A myopia prevention and control system and method based on synergistic regulation of multiple optical signals

Abstract

The application discloses a myopia prevention and control system and method based on multi-optical signal cooperative regulation, which comprises a transparent electronic lens, multi-sensor fusion, AI intelligent regulation, mobile terminal interaction and doctor terminal management module; the transparent electronic lens is embedded with a transparent microLED display screen, and an optical area and a prevention and control area are dynamically divided to realize pixel-level cooperative regulation of contrast, high-order aberration and chromatic aberration; multi-sensor real-time acquisition of illumination, eye distance, pupil diameter and head movement data; AI clusters analysis of myopia progression types through machine learning, dynamic adjustment of prevention and control parameters and switching of read-write, outdoor and other modes, and breaking of neural adaptation through dynamic switching of multi-form scattering points. The method comprises data acquisition, type analysis, optical regulation, report generation and doctor remote optimization steps, realizes whole-process electronic, information and intelligent myopia management, improves prevention and control efficiency, prolongs the bonus period, realizes personalized closed-loop management, and is suitable for myopia people of different ages and different progression types.

Description

Technical Field

[0001] This invention relates to the field of myopia prevention and control technology, specifically to a myopia prevention and control system and method based on the coordinated regulation of multiple optical signals. Background Technology

[0002] Myopia has become a serious public health problem worldwide, especially among teenagers, whose incidence is rising year by year and showing a trend of younger onset and higher severity. Myopia not only leads to decreased distance vision, affecting daily learning and life, but may also cause serious complications such as retinal detachment and macular degeneration, threatening eye health.

[0003] Currently, existing myopia control methods mainly include optical correction (such as eyeglasses and orthokeratology lenses), drug therapy (such as atropine eye drops), and behavioral intervention (such as increasing outdoor activity time). Among these, optical correction products are the most widely used control method due to their ease of use and high safety. However, existing optical control products have many technical shortcomings, making it difficult to meet the needs of efficient and long-term myopia control. 1. Neural adaptation leads to a decline in the effectiveness of myopia control: Existing myopia control lenses (such as lenses with diffusion point designs) mostly use a single shape and fixed arrangement of scattering points. These static optical interference signals are easily adapted to by the human visual nervous system. The brain will gradually "filter" or "ignore" these fixed noises, resulting in a significant decline in the control effect after 1-2 years of use, that is, a "shortened control bonus period", making it impossible to achieve long-term effective myopia suppression.

[0004] 2. Poor scene adaptability and fluctuating prevention and control effects: Teenagers' eye use scenarios are complex and diverse, including close-range reading and writing, outdoor distant viewing, and dynamic activities. The light intensity, viewing distance, and visual needs vary greatly in different scenarios. The optical parameters of existing lenses are fixed and cannot be adjusted in real time according to environmental changes and eye use status. This results in poor prevention and control effects in some scenarios (such as strong outdoor light, prolonged close-range reading and writing), and may even affect visual comfort.

[0005] 3. Lack of personalized control capabilities: There are significant individual differences among teenagers in the rate of myopia progression (slow / moderate / rapid progression), axial length, pupil size, and eye-use habits. Existing prevention and control products adopt a "one-size-fits-all" design, which cannot develop personalized prevention and control plans based on individual characteristics, resulting in unsatisfactory prevention and control effects for some users.

[0006] 4. Limited synergistic effects and single control methods: Existing optical control products mostly rely on a single optical mechanism (such as peripheral defocus) to achieve control, failing to fully utilize the synergistic effect of multiple optical signals. The regulatory power of a single optical signal is limited, making it difficult to effectively intervene in the complex physiological process of axial elongation; at the same time, existing products lack the ability to synergize and adapt with other control methods such as drug treatment and orthokeratology lenses, thus failing to form a comprehensive control system.

[0007] 5. Dynamic changes in pupil size lead to control failure: Pupil size changes dynamically with ambient light intensity and viewing distance. Existing lenses have fixed optical zone sizes, which cannot match the dynamically changing pupil. When the pupil diameter exceeds the optical zone range, the peripheral retina cannot receive effective optical control, leading to control failure. When the pupil diameter is smaller than the optical zone range, the excess optical zone introduces unnecessary visual interference, affecting visual quality.

[0008] To address the shortcomings of existing technologies, this invention proposes a myopia prevention and control system and method based on the coordinated regulation of multiple optical signals. By using a transparent microLED display screen to achieve dynamic coordinated regulation of multiple optical signals, and combining multi-sensor fusion and AI algorithms, it achieves full-scene adaptive and personalized prevention and control, breaks through neural adaptability, extends the benefit period of prevention and control, and significantly improves the prevention and control effect. Summary of the Invention

[0009] The purpose of this invention is to overcome the technical defects of existing myopia prevention and control technologies, such as poor neural adaptability, poor scene adaptability, and lack of personalized control, and to provide a myopia prevention and control system and method based on the coordinated control of multiple optical signals.

[0010] To address the aforementioned technical problems, embodiments of the present invention provide the following technical solution: a myopia prevention and control system based on multi-optical signal coordinated modulation, comprising: A transparent electronic lens module, comprising a high-transmittance transparent microLED display screen with an embedded lens, used to realize dynamic division of the optical zone and the control zone and pixel-level optical parameter adjustment; The multi-sensor fusion module integrates an ambient light sensor, an infrared distance sensor, a pupil-tracking camera, and a motion sensor to collect real-time data on light intensity, eye distance, pupil diameter, and head movement. The AI ​​intelligent control module is communicatively connected to the transparent electronic lens module and the multi-sensor fusion module. It is used to receive sensor data and user eye axis and eye behavior data, and to dynamically adjust the prevention and control parameters by clustering and analyzing the user's myopia progression type through machine learning algorithms. The mobile terminal interaction module is a mobile terminal APP with data collection, data transmission and display functions. It is used to collect users' axial length data and eye use behavior data, push prevention and control suggestions to users, and support interaction between users and doctors.

[0011] Furthermore, the transparent microLED display screen is a flexible transparent display panel with a pixel density ≥300PPI, a grayscale adjustment range of 0-255 levels for a single pixel, and supports independent pixel-level control. The optical zone is the central area of ​​the lens, and its diameter can be dynamically adjusted according to the pupil diameter, with an adjustment range of 3-8mm. The control zone is the annular area surrounding the optical zone, with a width of 5-15mm.

[0012] Furthermore, the ambient light sensor of the multi-sensor fusion module collects light intensity in the range of 10-100000 lux at a sampling frequency of 10Hz; the infrared distance sensor has a ranging range of 10cm-100cm; the pupil tracking camera has a frame rate of ≥30fps; and the motion sensor is a combination of a six-axis gyroscope and an accelerometer with a sampling frequency of ≥50Hz, used to detect the pitch, yaw, and roll angles of the head.

