Sighting mark moving method and device

Abstract

The invention discloses a sighting mark moving method and device, and the method comprises the steps: initializing a first sighting mark based on a preset point position, controlling the first sighting mark to move based on a preset speed and direction, and continuously collecting the image data of two eyes; responding to the first user instruction, stopping moving the first sighting mark, and determining a first moment; the first moment is the moment when the first sighting mark stops moving; screening the binocular image data based on the first moment and a preset time interval to obtain a target data sequence; and calculating a pupil change rate and eye movement stability based on the target data sequence, and adjusting the position of the first sighting mark based on the pupil change rate and the eye movement stability to complete sighting mark movement. By introducing real-time image acquisition and analysis and combining the pupil change rate and the eye movement stability, the precision and the automation level of sighting mark movement are improved, human intervention in a traditional method is reduced, and the precision of sighting mark movement control is improved.

Description

Technical Field

[0001] This invention relates to the field of image processing technology, and in particular to a method and apparatus for target movement. Background Technology

[0002] With the rapid development of digital display technology and computer image processing technology, image presentation and processing methods based on digital displays have been widely applied in various scenarios requiring precise image display and real-time analysis. In these applications, dynamically adjusting the displayed content and capturing and analyzing subtle changes in images in real time have become crucial for improving system performance and response accuracy. Traditional visual presentation methods typically rely on static images or preset content, while modern display technologies can flexibly adjust image content according to needs, thereby achieving more precise image interaction and feedback mechanisms. Especially in fields requiring precise detection and analysis of object changes, image recognition algorithms can provide richer dynamic information by acquiring images in real time and analyzing their feature changes. These algorithms can extract various physiological or physical features from images, such as object movement trajectories, size changes, and image stability. Through precise capture of image details, the system can complete the response and analysis of changes in a shorter time, thereby enhancing the system's interactivity and flexibility.

[0003] Existing methods for moving visual targets rely on human subjective perception to control the movement of the target. This subjective judgment is easily affected by factors such as human attention and reaction time, resulting in low accuracy in the position of the moving target. Summary of the Invention

[0004] This invention provides a target movement method and apparatus to improve the accuracy of target movement control.

[0005] To address the aforementioned technical problems, the present invention provides a target movement method, comprising: The first visual target is initialized based on a preset point, and the first visual target is moved based on a preset speed and direction, while continuously acquiring binocular image data; In response to a first user command, stop moving the first viewpoint and determine a first moment; the first moment is the moment when the first viewpoint stops moving; Based on the first moment and the preset time interval, the binocular image data is filtered to obtain the target data sequence; The pupil change rate and eye movement stability are calculated based on the target data sequence, and the position of the first optotype is adjusted based on the pupil change rate and eye movement stability to complete the optotype movement.

[0006] This invention initializes a first optotype at a preset point and controls its movement at a preset speed and direction, continuously collecting binocular image data. This ensures the standardization and repeatability of the optotype's movement and allows for real-time monitoring of the subject's eye responses, providing accurate image input for subsequent data analysis. When the first optotype stops in response to a user command and a specific moment is determined, the binocular image data is filtered based on this moment and a preset time interval to obtain a target data sequence. This allows for more precise capture of physiological response data at the time of optotype cessation, ensuring the timeliness and representativeness of the collected data. Next, based on the target data sequence, the system calculates pupillary change rate and eye movement stability. Pupil change rate reflects the physiological response of eye accommodation, while eye movement stability reveals the subject's visual stability. Through the calculation of these two parameters, the system can objectively determine the subject's response when the optotype stops, reducing errors caused by inaccurate subjective feedback or the subject's lack of concentration. This physiological data-based analysis method significantly improves the accuracy of the optotype's stopping position. Finally, the position of the first optotype is adjusted based on the calculated pupil change rate and eye movement stability to complete the optotype movement. By relying on objective data rather than simply the subjective judgment of the subjects, and by introducing real-time image acquisition and analysis, combined with pupil change rate and eye movement stability, the accuracy and automation level of optotype movement are improved, reducing human intervention in traditional methods and improving the precision of optotype movement control.

[0007] Furthermore, the step of filtering the binocular image data based on the first time point and a preset time interval to obtain a target data sequence includes: Using the first moment as the midpoint and the preset time interval as the radius, the binocular image data is cropped to obtain the target data sequence.

[0008] This invention refines the data acquisition process by filtering binocular image data based on a first moment and a preset time interval. By cropping the binocular image data with the first moment as the midpoint and the preset time interval as the radius, the selected data is ensured to be more representative in time and can accurately capture the relevant physiological responses when the visual target stops. This processing method improves the accuracy of data filtering, avoids interference from irrelevant data in subsequent analysis, and thus improves the accuracy of pupillary change rate and eye movement stability calculations.

[0009] Furthermore, the step of calculating pupillary change rate and eye movement stability based on the target data sequence, and adjusting the position of the first optotype based on the pupillary change rate and eye movement stability to complete the optotype movement, includes: The target data sequence is converted into continuous frames, and pupil change rate and eye movement stability are calculated based on a preset target detection algorithm and the continuous frames. The feedback score is calculated based on the pupil change rate and eye movement stability, and the position of the first optotype is adjusted based on the feedback score, pupil change rate, and eye movement stability to complete the optotype movement.

