Lens degree adjusting system and method based on touch technology

Abstract

The invention discloses a lens degree adjusting system and method based on a touch control technology, and relates to the technical field of data analysis, the system comprises an input module, an analysis module, a database module, a control module and an adjusting module; the input module is used for inputting influence factor information and a specified adjustment degree by a user; the analysis module is used for constructing an SVR regression model to recommend an adjustment degree according to historical influence factors, time and degree adjustment information; the database module is used for providing historical influence factors, time and degree adjustment information and storing new data; the control module is used for adjusting the lens degree according to the recommended adjustment degree or the specified adjustment degree input by the user; and the adjusting module is used for a user to control the touch panel to adjust the degree of the lens. The invention also provides a method for realizing the system. According to the invention, the situation that the degree adjustment of the lens lacks accuracy and individuation in the prior art can be effectively improved.

Description

Technical Field

[0001] The present invention relates to the technical field of data analysis, and in particular to a lens power adjustment system and method based on touch technology. Background Art

[0002] With the continuous development of science and technology, people's requirements for vision correction equipment are increasing day by day, especially the field of adjustable lens technology has received widespread attention. In today's digital age, people's eye habits are complex and diverse, and different eye activities and environmental factors have different effects on vision. Traditional fixed-degree lenses can no longer meet people's visual needs in various scenarios, so adjustable-degree lens technology came into being.

[0003] In the prior art, the adjustment of lens power often lacks precision and personalization. On the one hand, the adjustment method of lens power is relatively fixed, and does not fully consider the various factors that affect the vision changes of users under different eye activities. It is difficult to make intelligent degree adjustments according to the actual eye conditions of users, and cannot meet personalized visual needs. On the other hand, during the adjustment process, there is a lack of effective control over the adjustment accuracy, and the adjustment unit is not flexibly set according to the user's operating habits and dynamic characteristics, resulting in the adjustment process being inflexible and inaccurate. Summary of the invention

[0004] The purpose of the present invention is to provide a lens power adjustment system and method based on touch technology to solve the problems raised in the prior art.

[0005] To achieve the above-mentioned object, the present invention provides the following technical solutions: a lens power adjustment system based on touch technology, the system comprising an input module, an analysis module, a database module, a control module and an adjustment module; The input module is used for users to input influencing factor information and specify the adjustment degree; the analysis module is used to build an SVR regression model based on historical influencing factors, time and degree adjustment information to analyze new data and recommend adjustment degrees; the database module is used to provide historical influencing factor information, time information and degree adjustment information and store new data; the control module is used to adjust the lens degree according to the recommended adjustment degree or the specified adjustment degree input by the user; the adjustment module is used for the user to control the touch panel to adjust the lens degree; The specific method of adjustment is as follows: the lens is made of elastic polymer material, and the liquid in the lens is optical liquid; when the volume of the liquid in the lens is different, the lens is deformed and has different curvatures and refractive indices, and the degree of the lens at this time is determined according to the different refractive indices and curvatures, and a comparison table between the remaining volume of liquid in the liquid pump and the degree is formed, and the liquid corresponding to the adjusted degree in the liquid pump is controlled to be pushed or extracted to achieve the adjustment of the lens degree; The output end of the input module is connected to the input ends of the analysis module and the adjustment module; the output end of the analysis module is connected to the input end of the adjustment module; the output end of the database module is connected to the input end of the analysis module; the control module is connected to the adjustment module; the output end of the adjustment module is connected to the input end of the database module.

[0006] The influencing factors refer to factors related to eye activities and have a direct or indirect relationship with vision changes.

[0007] The analysis module includes a data collection unit, a regression model unit and a degree recommendation unit; The data collection unit is used to collect influencing factor information, time difference information and degree adjustment information when the user adjusts the lens degree; the regression model unit is used to construct an SVR regression model to fit the relationship between the influencing factor and the lens degree change; the degree recommendation unit is used to use the regression model to give a degree adjustment recommendation according to the influencing factor input by the user; The output end of the data collection unit is connected to the input end of the regression model unit; the output end of the regression model unit is connected to the input end of the degree recommendation unit; the output end of the degree recommendation unit is connected to the input end of the adjustment module.

[0008] The control module includes a comparison table unit, a control unit and a unit adjustment unit; The comparison table unit is used to store the comparison relationship between the remaining liquid volume in the liquid pump and the degree; the control unit is used to control the pushing or extraction of the liquid corresponding to the adjusted degree in the liquid pump to adjust the degree of the lens; the unit adjustment unit is used to set the degree adjustment unit according to the user's sliding speed; The comparison table unit is connected to the control unit; the output end of the unit adjustment unit is connected to the input end of the control unit; the output end of the control unit is connected to the input end of the adjustment module.

