Spectral control axis adjusting method and system for assisting myopia prevention and control

Abstract

The invention discloses a spectrum control axis adjusting method and system for assisting myopia prevention and control, and relates to the field of biomedical engineering.The method comprises the steps that a user uploads personal information, meanwhile, current illumination data and eyeball movement data of the user are monitored and collected, and the personal information, the current illumination data and the eyeball movement data of the user are preprocessed; establishing a user spectrum model based on the preprocessed personal information and the current illumination data of the user, predicting the optimal spectrum combination of the user, adjusting the specific gravity combination of each wave band in the LED light source according to the prediction result, monitoring the actual spectrum entering the eyes in real time, and comparing the actual spectrum with the optimal spectrum combination of the user, adjusting the spectrum output of the LED light source according to the difference; by establishing the user spectrum model, the spectrum combination can be dynamically adjusted according to the real-time environment condition of the user, and it is ensured that the light condition most suitable for the user is provided. And the visual comfort of the user and the myopia prevention and control effect are obviously improved.

Description

Technical Field

[0001] The present invention relates to the field of biomedical engineering, and in particular to a spectral axis control adjustment method and system for assisting in myopia prevention and control. Background Art

[0002] In recent years, with the rapid development of information technology and biomedical engineering, the field of myopia prevention and control has undergone unprecedented changes. Traditional myopia prevention and control methods mainly focus on eyeglass correction, orthokeratology lenses, and medication. However, these methods often only alleviate symptoms or slow the progression of myopia, but do not fundamentally solve the problem. With the advancement of smart wearable devices and spectral modulation technology, people are beginning to explore new ways to prevent and control myopia by optimizing lighting conditions.

[0003] Existing spectral adjustment technologies and myopia prevention and control methods have several shortcomings. First, they cannot dynamically adjust the spectral combination based on the user's real-time eye patterns and ambient lighting conditions to ensure that the actual spectrum is always optimal. Second, support for personalized needs is limited. Different users have different physiological characteristics and eye habits, and current technology makes it difficult to provide customized spectral adjustment solutions based on the specific needs of different users. Summary of the Invention

[0004] In view of the above existing problems, the present invention is proposed.

[0005] Therefore, the present invention provides a spectral axis control adjustment method to assist in myopia prevention and control, which solves the problem of being unable to dynamically adjust the spectral combination according to the user's real-time eye usage pattern and ambient lighting conditions to ensure that the actual spectrum is always in the best state.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: In a first aspect, the present invention provides a spectral axis control adjustment method for assisting myopia prevention and control, which comprises: Users upload their personal information, and the system monitors and collects their current lighting data and eye movement data; Preprocess personal information, user's current lighting data, and eye movement data; A user spectrum model is established based on pre-processed personal information and the user's current lighting data to predict the user's optimal spectrum combination. The proportion combination of each band in the LED light source is adjusted according to the prediction result. Monitor the actual spectrum entering the eye in real time, compare it with the user's optimal spectrum combination, and adjust the spectral output of the LED light source based on the difference; Identify the user's current eye usage pattern based on eye movement data and dynamically adjust the spectral output of the LED light source; Regularly monitor the changes in the user's axial length and collect the user's subjective feelings and feedback information.

[0007] As a preferred solution of the spectral axis control adjustment method for assisting myopia prevention and control described in the present invention, wherein: the user uploads personal information, and simultaneously monitors and collects the user's current light data and eye movement data, specifically including the following steps: Users upload their personal axial length, age, gender and eye habits through the app; Monitor the user's current lighting data in real time through smart glasses, where the current lighting data includes illuminance and color temperature; The user's gaze position and eye movement speed are collected in real time through an eye tracker.

[0008] As a preferred solution of the spectral axis control adjustment method for assisting myopia prevention and control described in the present invention, the personal information, the user's current light data and the eye movement data are pre-processed, specifically including the following steps: All collected data were subjected to outlier detection, missing value filling and data standardization.

