Myopia prevention and control management system and method based on multi-source data

Abstract

The application discloses a myopia prevention and control management system and method based on multi-source data, and particularly relates to the technical field of myopia prevention and control, based on a user eye health condition index, an eye appearance abnormality index and a use condition evaluation index, a user risk coefficient is obtained through comprehensive analysis, and a passive interaction instruction is generated when the user risk coefficient exceeds a threshold value; the application obtains multi-source data about a myopia massage device by collecting user end data, device operating condition data and interaction data of the myopia massage device, obtains a running performance evaluation index and an interaction quality evaluation index of the myopia massage device through analysis of the multi-source data, analyzes a myopia prevention and control management coefficient of the myopia massage device based on the running performance evaluation index and the interaction quality evaluation index, and compares the obtained myopia prevention and control management coefficient with a preset value, thereby solving the problem that the performance abnormality of the myopia massage device during use cannot be found in time in the prior art.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of myopia prevention and control, more specifically, the present application relates to a myopia prevention and control management system and method based on multi-source data. BACKGROUND

[0002] Through scientific prevention and treatment means, the myopia prevention and control management system can effectively reduce the incidence and degree of myopia, protect visual health, and for individuals, maintain healthy vision can reduce the occurrence of visual diseases and visual impairment, and thus improve the quality of life and work efficiency. Myopia prevention and control can help reduce the social medical burden, as it can reduce the burden of medical services, including ophthalmic treatment, lens fitting and visual correction, etc.

[0003] The working principle of the eye massage device is mainly through physical means, combined with modern ophthalmology theory or traditional Chinese medicine theory, to properly massage and stimulate the eyes to relieve visual fatigue, prevent myopia, amblyopia and other eye problems. The eye massage device will use pulse magnetic field and acupoint massage to act on each important acupoint around the eyes, stimulate and exercise the cone cells and optic nerve to promote metabolism, relieve eye fatigue and restore ciliary muscle elasticity. Specifically, these devices will use air pressure, microcomputer chips, far infrared heat compress, etc. to heat the eyes at a constant temperature, and through vibration massage and acupoint stimulation to relax the eyes and relieve fatigue; according to traditional Chinese medicine theory, the eye massage device will use meridian theory to stimulate the acupoints around the eyes to promote blood circulation and relieve eye fatigue.

[0004] In general, the eye massage device is a physical therapy device that can relieve eye fatigue and prevent eye problems. When using, you need to choose the appropriate massage method and intensity according to your individual situation to achieve the best massage effect.

[0005] However, the myopia prevention and control management system also has some shortcomings, the performance of the myopia massage device changes over time when in use, resulting in a decline in user experience; when the user is not suitable for massage, it cannot be detected in time; the interaction between the device and the user is abnormal, resulting in poor user experience. SUMMARY

[0006] In order to overcome the above-mentioned defects of the prior art, the present application provides a myopia prevention and control management system and method based on multi-source data, based on the user's eye health index, eye appearance abnormality index and use condition evaluation index, comprehensive analysis to obtain the user risk coefficient, when the user risk coefficient exceeds the threshold, passive interaction instruction is generated, the passive interaction instruction includes the instruction of stopping massage, reducing massage intensity and adjusting massage temperature, to solve the problems raised in the above background art.

[0007] To achieve the above object, the present application provides the following technical scheme: a myopia prevention and control management system based on multi-source data, comprising:

[0008] A data acquisition module is configured to acquire operation condition data of the myopia massage device, user condition data, and operation condition data of the user and the myopia massage device in an interactive condition, and transmit the acquired data to a data analysis module; the data analysis module comprises a device operation condition analysis module, a user condition analysis module, and a device interactive performance analysis module;

[0009] The device operation condition analysis module is configured to analyze the operation condition data of the myopia massage device in a non-interactive condition, acquire an operation performance evaluation index of the myopia massage device, and transmit the analysis result to the user condition analysis module and a monitoring and early warning module;

[0010] The user condition analysis module is configured to acquire a user eye health condition index by analyzing the user condition data, acquire a use condition evaluation index by analyzing the use condition, obtain a user risk coefficient based on the user eye health condition index, an eye appearance abnormality index, and the use condition evaluation index, generate a passive interaction instruction when the user risk coefficient exceeds a threshold value, and transmit the user risk coefficient to the monitoring and early warning module; the passive interaction instruction comprises a stop massage instruction, a massage intensity reduction instruction, and a massage temperature adjustment instruction.

[0011] The device interactive performance analysis module is configured to analyze the operation condition data of the myopia massage device in an interactive condition, acquire an interactive quality evaluation index of the myopia massage device, and transmit the analysis result to the monitoring and early warning module; the interactive condition comprises active interaction and passive interaction.

[0012] The monitoring and early warning module is configured to monitor the operation performance evaluation index of the myopia massage device, the user risk coefficient, and the interactive quality evaluation index of the myopia massage device.

