide the product data by one hundred to obtain the normalized offset; S22: Calculate the arctangent function value of the normalized offset to obtain the monocular deflection angle, and multiply the monocular deflection angle by two to obtain the binocular theoretical convergence angle.

[0029] In this preferred embodiment, the product data is obtained by multiplying the prism power by the target distance, and then the product data is divided by one hundred to obtain the normalized offset. This converts the optical stimulus parameters into a dimensionless geometric ratio, which conforms to the physical definition of prism power (i.e., 1 prism power corresponds to a 1 cm offset at 1 meter). Furthermore, the monocular deflection angle is obtained by calculating the arctangent function value from the normalized offset, and then the monocular deflection angle is multiplied by two to obtain the binocular theoretical convergence angle. This fully restores the physiological convergence requirement induced by prism stimulation in the binocular visual system, ensuring that the calculation of the theoretical convergence angle strictly follows the optical-physiological mapping relationship. This provides a benchmark value that conforms to the principles of optometry for the accurate assessment of subsequent convergence angle deviation.

[0030] Furthermore, in step S2, calculating the actual convergence angle at each moment can be achieved through the following preferred implementation method, including step S23, as follows: S23: In the eye movement trajectory data, based on the gaze direction vector of both eyes at each sampling moment, calculate the angle between the lines of sight of the two eyes in the horizontal plane, which is used as the actual convergence angle at that moment.

[0031] In this preferred embodiment, the angle between the lines of sight of the two eyes in the horizontal plane is calculated by the gaze direction vector as the actual convergence angle. The key physiological parameters reflecting the state of binocular coordinated movement are directly extracted from the original eye movement signal, which ensures that the calculation of the actual convergence angle has high spatiotemporal accuracy and physiological authenticity, and provides a reliable data basis for determining convergence stability.

[0032] Step S3: Extract fixation events from the eye movement trajectory data, and mark the fusion recovery time based on the convergence angle deviation within a preset time window before each fixation event and a preset convergence angle deviation threshold.

[0033] Furthermore, step S3 can be implemented through the following preferred embodiments, including steps S31-S33, as follows: S31: Perform a gaze detection algorithm on the eye movement trajectory data to segment the continuous eye movement sequence into discrete gaze events; wherein each gaze event contains the corresponding gaze center coordinates and gaze duration.

[0034] In this preferred embodiment, the continuous eye movement sequence is segmented into discrete fixation events containing corresponding fixation center coordinates and fixation duration. This effectively identifies the period when the subject's visual attention is relatively stable, providing structured event input for subsequent determination of fusion state at meaningful time anchors, and avoiding misjudgment of fusion recovery during saccades or drift stages.

[0035] S32: Determine whether the coordinates of the gaze center of each gaze event are located in the spatial region where the target is located, and whether the gaze duration is greater than or equal to the preset minimum effective gaze duration threshold. If the determination result is true, then the corresponding gaze event is determined as a valid gaze event. S33: Mark the fusion recovery time based on the convergence angle deviation within the preset time window before each effective gaze event and the preset convergence angle deviation threshold.

[0036] In this preferred embodiment, by determining whether the coordinates of the fixation center of each fixation event are located in the spatial region where the target is located and whether the fixation duration is greater than or equal to a preset minimum effective fixation duration threshold, if the conditions are met, it is determined as a valid fixation event, effectively eliminating the interference of invalid events such as fixation deviation or momentary gaze on the fusion determination; furthermore, the fusion recovery time is marked based on the convergence angle deviation within a preset time window before each valid fixation event and a preset convergence angle deviation threshold, ensuring that the determination of fusion recovery is only performed under the premise that the subject is truly fixating on the target and the fixation lasts for a sufficient time, thereby improving the accuracy and clinical significance of fusion recovery time identification.

[0037] Furthermore, step S33 can be implemented through the following preferred embodiments, as detailed below: For each valid fixation event, determine whether the convergence angle deviation at all times within the preset time window before the event occurs is continuously less than the convergence angle deviation threshold. If the determination result is true, mark the start time of the valid fixation event as the fusion recovery time. The convergence angle deviation threshold is set based on the half-width threshold of the fusion region.