[0013] Furthermore, the machine learning algorithms of the AI ​​intelligent control module include K-means clustering algorithm and random forest regression algorithm. The K-means clustering algorithm is used to cluster the user's myopia progression type based on the user's axial length growth data, eye use duration distribution data, and near-field eye use frequency data over the past 6-12 months. The random forest regression algorithm is used to establish a mapping model between environmental data, physiological data, and prevention and control parameters. The prevention and control parameters include optical zone diameter, prevention and control zone density, contrast gray value, higher-order aberration type and intensity, and red and blue light transmittance ratio.

[0014] Furthermore, the coordinated control of optical signals in the transparent electronic lens module specifically includes: Contrast signal control: By adjusting the pixel grayscale values ​​of the transparent microLED display, a low-contrast environment is simulated. The grayscale value adjustment range is 100-200 levels, corresponding to a contrast adjustment range of 0.3-0.7. Advanced aberration control: Generates asymmetric coma aberrations with coma coefficients adjustable in the range of 0.05-0.3μm, achieving precise superposition of aberrations through pixel-level phase modulation; Color difference signal control: Dynamically adjust the transmittance of red and blue light. The transmittance of red light is adjustable from 70% to 90%, and the transmittance of blue light is adjustable from 30% to 60%. Red and blue light are controlled separately through independent filter pixel units.

[0015] Furthermore, the morphology of the scattering points in the control zone includes circular, star-shaped, elliptical, short lines, irregular polygons, and micropores.

[0016] This invention also proposes a myopia prevention and control method based on the coordinated modulation of multiple optical signals, comprising the following steps: S1: The multi-sensor fusion module collects environmental and physiological data in real time, including light intensity, viewing distance, pupil diameter and head movement status; S2: The AI ​​intelligent control module receives the data collected in step S1, combines it with the user's axial length data and eye use behavior data uploaded by the mobile terminal interaction module, and uses machine learning algorithms to cluster and analyze the user's myopia progression type, which includes slow progression, moderate progression and rapid progression. S3: Based on the analysis results, the AI ​​intelligent control module automatically matches the preset basic prevention and control template, or calls the personalized setting template customized by the doctor and downloaded by the patient, and automatically switches the prevention and control mode. The prevention and control mode includes reading and writing mode, outdoor mode and dynamic eye use mode. S4: The transparent electronic lens module achieves coordinated control of contrast signal, higher-order aberration signal and chromatic aberration signal according to the control mode and the adjusted control parameters, and dynamically switches the shape and arrangement of scattering points in the control area. S5: The mobile interaction module receives control data from the AI ​​intelligent control module in real time, generates prevention and control suggestions, and synchronizes them to the doctor's management module.

[0017] Furthermore, the basic prevention and control template in step S3 presets uniform basic prevention and control parameters: initial diameter of the optical zone 4.5mm, prevention and control zone density 400 / mm², contrast grayscale value 140 levels, coma coefficient 0.15μm, red light transmittance 78%, and blue light transmittance 40%. The personalized setting template allows doctors to make customized adjustments based on their professional abilities and research data, combined with the user's individual eye characteristics, myopia progression type, and eye habits. The patient can download and apply the template through the mobile terminal interaction module to achieve exclusive prevention and control parameter configuration.

[0018] Furthermore, the dynamic switching of the control zone scattering points in step S4 also includes switching of combination strategies. The combination strategies include random distribution strategy, zonal distribution strategy, and gradient distribution strategy. Among them, the random distribution strategy is to randomly arrange scattering points of different shapes according to a preset ratio, with circles accounting for 30%-50%, stars accounting for 20%-30%, and other shapes accounting for 20%-50%; the zonal distribution strategy is to use a combination of short lines and micropores in the control zone corresponding to the nasal side of the retina, and a combination of stars and irregular polygons in the control zone corresponding to the temporal side of the retina; the gradient distribution strategy is to increase the size of the scattering points from 5μm to 50μm and the density from 100 points / mm² to 800 points / mm² from the edge of the optical zone to the periphery of the control zone.

[0019] Furthermore, step S4 implements the coordinated control of the contrast signal, higher-order aberration signal, and chromatic aberration signal, specifically including the following coordinated execution logic: S41: First, the contrast signal modulation is used as the basic intervention layer. The AI ​​intelligent modulation module determines the initial modulation intensity of the contrast signal based on the eye distance data collected in step S1: when the eye distance is ≤35cm, the contrast signal is adjusted to the low contrast range to suppress high contrast stimulation of the retina; when the eye distance is >35cm, the contrast signal intensity is appropriately increased to balance the prevention and control effect and visual clarity. S42: Based on the contrast signal modulation, a higher-order aberration signal is superimposed as an enhanced intervention layer, and the type and intensity of the higher-order aberration signal are adapted according to the myopia progression type determined in step S2: for users with rapid progression, coma-type asymmetric aberrations are selected first and set to a higher intensity; for users with slow progression, low-intensity spherical aberrations are selected. S43: Using color difference signal modulation as an adaptation layer, the red and blue light transmittance ratio is dynamically adjusted based on the ambient light intensity data collected in step S1, and a pixel-level color difference control area is formed within the control zone. Local color difference modulation is achieved through colored scattered dots: when the ambient light intensity is ≤500 lux, the proportion of red light transmittance is increased to enhance the refractive development guidance effect, and a colored scattered dot array dominated by red can be formed in the control zone; when the ambient light intensity is >500 lux, the proportion of blue light transmittance is reduced to reduce the risk of light damage, and a scattered dot distribution dominated by blue-green mixed colors can be formed in the control zone; at the same time, it is ensured that the modulation direction of the color difference modulation signal is consistent with that of the contrast signal and higher-order aberration signal. S44: During the coordinated output of the three types of signals, monitor the dynamic changes in the pupil collected by the pupil tracking camera in real time. If the change in pupil diameter is greater than 1mm, adjust the coverage of the three types of signals in real time: reduce the area of ​​action of the contrast signal and the higher-order aberration signal to match the shrinking pupil, or expand the area of ​​action of the chromatic aberration signal to cover the enlarged pupil, so as to ensure that the three types of signals always act on the key control area of ​​the retina.

[0020] The beneficial effects of the above-described technical solution of the present invention are as follows: 1. This invention achieves dynamic switching of multi-morphological scattering points through a transparent microLED display screen, including real-time changes in shape, density, and arrangement, generating unpredictable visual noise, avoiding the brain's "filtering" of static interference signals, and solving the problem of the decay of the control effect of traditional lenses over time.

[0021] 2. This invention proposes for the first time a synergistic control mechanism for three types of optical signals: contrast, higher-order aberrations, and chromatic aberration. Through pixel-level precise control, the three types of signals are optimized and combined to intervene in the physiological process of axial elongation through multiple pathways.