[0013] The comprehensive quality evaluation module is configured to obtain a myopia prevention and control management coefficient based on the acquired operation performance evaluation index and the interactive quality evaluation index.

[0014] Preferably, the data acquisition module comprises a device operation condition acquisition unit, a user condition acquisition unit, and a device interaction information acquisition unit. The device operation condition acquisition unit is configured to acquire device operation information, including pulse current information, hot compress area, hot compress temperature, interruption times, and interruption time of the device. The user condition acquisition unit is configured to acquire user condition information, including ophthalmic examination data and vision screening data of a medical institution, and self-reported data of an individual. The device interaction information acquisition unit is configured to acquire interaction information between the device and the user, including active interaction information and passive interaction information. The active interaction information includes a time when the user issues an interaction instruction, a time when the device executes the active interaction instruction, and an active interaction execution accuracy parameter. The passive interaction information includes a generation time of a passive interaction instruction, a time when the device executes the passive interaction instruction, and a passive interaction execution accuracy parameter.

[0015] Preferably, the running performance evaluation index is obtained by wearing the myopia massage device on a dummy head equipped with a sensor, testing, and acquiring running parameters of the myopia massage device, the running parameters at least including hot compress area, hot compress temperature, pulse current function, interruption time, and interruption times of the myopia massage device. Pulse current control quality parameters, hot compress function control quality parameters, and running stability parameters are obtained by analyzing the acquired data. The running performance evaluation index is obtained by joint analysis based on the pulse current control quality parameters, the hot compress function control quality parameters, and the running stability parameters.

[0016] Preferably, the pulse current control quality parameter is obtained by obtaining a pulse current function, which is a curve of the change of the pulse current with time, and denoted as md=f(t), where md represents the intensity of the pulse current, and f(t) represents the pulse current function. The pulse current control quality parameter dk is calculated by the formula where dk represents the pulse current control quality parameter, where md represents the preset pulse current function, t1 represents the time when the pulse current starts, and t2 represents the time when the pulse current ends. The hot compress function control quality parameter is obtained by obtaining an effective coverage area of the infrared hot compress and a design coverage area, and obtaining an actual temperature and a set temperature of the infrared hot compress. The hot compress function control quality parameter rk is calculated by the formula where fm represents the effective coverage area of the infrared hot compress, sm represents the design coverage area, sw represents the actual temperature value, and dw represents the set temperature value. The running stability parameter yw is obtained by obtaining the interruption times and interruption time of the myopia massage device in a unit running time, and the formula is where dt represents the set time length, gc represents the interruption times in the time dt, and gt represents the interruption time in the time dt.

[0017] Preferably, the running performance evaluation index is calculated by the formula , wherein Xz represents the running performance evaluation index, dk represents the pulse current control quality parameter, rk represents the hot compress function control quality parameter, yw represents the running stability parameter, a represents the influence factor of the hot compress function, b represents the influence factor of the pulse current control quality, g represents the influence factor of the running failure, and a+b+g=1.0, 0

[0018] Preferably, the user risk coefficient is obtained by , wherein Wy represents the eye appearance abnormality index, the eye appearance abnormality index is obtained by: obtaining a high-definition picture of the eye, inputting the trained convolutional neural network, and outputting an eye appearance abnormality parameter; obtaining an eye appearance feature parameter through the convolutional neural network, and obtaining the eye appearance parameter of the eye appearance abnormality index by the formula , wherein y i represents the i-th eye feature vector, k i represents the weight coefficient corresponding to the i-th eye feature vector; wherein YJ represents the user eye health status index, satisfying the formula , wherein yy represents the user eye pressure, sh represents the user eye retina thickness, jh represents the user lens thickness, and sv represents the user vision degree growth speed; Sp represents the use condition evaluation index, satisfying the formula , wherein md 均 represents the average intensity of the massage pulse current, at represents the massage time, wd represents the massage temperature, and am represents the coverage area of the massage.

[0019] Preferably, the interaction quality evaluation index is obtained by: obtaining the active interaction execution speed zv1, the passive interaction execution speed zv2, the active interaction execution accuracy parameter zx1, and the passive interaction execution accuracy parameter zx2, and the formula The interaction quality evaluation index is obtained, wherein f1 represents a weight factor of active interaction, f2 represents a weight factor of passive interaction, and f1+f2=1.0, w1 represents an influence factor of interaction execution speed, w2 represents an influence factor of interaction accuracy parameter, and w1+w2=1.0; wherein the active interaction execution speed is obtained in the following manner: the time of user input adjustment instruction is obtained, the time of device execution instruction is obtained, the execution speed parameter is obtained by dividing the time of device execution instruction by the time of user input adjustment instruction, and the execution speed parameter is obtained by averaging multiple values; the passive interaction execution speed is obtained in the following manner: the generation time of passive adjustment instruction is obtained, the time of device execution instruction is obtained, the execution speed parameter is obtained by dividing the generation time of passive adjustment instruction by the time of user input adjustment instruction, and the execution speed parameter is obtained by averaging multiple values; and the execution accuracy parameter is obtained in the following manner: the result of device execution instruction is compared with a preset result, whether the execution is accurate is determined, multiple execution results are counted, and the active interaction execution accuracy parameter and the passive interaction execution accuracy parameter are obtained.