[0009] As a preferred solution of the spectrum axis control adjustment method for assisting myopia prevention and control described in the present invention, a user spectrum model is established based on pre-processed personal information and the user's current light data, the user's optimal spectrum combination is predicted, and the proportion combination of each band in the LED light source is adjusted according to the prediction result. Specifically, the following steps are included: Extract multi-dimensional features of personal information and user's current lighting data to form a multi-dimensional feature vector; Define time windows and time-dependent functions; Calculate the value of the time-dependent function of all features at each time point and combine it with the exponential decay function to obtain the time decay; In the time window, the feature time dependency function values ​​at different time points are integrated into the user feature representation, which is expressed as follows: ; in, represents user feature representation, represents a multidimensional feature vector, represents the time window, represents the attenuation factor, Indicates the The time dependence function of the feature, Indicates time, represents the number of features, represents differential elements; Initialize the number of spectral bands and spectral combination vector, and define the benefit function and cost function; Based on the user feature representation, the benefits and costs of each spectral band are calculated, and the total benefits and costs of all spectral bands are calculated; Traverse all spectral combination vectors and find the spectral combination that maximizes the net value. The expression is: ; in, represents the predicted optimal spectral combination, represents the number of spectral bands, represents the spectral combination vector, Indicates the The benefit function of the band, Indicates the The cost function for each band, Indicates user feature representation; Generate adjustment instructions based on the predicted optimal spectral combination; Based on the adjustment instructions, the brightness of each band in the LED light source is adjusted by the controller.

[0010] As a preferred solution of the spectrum axis control adjustment method for assisting myopia prevention and control described in the present invention, the actual spectrum entering the eye is monitored in real time and compared with the user's optimal spectrum combination, and the spectrum output of the LED light source is adjusted according to the difference, specifically including the following steps: The actual spectrum entering the eye is monitored in real time through the spectral sensor of smart glasses; The mean square error formula is used to calculate the difference between the actual spectrum and the optimal spectrum combination, which is expressed as: ; in, It represents the difference between the actual spectrum and the optimal spectrum combination. Indicates that the actual spectrum is The proportion of the band, No. The proportion of each band; A difference threshold is set. When the difference between the actual spectrum and the optimal spectrum combination is greater than the difference threshold, the spectral output of the LED light source needs to be adjusted.

[0011] As a preferred solution of the spectral axis control adjustment method for assisting myopia prevention and control described in the present invention, the method includes the following steps: identifying the user's current eye usage pattern based on eye movement data and dynamically adjusting the spectral output of the LED light source. Extract the features of eye movement data to form an eye feature vector; Use the classifier to classify the eye feature vector and identify the user's current eye usage pattern. The expression is: ; in, Indicates that given the eye feature vector The user is in eye mode The probability of represents the number of classifiers, Indicates the classifiers, Indicates the number of eye usage patterns; Defining spectrum adjustment rules based on the identified user's current eye usage pattern; Generate the corresponding spectral output of the LED light source based on the identified user's current eye usage pattern; According to the spectral output of the corresponding LED light source, the actual spectral output of the LED light source is adjusted.

[0012] As a preferred solution of the spectral axis control adjustment method for assisting myopia prevention and control described in the present invention, the following steps are specifically included: regularly monitoring the changes in the user's axial length and collecting the user's subjective feelings and feedback information. Collect user feedback on visual comfort and fatigue, and adjust user spectral model parameters based on user feedback; Use the built-in axial length measurement device to automatically measure the user's axial length and analyze the changing trend of axial length; Adjust the spectral adjustment strategy according to the changing trend of axial length.