[0038] In this preferred embodiment, for each valid fixation event, it is determined whether the convergence angle deviation at all times within a preset time window prior to its occurrence is consistently less than the convergence angle deviation threshold. If so, the starting time of the valid fixation event is marked as the fusion recovery time, ensuring that the determination is based on the eye position being stably in a fusionable state for a period of time, rather than instantaneous fluctuations. The Paum fusion zone refers to the area on the retinas of both eyes where, even if the image of an object does not fall completely on the anatomically corresponding point (i.e., the corresponding retinal point) of the two eyes, as long as its positional deviation is within a certain range, the brain can still perceive it as a single image (i.e., without diplopia). The convergence angle deviation threshold is set based on the half-width threshold of the Paum fusion zone, so that the determination criterion is directly anchored to the anatomical-functional boundary of the physiological fusionability of the human eye, thereby ensuring that the marking of the fusion recovery time has a solid physiological basis and individual adaptability.

[0039] Step S4: Based on the fusion recovery time of each image, count the number of complete convergence-disconvergence cycles per unit time to obtain the convergence-disconvergence flexibility index.

[0040] Furthermore, step S4 can be implemented through the following preferred embodiment, including step S41, as follows: S41: Within a unit time period, count the number of pairs of fusion recovery times corresponding to base-in prism stimulation and base-out prism stimulation that satisfy the alternating sequence, and obtain the convergence and divergence flexibility index.

[0041] In this preferred embodiment, the convergence flexibility index is obtained by counting the paired number of fusion recovery times corresponding to base-inward prism stimulation and base-outward prism stimulation that satisfy the alternating sequence within a unit time period. This strictly follows the clinical definition of convergence flexibility testing, ensuring that the counted number of cycles truly reflects the subject's ability to complete a complete accommodation-convergence-fusion closed loop under bidirectional convergence stimulation. This outputs a quantitative index that meets international standards, enhancing the clinical comparability and diagnostic value of the test results.

[0042] In practical implementation, the standard clinical method for assessing convergence flexibility using existing technologies involves using a prism reversal test in conjunction with a near vision chart: the examiner manually flips the prism with base-in (BI) and base-out (BO) facing inwards. The subject verbally reports the moment "single vision restored" after diplopia, and the number of successful cycles per minute (cpm) is recorded. For example, the subject views the target with both eyes through a 1.5BI lens, goes from diplopia to single vision and verbally reports, then switches to a 6BO lens, waits for single vision to be restored and reports, and repeats this process, calculating the number of times one set of lenses is viewed within one minute (cpm). This restoration of single vision means fusing the images from both eyes into one image and viewing it clearly.

[0043] Although there are devices that can record eye movement trajectories, it is impossible to determine whether the image has truly fused simply by the eye position being close to the target, because the brain may still be in a state of diplopia perception.

[0044] The improved convergence and divergence flexibility testing method provided by this invention is based on the following: utilizing two objective signals derived from the physiological mechanism of binocular vision, "eye movement stability and pupillary clarity response," to construct deterministic judgment rules and automatically identify the fusion recovery moment, as follows: This invention introduces the following three key formulas: Formula 1, Calculation of required convergence and divergence angles (based on prism optics principles): According to the definition: ; Therefore, the demand for aggregation and dispersion The corresponding monocular deflection angle θ satisfies: ; When both eyes are focused, each eye rotates towards the nose by an angle θ. Therefore, the total convergence angle is: total convergence angle of both eyes = 2 × angle of rotation of one eye, that is: Function: Converts the applied prism power into the theoretical convergence angle (unit: circumference) required by both eyes, which is then compared with the actual eye position to determine whether fusion accommodation has been completed.

[0045] The variables are explained below: : The binocular convergence angle required under the current prism stimulation (in °); P: Prism diopter (unit: prism diopter, Δ), for example 8Δ; d: Target distance (unit: meters), 0.4 m (i.e. 40 cm) is commonly used in clinical practice; The coefficient 100 is derived from the definition of a prism (1Δ is defined as the ability to cause a light ray to deflect by 1 centimeter at a distance of 1 meter).