[0022] 3. This invention integrates a multi-sensor fusion module to collect environmental and physiological data in real time, automatically switch between reading / writing, outdoor, and dynamic eye use modes, and adjust optical parameters and scattering point morphology to ensure the effectiveness of prevention and control while taking into account visual comfort in different scenarios.

[0023] 4. This invention uses AI algorithms to cluster and analyze the myopia progression type of users, and combines this with age group, axial length data, and eye-use habits to formulate a personalized prevention and control plan. Users with different progression types and age groups can obtain targeted optical parameter adjustments, solving the "one-size-fits-all" design flaw of existing products and significantly improving the adaptability and effectiveness of the prevention and control plan.

[0024] 5. This invention is the first to deeply integrate transparent electronic imaging technology, intelligent sensing technology, AI algorithms, and medical optics principles, achieving cross-disciplinary innovation in "optics-electronics-medicine." Through pixel-level optical control, multi-sensor data fusion, and AI parameter optimization, it solves technical challenges that traditional lenses cannot achieve, such as dynamic adaptation, personalized control, and multi-signal coordination, providing a new solution for myopia prevention and control technology.

[0025] 6. This invention supports use in conjunction with existing prevention and control measures such as atropine drug therapy and orthokeratology lenses. By adjusting optical parameters through an AI intelligent control module, it achieves synergistic prevention and control through "optics + drug" and "optics + orthokeratology lenses", further improving the prevention and control effect and meeting the diverse needs of different users.

[0026] 7. This invention enables real-time sharing of user data and remote adjustment of prevention and control parameters by interacting with a mobile app and a doctor's terminal system, forming a closed-loop prevention and control system. Doctors can optimize prevention and control plans in a timely manner based on the user's axial length growth, avoiding decreased effectiveness due to outdated prevention and control parameters, and ensuring the continuity and effectiveness of prevention and control. Attached Figure Description

[0027] Figure 1 This is a system principle block diagram of the present invention; Figure 2 This is a flowchart of the method of the present invention; Figure 3 This is a simulation diagram of lens imaging according to the present invention; Figure 4 This is a schematic diagram of the lens structure related to the present invention. Detailed Implementation

[0028] To make the technical problems, technical solutions and advantages of the present invention clearer, a detailed description will be given below in conjunction with the accompanying drawings and specific embodiments.

[0029] like Figure 1 As shown, a myopia control system based on multi-optical signal coordinated regulation includes a transparent electronic lens module 101, a multi-sensor fusion module 102, an AI intelligent regulation module 103, a mobile terminal interaction module 104, and a doctor terminal management module 105. The modules are connected to each other through wired or wireless communication to form a closed-loop regulation system.

[0030] (a) Transparent electronic lens module 101 The transparent electronic lens module is the core optical control carrier of the entire system, including the lens substrate, transparent microLED display, driver chip and power supply unit.

[0031] Lens substrate: Made of medical-grade PC or resin material, it has good light transmittance, impact resistance and biocompatibility. The refractive index of the lens substrate is 1.50-1.67 and the Abbe number is ≥30, ensuring basic optical correction effect.

[0032] Transparent microLED display: Embedded in the corresponding area of ​​the lens substrate, it adopts a flexible transparent display panel with a light transmittance of ≥85%, ensuring that it does not affect normal visual function; the pixel density is ≥300PPI, and the grayscale adjustment range of a single pixel is 0-255 levels, supporting independent pixel-level control, which can realize dynamic division and parameter adjustment of the optical zone and the control zone. Among them, the optical zone is the central area of ​​the lens, which is used to achieve clear imaging. Its diameter can be dynamically adjusted according to the pupil diameter, with an adjustment range of 3-8mm; the control zone is the annular area surrounding the optical zone, with a width of 5-15mm, which is used to realize optical signal control and scattering point display.

[0033] The transparent microLED display integrates a contrast control unit, a high-order aberration control unit, and a chromatic aberration control unit, which respectively achieve independent control and synergistic effect of three types of optical signals: (1) Contrast control unit: By adjusting the pixel gray value, it simulates a low contrast environment and suppresses the high contrast signal of the retina. The gray value adjustment range is 100-200 levels, and the corresponding contrast adjustment range is 0.3-0.7. It can be adaptively adjusted according to the eye use scenario and user characteristics.

[0034] (2) Advanced aberration control unit: Asymmetric coma is generated through pixel-level phase modulation, with the coma coefficient adjustable in the range of 0.05-0.3μm, intervening in the physiological process of axial elongation. This unit has multiple preset coma modes, which can be accurately superimposed onto the control area according to the instructions of the AI ​​intelligent control module.

[0035] (3) Color difference control unit: adopts independent filter pixel unit to dynamically adjust the transmittance of red light and blue light. The transmittance of red light is adjusted within the range of 70%-90%, and the transmittance of blue light is adjusted within the range of 30%-60%. The color difference signal is used to influence refractive development, while avoiding excessive damage to the eyes from blue light.

[0036] Driver chip: Electrically connected to the transparent microLED display, it receives control commands from the AI ​​intelligent control module, driving the display to achieve pixel-level parameter adjustment, scattering point shape switching, and prevention mode switching. The driver chip has a built-in programmable "scattering unit shape library" with various micron-level scattering point shapes, including circles, stars, ellipses, short lines, irregular polygons, and micropores, each shape consisting of several pixels.

[0037] Power supply unit: It adopts a micro lithium battery or wireless power supply module. The lithium battery has a capacity of 50-100mAh, supports magnetic charging, and can be used continuously for 8-12 hours on a single charge, meeting the daily eye use needs; the wireless power supply module realizes wireless charging through electromagnetic induction, which is suitable for daily use scenarios.

[0038] (II) Multi-sensor fusion module 102 The multi-sensor fusion module integrates multiple sensors to collect environmental and user physiological data in real time, providing data support for adaptive regulation. These sensors include an ambient light sensor, an infrared distance sensor, a pupil-tracking camera, a motion sensor, and a data transmission unit.

[0039] Ambient light sensor: Employs a high-precision photoresistor or CMOS image sensor to collect ambient light intensity, with a collection range of 10-100000 lux and a collection frequency of 10Hz, used to determine the visual environment (such as indoor or outdoor).

[0040] Infrared distance sensor: Based on the principle of infrared reflection, the ranging range is 10-100cm and the acquisition frequency is 10Hz. It is used to detect the distance between the user and the object in sight and to determine whether it is close-range eye use.

[0041] Pupil tracking camera: It adopts a miniature CMOS camera with a frame rate of ≥30fps and a pixel resolution of ≥300,000. It acquires pupil images in real time and analyzes pupil diameter, pupil position and gaze direction to provide a basis for adjusting the size of the optical zone and optimizing control parameters.

[0042] Motion sensor: A combination of a six-axis gyroscope and an accelerometer, with a sampling frequency of ≥50Hz, used to detect the pitch, yaw and roll angles of the head, determine the user's motion state (such as static reading and writing, dynamic activities), and avoid visual interference during motion.