[0009] The adjustment module includes a preliminary adjustment unit, a secondary adjustment unit and an adjustment completion unit; The preliminary adjustment unit is used to adjust the lens according to the degree specified by the user or the recommended adjustment degree; the secondary adjustment unit is used for the user to adjust the degree of the lens using the touch pad; the adjustment completion unit is used to set a time period threshold, and when the user does not adjust the degree of the lens within the time period threshold, it is considered that the adjustment is completed; The output end of the preliminary adjustment unit is connected to the input end of the secondary adjustment unit and the adjustment completion unit; the output end of the secondary adjustment unit is connected to the input end of the adjustment completion unit and the control module; the output end of the adjustment completion unit is connected to the input end of the database module.

[0010] A method for adjusting the degree of a lens based on touch technology, the method comprising the following steps: Step 1, collecting influencing factor information, time difference information and degree adjustment information when the user adjusts the lens degree; Step 2, construct an SVR regression model to fit the relationship between the influencing factors and the change of lens power; Step 3: Use the regression model to give a degree adjustment recommendation based on the impact factor input by the user; Step 4: Adjust the lens according to the degree specified by the user or the recommended degree; Step 5: When the user uses the touchpad to adjust the lens degree, the degree adjustment unit is set according to the user's sliding speed, and the lens degree is adjusted in combination with the sliding direction; Step 6: Set a time period threshold. When the user does not adjust the lens power within the time period threshold, the adjustment is considered complete, and the adjustment time and the final lens power are recorded.

[0011] In step 1, the specific method of adjustment is as follows: when the volume of liquid in the lens is different, the lens has different curvature and refractive index, the degree of the lens at this time is determined according to the different refractive index and curvature, a comparison table between the remaining volume of liquid in the liquid pump and the degree is formed, and the liquid volume corresponding to the adjusted degree in the liquid pump is controlled to push or extract to control the adjustment of the lens degree; the specific adjustment should be within the allowable range of the degree; The influencing factors refer to factors related to eye activities and have direct or indirect links with vision changes; the influencing factors are expressed as: [A1, A2, …, A a ]; where a is a positive integer, indicating the number of impact factors, A1~A a Represent the 1st to ath impact factors respectively; The time difference information is represented by the time difference Δt between a certain degree adjustment corresponding moment and the previous degree adjustment corresponding moment; wherein Δt=t n -t n-1 ; n is a positive integer, indicating the degree adjustment frequency sequence, t n Indicates the time corresponding to the nth degree adjustment, t n-1 Indicates the time corresponding to the (n-1)th degree adjustment; The degree adjustment information is represented by the degree difference Δd between the corresponding degree after a certain degree adjustment is completed and the corresponding degree after the previous degree adjustment is completed; wherein Δd=d n -d n-1 ;d n Indicates the corresponding degree after the nth degree adjustment is completed, d n-1 Indicates the corresponding degree after the (n-1)th degree adjustment is completed; Integrate the collected data: [A1,A2,…,A a ,Δt,Δd]; clean and standardize the influencing factor data.

[0012] In step 2, the SVR regression model is constructed: the radial basis kernel function is expressed as: K(x i ,x j )=exp(-γ||x i -x j || 2 ), where i, j are positive integers, representing the data sample sequence; x i =[A1,A2,…,A a ,Δt] i , represents the feature vector of the i-th sample, x j =[A1,A2,…,Aa,Δt] j , represents the feature vector of the jth sample; γ represents the kernel width parameter; Determine the parameters: the insensitive parameter ε is used to define the error tolerance interval in the insensitive loss function; the ε-insensitive loss function is expressed as: ; Regularization parameter C controls the degree of penalty for samples beyond the ε-insensitivity band; where y represents the actual degree difference; f(x) represents the predicted degree difference; ε represents the error range; cross-validation combined with grid search is used to determine the parameters γ, C and ε; Model training: Use the collected data samples, including independent variables [A1, A2, …, A a ,Δt] and the corresponding dependent variable Δd are input into the radial basis kernel function SVR model for training; the model parameters are continuously adjusted through the sequential minimum optimization algorithm to minimize the loss of the model based on the ε-insensitive loss function on the training set; the SVR regression model is obtained: ; where x represents the new input sample vector; x l represents the lth support vector; m represents the number of support vectors; α i and α i * represents the Lagrange multiplier determined during the model training process; K(x,x l ) represents the radial basis kernel function; b represents the bias term.