[0010] This invention converts target data sequences into continuous frames and calculates pupil change rate and eye movement stability through a preset target detection algorithm. It can accurately track minute changes in the eyes and then use feedback scores to determine whether the stopping position of the target is accurate. This allows for real-time and precise capture of the subject's eye movement characteristics and physiological responses, reducing errors in traditional methods and improving the accuracy and reliability of target adjustment.

[0011] Furthermore, the step of converting the target data sequence into continuous frames and calculating pupil change rate and eye movement stability based on a preset target detection algorithm and the continuous frames includes: The target data sequence is converted into consecutive frames, and the pupil size and eye movement trajectory image of each consecutive frame are determined based on a preset target detection algorithm and the consecutive frames. The pupil change rate is calculated based on the pupil size of each consecutive frame; and eye movement stability is determined based on the eye movement trajectory image.

[0012] This invention clarifies the calculation process for consecutive frames, accurately determining the pupil size and eye movement trajectory image for each frame based on a preset target detection algorithm. By calculating the pupil change rate and eye movement stability, the physiological responses of the subject can be refined, providing a more accurate basis for adjusting the target position. This allows for more detailed image analysis, improving the measurement accuracy of pupil change and eye movement stability, and thus effectively enhancing the accuracy of the target stopping position.

[0013] Furthermore, the step of calculating a feedback score based on the pupillary change rate and eye movement stability, and adjusting the position of the first optotype based on the feedback score, pupillary change rate, and eye movement stability to complete the optotype movement, includes: A feedback score is calculated based on preset weights, the pupil change rate, and eye movement stability. The accuracy of the stopping position of the first visual target is determined based on the feedback score, pupil change rate, and eye movement stability. If accurate, record the final position of the first target and complete the target movement; Otherwise, reset the first target and control the target movement again.

[0014] This invention calculates a feedback score based on pupillary change rate and eye movement stability, and combines this with preset weights to further determine the accuracy of the target's stopping position. It can self-correct after the target stops, ensuring the accuracy of the test results. When the calculated feedback score, pupillary change rate, and eye movement stability meet the set thresholds, the target position is considered accurate, the final position is recorded, and the test is completed. If the requirements are not met, the target is reset and readjusted, effectively solving the problem of inaccurate target position caused by physiological reaction errors and ensuring the accuracy of the target's stopping position.

[0015] Furthermore, the step of determining whether the stopping position of the first visual target is accurate based on the feedback score, pupillary change rate, and eye movement stability includes: When the feedback score is greater than or equal to a preset score threshold, the pupil change rate is greater than a preset change threshold, and the eye movement stability is less than a preset eye movement threshold, the stopping position of the first visual target is accurate. Otherwise, the stopping position of the first target will be inaccurate.

[0016] This invention comprehensively judges the accuracy of the target's stopping position by considering feedback scores, pupil change rate, and eye movement stability. It ensures that the target position is considered accurate only when all parameters meet preset conditions, thereby greatly reducing erroneous judgments caused by a single physiological response. Through multi-level verification, it improves the reliability of the target's stopping position, reduces the influence of human intervention and subjective judgment, and enhances the automation and accuracy of target movement control.

[0017] In a second aspect, the present invention provides a target movement device, comprising: an initialization module, an instruction response module, an image filtering module, and an adjustment module; The initialization module is used to initialize the first visual target based on a preset point, control the first visual target to move based on a preset speed and direction, and continuously collect binocular image data. The instruction response module is used to respond to a first user instruction, stop moving the first target, and determine a first moment; the first moment is the moment when the first target stops moving; The image filtering module is used to filter the binocular image data based on the first moment and a preset time interval to obtain a target data sequence; The adjustment module is used to calculate the pupil change rate and eye movement stability based on the target data sequence, and adjust the position of the first optotype based on the pupil change rate and eye movement stability to complete the optotype movement.

[0018] Furthermore, the image filtering module is used to filter the binocular image data based on the first time point and a preset time interval to obtain a target data sequence, including: Using the first moment as the midpoint and the preset time interval as the radius, the binocular image data is cropped to obtain the target data sequence.

[0019] Furthermore, the adjustment module is used to calculate the pupillary change rate and eye movement stability based on the target data sequence, and adjust the position of the first optotype based on the pupillary change rate and eye movement stability to complete the optotype movement, including: The target data sequence is converted into continuous frames, and pupil change rate and eye movement stability are calculated based on a preset target detection algorithm and the continuous frames. The feedback score is calculated based on the pupil change rate and eye movement stability, and the position of the first optotype is adjusted based on the feedback score, pupil change rate, and eye movement stability to complete the optotype movement.