[0043] Data transmission unit: Using Bluetooth 5.0 or Wi-Fi module, the collected sensor data is transmitted to the AI ​​intelligent control module in real time with a transmission delay of ≤100ms to ensure the real-time control.

[0044] (III) AI Intelligent Control Module 103 The AI ​​intelligent control module is the core control unit of the system, including a data processing unit, a machine learning algorithm unit, a control parameter decision unit, and a mode switching unit. It can be integrated into the control chip of the transparent electronic lens module or remotely calculated through a cloud server.

[0045] Data processing unit: Receives real-time data transmitted from the multi-sensor fusion module and user axial length data and eye behavior data uploaded from the mobile interaction module. Performs data cleaning and normalization to remove outliers and ensure data accuracy. User axial length data includes measurements of axial length over the past 6-12 months, while eye behavior data includes daily screen time, frequency of near-vision activities, and distribution of screen time across different scenarios.

[0046] Machine learning algorithm unit: includes K-means clustering algorithm and random forest regression algorithm, used for user type analysis and prevention parameter mapping. (1) K-means clustering algorithm: Based on user axial length growth data, eye usage time distribution data, and near-field eye usage frequency data, users are divided into three categories: slow-progression type, medium-progression type, and fast-progression type. Among them, the annual axial length growth of slow-progression type users is ≤0.2mm, the annual axial length growth of medium-progression type users is 0.2-0.4mm, and the annual axial length growth of fast-progression type users is ≥0.4mm.

[0047] (2) Random Forest Regression Algorithm: A mapping model is established between environmental data (light intensity), physiological data (eye distance, pupil diameter, head movement state) and control parameters. The control parameters include optical zone diameter, control zone density, contrast gray value, higher-order aberration coefficients, red and blue light transmittance ratio, scattering point morphology and arrangement. This algorithm is trained with a large amount of sample data to ensure the accuracy of parameter mapping.

[0048] Prevention and control parameter decision unit: Based on user type analysis results, real-time sensor data, and preset age group templates, the prevention and control parameters are dynamically adjusted to achieve personalized control with "one policy per person". The age group templates include a low myopia template for 8-10 years old, a moderate myopia template for 11-12 years old, and a high myopia template for 13-15 years old. Each template has corresponding preset basic prevention and control parameters, which are then fine-tuned based on individual user data.

[0049] Mode switching unit: Based on sensor data, it determines the user's eye usage scenario and automatically switches between prevention and control modes, including reading and writing mode, outdoor mode, and dynamic eye usage mode. (1) Reading and writing mode: When the eye distance is ≤30cm, the light intensity is 100-10000 lux, and the head movement is stable, switch to this mode. In this mode, the control parameters are based on enhancing the control effect, and adopt a combination of high interference scattering points, a high density of control area, and appropriate aberration and color difference control intensity.

[0050] (2) Outdoor mode: When the light intensity is detected to be ≥10000 lux and the viewing distance is ≥50cm, switch to this mode. In this mode, the control parameters are based on ensuring visual comfort and distance vision clarity, and adopt a combination of low interference scattering points, a lower control zone density, and appropriately reduce the aberration control intensity.

[0051] (3) Dynamic eye use mode: When unstable head movement is detected, the system switches to this mode. In this mode, the system automatically adjusts the size of the optical zone and the parameters of the control zone to avoid visual blurring and interference caused by movement, and to ensure uninterrupted control.

[0052] (iv) Mobile Interaction Module 104 The mobile interaction module is an app installed on mobile devices such as smartphones and tablets, and has functions such as data collection, data transmission, display feedback, and user interaction. Data acquisition function: Supports users to manually input or upload eye examination results such as axial length, myopia degree, and cycloplegic refraction data; collects eye behavior data such as daily eye use time, eye distance distribution, and outdoor activity time through the mobile terminal's sensors; supports integration with hospital ophthalmology systems to automatically synchronize examination reports.

[0053] Data transmission function: The collected user data is transmitted to the AI ​​intelligent control module in real time, and the control parameters and control modes of the AI ​​intelligent control module are received at the same time to realize two-way data interaction.

[0054] Display feedback function: Show users the real-time prevention and control status (prevention and control mode, optical parameters, scattering point morphology), "Eye Health Report" (including axial length growth trend, eye behavior analysis, prevention and control effect evaluation) and personalized prevention and control suggestions (such as increasing outdoor activity time, adjusting reading and writing posture, etc.).

[0055] User interaction features: Supports users to manually switch between prevention and control modes, adjust prevention and control parameter intensity (such as high / medium / low levels), and record feedback on eye use scenarios (such as visual comfort and clarity scores); provides online consultation function to facilitate communication between users and doctors.

[0056] In addition, the system supports a collaborative control mode, which can be used in conjunction with atropine drug treatment and orthokeratology lenses. When the user uses atropine eye drops at the same time, the AI ​​intelligent control module will adjust the optical control parameters according to the drug concentration to reduce the intensity of optical interference and avoid over-control. When the user wears orthokeratology lenses at the same time, the system monitors the positioning status of the orthokeratology lenses through a pupil tracking camera, adjusts the position of the optical zone and control parameters, and achieves synergistic effect of "optics + orthokeratology lenses".

[0057] like Figure 2 As shown, this invention also proposes a myopia prevention and control method based on the coordinated modulation of multiple optical signals, comprising the following steps: S1: System Initialization and User Data Entry. Users enter their basic personal information (age, gender), eye examination data (axial length, myopia degree, pupil diameter range), and myopia progression (axial length growth data over the past 6-12 months) through the mobile interaction module. The mobile interaction module uploads the data to the AI ​​intelligent control module. Doctors review the user data through the doctor's management module and select the corresponding age group template based on the user's age and myopia status as the basis for initial prevention and control parameters.

[0058] S2: Real-time acquisition of multi-sensor data. After the multi-sensor fusion module is started, it collects ambient light intensity, eye distance, pupil diameter, and head movement data in real time. The data is then transmitted to the AI ​​intelligent control module through the data transmission unit. The acquisition frequency is 10-50Hz to ensure the real-time and continuous nature of the data.

[0059] S3: User Type Analysis and Prevention Mode Judgment. The AI ​​intelligent control module uses the K-means clustering algorithm to perform cluster analysis on the user's axial length growth data and eye behavior data to determine the user's myopia progression type (slow / medium / fast progression). At the same time, based on the light intensity, eye distance, and head movement data collected by the sensor, it judges the user's current eye use scenario and automatically switches the corresponding prevention mode (reading and writing mode, outdoor mode, dynamic eye use mode).