[0013] In step 3, when the user adjusts the lens power, the influencing factor information is input, the time difference is calculated, and input into the SVR regression model to obtain the recommended power difference Δd new , combined with the degree d when no adjustment is made old Calculate the recommended adjustment degree d new =d old +Δd new ; In step 4, when the user inputs a specified degree, the degree of the lens is adjusted according to the user-specified degree; when the user does not input a specified degree, the lens is adjusted according to the obtained recommended adjustment degree.

[0014] In step 5, set the minimum adjustment unit, that is, the minimum change in each adjustment, expressed as u min ; Calculate the user's sliding speed: Calculate the user's sliding speed v=s / ΔT based on the distance s that the user slides on the touchpad and the time difference ΔT between the start and end of sliding; Set the speed threshold V h , when v≤V h When the adjustment unit u=u min ; When v>V h When the adjustment unit u=u min +k(vV h ), where k is the dynamic adjustment coefficient; When the sliding direction is set to be backward, the lens power is reduced according to the adjustment unit corresponding to the sliding speed; conversely, when the sliding direction is set to be forward, the lens power is increased according to the adjustment unit corresponding to the sliding speed; the liquid in the lens is adjusted in accordance with the comparison table between the remaining liquid volume in the liquid pump and the power; In step 6, set the time period threshold T h When the user does not adjust the lens power within the time period threshold, the adjustment is considered complete, and the adjustment time and the final lens power are recorded; the adjustment time is the current time minus the time period threshold T h .

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention introduces a support vector regression model, and provides intelligent power adjustment recommendations by analyzing user eye influencing factors and historical adjustment data; dynamically adjusts the adjustment unit in combination with user touch operation, thereby achieving more delicate and accurate lens power adjustment; the present invention avoids lens power adjustment beyond a reasonable range or adjustment errors caused by misoperation by setting power adjustment range limits and minimum adjustment units, thereby further improving the reliability and safety of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the process of a lens power adjustment system based on touch technology of the present invention; Figure 2 The present invention is a schematic diagram of the steps of a method for adjusting the lens power based on touch technology. DETAILED DESCRIPTION

[0017] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0018] Example: Figure 1-Figure 2 As shown, the present invention provides a technical solution, a lens power adjustment system based on touch technology, the system includes an input module, an analysis module, a database module, a control module and an adjustment module; The input module is used for users to input influencing factor information and specify the adjustment degree; the analysis module is used to build an SVR regression model based on historical influencing factors, time and degree adjustment information to analyze new data and recommend adjustment degrees; the database module is used to provide historical influencing factor information, time information and degree adjustment information and store new data; the control module is used to adjust the lens degree according to the recommended adjustment degree or the specified adjustment degree input by the user; the adjustment module is used for the user to control the touch panel to adjust the lens degree; The specific method of adjustment is as follows: the lens is made of elastic polymer material, and the liquid in the lens is optical liquid; when the volume of the liquid in the lens is different, the lens is deformed and has different curvatures and refractive indices, and the degree of the lens at this time is determined according to the different refractive indices and curvatures, and a comparison table between the remaining volume of liquid in the liquid pump and the degree is formed, and the liquid corresponding to the adjusted degree in the liquid pump is controlled to be pushed or extracted to achieve the adjustment of the lens degree; The output end of the input module is connected to the input ends of the analysis module and the adjustment module; the output end of the analysis module is connected to the input end of the adjustment module; the output end of the database module is connected to the input end of the analysis module; the control module is connected to the adjustment module; the output end of the adjustment module is connected to the input end of the database module.

[0019] The influencing factors refer to factors related to eye activities and have a direct or indirect relationship with vision changes.

[0020] The analysis module includes a data collection unit, a regression model unit and a degree recommendation unit; The data collection unit is used to collect influencing factor information, time difference information and degree adjustment information when the user adjusts the lens degree; the regression model unit is used to construct an SVR regression model to fit the relationship between the influencing factor and the lens degree change; the degree recommendation unit is used to use the regression model to give a degree adjustment recommendation according to the influencing factor input by the user; The output end of the data collection unit is connected to the input end of the regression model unit; the output end of the regression model unit is connected to the input end of the degree recommendation unit; the output end of the degree recommendation unit is connected to the input end of the adjustment module.