[0020] Furthermore, the adjustment module is used to convert the target data sequence into continuous frames, and calculate the pupil change rate and eye movement stability based on a preset target detection algorithm and the continuous frames, including: The target data sequence is converted into consecutive frames, and the pupil size and eye movement trajectory image of each consecutive frame are determined based on a preset target detection algorithm and the consecutive frames. The pupil change rate is calculated based on the pupil size of each consecutive frame; and eye movement stability is determined based on the eye movement trajectory image. Attached Figure Description

[0021] Figure 1 This is a flowchart illustrating a target movement method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of a target moving device provided in an embodiment of the present invention. Detailed Implementation

[0022] The specific embodiments of the present invention will be described in further detail below with reference to the accompanying drawings and examples. The following examples are for illustrative purposes only and are not intended to limit the scope of the invention.

[0023] The terms "first" and "second," etc., in the specification, claims, and drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to such processes, methods, products, or apparatus.

[0024] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0025] Example 1 See Figure 1 , Figure 1 This is a schematic flowchart illustrating a target movement method provided in an embodiment of the present invention. The embodiment of the present invention provides a target movement method, including steps 101 to 104, as detailed below: Step 101: Initialize the first visual target based on the preset point, control the first visual target to move based on the preset speed and direction, and continuously collect binocular image data; In this embodiment, the initial position of the first visual target is first determined based on a set distance and direction. This position can be set according to the requirements of the specific application scenario, for example, the initial position is 40 centimeters away from the subject's eyes. Based on this, the movement of the visual target is controlled according to a preset speed and direction. For example, the visual target can move at a constant or gradually changing speed in the horizontal or vertical direction to ensure that the movement trajectory of the visual target meets the design requirements. Furthermore, binocular image data of the subject is continuously collected to monitor eye responses in real time.

[0026] In this embodiment, during the movement of the visual target, binocular image data is acquired in real time using dedicated camera equipment or sensors. The image acquisition module can capture images of the subject's eyes at a high frequency, ensuring that every minute change in the eyes is captured. This image data will be used for subsequent analysis to extract indicators such as changes in the subject's pupil diameter and eye movement trajectory, thereby providing a basis for adjusting and stopping the visual target.

[0027] In this embodiment, the visual target is initialized as E, and is set to approach the subject's eyes at a speed of 1 cm per second in a horizontal direction. During the movement, binocular image data is automatically and continuously acquired to ensure that the eye's response at different visual target positions is captured. The binocular image data includes, but is not limited to, information such as pupil diameter, eye position, and eye movement trajectory. This information provides the data foundation for subsequent calculations of pupil change rate and eye movement stability.

[0028] In this embodiment, the image acquisition frequency can be set according to actual needs, such as acquiring images at a frequency of 30 frames per second or higher. This high-frequency acquisition helps to accurately capture the dynamic changes in the subject's eye responses, providing sufficient samples for subsequent data processing. Simultaneously, the image acquisition frequency can be dynamically adjusted to ensure that sufficiently accurate data is captured at critical moments. For example, when the visual target begins to approach the eye, the system can increase the image acquisition frequency to more accurately record pupil changes and eye movement responses.

[0029] Step 102: In response to the first user's instruction, stop moving the first viewpoint and determine the first moment; the first moment is the moment when the first viewpoint stops moving; In this embodiment, the movement of the first target is immediately stopped upon receiving a first user instruction, and the first moment is defined as the local clock time at which the instruction reaches the system controller. The first user instruction may include physical button input, touch input, voice input, or gesture recognition.

[0030] In this embodiment, user commands are collected by the input module and transmitted to the motion control unit via an interrupt or event queue. After completing the safe termination action of the current control cycle, the motion control unit stops the target and records the system clock as the first moment, ensuring the determinism of the stopping action and the moment recording, and providing a clear time anchor for subsequent image data filtering based on that moment.

[0031] Step 103: Filter the binocular image data based on the first time point and the preset time interval to obtain the target data sequence; In this embodiment, the step of filtering the binocular image data based on the first time point and a preset time interval to obtain the target data sequence includes: Using the first moment as the midpoint and the preset time interval as the radius, the binocular image data is cropped to obtain the target data sequence.

[0032] In this embodiment, upon responding to the first user command and determining the first moment, the binocular image data is filtered based on this moment and a preset time interval. Specifically, the first moment is used as a time anchor point, and a certain time interval (e.g., ±0.5 seconds) is set before and after this moment. The length of this time interval is a preset value, i.e., a time window. Through this time window, all image frames within this time interval are extracted from the binocular image data and used as the target data sequence. This operation ensures that the selected data accurately reflects the subject's ocular response when the visual target stops, eliminating interference from irrelevant data.

[0033] In this embodiment, the real-time acquired binocular image data stream is time-stamped, with each frame of the image being appended with a timestamp. Based on a first moment and a preset time interval, all image frames contained within that time range are selected and extracted for subsequent analysis. This ensures the consistency and accuracy of data selection and effectively avoids analysis errors caused by time misalignment or data mismatch.

[0034] In this embodiment, the binocular image data is further filtered and synchronized based on the relationship between the first moment and the preset time interval. Assuming the preset time interval is ±0.5 seconds, the system will use the first moment as the midpoint and match the image frames in the binocular image data with the frame data within 0.5 seconds before and after that moment according to their timestamps. To ensure data synchronization and integrity, image frames with different time sampling intervals need to be processed. For example, if the sampling frequency is 30 frames per second, the time interval between each image frame is 1 / 30 of a second. The system positions the corresponding image frame within the time window based on the timestamp.