[0013] In a second aspect, the present invention provides a spectral axis control adjustment system for assisting myopia prevention and control, comprising: Information collection module, where users upload their personal information and simultaneously monitor and collect the user's current lighting data and eye movement data; Preprocessing module, which preprocesses personal information, user's current lighting data and eye movement data; The prediction module builds a user spectrum model based on pre-processed personal information and the user's current lighting data, predicts the user's optimal spectrum combination, and adjusts the proportion combination of each band in the LED light source according to the prediction results; The adjustment module monitors the actual spectrum entering the eye in real time, compares it with the user's optimal spectrum combination, and adjusts the spectral output of the LED light source based on the difference; The spectrum adjustment module identifies the user's current eye usage pattern based on eye movement data and dynamically adjusts the spectral output of the LED light source; The feedback module regularly monitors the changes in the user's axial length and collects the user's subjective feelings and feedback information.

[0014] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program is executed by the processor, any step of the spectral axis control adjustment method for assisting myopia prevention and control as described in the first aspect of the present invention is implemented.

[0015] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program is executed by a processor, it implements any step of the spectral axis control adjustment method for assisting myopia prevention and control as described in the first aspect of the present invention.

[0016] The beneficial effects of the present invention are as follows: by establishing a user spectrum model, the spectrum combination can be dynamically adjusted according to the user's real-time environmental conditions to ensure that the most suitable lighting conditions are provided for the user. This intelligent adjustment method not only improves the accuracy and effectiveness of spectrum adjustment, but also significantly improves the user's visual comfort and myopia prevention and control effects. Secondly, by extracting the characteristics of eye movement data, the user's current eye use pattern is identified, and the corresponding spectrum adjustment rules are defined based on the identified eye use pattern, and the corresponding spectrum combination is generated, and then the spectrum is adjusted, which can provide the most suitable lighting conditions according to different eye use patterns. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 This is a flow chart of the spectral axis control adjustment method for assisting myopia prevention and control in Example 1.

[0019] Figure 2 Schematic diagram of spectral output in Example 1. DETAILED DESCRIPTION

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0021] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0022] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in one embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive of other embodiments.

[0023] Example 1, with reference to Figure 1 and Figure 2 , which is the first embodiment of the present invention, provides a spectral axis control adjustment method for assisting myopia prevention and control, comprising the following steps: S1. The user uploads personal information and monitors and collects the user's current lighting data and eye movement data.

[0024] The specific steps include: S1.1. Personal information uploaded through the app includes individual eye axial length, age, gender, and eye habits; Personal axial length is the axial length data obtained by the user through a medical institution, in millimeters.

[0025] Eye usage habits means asking users to select common eye usage scenarios, such as long-term reading, use of electronic devices, outdoor activities, etc., and fill in the average daily eye usage time (hours).

[0026] S1.2, using smart glasses equipped with ambient light sensors to monitor the user's current lighting conditions in real time, including illumination and color temperature parameters; The sensor automatically records the current environment's illuminance (unit: lux, lx) and color temperature (unit: Kelvin, K) every 5 minutes.

[0027] Illuminance refers to the luminous flux received per unit area, and color temperature refers to the color characteristics of the light source.

[0028] It is further explained that through the dual monitoring of contrast and color temperature, we can fully understand the lighting environment in which the user is located and provide a more accurate spectrum adjustment solution.

[0029] S1.3. A high-precision eye tracker is built into the smart glasses to collect the user's eye movement data in real time; The eye tracker collects data such as the user's gaze position and eye movement speed at a fixed frequency (such as 60 times per second) to ensure the real-time and accuracy of the data.

[0030] It is further explained that by analyzing the gaze point position and eye movement speed, the user's current eye usage mode (such as reading, working, resting, etc.) can be accurately identified, thereby providing targeted spectral adjustment solutions.

[0031] S2. Preprocess personal information, user's current lighting data, and eye movement data.

[0032] The specific steps include: Use statistical methods (such as the Z-score method) to detect and remove outliers. For example, for illuminance data, if the illuminance value of a certain record exceeds 3 standard deviations of the average of the past 10 records, it is considered an outlier and removed.

[0033] For missing data (such as when the user did not fill in certain information), the application uses interpolation to fill in the missing data.

[0034] All data are standardized to ensure that data from different sources have the same scale for subsequent modeling and analysis.