[0020] Preferably, the monitoring and early warning module comprises a running performance monitoring and early warning unit, an interaction performance monitoring and early warning unit, and a user condition monitoring and early warning unit. The running performance monitoring and early warning unit is used to monitor the running performance evaluation index of the myopia massage device. When the running performance evaluation index exceeds a preset value A, it indicates that the myopia massage device is running abnormally, and an abnormal running alarm of the myopia massage device is sent to the manager or the user. When the running performance evaluation index does not exceed the preset value A, it indicates that the myopia massage device is running normally and no measures need to be taken. The interaction performance monitoring and early warning unit is used to monitor the interaction quality evaluation index of the myopia massage device. When the interaction quality evaluation index exceeds a preset value B, it indicates that the interaction performance of the myopia massage device is abnormal, and an alarm reminding of improving the interaction performance is sent to the manager. When the interaction quality evaluation index does not exceed the preset value B, it indicates that the interaction performance of the myopia massage device is normal. The user condition monitoring and early warning unit is used to monitor the eye health condition of the user. When the user risk coefficient exceeds a preset value C, the user is warned to pay attention to eye health and seek medical treatment in time, and the user is prompted to reduce the pulse current intensity of myopia massage, pause the pulse current intensity of myopia massage, and shorten the myopia massage time.

[0021] Preferably, the numerical values of the preset value A, the preset value B, and the preset value C are based on the experience values set by the manager according to actual situations.

[0022] Preferably, the comprehensive quality evaluation module obtains the myopia prevention and control management coefficient based on the running performance evaluation index and the interaction quality evaluation index, and the myopia prevention and control management coefficient satisfies the formula Wherein Fg represents the myopia prevention and control management coefficient, Xz represents the operation performance evaluation index, and JP represents the interaction quality evaluation index, when Fg exceeds the preset value D, it indicates that the myopia prevention and control effect of the myopia massage equipment is abnormal, prompting the management personnel to maintain the myopia massage equipment, and prompting the user to replace the equipment.

[0023] To achieve the above object, the present application provides the following technical scheme: a myopia prevention and control management method based on multi-source data, comprising the following steps:

[0024] Collecting the operation condition data of the myopia massage equipment, the user condition data, and the operation condition data of the user and the myopia massage equipment in the interaction condition;

[0025] Analyzing the operation condition data of the myopia massage equipment in the non-interaction condition to obtain the operation performance evaluation index of the myopia massage equipment;

[0026] Analyzing the operation condition data of the myopia massage equipment in the interaction condition, the interaction condition including active interaction and passive interaction, to obtain the interaction quality evaluation index of the myopia massage equipment;

[0027] Based on the obtained operation performance evaluation index and interaction quality evaluation index, the myopia prevention and control management coefficient is obtained through comprehensive analysis;

[0028] Based on the relationship between the myopia prevention and control management coefficient and the preset myopia prevention and control management coefficient, corresponding measures are taken.

[0029] Preferably, compared with the preset myopia prevention and control management coefficient, if Fg exceeds the preset value D, it indicates that the myopia prevention and control effect of the myopia massage equipment is abnormal, prompting the management personnel to maintain the myopia massage equipment, and prompting the user to replace the equipment; if Fg does not exceed the preset value D, it indicates that the myopia prevention and control effect of the myopia massage equipment is normal, and no corresponding measures need to be taken.

[0030] The technical effects and advantages of the present application are as follows:

[0031] (1) The system and method of the present application are applied to the myopia massage equipment, and the myopia prevention and control management is carried out around the myopia massage equipment. Through analysis and judgment, the user experience is improved, improper operation is avoided to affect the eye health of the user, and the vision degree of the user is not reduced. The present application collects the user end data, equipment operation condition data and interaction data of the myopia massage equipment to obtain multi-source data about the myopia massage equipment. Through analysis of the multi-source data, the operation performance evaluation index and the interaction quality evaluation index of the myopia massage equipment are obtained. Based on the operation performance evaluation index and the interaction quality evaluation index, the myopia prevention and control management coefficient of the myopia massage equipment is obtained. The obtained myopia prevention and control management coefficient is compared with the preset value, and the management personnel takes corresponding measures based on the comparison result. The problem that the performance abnormality of the myopia massage equipment during use cannot be found in time in the prior art is solved.