[0035] In this embodiment, the data acquisition process is further refined by filtering the binocular image data based on a first moment and a preset time interval. By cropping the binocular image data with the first moment as the midpoint and the preset time interval as the radius, the selected data is ensured to be more representative in time and can accurately capture the relevant physiological responses when the visual target stops. This processing method improves the accuracy of data filtering, avoids interference from irrelevant data in subsequent analysis, and thus improves the accuracy of pupillary change rate and eye movement stability calculations.

[0036] Step 104: Calculate the pupil change rate and eye movement stability based on the target data sequence, and adjust the position of the first optotype based on the pupil change rate and eye movement stability to complete the optotype movement.

[0037] Furthermore, the step of calculating pupillary change rate and eye movement stability based on the target data sequence, and adjusting the position of the first optotype based on the pupillary change rate and eye movement stability to complete the optotype movement, includes: The target data sequence is converted into continuous frames, and pupil change rate and eye movement stability are calculated based on a preset target detection algorithm and the continuous frames. The feedback score is calculated based on the pupil change rate and eye movement stability, and the position of the first optotype is adjusted based on the feedback score, pupil change rate, and eye movement stability to complete the optotype movement.

[0038] In this embodiment, the target data sequence is converted into continuous frames, and the pupil change rate and eye movement stability are calculated by a preset target detection algorithm. This enables precise tracking of minute changes in the eyes, and the accuracy of the stopping position of the visual target is determined by the feedback score. This allows for real-time and accurate capture of the subject's eye movement characteristics and physiological responses, reducing errors in traditional methods and improving the accuracy and reliability of visual target adjustment.

[0039] In this embodiment, the step of converting the target data sequence into continuous frames and calculating the pupil change rate and eye movement stability based on a preset target detection algorithm and the continuous frames includes: The target data sequence is converted into consecutive frames, and the pupil size and eye movement trajectory image of each consecutive frame are determined based on a preset target detection algorithm and the consecutive frames. The pupil change rate is calculated based on the pupil size of each consecutive frame; and eye movement stability is determined based on the eye movement trajectory image.

[0040] In this embodiment, after the target data sequence is selected through a first moment and a preset time interval, these image data are first converted into consecutive frames. To ensure the temporal consistency of the data, the selected images are sorted and numbered according to the timestamp of each frame. During this process, timestamp alignment is performed to ensure that the time interval between consecutive frames is constant, avoiding misalignment problems caused by data loss or different sampling frequencies.

[0041] In this embodiment, by converting the target data sequence into consecutive frames, the system can ensure independent analysis of each frame and continuously track dynamic changes in the eye. Processing consecutive frames allows the system to accurately capture minute changes in pupil size and eye movement.

[0042] In this embodiment, the converted consecutive frames are processed using a preset target detection algorithm to calculate the pupil change rate and eye movement stability in each frame. First, the system accurately detects the pupil region in each frame image using an image recognition algorithm, such as a deep learning-based convolutional neural network. Then, by analyzing the size changes of the pupil region, the system calculates the relative change rate of the pupil, representing the intensity of the eye's accommodation response.

[0043] Simultaneously, the system calculates eye movement stability in each frame based on eye-tracking images. Eye movement stability is quantified by assessing the trajectory of eye movements and the amplitude of jitter at the gaze point. Specifically, the system determines whether the subject is stably gazing at the target or exhibiting significant searching eye movements (such as small eye jumps) by detecting the standard deviation of the eye movement path. Pupil variability and eye movement stability are key indicators for determining the effectiveness of the subject's feedback.

[0044] In this embodiment, the calculation process for consecutive frames is clearly defined. Based on a preset target detection algorithm, the pupil size and eye movement trajectory image of each frame are accurately determined. By calculating the pupil change rate and eye movement stability, the physiological response of the subject can be refined, providing a more accurate basis for adjusting the target position. This allows for more refined image analysis, improving the measurement accuracy of pupil change and eye movement stability, and thus effectively enhancing the accuracy of the target stopping position.

[0045] In this embodiment, the step of calculating a feedback score based on the pupillary change rate and eye movement stability, and adjusting the position of the first visual target based on the feedback score, pupillary change rate, and eye movement stability to complete the visual target movement includes: A feedback score is calculated based on preset weights, the pupil change rate, and eye movement stability. The accuracy of the stopping position of the first visual target is determined based on the feedback score, pupil change rate, and eye movement stability. If accurate, record the final position of the first target and complete the target movement; Otherwise, reset the first target and control the target movement again.

[0046] In this embodiment, after the pupil region is determined, the system calculates the pupil size in each frame of the image, typically by measuring the pupil's diameter or area to quantify pupil changes. Simultaneously, the system also extracts eye movement trajectory images by analyzing eye movement patterns. These eye movement trajectory images demonstrate the eye's movement path in each frame, helping the system analyze the subject's eye movement stability.