[0035] S3. Based on the pre-processed personal information and the user's current lighting data, a user spectrum model is established to predict the user's optimal spectrum combination, and the proportion combination of each band in the LED light source is adjusted according to the prediction result.

[0036] The specific steps include: S3.1. Extracting static and dynamic features of user personal information and user current lighting data; Through user input, static features are obtained from the built-in interactive interface of the smart glasses, including basic information such as the user's age and gender.

[0037] Dynamic characteristics include the changing trend of axial length, eye usage habits (such as reading time, time using electronic devices) and lighting environment (illuminance, color temperature).

[0038] Use statistical analysis to identify trends in axial length. Real-time eye movement data is monitored and combined with machine learning algorithms to identify users' eye usage patterns. These patterns are then used as visual habits.

[0039] The characteristics of the lighting environment are obtained through sensors.

[0040] Use feature concatenation to combine each feature into a multi-dimensional feature vector.

[0041] It is further explained that the multi-dimensional feature vector covers all relevant information of the user, ensuring the comprehensiveness and accuracy of subsequent analysis and prediction.

[0042] S3.2, in order to capture the changes in user behavior and environmental conditions, time windows and time-dependent functions are introduced; The time-dependent function describes how each feature changes over time. For example, illuminance and color temperature may change depending on the time of day.

[0043] The time window can be set to one day or one week to integrate feature changes over a period of time.

[0044] It is further explained that by introducing time windows and time-dependent functions, the dynamic changes of user behavior and environmental conditions can be captured, providing more flexible and accurate spectral adjustment.

[0045] An exponential decay function is introduced to highlight the importance of recent data.

[0046] In the time window, the characteristic time-dependent function values ​​at different time points are integrated to obtain the user feature representation, which is expressed as follows: ; in, represents user feature representation, represents a multidimensional feature vector, represents the time window, represents the attenuation factor, Indicates the The time dependence function of the feature, Indicates time, represents the number of features, Represents a differential element.

[0047] It is further explained that through integral operation, the user's feature performance over a period of time is comprehensively evaluated to provide a more comprehensive and stable feature representation, and the user feature representation summarizes the information of all relevant features, providing accurate basic data for subsequent spectral combination prediction.

[0048] S3.3. Initialize the number of spectral bands and spectral combination vector, and define the benefit function and cost function.

[0049] The benefit function measures the positive impact of a certain spectrum combination on user visual comfort and myopia prevention, while the cost function takes into account possible negative effects (such as blue light damage).

[0050] Furthermore, by defining benefit and cost functions, we can meticulously evaluate the effects of each spectral combination, ensuring the optimal solution is selected. Furthermore, the combination of benefit and cost functions can find the optimal balance between multiple objectives, avoiding the one-sided pursuit of a single indicator while ignoring other factors.

[0051] According to user characteristics , calculate the benefits and costs of each spectral band, and summarize the total benefits and costs of all bands, the expression is: ; ; It is further explained that by calculating the total benefit and total cost, the overall effect of different spectral combinations was comprehensively evaluated to ensure the selection of the most appropriate solution.

[0052] Traverse all possible spectral combination vectors and find the spectral combination that maximizes the net value. The expression is: ; in, represents the best predicted spectral combination, represents the number of spectral bands, represents the spectral combination vector, Indicates the The benefit function of the band, Indicates the The cost function for each band, Indicates user feature representation; Furthermore, by traversing all possible spectral combinations and finding a set of parameters that maximizes the net value, the spectral adjustment scheme is ensured to achieve the best results. Furthermore, mathematical optimization methods are utilized to complete the evaluation of a large number of combinations in a short period of time, improving computational efficiency and response speed.

[0053] S3.4. Optimal spectral combination based on prediction , the best spectrum combination The weight of each band in the image is converted into a corresponding brightness value, and specific adjustment instructions are generated based on the brightness value. These instructions include the brightness setting of each band.