[0046] Formula 2, convergence angle deviation calculation, is used to determine whether the image has entered the fusion zone: Function: To measure the deviation between the actual eye position and the theoretical requirement, and to determine whether the two eyes have been adjusted to the range of fusion.

[0047] in, This represents the actual convergence / divergence angle calculated by the eye-tracking system at time t. This indicates the deviation of the convergence / divergence angle.

[0048] when Continuously smaller than the half-width threshold of the Pam fusion region (The convergence angle stability threshold is set based on the principle of Paum fusion zone, preferably 0.15°). If the eye position is less than this threshold, it is considered that the eye position has entered the physiological fusion range.

[0049] Formula 3, calculation of pupil clarity response slope, is used to determine whether subjective clarity has been restored: Function: To quantify whether the pupil constricts significantly in a short period of time, serving as a sign that the visual target becomes clearer.

[0050] Eye-tracking data is typically processed into a series of fixation events f, each fixation event f containing the coordinates of the fixation center ( Duration Where R represents the spatial region where the target object is located (e.g., a rectangular region). ), This represents the minimum effective fixation duration threshold. The judgment result is indicated as follows: 1 means "I saw it clearly", and 0 means "I did not see it clearly".

[0051] The gaze event (including location and duration) output by the eye-tracking device is used as input. If the gaze event meets the conditions, it can be determined that the object is seen clearly.

[0052] For example, the inspection lasts 60 seconds and consists of multiple rounds. In each round, an E-beacon is displayed (randomly in one of the four directions: up, down, left, or right). During the display, it is determined whether Formula 2 is satisfied. If the condition is met, continue to evaluate Formula 3. Check if the condition "see clearly" is met. If it is, complete this round. If not, continue waiting until Formula 3 meets the condition "see clearly". At this point, one round ends, and the next round begins. The check ends when the 60-second countdown ends.

[0053] In summary, the steps can be organized as follows: Step 1, System Initialization and Calibration: (1) The subject fixates on a standardized near vision target at 40 cm; (2) Start the infrared eye tracking system (sampling rate ≥ 120 Hz) and complete the initial eye position calibration of both eyes; (3) Record the static pupil diameter as a baseline.

[0054] Step 2: Automatically apply prism stimulation: (1) Using an electric prism switching device, apply BI (base in) and BO (base out) prisms of preset degrees alternately in front of the subject's eyes (e.g., 1.5ΔBI, 6ΔBO). (2) The timing of each switch is accurately recorded by the system.

[0055] Step 3: Real-time acquisition of eye-tracking data and extraction of fixation events: The eye-tracking system continuously records raw eye-tracking data. A standard gaze detection algorithm is used to segment the raw eye-tracking data into discrete gaze events, obtaining the coordinates of the gaze point. Sequence and duration .

[0056] Step 4: Determine the fusion recovery time. After each prism switch, perform the following determination: (1) Calculate the theoretical convergence angle (Formula 1); (2) Calculate the divergence angle deviation (Formula 2); A valid gaze event was detected: 1) (i.e., the gaze falls within the visual target area); 2) ; If the above gaze occurs before Inside, If the image fusion is successful, it indicates that the image has been restored and one prism stimulation has been completed.

[0057] Step 5: Calculate the aggregation and dispersal flexibility index: Once a BI and BO are completed, it is counted as one cycle. The number of cycles completed within 60 seconds is recorded as the CPM, which is the aggregation and dispersal flexibility index. If no cycle is completed, it is 0. At the same time, auxiliary indicators such as average fusion recovery latency and failure rate can be output.

[0058] Furthermore, it should be noted that "Panum's fusional area" is a classic concept in binocular visual physiology, used to explain why the human eye can perceive a single image (i.e., without diplopia) even with slight parallax. It refers to the area on the retinas where, even if the image of a point does not fall exactly on the corresponding anatomical point in each eye (i.e., the retinal correspondence point), as long as the positional deviation is within a certain range, the brain can still perceive it as a single image (i.e., without diplopia).

[0059] The classic Panum zone specifically refers to the limit of sensory monocular vision, typically <0.2°. The convergence / divergence angle deviation threshold described in this invention... Preferably, the value is no more than 0.2°, which is based on the retinal image position tolerance range required to maintain monocular vision under the central visual field of the human eye.