[0047] In this embodiment, the pupil change rate is calculated based on the pupil size of each frame in a series of images. During this process, the system first precisely quantifies the pupil size of each frame, for example, by calculating the relative change rate of pupil diameter Δd / d. This is used as the pupil change rate, which reflects the intensity of the subject's ocular accommodation response. When the pupil significantly constricts or dilates, the system can detect a large change rate, indicating that an accommodation response has occurred. If the change rate is too small, it may indicate that ocular accommodation has not occurred, or that the subject has failed to concentrate. The pupil change rate provides an important reference for subsequent eye movement stability assessment.

[0048] In this embodiment, eye movement stability is calculated based on eye movement trajectory images in consecutive frames. Eye movement stability reflects the stability of the subject's gaze point during target fixation. Typically, when a subject gazes at a target, the eye movement should exhibit small jumps and a stable trajectory. If the subject is not focused, the eye movement trajectory may exhibit large fluctuations and searching jumps, such as tiny eye jumps. To quantify eye movement stability, the system calculates the standard deviation σ of the eye movement trajectory in each frame, i.e., the amplitude of the eye movement trajectory fluctuation. Specifically, the system tracks the change in the center position of the eye in each frame and calculates its deviation or standard deviation. The smaller the standard deviation, the more stable the eye movement and the more accurate the gaze at the target. Conversely, if the standard deviation is large, it indicates more irregular eye movements and unstable gaze, which may affect the accuracy of the target.

[0049] In this embodiment, a feedback score is calculated by comprehensively analyzing pupillary change rate and eye movement stability, and the target position is adjusted based on this score. The system first calculates a comprehensive feedback score F based on preset weighting coefficients, combined with pupillary change rate and eye movement stability: F = α * Δd / d + β*σ (1) Where Δd / d is the relative rate of change of pupil diameter (reflecting accommodation initiation / relaxation); σ is the standard deviation of eye movement trajectory (reflecting fixation stability); α and β are weighted parameters related to the examination scenario (which can be obtained through clinical calibration).

[0050] In this embodiment, a feedback score is calculated based on pupillary change rate and eye movement stability, and combined with preset weights to further determine the accuracy of the target stopping position. This allows for self-correction after the target stops, ensuring the accuracy of the test results. When the calculated feedback score, pupillary change rate, and eye movement stability meet set thresholds, the target position is considered accurate, the final position is recorded, and the test is completed. If the requirements are not met, the target is reset and readjusted, effectively solving the problem of inaccurate target position caused by physiological reaction errors and ensuring the accuracy of the target stopping position.

[0051] In this embodiment, determining whether the stopping position of the first visual target is accurate based on the feedback score, pupillary change rate, and eye movement stability includes: When the feedback score is greater than or equal to a preset score threshold, the pupil change rate is greater than a preset change threshold, and the eye movement stability is less than a preset eye movement threshold, the stopping position of the first visual target is accurate. Otherwise, the stopping position of the first target will be inaccurate.

[0052] In this embodiment, the accuracy of the stopping position of the first optotype is determined by comprehensively analyzing the feedback score, pupillary change rate, and eye movement stability. After the system calculates the feedback score, pupillary change rate, and eye movement stability, it first compares the feedback score with a preset score threshold. If the feedback score is lower than the preset threshold, the system considers the optotype position inaccurate and may require readjustment or retesting. However, if the feedback score is higher than the preset threshold, the system further evaluates the pupillary change rate and eye movement stability. Specifically, the system compares the pupillary change rate with a preset change threshold. If the pupillary change rate exceeds the preset change threshold and the eye movement stability is lower than a preset stability threshold, the stopping position of the optotype is determined to be accurate. This judgment criterion ensures that the subject's pupillary change and eye movement stability meet expectations within a specific range, thereby enhancing the reliability of the test results.

[0053] In this embodiment, to improve the accuracy of the judgment, the system has refined the preset scoring threshold, pupil change rate threshold, and eye movement stability threshold in practical applications. First, the preset scoring threshold is adjusted based on clinical data and experimental verification to ensure it reflects the subject's ocular response during the test. Second, the pupil change rate threshold is set based on the subject's physiological response during the experiment to ensure accurate capture of the eye's accommodative response. Furthermore, the eye movement stability threshold is used to determine whether the subject is concentrating. If eye movement stability exceeds the set threshold, it indicates instability in the subject's eye movements, which may lead to incorrect target position judgment. By optimizing the threshold settings, the system can adjust the judgment criteria according to different subjects' response patterns, making the accuracy of target stopping position judgment more precise each time. Simultaneously, the system can continuously adjust and optimize these thresholds based on data feedback obtained during the experiment, improving the personalization and adaptability of the test.

[0054] In this embodiment, if |Δd / d| > the change threshold θ1 (e.g., 3%), it is determined that the eye has made a real accommodation response, indicating that the user's subjective feedback is likely real. In this case, the stopping position of the first visual target is accurate. If |Δd / d| ≤ the change threshold θ1, it is considered that the user's feedback may be inaccurate (e.g., the user said "blurry" in advance, or the user was not focused). In this case, the stopping position of the first visual target is inaccurate.