[0032] (2) The application obtains a user eye health condition index by analyzing user condition data, obtains a use condition evaluation index by analyzing use condition, and obtains a user risk coefficient by comprehensive analysis based on the user eye health condition index, the eye appearance abnormality index and the use condition evaluation index, generates a passive interaction instruction when the user risk coefficient exceeds a threshold value, and the passive interaction instruction includes instructions of stopping massage, reducing massage intensity and adjusting massage temperature; the passive interaction is beneficial to guarantee the eye health of the user, improve the user experience and avoid improper operation affecting the eye health of the user; and the problems that the interaction between the myopia massage device and the user cannot be found abnormally in time and the user exists in an unsuitable massage condition in the prior art are solved. BRIEF DESCRIPTION OF DRAWINGS

[0033] Figure 1 It is a whole structure block diagram of the myopia prevention and control management system.

[0034] Figure 2 It is a structure block diagram of the monitoring and early warning module of the system.

[0035] Figure 3 It is a flow chart of the myopia prevention and control management method. DETAILED DESCRIPTION

[0036] Exemplary embodiments of the present disclosure will be described more fully hereinafter with reference to the accompanying drawings. While example embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure can be more thoroughly understood, and so that the scope of the present disclosure can be completely conveyed to those skilled in the art.

[0037] The following description of at least one example embodiment is merely illustrative in nature and is in no way limiting to the scope of the application or its applications or uses.

[0038] Techniques, methods, and devices known to those of ordinary skill in the relevant art can not be discussed in detail herein, but should be considered as part of the specification, where appropriate.

[0039] The computer system / server can be described in the general context of computer system-executable instructions, such as program modules, being executed by a computer system. Generally, program modules can include routines, programs, objects, components, logic, data structures, and so on that perform particular tasks or implement particular abstract data types. Computer system / server can operate in a distributed cloud computing environment where tasks are performed by remote processing devices that are linked through a communications network. In a distributed cloud computing environment, program modules can be located in local or remote computer system storage media including memory storage devices.

[0040] The application provides a myopia prevention and control management system based on multi-source data, as shown in Figure 1 The application provides a myopia prevention and control management system based on multi-source data, as shown in

[0041] The data acquisition module is used for acquiring operation condition data of the myopia massage device, user condition data, and operation condition data of the user and the myopia massage device in an interaction condition, and transmitting the acquired data to the data analysis module; the data analysis module comprises an equipment operation condition analysis module, a user condition analysis module and a device interaction performance analysis module.

[0042] The equipment operation condition analysis module is used for analyzing the operation condition data of the myopia massage device in a non-interaction condition, acquiring an operation performance evaluation index of the myopia massage device, and transmitting the analysis result to the user condition analysis module and the monitoring and early warning module.

[0043] The user condition analysis module acquires a user eye health condition index by analyzing the user condition data, acquires a use condition evaluation index by analyzing the use condition, comprehensively analyzes the user risk coefficient based on the user eye health condition index, an eye appearance abnormality index and the use condition evaluation index, generates a passive interaction instruction when the user risk coefficient exceeds a threshold value, the passive interaction instruction comprises instructions of stopping massage, reducing massage intensity and adjusting massage temperature, and transmits the user risk coefficient to the monitoring and early warning module.

[0044] The device interaction performance analysis module is used for analyzing the operation condition data of the myopia massage device in an interaction condition, acquiring an interaction quality evaluation index of the myopia massage device, and transmitting the analysis result to the monitoring and early warning module.

[0045] The monitoring and early warning module is used for monitoring the operation performance evaluation index of the myopia massage device, the user risk coefficient and the interaction quality evaluation index of the myopia massage device.

[0046] The comprehensive quality evaluation module comprehensively analyzes a myopia prevention and control management coefficient based on the acquired operation performance evaluation index and the interaction quality evaluation index.

[0047] The data acquisition module is connected with the device operation condition analysis module, the user condition analysis module and the device interaction performance analysis module; the device operation condition analysis module, the user condition analysis module and the device interaction performance analysis module are connected with the monitoring and early warning module; the device operation condition analysis module and the device interaction performance analysis module are connected with the comprehensive quality evaluation module.

[0048] In the embodiment of the present application, it needs to be explained that the data acquisition module includes a device operation condition acquisition unit, a user condition acquisition unit and a device interaction information acquisition unit, the device operation condition acquisition unit is used for acquiring device operation information, including pulse current information, hot compress area, hot compress temperature, running interruption times and interruption time of the device; the user condition acquisition unit is used for acquiring user condition information, the user condition information includes ophthalmic examination data, vision screening data of the medical institution and self-report data of the individual; the device interaction information acquisition unit is used for acquiring interaction information between the device and the user, including active interaction information and passive interaction information, the active interaction information includes the time of the user issuing an interaction instruction, the time of the device executing the active interaction instruction and the active interaction execution accuracy parameter; the passive interaction information includes the generation time of the passive interaction instruction, the time of the device executing the passive interaction instruction and the passive interaction execution accuracy parameter.