[0060] S4: Personalized Prevention and Control Parameter Calculation AI Intelligent Adjustment Module calculates personalized prevention and control parameters based on the user's myopia progression type, prevention and control mode, and age group template using a random forest regression algorithm, including: Optical zone diameter: dynamically adjusted according to the pupil diameter to ensure that the optical zone completely covers the pupil; the adjustment range is 3-8mm. Parameters of the control zone: including control zone density (100-800 units / mm²), contrast grayscale value (100-200 levels), coma coefficient (0.05-0.3μm), and red and blue light transmittance ratio (red light 70%-90%, blue light 30%-60%). Scattering point parameters include morphological combinations (circle + star, star + irregular polygon, etc.), arrangement (random distribution, partitioned distribution, gradient distribution), and switching frequency (0.5-5Hz).

[0061] S5: The transparent electronic lens module, which features multi-optical signal coordinated modulation and dynamic switching of scattering points, receives control parameter instructions from the AI ​​intelligent modulation module and controls the transparent microLED display screen through the driver chip. Divide the optical zone into a control zone and adjust the diameter of the optical zone and the extent of the control zone; The contrast, higher-order aberration, and chromatic aberration control units are activated to achieve coordinated control of the three types of optical signals, adjusting the grayscale value, coma coefficient, and red and blue light transmittance according to the calculated parameter values. The corresponding scattering point shape is called from the scattering unit shape library, displayed in a preset arrangement, and the shape, density and arrangement of the scattering points are dynamically switched according to the switching frequency to break the neural adaptation.

[0062] S6: Prevention and Control Data Feedback and Report Generation The mobile interaction module receives prevention and control parameters and mode data from the AI ​​intelligent control module in real time. Combined with user eye behavior data, it generates an "Eye Health Report" which includes daily eye usage time statistics, near-field eye use warnings, axial length growth trend analysis, prevention and control effect evaluation, and personalized suggestions, and pushes them to the user.

[0063] S7: Collaborative Prevention and Control Mode Adaptation (Optional) If the user is simultaneously using atropine for treatment, the user can input the drug concentration and frequency of use through the mobile interaction module. The AI ​​intelligent control module will adjust the optical control parameters, reduce the contrast suppression intensity and aberration control intensity, and avoid visual discomfort caused by the superposition of "optics + drugs". If the user is simultaneously wearing orthokeratology lenses, the pupil tracking camera will monitor the positioning status of the orthokeratology lenses in real time. The AI ​​intelligent control module will adjust the position of the optical zone to ensure that the optical zone is aligned with the optical center of the orthokeratology lenses, thereby optimizing the prevention and control effect.

[0064] To make the technical solution of the present invention clearer, the present invention will be further described in detail below with reference to specific embodiments.

[0065] Example 1: System Hardware Structure Implementation This embodiment provides a hardware structure implementation scheme for a myopia prevention and control system based on the coordinated modulation of multiple optical signals, as detailed below: (I) Hardware Implementation of Transparent Electronic Lens Module Lens substrate: Made of PC material with a refractive index of 1.60, Abbe number of 32, lens diameter of 65mm, center thickness of 1.5mm, and edge thickness of 2.5mm, meeting the optical correction needs of daily wear.

[0066] Transparent microLED display: It adopts a flexible OLED transparent display panel with a light transmittance of 88%, a pixel density of 350PPI, and a ring-shaped screen size with an inner diameter of 8mm and an outer diameter of 20mm (corresponding to an optical area diameter of 3-8mm and a control area width of 5-12mm). The individual pixel size is 50μm×50μm, the grayscale adjustment range is 0-255 levels, the response time is ≤10ms, and it supports pixel-level independent driving.

[0067] The contrast control unit controls contrast by adjusting pixel grayscale values. When the grayscale value is set to 150 levels, the corresponding ambient contrast simulation is 0.5. The high-order aberration control unit generates coma aberration through pixel phase modulation technology. The coma coefficient can be continuously adjusted between 0.05-0.3μm. The phase control algorithm of the driver chip achieves precise superposition of aberrations. The color difference control unit adopts red and blue light separation filtering technology. The red light transmittance is adjustable from 70% to 90% by adjusting the voltage of the red filter pixel, and the blue light transmittance is adjustable from 30% to 60% by adjusting the voltage of the blue filter pixel.

[0068] Driver chip: A microcontroller with an ARM Cortex-M4 core, 100MHz clock speed, 1MB Flash and 128KB RAM, supporting I2C and SPI communication interfaces. It connects to the transparent microLED display via the SPI interface with a communication rate of 10Mbps. The driver chip has a built-in scattering unit shape library, storing data for six scattering point shapes: circular, star-shaped, elliptical, short line, irregular polygon, and micro-hole-shaped. Each shape corresponds to a different pixel lighting mode.

[0069] Power supply unit: It adopts an 80mAh micro lithium battery with a voltage of 3.7V and a size of 5mm×10mm×2mm, which is integrated inside the temple; the charging interface adopts a magnetic interface, the charging current is 50mA, the full charge time is 1.5 hours, and a single charge can be used continuously for 10 hours.

[0070] (II) Hardware Implementation of Multi-Sensor Fusion Module Ambient light sensor: It adopts a high-precision photosensitive sensor of model TSL2591, with a sampling range of 10-100000 lux, I2C communication interface, power supply voltage of 3.3V, operating current of 12μA, and is integrated into the front end of the temple.

[0071] Infrared distance sensor: The laser rangefinder sensor, model VL53L0X, is used. It has a range of 10-100cm, an I2C communication interface, a measurement frequency of 10Hz, a power supply voltage of 3.3V, and an operating current of 20μA. It is installed on the bridge of the lens frame, facing the user's viewing direction.

[0072] Pupil tracking camera: It adopts a miniature CMOS camera of model OV7725 with a resolution of 640×480, a frame rate of 30fps, a lens focal length of 2.8mm, a field of view of 60°, a power supply voltage of 3.3V, and an operating current of 30mA. It transmits image data through a MIPI interface and is installed inside the frame, aimed at the user's pupil area.

[0073] Motion sensor: It adopts a six-axis gyroscope and accelerometer of model MPU6050, with a sampling frequency of 50Hz, an acceleration measurement range of ±2g, an I2C communication interface, a power supply voltage of 3.3V, and an operating current of 40μA. It is integrated inside the temple and used to detect head movement.

[0074] Data transmission unit: Uses a Bluetooth 5.0 module of model nRF52832, with a communication distance of 10m, a transmission rate of 2Mbps, and supports low power mode. It transmits sensor data with the AI ​​intelligent control module via Bluetooth.

[0075] (III) Hardware Implementation of AI Intelligent Control Module The AI ​​intelligent control module is integrated into the temple control box of the transparent electronic lens. It uses an STM32F407 microcontroller with a main frequency of 168MHz, 1MB Flash and 192KB RAM, and supports Bluetooth 5.0 and Wi-Fi communication (Wi-Fi module model ESP8266) for data transmission with the multi-sensor fusion module and mobile interaction module.