[0055] In this embodiment, when the target is clear, eye movements are relatively stable, and the gaze point jitter is small; when it is blurry, eye movements exhibit more frequent microsaccades. If σ < preset eye movement threshold θ2, it indicates stable gaze and reliable user feedback; in this case, the stopping position of the first target is accurate. If σ > preset eye movement threshold θ2, it indicates that the eye is searching for a clear target, and the feedback is questionable; in this case, the stopping position of the first target is inaccurate.

[0056] In this embodiment, when F ≥ preset score threshold T2, it indicates that the user's subjective feedback is credible, and the stopping position of the first target is accurate.

[0057] In this embodiment, by comprehensively judging the feedback score, pupil change rate, and eye movement stability, the accuracy of the target stopping position can be determined through multiple conditions. This ensures that the target position is considered accurate only when all parameters meet the preset conditions, thereby greatly reducing erroneous judgments caused by a single physiological response. Through multi-level verification, the reliability of the target stopping position is improved, the influence of manual intervention and subjective judgment is reduced, and the automation and accuracy of target movement control are enhanced.

[0058] In this embodiment, the present invention initializes a first optotype based on a preset point and controls its movement at a preset speed and direction, continuously collecting binocular image data. This ensures the standardization and repeatability of the optotype's movement and allows for real-time monitoring of the subject's eye responses, providing accurate image input for subsequent data analysis. When the first optotype stops in response to a user command and a first moment is determined, the binocular image data is filtered based on this moment and a preset time interval to obtain a target data sequence. This allows for more precise capture of physiological response data at the time the optotype stops, ensuring the timeliness and representativeness of the collected data. Next, based on the target data sequence, the system calculates pupillary change rate and eye movement stability. Pupil change rate reflects the physiological response of eye accommodation, while eye movement stability reveals the subject's visual stability. Through the calculation of these two parameters, the system can objectively judge the subject's reaction when the optotype stops, reducing errors caused by inaccurate subjective feedback or the subject's lack of concentration. This physiological data-based analysis method significantly improves the accuracy of the optotype's stopping position. Finally, the position of the first optotype is adjusted based on the calculated pupil change rate and eye movement stability to complete the optotype movement. By relying on objective data rather than simply the subjective judgment of the subjects, and by introducing real-time image acquisition and analysis, combined with pupil change rate and eye movement stability, the accuracy and automation level of optotype movement are improved, reducing human intervention in traditional methods and improving the precision of optotype movement control.

[0059] This invention also provides a method for checking the adjustment range, which uses the above-described target movement method to determine the target movement position and uses the final movement position of the target as the user's adjustment range.

[0060] In this embodiment, a first visual target is first initialized based on a preset point and its movement is controlled according to a preset speed and direction, while simultaneously acquiring binocular image data from the user in real time. When the system detects that the user issues a first user command via voice, key press, or gaze signal, it immediately stops the visual target movement and records this moment as the first moment. Subsequently, the system uses the first moment as the midpoint and crops the binocular image data according to a preset time interval to obtain a target data sequence. By processing this data sequence, the pupillary rate of change and eye movement stability are calculated, and the user's gaze accuracy towards the visual target is determined accordingly. When the feedback score meets a preset threshold condition, the system confirms the current visual target position as a valid position, and the distance corresponding to this position is the user's accommodation amplitude.

[0061] In this embodiment, a joint calculation mechanism for pupil change rate, eye movement stability, and feedback score is further introduced. The target data sequence is converted into continuous frames, and the pupil size and eye movement trajectory of each frame are extracted using a preset target detection algorithm. By calculating the rate of change of pupil size over time, the system can reflect the speed and amplitude of changes in eye focus; by analyzing the stability index of the eye movement trajectory, the system can determine the degree of concentration during the user's fixation process. Subsequently, the system calculates a feedback score F based on the above two indicators and compares it with the clarity threshold T1 and the blur threshold T2 to confirm the validity of the patient's feedback. If the feedback is valid, the system records the spatial position of the target at this time, and the distance between this position and the initial position is the final accommodation amplitude result.

[0062] In this embodiment, when the user reports "clear" and F ≤ T1, the system considers the target position accurate and records the current position as the final result; when the user reports "blurry" and F ≥ T2, the result is also considered valid. If the feedback conditions are not met for three consecutive tests, the system automatically resets the display to the initial position (40 cm) and issues a voice or text prompt indicating an abnormality and suggesting doctor intervention. Through this adaptive adjustment and feedback confirmation mechanism, the system can flexibly switch between automatic detection and manual intervention, ensuring reliable accommodation amplitude measurement results even in complex or unstable fixation environments.

[0063] In this embodiment, multiple optotype movement tests are performed on the same user, and the final position of the effective optotype is recorded for each test. The final accommodation amplitude is calculated based on a weighted average or median filtering algorithm. The weighting factor can be automatically adjusted according to the eye movement stability and pupillary change rate of each test, so that results with high stability and significant change rate are given higher weight. Through this fusion mechanism, the system effectively eliminates the influence of individual instantaneous fluctuations or environmental interference on the results, thereby obtaining more stable and reliable user accommodation amplitude values, providing accurate data support for clinical optometry or visual function assessment.