[0060] In summary, compared with the prior art, the above embodiments of this application have the following beneficial effects: by acquiring binocular eye movement trajectory data, a high temporal resolution physiological signal basis is provided for subsequent objective determination of fusion status; furthermore, by calculating the actual convergence angle at each moment based on the eye movement trajectory data, and combining it with the binocular theoretical convergence angle calculated based on the prism diopter and target distance, the convergence angle deviation at each moment is calculated, enabling the system to quantify the degree of deviation between the current eye position and the theoretically required eye position, thereby establishing a calculable fusion stability criterion; simultaneously, by extracting fixation events from the eye movement trajectory data, and marking the fusion recovery moment based on the convergence angle deviation within a preset time window before each fixation event and a preset convergence angle deviation threshold, the fusion recovery moment is determined. An automated fusion assessment mechanism based on eye position stability was implemented, avoiding reliance on subjective reports. Furthermore, by statistically analyzing the number of complete convergence-divergence cycles per unit time at each fusion recovery moment, a convergence-divergence flexibility index was obtained, completing the automated mapping from raw physiological signals to clinical quantitative indicators. The synergistic effect of these features enables the entire scheme to automatically identify fusion recovery events and calculate dynamic convergence-divergence capability based on the objective standard of whether the convergence-divergence angle deviation of both eyes continuously enters the physiological range of fusion (such as the Paum zone) without the need for active feedback from the subject. This solves the fundamental problem of existing technologies where convergence-divergence flexibility testing relies on subjective perception and cannot be objectively and automatically executed, significantly improving the universality, repeatability, and clinical reliability of the test.

[0061] Example 2: Please refer to Figure 2 Based on the same inventive concept, the present invention discloses a system for checking the flexibility of aggregation and dispersion, comprising: a data acquisition module M1, a calculation module M2, a marking module M3, and an output module M4; The data acquisition module M1 is used to acquire binocular eye movement trajectory data of the examinee; wherein the binocular eye movement trajectory data is collected synchronously during the prism stimulation test; the prism stimulation test is a process in which the examinee fixates on a preset target and alternately receives stimulation from a base-in prism and a base-out prism.

[0062] The calculation module M2 is used to calculate the actual convergence angle at each moment based on the eye movement trajectory data, and to calculate the convergence angle deviation at each moment based on the actual convergence angle at each moment and the binocular theoretical convergence angle of the prism used at that moment; wherein, the binocular theoretical convergence angle is calculated based on the prism diopter and the target distance.

[0063] Furthermore, the computing module M2 includes: a first computing unit and a second computing unit; The first calculation unit is used to multiply the prism diopter by the target distance to obtain the product data, and divide the product data by one hundred to obtain the normalized offset. The second calculation unit is used to calculate the arctangent function value of the normalized offset to obtain the monocular deflection angle, and multiply the monocular deflection angle by two to obtain the binocular theoretical convergence angle.

[0064] In this preferred embodiment, the product data is obtained by multiplying the prism power by the target distance, and then the product data is divided by one hundred to obtain the normalized offset. This converts the optical stimulus parameters into a dimensionless geometric ratio, which conforms to the physical definition of prism power (i.e., 1 prism power corresponds to a 1 cm offset at 1 meter). Furthermore, the monocular deflection angle is obtained by calculating the arctangent function value from the normalized offset, and then the monocular deflection angle is multiplied by two to obtain the binocular theoretical convergence angle. This fully restores the physiological convergence requirement induced by prism stimulation in the binocular visual system, ensuring that the calculation of the theoretical convergence angle strictly follows the optical-physiological mapping relationship. This provides a benchmark value that conforms to the principles of optometry for the accurate assessment of subsequent convergence angle deviation.

[0065] Furthermore, the calculation module M2 also includes: an angle calculation unit; The angle calculation unit is used to calculate the angle between the lines of sight of the two eyes in the horizontal plane based on the gaze direction vector of the two eyes at each sampling moment in the eye movement trajectory data, and use it as the actual convergence angle at that moment.