[0076] This module has built-in firmware programs for K-means clustering and random forest regression algorithms. Model parameters obtained through offline training are stored in Flash memory, allowing for rapid algorithm invocation for data processing and parameter calculation. Algorithm processing latency is ≤50ms, ensuring real-time adjustment of control parameters.

[0077] (iv) Implementation of mobile terminal interaction module and doctor terminal management module The mobile interaction module is developed for both Android and iOS platforms, supporting Android 8.0 and above, and iOS 12.0 and above. The app interface includes five functional modules: User Center, Data Collection, Prevention and Control Status, Health Report, and Doctor Consultation. The User Center stores personal information and eye data; the Data Collection module supports manual input of axial length data, uploading of examination reports, and automatic collection of eye behavior data; the Prevention and Control Status module displays the current prevention and control mode, optical parameters, and scattering point morphology in real time; the Health Report module generates a weekly "Eye Health Report"; and the Doctor Consultation module supports text and video consultations.

[0078] The doctor-side management module adopts a B / S architecture, is developed based on the web, and supports access from both computers and tablets. The backend database uses MySQL to store user data, prevention and control parameters, health reports, and other information. The doctor-side interface includes four functional modules: user management, data viewing, parameter adjustment, and effect evaluation. The user management module manages patients; the data viewing module allows viewing users' eye data and eye behavior data; the parameter adjustment module supports manual adjustment of prevention and control parameters or the generation of parameter suggestions through AI-assisted design; and the effect evaluation module compares the user's axial length data at different times and generates an evaluation report.

[0079] Example 2: System Software and Algorithm Implementation This embodiment provides the system's software and algorithm implementation scheme, as detailed below: (I) Implementation of AI Intelligent Control Module Algorithm The K-means clustering algorithm is used to classify the types of myopia progression in users. The specific steps are as follows: (1) Data preprocessing: Collect the axial length growth data (y1, y2, ..., y6), average daily eye use time (t), and daily near-field eye use frequency (f, unit: times / hour) of users in the past 6 months. Normalize the data. The normalization formula is: x'=(x-x_min) / (x_max-x_min), where x is the original data, x_min is the minimum value of the data, and x_max is the maximum value of the data.

[0080] (2) Initialize cluster centers: Set the number of clusters k=3 (corresponding to slow, medium and fast progress types), and randomly select 3 samples as initial cluster centers C1, C2 and C3.

[0081] (3) Calculate the sample distance: Use Euclidean distance to calculate the distance between each sample and the three cluster centers.

[0082] (4) Update cluster centers: Assign each sample to the nearest cluster center to form 3 clusters, calculate the mean of each cluster, and use it as the new cluster center.

[0083] (5) Iterative convergence: Repeat steps (3)-(4) until the change in the cluster center is less than the threshold (0.001), the iteration ends, and three clusters are obtained, corresponding to slow, medium and fast progress users respectively.

[0084] The random forest regression algorithm is used to establish a mapping model between environmental data, physiological data, and prevention and control parameters. The specific steps are as follows: (1) Sample dataset construction: Collect sample data from 1,000 users of different ages and different myopia progression types. Each sample includes input features (light intensity L, eye distance D, pupil diameter P, head movement angle A) and output labels (optical zone diameter O, control zone density Density, contrast gray value Gray, coma coefficient Coma, red light transmittance R, blue light transmittance B).

[0085] (2) Data set partitioning: The sample dataset is divided into a training set and a test set in a ratio of 7:3. The training set is used for model training and the test set is used for model performance evaluation.

[0086] (3) Decision tree construction: 100 decision trees are constructed. The training samples of each decision tree are selected from the training set by bootstrap sampling. The splitting features of each decision tree are determined by randomly selecting k features. The splitting criterion adopts the minimization of mean square error.

[0087] (4) Model training: Each decision tree is trained independently without pruning. After training, the average of the prediction results of all decision trees is taken as the final prediction result.

[0088] (5) Model evaluation: The model performance is evaluated using the test set, and the mean absolute error (MAE) between the predicted and the true values ​​is calculated.

[0089] (II) Implementation of dynamic switching strategy for scattering points The dynamic switching strategy for scattering points is based on adaptive adjustment using sensor data. The specific implementation logic is as follows: High-interference mode switching logic: When the infrared distance sensor detects an eye distance ≤30cm for a duration ≥10 minutes, and the ambient light sensor detects a light intensity of 100-10000 lux, the system switches to high-interference mode. In this mode, the scattering point shape is selected as a combination of star and irregular polygon, the density is set to 600 points / mm², the arrangement is random, and the switching frequency is 2Hz.

[0090] Low-interference mode switching logic: When the ambient light sensor detects a light intensity ≥10000 lux, or the infrared distance sensor detects an eye distance ≥50cm, the system switches to low-interference mode. In this mode, the scattering point shape is selected as a combination of circles and ellipses, the density is set to 200 points / mm², the arrangement is a gradient distribution, and the switching frequency is 0.5Hz.

[0091] Dynamic eye-use mode switching logic: When the motion sensor detects a change in head movement angle ≥5° / s for a duration ≥3 seconds, the system switches to dynamic eye-use mode. In this mode, the diameter of the optical zone automatically increases by 0.5mm, the density of the control zone decreases by 100 points / mm², the scattering point shape is selected as circular, the arrangement is randomly distributed, and the switching frequency is 1Hz to avoid visual blurring caused by motion.

[0092] Example 3: Verification in a specific application scenario This embodiment uses a 12-year-old user with moderate myopia (300 degrees of myopia, axial length of 24.5 mm, and axial length increase of 0.3 mm in the past 6 months, belonging to the moderately progressive type) as an example to verify the practical application effect of the present invention: (a) User data entry and initialization Users enter their personal information (12-year-old male), eye examination data (myopia of 300 degrees, axial length of 24.5 mm, pupil diameter range of 3.5-6 mm), and myopia progression data (axial length increase of 0.3 mm in the past 6 months) through a mobile app. The app then uploads the data to the AI ​​intelligent control module. Doctors review the data through the doctor's management module and select an 11-12 year old moderate myopia template as the initial control parameters: initial optical zone diameter of 4.5 mm, control zone density of 400 zones / mm², contrast grayscale value of 140 levels, coma coefficient of 0.15 μm, red light transmittance of 78%, and blue light transmittance of 40%.

[0093] (II) Prevention and control processes in different scenarios Reading / writing scenario (indoors, 500 lux light intensity, 25cm viewing distance): The multi-sensor fusion module collects data in real time: 500 lux light intensity, 25cm viewing distance, 4mm pupil diameter, and head movement angle change ≤2° / s. After analyzing the data, the AI ​​intelligent control module determines that it is in reading / writing mode and the user is in intermediate-stage progression. Based on the random forest regression algorithm, it adjusts the control parameters: optical zone diameter 4mm (matching pupil diameter 4mm), control zone density 450 / mm², contrast grayscale value 135 levels, coma coefficient 0.18μm, red light transmittance 76%, and blue light transmittance 38%. The transparent electronic lens module executes according to the parameters, and the scattering points adopt a combination of star-shaped and irregular polygonal shapes, randomly distributed, with a switching frequency of 2Hz to achieve high interference control.