[0049] It is explained that when not interacting with the user, the myopia massage device operates according to the established massage mode, at this time, the myopia massage device at least includes a massage function and a hot compress function, that is, the myopia massage device operates according to the set mode, by wearing the myopia massage device to the dummy head equipped with sensors for testing, the operation parameters of the myopia massage device are collected, and the operation parameters at least include the hot compress area, the hot compress temperature, the pulse current function, the interruption time and the interruption times of the myopia massage device.

[0050] In the embodiment of the present application, it needs to be explained that the running performance evaluation index is obtained in the following manner: wearing the myopia massage device to the dummy head equipped with sensors for testing, collecting the operation parameters of the myopia massage device, and the operation parameters at least include the hot compress area, the hot compress temperature, the pulse current function, the interruption time and the interruption times of the myopia massage device; analyzing the collected data to obtain the pulse current control quality parameter, the hot compress function control quality parameter and the running stability parameter; based on the pulse current control quality parameter, the hot compress function control quality parameter and the running stability parameter, joint analysis is performed to obtain the running performance evaluation index.

[0051] In the embodiment of the present application, it needs to be explained that the pulse current control quality parameter is obtained in the following manner: obtaining the pulse current function refers to the curve of the change of the pulse current with time, the pulse current function is denoted as md=f(t), md represents the intensity of the pulse current, f(t) represents the pulse current function, and the pulse current control quality parameter is obtained by the formula The pulse current control quality parameter dk is calculated, wherein dk represents the pulse current control quality parameter, The preset pulse current function is represented, t1 represents the time when the pulse current starts, and t2 represents the time when the pulse current ends; the acquisition method of the hot compress function control quality parameter is as follows: the infrared hot compress effective coverage area and the design coverage area are acquired, the actual temperature and the set temperature of the infrared hot compress are acquired, and the hot compress function control quality parameter rk is calculated through the formula The hot compress function control quality parameter rk is calculated, wherein fm represents the infrared hot compress effective coverage area, sm represents the design coverage area, sw represents the actual temperature value, and dw represents the set temperature value; the acquisition method of the running stability parameter is as follows: the interruption times and interruption time of the myopia massage equipment in a unit running time are acquired, and the running stability parameter yw is calculated through the formula The running stability parameter yw is acquired, dt represents the set time length, gc represents the interruption times in the time dt, and gt represents the interruption time in the time dt.

[0052] In the embodiment of the present application, it is explained that the running performance evaluation index Xz is calculated through the formula The running performance evaluation index Xz is calculated, wherein Xz represents the running performance evaluation index, dk represents the pulse current control quality parameter, rk represents the hot compress function control quality parameter, yw represents the running stability parameter, a represents the influence factor of the hot compress function, β represents the influence factor of the pulse current control quality, γ represents the influence factor of the running fault, and a+β+γ=1.0, 0

[0053] In the embodiment of the present application, it is explained that the acquisition method of the user risk coefficient is as follows: The eye appearance abnormality index is acquired, wherein Wy represents the eye appearance abnormality index, the acquisition method of the eye appearance abnormality index is as follows: the high-definition picture of the eye is acquired, the trained convolutional neural network is input, and the eye appearance abnormality parameter is output; the eye appearance feature parameter is acquired through the convolutional neural network, and the eye appearance abnormality index of the eye appearance parameter is calculated through the formula The eye appearance abnormality index of the eye appearance parameter is acquired, wherein y i The i-th eye feature vector is represented, k i The weight coefficient corresponding to the i-th eye feature vector is represented; wherein YJ represents the user eye health condition index, and the formula is satisfied The user eye health condition index YJ is calculated, wherein yy represents the user eye pressure, sh represents the user eye retina thickness, jh represents the user lens thickness, and sv represents the user vision degree growth speed; Sp represents the use condition evaluation index, and the formula is satisfied The use condition evaluation index Sp is calculated, wherein md 均The average intensity of the massage pulse current, the massage time at, the massage temperature wd, and the coverage area of the massage am are represented.

[0054] The training method of the convolutional neural network model is explained as follows:

[0055] The eye image is identified by an artificial person, and an eye feature vector is labeled. The eye image with the labeled feature vector is transmitted to the convolutional neural network model, and the training is completed through the two processes of forward propagation and back propagation. In the forward propagation process, the input data passes through the convolutional layer, the pooling layer and the full connection layer, and finally the output of the network is obtained. In the back propagation process, the error between the network output and the real feature vector is calculated, and the gradient descent algorithm is used to update the parameters in the network, thereby optimizing the performance of the neural network.

[0056] The present application provides a passive instruction generation method, which obtains a user risk coefficient, generates passive instructions according to the user risk coefficient, and generates a close myopia massage device instruction, a reduce massage duration instruction of the myopia massage device, and a reduce pulse current intensity instruction of the massage when the user risk coefficient exceeds a preset value.