[0054] PWM (Pulse Width Modulation) is a technique that controls average power by varying the duty cycle of an output signal. For LED light sources, PWM can precisely control the brightness of each wavelength by adjusting the duty cycle.

[0055] The brightness value is mapped to the duty cycle of the PWM controller, which drives the various bands in the LED light source according to the duty cycle. The controller controls the switching frequency and time of the LED according to the duty cycle of each band, thereby achieving precise brightness control.

[0056] Generate specific adjustment instructions to control the proportion of each band in the LED light source.

[0057] It is further explained that the brightness of the LED light source is adjusted in real time according to the prediction results to ensure that the spectrum adjustment is always in the optimal state, significantly improving visual comfort and myopia prevention and control effects.

[0058] S4. Monitor the actual spectrum entering the eye in real time, compare it with the user's optimal spectrum combination, and adjust the spectral output of the LED light source based on the difference.

[0059] The specific steps include: S4.1. The smart glasses use a high-precision spectral sensor built into the glasses to monitor the actual spectral distribution of light entering the user's eyes in real time. Spectral data is collected at a high frequency (e.g., 60 times per second) to ensure rapid response to changing lighting conditions. The data collected at each time point includes information on light intensity across different wavelengths, forming the actual spectrum.

[0060] It is further explained that high-frequency data collection ensures that changes in lighting conditions can be monitored in real time and responded to in a timely manner.

[0061] S4.2. Use the mean square error formula to quantify the difference between the actual spectrum and the optimal spectrum combination, which is expressed as: ; in, It represents the difference between the actual spectrum and the optimal spectrum combination. Indicates that the actual spectrum is The proportion of the band, No. The proportion of each band; It is further explained that the mean square error is a widely recognized evaluation indicator that ensures the consistency and reliability of the evaluation results and quantifies the spectral difference into a specific value, which facilitates subsequent comparison and decision-making.

[0062] S4.3. Set a difference threshold to determine whether the spectral output of the LED light source needs to be adjusted. When it is greater than this threshold, the spectrum adjustment mechanism is triggered, and the brightness of each band in the LED light source is adjusted through the controller to make the actual spectrum approach the optimal spectrum combination as quickly as possible.

[0063] For example, the difference threshold at this time is 0.03. If the difference is less than the threshold, it is considered that the current spectrum is close to the optimal state and there is no need to adjust the spectrum output of the LED light source immediately. If it is greater than the threshold, adjustments are made.

[0064] The difference threshold is customized according to the user's actual situation and specific scenario.

[0065] Furthermore, setting a difference threshold enables automated spectral adjustment, enabling timely response to spectral deviations. Furthermore, a reasonable threshold setting avoids frequent adjustments due to minor fluctuations, improving stability.

[0066] S5. Identify the user's current eye usage pattern based on eye movement data and dynamically adjust the spectral output of the LED light source.

[0067] The specific steps include: S5.1. Extract the gaze point position, eye movement speed, eye movement acceleration, and eye dwell time features of the eye movement data. All of these features together constitute an eye feature vector.

[0068] It is further explained that the eye feature vector covers a variety of eye features, provides rich information, and enhances recognition accuracy. In addition, different users have different eye habits and eye movement characteristics. The multi-dimensional feature vector can capture these differences and provide a basis for personalized services.

[0069] S5.2. Use multiple classifiers to classify eye feature vectors and identify the user's current eye usage mode (such as reading mode, outdoor mode, office mode, and leisure mode). The number of classifiers is It can be adjusted according to the needs. Each classifier calculates the probability that the user is in a certain eye usage mode under a given eye feature vector. Its expression is: ; in, Indicates that given the eye feature vector The user is in eye mode The probability of represents the number of classifiers, Indicates the classifiers, Indicates the number of eye usage patterns; Furthermore, the collaborative work of multiple classifiers can more accurately identify the user's current eye usage pattern, reducing the possibility of misjudgment. The classifiers are continuously optimized based on actual feedback to improve recognition accuracy and stability.