[0064] Please refer to Figure 2 , Figure 2 This is a schematic diagram of a target moving device provided in an embodiment of the present invention, including an initialization module 201, an instruction response module 202, an image filtering module 203, and an adjustment module 204; The initialization module 201 is used to initialize the first visual target based on a preset point, control the first visual target to move based on a preset speed and direction, and continuously collect binocular image data. The instruction response module 202 is used to respond to a first user instruction, stop moving the first target, and determine a first moment; the first moment is the moment when the first target stops moving; The image filtering module 203 is used to filter the binocular image data based on the first moment and a preset time interval to obtain a target data sequence; The adjustment module 204 is used to calculate the pupil change rate and eye movement stability based on the target data sequence, and adjust the position of the first optotype based on the pupil change rate and eye movement stability to complete the optotype movement.

[0065] In this embodiment, the image filtering module is used to filter the binocular image data based on the first time point and a preset time interval to obtain a target data sequence, including: Using the first moment as the midpoint and the preset time interval as the radius, the binocular image data is cropped to obtain the target data sequence.

[0066] In this embodiment, the adjustment module is used to calculate the pupillary change rate and eye movement stability based on the target data sequence, and adjust the position of the first optotype based on the pupillary change rate and eye movement stability to complete the optotype movement, including: The target data sequence is converted into continuous frames, and pupil change rate and eye movement stability are calculated based on a preset target detection algorithm and the continuous frames. The feedback score is calculated based on the pupil change rate and eye movement stability, and the position of the first optotype is adjusted based on the feedback score, pupil change rate, and eye movement stability to complete the optotype movement.

[0067] In this embodiment, the adjustment module is used to convert the target data sequence into continuous frames, and calculate the pupil change rate and eye movement stability based on a preset target detection algorithm and the continuous frames, including: The target data sequence is converted into consecutive frames, and the pupil size and eye movement trajectory image of each consecutive frame are determined based on a preset target detection algorithm and the consecutive frames. The pupil change rate is calculated based on the pupil size of each consecutive frame; and eye movement stability is determined based on the eye movement trajectory image.

[0068] In this embodiment, the adjustment module is used to calculate a feedback score based on the pupillary change rate and eye movement stability, and to adjust the position of the first optotype based on the feedback score, pupillary change rate, and eye movement stability to complete the optotype movement, including: A feedback score is calculated based on preset weights, the pupil change rate, and eye movement stability. The accuracy of the stopping position of the first visual target is determined based on the feedback score, pupil change rate, and eye movement stability. If accurate, record the final position of the first target and complete the target movement; Otherwise, reset the first target and control the target movement again.

[0069] In this embodiment, the adjustment module is used to determine whether the stopping position of the first visual target is accurate based on the feedback score, pupil change rate, and eye movement stability, including: When the feedback score is greater than or equal to a preset score threshold, the pupil change rate is greater than a preset change threshold, and the eye movement stability is less than a preset eye movement threshold, the stopping position of the first visual target is accurate. Otherwise, the stopping position of the first target will be inaccurate.

[0070] This invention also provides a terminal device, including a processor, a memory, and a computer program stored in the memory and configured to be executed by the processor, wherein the processor executes the computer program to implement the above-described target movement method.

[0071] This invention also provides a computer-readable storage medium, which includes a stored computer program, wherein the computer program controls the device where the computer-readable storage medium is located to execute the above-described target movement method when it is running.

[0072] For example, a computer program can be divided into one or more modules, one or more of which are stored in memory and executed by a processor to perform the present invention. The one or more modules can be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program in a terminal device.

[0073] The terminal device may be a desktop computer, laptop, handheld computer, or cloud server, etc. The terminal device may include, but is not limited to, a processor, memory, and display. Those skilled in the art will understand that the above components are merely examples of terminal devices and do not constitute a limitation on the terminal device. It may include more or fewer components, or combinations of certain components, or different components. For example, the terminal device may also include input / output devices, network access devices, buses, etc.

[0074] The processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. The processor is the control center of the terminal device, connecting all parts of the terminal device through various interfaces and lines.

[0075] Memory can be used to store computer programs and / or modules. The processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory, and by accessing data stored in the memory. Memory can mainly include a program storage area and a data storage area. The program storage area can store the operating system, application programs required for at least one function (such as sound playback, text conversion, etc.), etc.; the data storage area can store data created based on the use of the mobile phone (such as audio data, text message data, etc.). In addition, memory can include high-speed random access memory, and can also include non-volatile memory, such as hard disks, RAM, plug-in hard disks, smart media cards (SMC), secure digital cards (SD cards), flash cards, at least one disk storage device, flash memory device, or other volatile solid-state storage devices.

[0076] If the module based on target movement is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the above embodiments of the present invention can also be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include: any entity or device capable of carrying computer program code, recording media, USB flash drives, portable hard drives, magnetic disks, optical disks, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signals, telecommunication signals, and software distribution media, etc. Those skilled in the art can understand and implement this without any inventive effort.