[0066] In this preferred embodiment, the angle between the lines of sight of the two eyes in the horizontal plane is calculated by the gaze direction vector as the actual convergence angle. The key physiological parameters reflecting the state of binocular coordinated movement are directly extracted from the original eye movement signal, which ensures that the calculation of the actual convergence angle has high spatiotemporal accuracy and physiological authenticity, and provides a reliable data basis for determining convergence stability.

[0067] The marking module M3 is used to extract gaze events from the eye movement trajectory data and mark the fusion recovery time based on the convergence angle deviation within a preset time window before each gaze event and a preset convergence angle deviation threshold.

[0068] Furthermore, the marking module M3 includes: a gaze detection unit; The gaze detection unit is used to perform a gaze detection algorithm on the eye movement trajectory data to segment the continuous eye movement sequence into discrete gaze events; wherein each gaze event includes the corresponding gaze center coordinates and gaze duration.

[0069] In this preferred embodiment, the continuous eye movement sequence is segmented into discrete fixation events containing corresponding fixation center coordinates and fixation duration. This effectively identifies the period when the subject's visual attention is relatively stable, providing structured event input for subsequent determination of fusion state at meaningful time anchors, and avoiding misjudgment of fusion recovery during saccades or drift stages.

[0070] Furthermore, the marking module M3 also includes: a validity verification unit and a calibration unit; The validity verification unit is used to determine whether the gaze center coordinates of each gaze event are located in the spatial region where the target is located, and whether the gaze duration is greater than or equal to a preset minimum effective gaze duration threshold. If the judgment result is true, the corresponding gaze event is determined as a valid gaze event. The calibration unit is used to mark the fusion recovery time based on the convergence angle deviation within a preset time window before each effective gaze event and a preset convergence angle deviation threshold.

[0071] In this preferred embodiment, by determining whether the coordinates of the fixation center of each fixation event are located in the spatial region where the target is located and whether the fixation duration is greater than or equal to a preset minimum effective fixation duration threshold, if the conditions are met, it is determined as a valid fixation event, effectively eliminating the interference of invalid events such as fixation deviation or momentary gaze on the fusion determination; furthermore, the fusion recovery time is marked based on the convergence angle deviation within a preset time window before each valid fixation event and a preset convergence angle deviation threshold, ensuring that the determination of fusion recovery is only performed under the premise that the subject is truly fixating on the target and the fixation lasts for a sufficient time, thereby improving the accuracy and clinical significance of fusion recovery time identification.

[0072] Furthermore, the calibration unit includes: a calibration subunit; The calibration subunit is used to determine, for each valid fixation event, whether the convergence angle deviation at all times within the preset time window before the event occurs is continuously less than the convergence angle deviation threshold. If the determination result is true, the start time of the valid fixation event is marked as the fusion recovery time. The convergence angle deviation threshold is set based on the half-width threshold of the fusion region.

[0073] In this preferred embodiment, for each valid fixation event, it is determined whether the convergence angle deviation at all times within a preset time window prior to its occurrence is consistently less than the convergence angle deviation threshold. If so, the starting time of the valid fixation event is marked as the fusion recovery time, ensuring that the determination is based on the eye position being stably in a fusionable state for a period of time, rather than instantaneous fluctuations. The Paum fusion zone refers to the area on the retinas of both eyes where, even if the image of an object does not fall completely on the anatomically corresponding point (i.e., the corresponding retinal point) of the two eyes, as long as its positional deviation is within a certain range, the brain can still perceive it as a single image (i.e., without diplopia). The convergence angle deviation threshold is set based on the half-width threshold of the Paum fusion zone, so that the determination criterion is directly anchored to the anatomical-functional boundary of the physiological fusionability of the human eye, thereby ensuring that the marking of the fusion recovery time has a solid physiological basis and individual adaptability.

[0074] The output module M4 is used to count the number of complete convergence-disconvergence cycles per unit time based on each of the fusion recovery times, and obtain the convergence-disconvergence flexibility index.

[0075] Furthermore, the output module M4 includes: a statistical unit; The statistical unit is used to count the number of pairs of fusion recovery times corresponding to base-in prism stimulation and base-out prism stimulation that satisfy the alternating sequence within a unit time period, thereby obtaining the convergence and divergence flexibility index.