[0070] S5.3. Define corresponding spectrum adjustment rules based on the identified user eye usage patterns. For example, if it is identified that the user is reading, the proportion of blue light will be reduced and the proportion of red and green light will be increased to reduce eye fatigue. If it is identified that the user is performing fine work, the brightness and color temperature will be optimized to improve visual clarity.

[0071] It further explains that providing the most suitable lighting conditions according to different eye usage patterns significantly improves user experience and comfort, reduces eye strain, and further enhances the effectiveness of myopia prevention and control.

[0072] S5.4. Generate a specific spectral output combination of the LED light source according to the defined spectral adjustment rules. This combination includes specific brightness values ​​of each band, for example, , which respectively represent the brightness ratio of red light, green light and blue light.

[0073] It is further explained that the generated LED spectrum combination accurately reflects the needs of the current eye usage mode, ensuring the most suitable lighting conditions.

[0074] The controller adjusts the brightness of each wavelength in the LED light source to make the actual spectrum close to the generated spectral output combination of the LED light source as quickly as possible. The adjustment process is gradual to avoid sudden changes in the spectrum that may cause discomfort.

[0075] It is further explained that the gradual adjustment method ensures a smooth transition of spectrum changes and improves the user experience.

[0076] S6. Regularly monitor the changes in the user's axial length and collect the user's subjective feelings and feedback information.

[0077] The specific steps include: S6.1. Users can collect subjective feedback on their visual comfort and fatigue levels regularly (e.g., daily or weekly) through simple questionnaires.

[0078] Dynamically adjust model parameters and spectral adjustment strategies based on user feedback. For example, if multiple users report experiencing eye fatigue during a specific time period, the spectral composition during that time period will be re-evaluated, and brightness or color temperature will be adjusted to improve comfort.

[0079] It is further explained that by collecting users' subjective feedback, we can more accurately understand their actual needs and provide personalized spectrum adjustment solutions.

[0080] S6.2. Automatically measure the user's axial length regularly (e.g., monthly). The data from each measurement is recorded and compared with historical data to form a trend chart of axial length changes. Linear regression is used to analyze this data to identify trends in axial length changes (e.g., growth rate, fluctuations, etc.). Trend analysis results are not only used to evaluate the effectiveness of the current spectral adjustment strategy, but also provide a scientific basis for future adjustments. For example, if an accelerating trend in axial length is found, prevention and control measures will be strengthened and the spectral combination will be further optimized to slow the progression of myopia.

[0081] It is further explained that through regular measurements and trend analysis, the effectiveness of the spectrum adjustment strategy is scientifically evaluated to ensure the effectiveness of prevention and control measures.

[0082] The spectral adjustment strategy is dynamically adjusted based on the changing trend of axial length. For example, if axial length shows a slow growth trend, the current spectral combination will be maintained; if axial length increases rapidly, stronger prevention and control measures will be implemented, such as increasing blue light filtering and optimizing the color temperature and brightness ratio.

[0083] This further demonstrates that continuous adjustment and optimization can effectively prevent and control the progression of myopia. Furthermore, the entire process forms a closed loop, improving reliability and effectiveness.

[0084] This embodiment also provides a spectral axis control adjustment system for assisting in myopia prevention and control, including: Information collection module, where users upload their personal information and simultaneously monitor and collect the user's current lighting data and eye movement data; Preprocessing module, which preprocesses personal information, user's current lighting data and eye movement data; The prediction module builds a user spectrum model based on pre-processed personal information and the user's current lighting data, predicts the user's optimal spectrum combination, and adjusts the proportion combination of each band in the LED light source according to the prediction results; The adjustment module monitors the actual spectrum entering the eye in real time, compares it with the user's optimal spectrum combination, and adjusts the spectral output of the LED light source based on the difference; The spectrum adjustment module identifies the user's current eye usage pattern based on eye movement data and dynamically adjusts the spectral output of the LED light source; The feedback module regularly monitors the changes in the user's axial length and collects the user's subjective feelings and feedback information.