[0057] The myopia massage device needs to interact with the user in real time in actual use, and the user's requirements are met through real-time interaction to avoid causing harm to the user. The interaction between the myopia massage device and the user can be divided into active interaction and passive interaction according to the user's requirements. The active interaction refers to the user actively setting the pulse current intensity of the massage, the hot compress temperature, the massage duration, and the massage mode. The passive interaction refers to the myopia massage device taking corresponding measures through analysis and judgment based on the monitoring of the user, and finally acting on the user.

[0058] In the active interaction process, the interaction of the myopia massage device with the user is fed back in time, which helps to improve the user experience. In the passive interaction process, the device takes corresponding measures based on the user's condition, and when it is judged that the appearance condition of the user is not suitable for massage, the massage and hot compress functions are turned off in time. The scenarios in which the user is not suitable to continue using the myopia massage device include: abnormal development of the user's vision, rapid decline of the user's vision, abnormality of the user's eyes, and long-time use of the user.

[0059] In the embodiment of the present application, the method for obtaining the interaction quality evaluation index is as follows: obtaining the active interaction execution speed zv1, the passive interaction execution speed zv2, the active interaction execution accuracy parameter zx1, and the passive interaction execution accuracy parameter zx2, and calculating the interaction quality evaluation index through the formula The interaction quality evaluation index is obtained, wherein f1 represents a weight factor of active interaction, f2 represents a weight factor of passive interaction, and f1+f2=1.0, w1 represents an influence factor of interaction execution speed, w2 represents an influence factor of interaction accuracy parameter, and w1+w2=1.0; wherein the active interaction execution speed is obtained in the following manner: the time of inputting the adjustment instruction by the user, the time of executing the instruction by the device, the execution speed parameter is obtained by dividing the time of executing the instruction by the device by the time of inputting the adjustment instruction by the user, and the execution speed parameter is obtained by averaging multiple values; the passive interaction execution speed is obtained in the following manner: the generation time of the passive adjustment instruction, the time of executing the instruction by the device, the execution speed parameter is obtained by dividing the generation time of the passive adjustment instruction by the time of inputting the adjustment instruction by the user, and the execution speed parameter is obtained by averaging multiple values; the execution accuracy parameter is obtained in the following manner: the result of executing the instruction by the device is compared with a preset result, whether the execution is accurate is judged, the execution result is counted multiple times, and the active interaction execution accuracy parameter and the passive interaction execution accuracy parameter are obtained.

[0060] As shown in Figure 2 The monitoring and early warning module includes a running performance monitoring and early warning unit, an interaction performance monitoring and early warning unit, and a user condition monitoring and early warning unit. The running performance monitoring and early warning unit is used for monitoring the running performance evaluation index of the myopia massage device. When the running performance evaluation index exceeds a preset value A, it indicates that the myopia massage device is running abnormally, and an abnormal running alarm of the myopia massage device is sent to the manager or the user. When the running performance evaluation index does not exceed the preset value A, it indicates that the myopia massage device is running normally and no measures need to be taken. The interaction performance monitoring and early warning unit is used for monitoring the interaction quality evaluation index of the myopia massage device. When the interaction quality evaluation index exceeds a preset value B, it indicates that the interaction performance of the myopia massage device is abnormal, and an alarm reminding of improving the interaction performance is sent to the manager. When the interaction quality evaluation index does not exceed the preset value B, it indicates that the interaction performance of the myopia massage device is normal. The user condition monitoring and early warning unit is used for monitoring the eye health condition of the user. When the user risk coefficient exceeds a preset value C, an early warning is sent to the user, prompting the user to pay attention to eye health and go to a doctor in time, prompting the user to reduce the myopia massage, to suspend the pulse current intensity of the myopia massage, and to shorten the myopia massage time.

[0061] In the embodiments of the present application, it needs to be explained that the values of the preset value A, the preset value B, the preset value C, and the preset value D are based on the experience values set by the manager according to the actual situation.

[0062] In the embodiments of the present application, it needs to be explained that the myopia prevention and control management coefficient is obtained by the comprehensive quality evaluation module based on the comprehensive analysis of the running performance evaluation index and the interaction quality evaluation index, and the myopia prevention and control management coefficient satisfies the formula Wherein Fg represents a myopia prevention and control management coefficient, Xz represents an operation performance evaluation index, and JP represents an interaction quality evaluation index, when Fg exceeds a preset value D, it indicates that the myopia prevention and control effect of the myopia massage equipment is abnormal, prompting the management personnel to maintain the myopia massage equipment and prompting the user to replace the equipment.