[0094] Outdoor scene (illuminance 50,000 lux, viewing distance 100cm): Data collected by the multi-sensor fusion module: illuminance 50,000 lux, viewing distance 100cm, pupil diameter 3.5mm, head movement angle change ≤3° / s. The AI ​​intelligent control module determines it is outdoor mode and adjusts the control parameters: optical zone diameter 3.5mm, control zone density 250 / mm², contrast grayscale value 160 levels, coma coefficient 0.1μm, red light transmittance 85%, blue light transmittance 45%. The scattering points adopt a combination of circles and ellipses, with a gradient distribution and a switching frequency of 0.5Hz to ensure visual comfort.

[0095] Dynamic activity scenario (walking, light intensity 20000 lux, variable viewing distance): Data collected by the multi-sensor fusion module: light intensity 20000 lux, viewing distance 50-80cm, head movement angle change ≥6° / s. The AI ​​intelligent control module determines it to be a dynamic eye use mode and adjusts the control parameters: optical zone diameter 4mm, control zone density 350 / mm², contrast grayscale value 150 levels, coma coefficient 0.12μm, red light transmittance 80%, blue light transmittance 42%. The scattering points are circular, randomly distributed, and the switching frequency is 1Hz to avoid visual interference caused by movement.

[0096] (III) Verification of Prevention and Control Effectiveness After using the system for 6 months, users underwent eye examinations. The results showed that the axial length of the eye was 24.6mm, an increase of only 0.1mm, which was much lower than the 0.3mm / 6 months before use. The myopia degree remained stable at 300 degrees with no increase. Users reported good visual comfort and no discomfort symptoms such as dizziness or blurred vision. The "Eye Health Report" showed that the time spent using the eyes at close range decreased by 20% compared to before, and the time spent on outdoor activities increased by 15%, demonstrating a significant prevention and control effect.

[0097] Example 4: Application of Collaborative Prevention and Control Model This example uses a 10-year-old rapidly progressive myopia patient (200 degrees of myopia, 24.0 mm axial length, and 0.5 mm axial length increase in the past 6 months) as an example to verify the application effect of the "optics + atropine" synergistic prevention and control mode: (I) Adjustment of Coordinated Prevention and Control Parameters Users input atropine usage information (concentration 0.01%, once daily before bedtime) via a mobile app. After receiving the information, the AI ​​intelligent control module adjusts the optical control parameters: the contrast grayscale value is increased by 20 levels (from 150 levels to 170 levels), the coma coefficient is reduced by 0.05μm (from 0.2μm to 0.15μm), and the control zone density is reduced by 100 particles / mm² (from 500 particles / mm² to 400 particles / mm²), to avoid visual discomfort caused by the superposition of "optics + drug".

[0098] (II) Prevention and Control Process and Effects The user used the system of this invention and 0.01% atropine eye drops simultaneously, wearing the system for 8 hours daily and taking the medication before bedtime. After 3 months, the examination results showed: axial length was 24.1 mm, an increase of 0.1 mm / 3 months, significantly lower than the previous 0.5 mm / 6 months (i.e., 0.25 mm / 3 months); myopia stabilized at 200 degrees; the user reported good visual comfort, with no obvious photophobia, blurred near vision, or other drug side effects, demonstrating that the synergistic prevention and control effect was significantly better than single prevention and control methods.

[0099] Example 5 like Figure 3 As shown, the left side is a lens partitioning diagram: dividing the lens into a "central zone" (a blank circle) and a "functional zone" (an area surrounded by micro-dots). The lens has a uniform refractive power distribution in both the central and functional zones, allowing for effective myopia correction; the thousands of micro-dots in the functional zone gently scatter light passing through it. The right side is a schematic diagram of light passing through the lens and acting on the eyeball: after passing through the lens, light, whether through the central or functional zone, can focus on the retina to meet visual needs; simultaneously, the light scattered by the functional zone slightly reduces retinal contrast, the core purpose of this design being to slow the progression of myopia.

[0100] like Figure 4 As shown, a schematic diagram of the myopia control lens related to this invention is given (corresponding to...). Figure 4 (left side) The lens body 1 includes a correction zone inside the lens body 1, a central optical correction zone 2 inside the correction zone, and a defocus control zone 3 surrounding the central optical correction zone 2. The defocus control zone 3 has multiple defocus points arranged in a spiral and uniform distribution. Dot matrix areas 4 are located in the gaps between the multiple defocus points. The lens body 1 is an enhanced version. In the enhanced version, the additional vertex power of the defocus control zone 3 increases from the inside out: +3.50D to +4.50D. The central optical correction zone 2 has a diameter of 8mm and uses positive spherical lenses with four diopter options: +0.00D, +0.37D, +0.50D, and +0.62D. The enhanced lens body 1 has 950 defocus points, each 1mm in diameter, covering a diameter of 57.5mm with a spacing of 0.737mm. The lens body 1 uses 0... The .12D precision gradient system manufacturing process improves the maximum tolerance accuracy to ±0.06D, which can make the vision clearer and more accurate, and the binocular vision more balanced.

[0101] The above description represents the preferred embodiments of the present invention. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A myopia control system based on the coordinated modulation of multiple optical signals, characterized in that, include: A transparent electronic lens module, comprising a high-transmittance transparent microLED display screen with an embedded lens, used to realize dynamic division of the optical zone and the control zone and pixel-level optical parameter adjustment; The multi-sensor fusion module integrates an ambient light sensor, an infrared distance sensor, a pupil-tracking camera, and a motion sensor to collect real-time data on light intensity, eye distance, pupil diameter, and head movement. The AI ​​intelligent control module is communicatively connected to the transparent electronic lens module and the multi-sensor fusion module. It is used to receive sensor data and user eye axis and eye behavior data, and to dynamically adjust the prevention and control parameters by clustering and analyzing the user's myopia progression type through machine learning algorithms. The mobile terminal interaction module is a mobile terminal APP with data collection, data transmission and display functions. It is used to collect users' axial length data and eye use behavior data, push prevention and control suggestions to users, and support interaction between users and doctors.

2. The myopia prevention and control system according to claim 1, characterized in that, The transparent microLED display screen is a flexible transparent display panel with a pixel density of ≥300PPI and a grayscale adjustment range of 0-255 levels for a single pixel. It supports independent pixel-level control. The optical zone is the central area of ​​the lens, and its diameter can be dynamically adjusted according to the pupil diameter, with an adjustment range of 3-8mm. The control zone is the annular area surrounding the optical zone, with a width of 2-15mm.