[0085] This embodiment also provides a computer device, which is suitable for the spectral axis control adjustment method for assisting myopia prevention and control, including: a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute computer-executable instructions to implement the spectral axis control adjustment method for assisting myopia prevention and control as proposed in the above embodiment.

[0086] The computer device may be a terminal, comprising a processor, memory, a communication interface, a display, and an input device connected via a system bus. The processor provides computing and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores an operating system and computer programs. The internal memory provides an environment for the operating system and computer programs stored in the non-volatile storage media. The communication interface of the computer device is used to communicate with external terminals via wired or wireless communication. Wireless communication may be achieved via Wi-Fi, a carrier network, NFC (near-field communication), or other technologies. The display of the computer device may be a liquid crystal display or an electronic ink display. The input device may be a touchscreen overlay on the display, buttons, a trackball, or a touchpad on the computer device housing, or an external keyboard, touchpad, or mouse.

[0087] This embodiment also provides a storage medium having a computer program stored thereon, which, when executed by a processor, implements the spectral axis control adjustment method for assisting myopia prevention and control proposed in the above embodiment; the storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0088] In summary, the present invention can dynamically adjust the spectrum combination according to the user's real-time environmental conditions by establishing a user spectrum model, ensuring that the most suitable lighting conditions for the user are provided. This intelligent adjustment method not only improves the accuracy and effectiveness of spectrum adjustment, but also significantly improves the user's visual comfort and myopia prevention and control effects. Secondly, by extracting the characteristics of eye movement data, the user's current eye usage pattern is identified, and the corresponding spectrum adjustment rules are defined based on the identified eye usage pattern, and the corresponding spectrum combination is generated, and then the spectrum is adjusted, which can provide the most suitable lighting conditions according to different eye usage patterns.

[0089] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A spectral axis control adjustment method for assisting myopia prevention and control, characterized by: include, Users upload their personal information, and the system monitors and collects their current lighting data and eye movement data; Preprocess personal information, user's current lighting data, and eye movement data; A user spectrum model is established based on pre-processed personal information and the user's current lighting data to predict the user's optimal spectrum combination. The proportion combination of each band in the LED light source is adjusted according to the prediction result. Monitor the actual spectrum entering the eye in real time, compare it with the user's optimal spectrum combination, and adjust the spectral output of the LED light source based on the difference; Identify the user's current eye usage pattern based on eye movement data and dynamically adjust the spectral output of the LED light source; Regularly monitor the changes in the user's axial length and collect the user's subjective feelings and feedback information.

2. The spectral axis control adjustment method for assisting myopia prevention and control according to claim 1, characterized in that: The user uploads personal information and monitors and collects the user's current lighting data and eye movement data. The specific steps include the following: Users upload their personal axial length, age, gender and eye habits through the app; Monitor the user's current lighting data in real time through smart glasses, where the current lighting data includes illuminance and color temperature; The user's gaze position and eye movement speed are collected in real time through an eye tracker.

3. The spectral axis control method for assisting myopia prevention and control according to claim 2, characterized in that: Preprocessing of personal information, user's current lighting data and eye movement data includes the following steps: All collected data were subjected to outlier detection, missing value filling and data standardization.

4. The spectral axis control adjustment method for assisting myopia prevention and control according to claim 3, characterized in that: Based on the pre-processed personal information and the user's current lighting data, a user spectrum model is established to predict the user's optimal spectrum combination, and the proportion combination of each band in the LED light source is adjusted according to the prediction result. The specific steps include the following: Extract multi-dimensional features of personal information and user's current lighting data to form a multi-dimensional feature vector; Define time windows and time-dependent functions; Calculate the value of the time-dependent function of all features at each time point and combine it with the exponential decay function to obtain the time decay; In the time window, the feature time dependency function values ​​at different time points are integrated into the user feature representation, which is expressed as follows: ； in, represents user feature representation, represents a multidimensional feature vector, represents the time window, represents the attenuation factor, Indicates the The time dependence function of the feature, Indicates time, represents the number of features, represents differential elements; Initialize the number of spectral bands and spectral combination vector, and define the benefit function and cost function; Based on the user feature representation, the benefits and costs of each spectral band are calculated, and the total benefits and costs of all spectral bands are calculated; Traverse all spectral combination vectors and find the spectral combination that maximizes the net value. The expression is: ； in, represents the predicted optimal spectral combination, represents the number of spectral bands, represents the spectral combination vector, Indicates the The benefit function of the band, Indicates the The cost function for each band, Indicates user feature representation; Generate adjustment instructions based on the predicted optimal spectral combination; Based on the adjustment instructions, the brightness of each band in the LED light source is adjusted by the controller.