[0063] To achieve the above-mentioned purpose as shown in Figure 3 The present application provides the following technical solutions: a myopia prevention and control management method based on multi-source data, comprising the following steps:

[0064] Collecting operation condition data of the myopia massage equipment, user condition data, and operation condition data of the user and the myopia massage equipment in an interaction condition;

[0065] Analyzing the operation condition data of the myopia massage equipment in a non-interaction condition to obtain an operation performance evaluation index of the myopia massage equipment;

[0066] Analyzing the operation condition data of the myopia massage equipment in an interaction condition, the interaction condition including active interaction and passive interaction, to obtain an interaction quality evaluation index of the myopia massage equipment;

[0067] Based on the obtained operation performance evaluation index and interaction quality evaluation index, a myopia prevention and control management coefficient is comprehensively analyzed;

[0068] Based on the relationship between the myopia prevention and control management coefficient and a preset myopia prevention and control management coefficient, corresponding measures are taken.

[0069] In the embodiments of the present application, it is necessary to explain that, compared with the preset myopia prevention and control management coefficient, if Fg exceeds the preset value D, it indicates that the myopia prevention and control effect of the myopia massage equipment is abnormal, prompting the management personnel to maintain the myopia massage equipment and prompting the user to replace the equipment; if Fg does not exceed the preset value D, it indicates that the myopia prevention and control effect of the myopia massage equipment is normal, and no corresponding measures need to be taken.

[0070] Finally: the above-mentioned only for the preferred embodiments of the present application, and does not limit the present application, any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application, should be included in the protection scope of the present application.

Claims

1. A myopia prevention and control management system based on multi-source data, characterized in that, The method comprises the following steps: A data acquisition module is used to acquire running condition data of the myopia massage device, user condition data, and running condition data of the user and the myopia massage device in an interactive situation; A device running condition analysis module is used to analyze the running condition data of the myopia massage device in a non-interactive situation, acquire a running performance evaluation index of the myopia massage device, and transmit the analysis result to a user condition analysis module and a monitoring and early warning module; The running performance evaluation index is acquired by the following method: the myopia massage device is worn on a mannequin head equipped with a sensor, a test is performed, and running parameters of the myopia massage device are acquired, the running parameters at least including a hot compress area, a hot compress temperature, a pulse current function, an interruption time, and an interruption frequency of the myopia massage device; pulse current control quality parameters, hot compress function control quality parameters, and running stability parameters are obtained by analyzing the acquired data, and the running performance evaluation index is obtained by joint analysis; The value dk of the pulse current control quality parameter is calculated by the formula f(t) represents the pulse current function, represents the preset pulse current function, t1 represents the time when the pulse current starts, and t2 represents the time when the pulse current ends; the value rk of the hot compress function control quality parameter is calculated by the formula fm represents the effective coverage area of the infrared hot compress, sm represents the designed coverage area, sw represents the actual temperature value, and dw represents the set temperature value; the value yw of the operation stability parameter is obtained by the formula dt represents the set time length, gc represents the number of interruptions in the time dt, and gt represents the interruption time in the time dt; the value Xz of the operation performance evaluation index is calculated by the formula α represents the influence factor of the hot compress function, β represents the influence factor of the pulse current control quality, γ represents the influence factor of the operation failure, and α+β+γ=1.0, 0<α<0.7, 0.3<β<1, 0<γ<0.7, which are specifically set by the management personnel according to the actual situation; A user condition analysis module is used to analyze the user condition data to obtain a user eye health condition index, an eye appearance abnormality index, and a use condition evaluation index, comprehensively analyze to obtain a user risk coefficient, and transmit the user risk coefficient to the monitoring and early warning module; Wherein, the user risk coefficient is obtained by , AF represents the calculation result of the user risk coefficient, Wy represents the eye appearance abnormality index, and the eye appearance abnormality index is obtained by: obtaining an eye high-definition picture, inputting the trained convolutional neural network, and outputting an eye appearance abnormality parameter; the eye appearance feature parameter is obtained by the convolutional neural network, and the eye appearance abnormality index y is obtained by the formula i represents the i-th eye feature vector, k i represents the weight coefficient corresponding to the i-th eye feature vector; YJ represents the user eye health index, satisfying the formula , yy represents the user eye pressure, sh represents the user eye retina thickness, jh represents the user lens thickness, and sv represents the user vision degree growth speed; Sp represents the use condition evaluation index, satisfying the formula , wherein md 均 represents the average intensity of the massage pulse current, at represents the massage time, wd represents the massage temperature, and am represents the coverage area of the massage. A device interactive performance analysis module is used to analyze the running condition data of the myopia massage device in an interactive situation, the interactive situation including active interaction and passive interaction, acquire an interactive quality evaluation index of the myopia massage device, and transmit the analysis result to the monitoring and early warning module; The interaction quality evaluation index is obtained by obtaining an active interaction execution speed zv1, a passive interaction execution speed zv2, an active interaction execution accuracy parameter zx1, and a passive interaction execution accuracy parameter zx2, and using the following formula The value of the interaction quality evaluation index JP,f1 represents a weight factor of the active interaction, f2 represents a weight factor of the passive interaction, and f1+f2=1.