[0076] In this preferred embodiment, the convergence flexibility index is obtained by counting the paired number of fusion recovery times corresponding to base-inward prism stimulation and base-outward prism stimulation that satisfy the alternating sequence within a unit time period. This strictly follows the clinical definition of convergence flexibility testing, ensuring that the counted number of cycles truly reflects the subject's ability to complete a complete accommodation-convergence-fusion closed loop under bidirectional convergence stimulation. This outputs a quantitative index that meets international standards, enhancing the clinical comparability and diagnostic value of the test results.

[0077] In summary, compared with the prior art, the embodiments of this application have the following beneficial effects: by acquiring binocular eye movement trajectory data, a high temporal resolution physiological signal basis is provided for subsequent objective determination of fusion status; furthermore, by calculating the actual convergence angle at each moment based on the eye movement trajectory data, and combining it with the binocular theoretical convergence angle calculated based on the prism diopter and target distance, the convergence angle deviation at each moment is calculated, enabling the system to quantify the degree of deviation between the current eye position and the theoretically required eye position, thereby establishing a calculable fusion stability criterion; simultaneously, by extracting fixation events from the eye movement trajectory data, and marking the fusion recovery time based on the convergence angle deviation within a preset time window before each fixation event and a preset convergence angle deviation threshold, the fusion recovery time is effectively achieved. An automated fusion assessment mechanism based on eye position stability has been developed, avoiding reliance on subjective reports. Furthermore, by statistically analyzing the number of complete convergence-divergence cycles per unit time at each fusion recovery moment, a convergence-divergence flexibility index is obtained, completing the automated mapping from raw physiological signals to clinical quantitative indicators. The synergistic effect of these features enables the entire scheme to automatically identify fusion recovery events and calculate dynamic convergence-divergence capability based on the objective standard of whether the convergence-divergence angle deviation of both eyes continuously enters the physiological range of fusion (such as the Paum zone) without the need for active feedback from the subject. This solves the fundamental problem of existing technologies where convergence-divergence flexibility testing relies on subjective perception and cannot be objectively and automatically executed, significantly improving the universality, repeatability, and clinical reliability of the test.

[0078] Example 3: This invention also provides a computer program product, including a computer program or instructions, capable of running on a computing device or stored in any available medium. When the computer program product is run on at least one computing device, it causes the at least one computing device to perform any of the aggregation and dispersal flexibility checking methods of this invention.

[0079] Example 4: This invention also provides a computer-readable storage medium storing at least one executable instruction that, when executed on a system for checking the flexibility of aggregation and dispersion, causes the system to perform a method for checking the flexibility of aggregation and dispersion in any of the above-described method embodiments.

[0080] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of this application may be practiced without these specific details. Similarly, for the purpose of simplification and aiding understanding of one or more aspects of the invention, in the above description of exemplary embodiments of this application, various features of the embodiments are sometimes grouped together in a single embodiment, figure, or description thereof. The claims, which follow the detailed description, are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of this application.

[0081] Those skilled in the art will understand that the modules in the system of the embodiments can be adaptively changed and placed in one or more systems different from that embodiment. Modules, units, or components in the embodiments can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components, except that at least some of such features and / or processes or units are mutually exclusive.

Claims

1. A method for checking the flexibility of assembly and disassembly, characterized in that, include: Acquire binocular eye movement trajectory data of the examinee; wherein, the binocular eye movement trajectory data is collected synchronously during the prism stimulation test; the prism stimulation test is the process in which the examinee fixates on a preset target and alternately receives stimulation from a base-in prism and a base-out prism. Based on the eye movement trajectory data, the actual convergence angle at each moment is calculated, and the convergence angle deviation at each moment is calculated based on the actual convergence angle at each moment and the binocular theoretical convergence angle of the prism used at that moment; wherein, the binocular theoretical convergence angle is calculated based on the prism power and the target distance of the prism. Fixation events are extracted from the eye-tracking data, and the fusion recovery time is marked based on the convergence angle deviation within a preset time window before each fixation event and a preset convergence angle deviation threshold. Based on the fusion recovery time of each image, the number of complete convergence-disconvergence cycles per unit time is counted to obtain the convergence-disconvergence flexibility index.