5. The spectral axis control adjustment method for assisting myopia prevention and control according to claim 4, characterized in that: Monitor the actual spectrum entering the eye in real time and compare it with the user's optimal spectrum combination. Adjust the spectral output of the LED light source according to the difference. The specific steps include the following: The actual spectrum entering the eye is monitored in real time through the spectral sensor of smart glasses; The mean square error formula is used to calculate the difference between the actual spectrum and the optimal spectrum combination, which is expressed as: ； in, It represents the difference between the actual spectrum and the optimal spectrum combination. Indicates that the actual spectrum is The proportion of the band, Indicates the best spectral combination predicted in The proportion of each band; A difference threshold is set. When the difference between the actual spectrum and the optimal spectrum combination is greater than the difference threshold, the spectral output of the LED light source needs to be adjusted.

6. The spectral axis control method for assisting myopia prevention and control according to claim 5, characterized in that: Identify the user's current eye usage pattern based on eye movement data and dynamically adjust the spectral output of the LED light source. Specifically, the following steps are included: Extract the features of eye movement data to form an eye feature vector; Use the classifier to classify the eye feature vector and identify the user's current eye usage pattern. The expression is: ； in, Indicates that given the eye feature vector The user is in eye mode The probability of represents the number of classifiers, Indicates the classifiers, Indicates the number of eye usage patterns; Defining spectrum adjustment rules based on the identified user's current eye usage pattern; Generate the corresponding spectral output of the LED light source based on the identified user's current eye usage pattern; According to the spectral output of the corresponding LED light source, the actual spectral output of the LED light source is adjusted.

7. The spectral axis control method for assisting myopia prevention and control according to claim 6, characterized in that: Regularly monitor the changes in the user's axial length and collect the user's subjective feelings and feedback information, specifically including the following steps: Collect user feedback on visual comfort and fatigue, and adjust user spectral model parameters based on user feedback; Use the built-in axial length measurement device to automatically measure the user's axial length and analyze the changing trend of axial length; Adjust the spectral adjustment strategy according to the changing trend of axial length.

8. A spectral axis control adjustment system for assisting myopia prevention and control, based on the spectral axis control adjustment method for assisting myopia prevention and control according to any one of claims 1 to 7, characterized in that: include, Information collection module, where users upload their personal information and simultaneously monitor and collect the user's current lighting data and eye movement data; Preprocessing module, which preprocesses personal information, user's current lighting data and eye movement data; The prediction module builds a user spectrum model based on pre-processed personal information and the user's current lighting data, predicts the user's optimal spectrum combination, and adjusts the proportion combination of each band in the LED light source according to the prediction results; The adjustment module monitors the actual spectrum entering the eye in real time, compares it with the user's optimal spectrum combination, and adjusts the spectral output of the LED light source based on the difference; The spectrum adjustment module identifies the user's current eye usage pattern based on eye movement data and dynamically adjusts the spectral output of the LED light source; The feedback module regularly monitors the changes in the user's axial length and collects the user's subjective feelings and feedback information.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the spectral axis control adjustment method for assisting myopia prevention and control as described in any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the spectral axis control adjustment method for assisting myopia prevention and control as described in any one of claims 1 to 7 are implemented.

Images