0. w1 represents an influence factor of the interaction execution speed, w2 represents an influence factor of the interaction accuracy parameter, and w1+w2=1.

0. The active interaction execution speed is obtained by obtaining a time of inputting an adjustment instruction by a user and a time of executing the instruction by a device, dividing the time of executing the instruction by the time of inputting the adjustment instruction to obtain an execution speed parameter, and averaging multiple values. The passive interaction execution speed is obtained by obtaining a generation time of a passive adjustment instruction and a time of executing the instruction by the device, dividing the generation time of the passive adjustment instruction by the time of inputting the adjustment instruction to obtain an execution speed parameter, and averaging multiple values. The execution accuracy of the device executing the instruction is compared with a preset result to determine whether the execution is accurate, and multiple execution results are counted to obtain the active interaction execution accuracy parameter and the passive interaction execution accuracy parameter. A monitoring and early warning module is used to monitor the running performance evaluation index of the myopia massage device, the user risk coefficient, and the interactive quality evaluation index of the myopia massage device; A comprehensive quality evaluation module is used to comprehensively analyze the running performance evaluation index and the interactive quality evaluation index to obtain a myopia prevention and control management coefficient.

2. The myopia prevention and control management system based on multi-source data according to claim 1, characterized in that, The data acquisition module comprises a device running condition acquisition unit, a user condition acquisition unit, and a device interactive information acquisition unit; the device running condition acquisition unit is used to acquire device running information, including pulse current information, a hot compress area, a hot compress temperature, an interruption frequency, and an interruption time of the device; the user condition acquisition unit is used to acquire user condition information, including ophthalmic examination data and vision screening data of a medical institution, and self-reported data of an individual; and the device interactive information acquisition unit is used to acquire interactive information between the device and the user, including active interaction information and passive interaction information; the active interaction information includes a time when the user issues an interactive instruction, a time when the device executes an active interaction instruction, and an active interaction execution accuracy parameter; and the passive interaction information includes a generation time of a passive interaction instruction, a time when the device executes the passive interaction instruction, and a passive interaction execution accuracy parameter.

3. The myopia prevention and control management system based on multi-source data according to claim 1, characterized in that, The monitoring and early warning module comprises a running performance monitoring and early warning unit, an interaction performance monitoring and early warning unit and a user condition monitoring and early warning unit. The running performance monitoring and early warning unit is used to monitor the running performance evaluation index of the myopia massage device. When the running performance evaluation index exceeds a preset value A, it indicates that the myopia massage device is running abnormally, and an abnormal running alarm of the myopia massage device is sent to the manager or user. When the running performance evaluation index does not exceed the preset value A, it indicates that the myopia massage device is running normally and no measures need to be taken. The interaction performance monitoring and early warning unit is used to monitor the interaction quality evaluation index of the myopia massage device. When the interaction quality evaluation index exceeds a preset value B, it indicates that the interaction performance of the myopia massage device is abnormal, and an alarm reminding of improving the interaction performance is sent to the manager. When the interaction quality evaluation index does not exceed the preset value B, it indicates that the interaction performance of the myopia massage device is normal. The user condition monitoring and early warning unit is used to monitor the eye health condition of the user. When the user risk coefficient exceeds a preset value C, the user is warned to pay attention to eye health and seek medical treatment in time, and the user is prompted to reduce the pulse current intensity of myopia massage, suspend the myopia massage, and shorten the myopia massage time.

4. The myopia prevention and control management system based on multi-source data according to claim 1, characterized in that, The comprehensive quality evaluation module obtains the myopia prevention and control management coefficient through comprehensive analysis based on the running performance evaluation index and the interaction quality evaluation index, and the myopia prevention and control management coefficient satisfies the formula Wherein, Fg represents the myopia prevention and control management coefficient, when Fg exceeds the preset value D, it indicates that the myopia prevention and control effect of the myopia massage equipment is abnormal, prompting the management personnel to maintain the myopia massage equipment and prompting the user to replace the equipment.

5. A myopia prevention and control management method based on multi-source data, executed by the system of claim 1, characterized in that, The method comprises the following steps: collecting running condition data of the myopia massage device, user condition data, and running condition data of the user and the myopia massage device in an interaction condition; analyzing the running condition data of the myopia massage device in a non-interaction condition to obtain a running performance evaluation index of the myopia massage device; analyzing the running condition data of the myopia massage device in an interaction condition, which includes active interaction and passive interaction, to obtain an interaction quality evaluation index of the myopia massage device; comprehensively analyzing the running performance evaluation index and the interaction quality evaluation index to obtain a myopia prevention and control management coefficient; based on the relationship between the myopia prevention and control management coefficient and a preset myopia prevention and control management coefficient, taking corresponding measures.

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