2. The method for checking the flexibility of assembly and disassembly as described in claim 1, characterized in that, The binocular theoretical convergence angle is calculated based on the prism power and the target distance, including: Multiply the prism power by the target distance to obtain the product data, and divide the product data by one hundred to obtain the normalized offset. The arctangent function value is calculated for the normalized offset to obtain the monocular deflection angle, and the monocular deflection angle is multiplied by two to obtain the binocular theoretical convergence angle.

3. The method for checking the flexibility of assembly and disassembly as described in claim 1, characterized in that, The step of calculating the actual convergence angle at each moment based on the eye-tracking trajectory data includes: In the eye-tracking data, the angle between the lines of sight of the two eyes in the horizontal plane is calculated based on the gaze direction vector of the two eyes at each sampling moment, which is used as the actual convergence angle at that moment.

4. The method for checking the flexibility of assembly and disassembly as described in claim 1, characterized in that, Extracting gaze events from the eye-tracking data includes: A gaze detection algorithm is executed on the eye movement trajectory data to segment the continuous eye movement sequence into discrete gaze events; wherein each gaze event contains the corresponding gaze center coordinates and gaze duration.

5. The method for checking the flexibility of convergence and divergence as described in claim 4, characterized in that, The step of marking the fusion recovery time based on the convergence angle deviation within a preset time window before each gaze event and a preset convergence angle deviation threshold includes: For each gaze event, determine whether the gaze center coordinates are located in the spatial region where the target is located, and whether the gaze duration is greater than or equal to the preset minimum effective gaze duration threshold. If the determination result is true, the corresponding gaze event is determined as a valid gaze event. The fusion recovery time is marked based on the convergence angle deviation within a preset time window before each effective fixation event and the preset convergence angle deviation threshold.

6. The method for checking the flexibility of assembly and disassembly as described in claim 5, characterized in that, The step of marking the fusion recovery time based on the convergence angle deviation within a preset time window before each effective fixation event and a preset convergence angle deviation threshold includes: For each valid fixation event, determine whether the convergence angle deviation at all times within the preset time window before the event occurs is continuously less than the convergence angle deviation threshold. If the determination result is true, mark the start time of the valid fixation event as the fusion recovery time. The convergence angle deviation threshold is set based on the half-width threshold of the fusion region.

7. The method for checking the flexibility of assembly and disassembly as described in claim 1, characterized in that, The aggregation flexibility index is obtained by counting the number of complete aggregation cycles per unit time based on the fusion recovery time of each of the aforementioned images, including: Within a unit time period, the number of pairs of fusion recovery times corresponding to base-in prism stimulation and base-out prism stimulation that satisfy the alternating sequence are counted to obtain the convergence and divergence flexibility index.

8. A system for checking the flexibility of assembly and disassembly, characterized in that, include: Data acquisition module, calculation module, labeling module, and output module; The data acquisition module is used to acquire binocular eye movement trajectory data of the examinee; wherein the binocular eye movement trajectory data is collected synchronously during the prism stimulation test; the prism stimulation test is a process in which the examinee fixates on a preset target and alternately receives stimulation from a base-in prism and a base-out prism. The calculation module is used to calculate the actual convergence angle at each moment based on the eye movement trajectory data, and to calculate the convergence angle deviation at each moment based on the actual convergence angle at each moment and the binocular theoretical convergence angle of the prism used at that moment; wherein, the binocular theoretical convergence angle is calculated based on the prism power and the target distance of the prism. The marking module is used to extract gaze events from the eye movement trajectory data and mark the fusion recovery time based on the convergence angle deviation within a preset time window before each gaze event and a preset convergence angle deviation threshold. The output module is used to count the number of complete convergence-disconvergence cycles per unit time based on each of the fusion recovery times, and obtain the convergence-disconvergence flexibility index.

9. A computer program product, comprising a computer program or instructions, characterized in that, When the computer program or instructions are executed, they implement a method for checking the flexibility of aggregation and dispersal as described in any one of claims 1-7.

10. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, it implements a method for checking the flexibility of aggregation and dispersal as described in any one of claims 1-7.

Images