[0077] The specific embodiments described above further illustrate the purpose, technical solution, and beneficial effects of the present invention. It should be understood that the above descriptions are merely specific embodiments of the present invention and are not intended to limit the scope of protection of the present invention. In particular, it should be noted that any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention for those skilled in the art.

Claims

1. A method for moving a target, characterized in that, include: The first visual target is initialized based on a preset point, and the first visual target is moved based on a preset speed and direction, while continuously acquiring binocular image data; In response to a first user command, stop moving the first viewpoint and determine a first moment; the first moment is the moment when the first viewpoint stops moving; Based on the first moment and the preset time interval, the binocular image data is filtered to obtain the target data sequence; The pupil change rate and eye movement stability are calculated based on the target data sequence, and the position of the first optotype is adjusted based on the pupil change rate and eye movement stability to complete the optotype movement.

2. The target movement method as described in claim 1, characterized in that, The step of filtering the binocular image data based on the first time point and a preset time interval to obtain a target data sequence includes: Using the first moment as the midpoint and the preset time interval as the radius, the binocular image data is cropped to obtain the target data sequence.

3. The target movement method as described in claim 2, characterized in that, The step of calculating pupillary change rate and eye movement stability based on the target data sequence, and adjusting the position of the first optotype based on the pupillary change rate and eye movement stability to complete optotype movement includes: The target data sequence is converted into continuous frames, and pupil change rate and eye movement stability are calculated based on a preset target detection algorithm and the continuous frames. The feedback score is calculated based on the pupil change rate and eye movement stability, and the position of the first optotype is adjusted based on the feedback score, pupil change rate, and eye movement stability to complete the optotype movement.

4. The target movement method as described in claim 3, characterized in that, The step of converting the target data sequence into continuous frames and calculating pupil change rate and eye movement stability based on a preset target detection algorithm and the continuous frames includes: The target data sequence is converted into consecutive frames, and the pupil size and eye movement trajectory image of each consecutive frame are determined based on a preset target detection algorithm and the consecutive frames. The pupil change rate is calculated based on the pupil size of each consecutive frame; and eye movement stability is determined based on the eye movement trajectory image.

5. The target movement method as described in claim 4, characterized in that, The step of calculating a feedback score based on the pupillary change rate and eye movement stability, and adjusting the position of the first optotype based on the feedback score, pupillary change rate, and eye movement stability to complete the optotype movement includes: A feedback score is calculated based on preset weights, the pupil change rate, and eye movement stability. The accuracy of the stopping position of the first visual target is determined based on the feedback score, pupil change rate, and eye movement stability. If accurate, record the final position of the first target and complete the target movement; Otherwise, reset the first target and control the target movement again.

6. The target movement method as described in claim 5, characterized in that, The step of determining whether the stopping position of the first visual target is accurate based on the feedback score, pupillary change rate, and eye movement stability includes: When the feedback score is greater than or equal to a preset score threshold, the pupil change rate is greater than a preset change threshold, and the eye movement stability is less than a preset eye movement threshold, the stopping position of the first visual target is accurate. Otherwise, the stopping position of the first target will be inaccurate.

7. A target movement device, characterized in that, include: Initialization module, command response module, image filtering module, and adjustment module; The initialization module is used to initialize the first visual target based on a preset point, control the first visual target to move based on a preset speed and direction, and continuously collect binocular image data. The instruction response module is used to respond to a first user instruction, stop moving the first target, and determine a first moment; the first moment is the moment when the first target stops moving; The image filtering module is used to filter the binocular image data based on the first moment and a preset time interval to obtain a target data sequence; The adjustment module is used to calculate the pupil change rate and eye movement stability based on the target data sequence, and adjust the position of the first optotype based on the pupil change rate and eye movement stability to complete the optotype movement.

8. A target moving device as described in claim 7, characterized in that, The image filtering module is used to filter the binocular image data based on the first time point and a preset time interval to obtain a target data sequence, including: Using the first moment as the midpoint and the preset time interval as the radius, the binocular image data is cropped to obtain the target data sequence.

9. A target moving device as described in claim 8, characterized in that, The adjustment module is used to calculate the pupillary change rate and eye movement stability based on the target data sequence, and adjust the position of the first optotype based on the pupillary change rate and eye movement stability to complete the optotype movement, including: The target data sequence is converted into continuous frames, and pupil change rate and eye movement stability are calculated based on a preset target detection algorithm and the continuous frames. The feedback score is calculated based on the pupil change rate and eye movement stability, and the position of the first optotype is adjusted based on the feedback score, pupil change rate, and eye movement stability to complete the optotype movement.

10. A target movement device as described in claim 9, characterized in that, The adjustment module is used to convert the target data sequence into continuous frames, and calculate the pupil change rate and eye movement stability based on a preset target detection algorithm and the continuous frames, including: The target data sequence is converted into consecutive frames, and the pupil size and eye movement trajectory image of each consecutive frame are determined based on a preset target detection algorithm and the consecutive frames. The pupil change rate is calculated based on the pupil size of each consecutive frame; and eye movement stability is determined based on the eye movement trajectory image.

Images