3. The myopia prevention and control system according to claim 1, characterized in that, The ambient light sensor of the multi-sensor fusion module has a light intensity range of 10-100,000 lux and a sampling frequency of 10 Hz; the infrared distance sensor has a ranging range of 10-100 cm; the pupil tracking camera has a frame rate of ≥30 fps; and the motion sensor is a combination of a six-axis gyroscope and an accelerometer with a sampling frequency of ≥50 Hz, used to detect the pitch, yaw, and roll angles of the head.

4. The myopia prevention and control system according to claim 1, characterized in that, The machine learning algorithms of the AI ​​intelligent control module include K-means clustering algorithm and random forest regression algorithm. The K-means clustering algorithm is used to cluster the user's myopia progression type based on the user's past axial length growth data, eye use duration distribution data, and near-field eye use frequency data. The random forest regression algorithm is used to establish a mapping model between environmental data, physiological data, and prevention and control parameters. The prevention and control parameters include optical zone diameter, prevention and control zone density, contrast gray value, higher-order aberration type and intensity, and red and blue light transmittance ratio.

5. The myopia prevention and control system according to claim 1, characterized in that, The optical signal coordinated modulation of the transparent electronic lens module specifically includes: Contrast signal control: By adjusting the pixel grayscale values ​​of the transparent microLED display, a low-contrast environment is simulated. The grayscale value adjustment range is 100-200 levels, corresponding to a contrast adjustment range of 0.3-0.

7. Advanced aberration control: Generates asymmetric coma aberrations with coma coefficients adjustable in the range of 0.05-0.3μm, achieving precise superposition of aberrations through pixel-level phase modulation; Color difference signal control: Dynamically adjust the transmittance of red and blue light. The transmittance of red light is adjustable from 70% to 90%, and the transmittance of blue light is adjustable from 30% to 60%. Red and blue light are controlled separately through independent filter pixel units.

6. The myopia prevention and control system according to claim 1, characterized in that, The scattering point morphology of the control zone includes circular, star-shaped, elliptical, short line, irregular polygon, and micropore-shaped.

7. A myopia control method based on the coordinated modulation of multiple optical signals, characterized in that, Includes the following steps: S1: The multi-sensor fusion module collects environmental and physiological data in real time, including light intensity, viewing distance, pupil diameter and head movement status; S2: The AI ​​intelligent control module receives the data collected in step S1, combines it with the user's axial length data and eye use behavior data uploaded by the mobile terminal interaction module, and uses machine learning algorithms to cluster and analyze the user's myopia progression type, which includes slow progression, moderate progression and rapid progression. S3: Based on the analysis results, the AI ​​intelligent control module automatically matches the preset basic prevention and control template, or calls the personalized setting template customized by the doctor and downloaded by the patient, and automatically switches the prevention and control mode. The prevention and control mode includes reading and writing mode, outdoor mode and dynamic eye use mode. S4: The transparent electronic lens module achieves coordinated control of contrast signal, higher-order aberration signal and chromatic aberration signal according to the control mode and the adjusted control parameters, and dynamically switches the shape and arrangement of scattering points in the control area. S5: The mobile interaction module receives control data from the AI ​​intelligent control module in real time and generates prevention and control suggestions.

8. The myopia prevention and control method according to claim 7, characterized in that, The basic prevention and control template in step S3 presets uniform basic prevention and control parameters: initial diameter of the optical zone 4.5mm, prevention and control zone density 400 / mm², contrast grayscale value 140 levels, coma coefficient 0.15μm, red light transmittance 78%, and blue light transmittance 40%. The personalized setting template allows doctors to customize adjustments based on their professional abilities and research data, combined with the user's individual eye characteristics, myopia progression type, and eye habits. The patient can download and apply the template through the mobile terminal interaction module to achieve personalized prevention and control parameter configuration.

9. The myopia prevention and control method according to claim 7, characterized in that, The dynamic switching of scattering points in the control area in step S4 also includes switching of combination strategies. The combination strategies include random distribution strategy, zonal distribution strategy and gradient distribution strategy. Among them, the random distribution strategy is to randomly arrange scattering points of different shapes according to a preset ratio, with circles accounting for 30%-50%, stars accounting for 20%-30%, and other shapes accounting for 20%-50%; the zonal distribution strategy is to use a combination of short lines and micropores in the control area corresponding to the nasal side of the retina, and a combination of stars and irregular polygons in the control area corresponding to the temporal side of the retina; the gradient distribution strategy is to increase the size of scattering points from 5μm to 50μm and the density from 100 points / mm² to 800 points / mm² from the edge of the optical area to the periphery of the control area.

10. The myopia prevention and control method according to claim 7, characterized in that, Step S4 implements the coordinated control of contrast signal, higher-order aberration signal, and chromatic aberration signal, specifically including the following coordinated execution logic: S41: First, the contrast signal modulation is used as the basic intervention layer. The AI ​​intelligent modulation module determines the initial modulation intensity of the contrast signal based on the eye distance data collected in step S1: when the eye distance is ≤40cm, the contrast signal is adjusted to the low contrast range to suppress high contrast stimulation of the retina; when the eye distance is >40cm, the contrast signal intensity is appropriately increased to balance the prevention and control effect and visual clarity. S42: Based on the contrast signal modulation, a higher-order aberration signal is superimposed as an enhanced intervention layer, and the type and intensity of the higher-order aberration signal are adapted according to the myopia progression type determined in step S2: for users with rapid progression, coma-type asymmetric aberrations are selected first and set to a higher intensity; for users with slow progression, low-intensity spherical aberrations are selected. S43: Using color difference signal modulation as an adaptation layer, the red and blue light transmittance ratio is dynamically adjusted based on the ambient light intensity data collected in step S1, and a pixel-level color difference control area is formed within the control zone. Local color difference modulation is achieved through colored scattered dots: when the ambient light intensity is ≤500 lux, the proportion of red light transmittance is increased to enhance the refractive development guidance effect, and a colored scattered dot array dominated by red can be formed in the control zone; when the ambient light intensity is >500 lux, the proportion of blue light transmittance is reduced to reduce the risk of light damage, and a scattered dot distribution dominated by blue-green mixed colors can be formed in the control zone; at the same time, it is ensured that the modulation direction of the color difference modulation signal is consistent with that of the contrast signal and higher-order aberration signal. S44: During the coordinated output of the three types of signals, monitor the dynamic changes in the pupil collected by the pupil tracking camera in real time. If the change in pupil diameter is greater than 1mm, adjust the coverage of the three types of signals in real time: reduce the effective area of ​​the contrast signal and the higher-order aberration signal to match the shrinking pupil, or expand the effective area of ​​the chromatic aberration signal to cover the enlarged pupil.

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