[0021] The control module includes a comparison table unit, a control unit and a unit adjustment unit; The comparison table unit is used to store the comparison relationship between the remaining liquid volume in the liquid pump and the degree; the control unit is used to control the pushing or extraction of the liquid corresponding to the adjusted degree in the liquid pump to adjust the degree of the lens; the unit adjustment unit is used to set the degree adjustment unit according to the user's sliding speed; The comparison table unit is connected to the control unit; the output end of the unit adjustment unit is connected to the input end of the control unit; the output end of the control unit is connected to the input end of the adjustment module.

[0022] The adjustment module includes a preliminary adjustment unit, a secondary adjustment unit and an adjustment completion unit; The preliminary adjustment unit is used to adjust the lens according to the degree specified by the user or the recommended adjustment degree; the secondary adjustment unit is used for the user to adjust the degree of the lens using the touch pad; the adjustment completion unit is used to set a time period threshold, and when the user does not adjust the degree of the lens within the time period threshold, it is considered that the adjustment is completed; The output end of the preliminary adjustment unit is connected to the input end of the secondary adjustment unit and the adjustment completion unit; the output end of the secondary adjustment unit is connected to the input end of the adjustment completion unit and the control module; the output end of the adjustment completion unit is connected to the input end of the database module.

[0023] A method for adjusting the degree of a lens based on touch technology, the method comprising the following steps: Step 1, collecting influencing factor information, time difference information and degree adjustment information when the user adjusts the lens degree; Step 2, construct an SVR regression model to fit the relationship between the influencing factors and the change of lens power; Step 3: Use the regression model to give a degree adjustment recommendation based on the impact factor input by the user; Step 4: Adjust the lens according to the degree specified by the user or the recommended degree; Step 5: When the user uses the touchpad to adjust the lens degree, the degree adjustment unit is set according to the user's sliding speed, and the lens degree is adjusted in combination with the sliding direction; Step 6: Set a time period threshold. When the user does not adjust the lens power within the time period threshold, the adjustment is considered complete, and the adjustment time and the final lens power are recorded.

[0024] In step 1, the specific method of adjustment is as follows: when the volume of liquid in the lens is different, the lens has different curvature and refractive index, the degree of the lens at this time is determined according to the different refractive index and curvature, a comparison table between the remaining volume of liquid in the liquid pump and the degree is formed, and the liquid volume corresponding to the adjusted degree in the liquid pump is controlled to push or extract to control the adjustment of the lens degree; the specific adjustment should be within the allowable range of the degree; The influencing factors refer to factors related to eye activities and have direct or indirect links with vision changes; the influencing factors are expressed as: [A1, A2, …, A a ]; where a is a positive integer, indicating the number of impact factors, A1~A a Represent the 1st to ath impact factors respectively; The time difference information is represented by the time difference Δt between a certain degree adjustment corresponding moment and the previous degree adjustment corresponding moment; wherein Δt=t n -t n-1 ; n is a positive integer, indicating the degree adjustment frequency sequence, t n Indicates the time corresponding to the nth degree adjustment, t n-1 Indicates the time corresponding to the (n-1)th degree adjustment; The degree adjustment information is represented by the degree difference Δd between the corresponding degree after a certain degree adjustment is completed and the corresponding degree after the previous degree adjustment is completed; wherein Δd=d n -d n-1 ;d n Indicates the corresponding degree after the nth degree adjustment is completed, d n-1 Indicates the corresponding degree after the (n-1)th degree adjustment is completed; Integrate the collected data: [A1,A2,…,A a ,Δt,Δd]; clean and standardize the influencing factor data.

[0025] In step 2, the SVR regression model is constructed: the radial basis kernel function is expressed as: K(x i ,x j )=exp(-γ||x i -x j || 2 ), where i, j are positive integers, representing the data sample sequence; x i =[A1,A2,…,A a ,Δt] i , represents the feature vector of the i-th sample, x j =[A1,A2,…,Aa,Δt] j , represents the feature vector of the jth sample; γ represents the kernel width parameter; Determine the parameters: the insensitive parameter ε is used to define the error tolerance interval in the insensitive loss function; the ε-insensitive loss function is expressed as: ; Regularization parameter C controls the degree of penalty for samples beyond the ε-insensitivity band; where y represents the actual degree difference; f(x) represents the predicted degree difference; ε represents the error range; cross-validation combined with grid search is used to determine the parameters γ, C and ε; Model training: Use the collected data samples, including independent variables [A1, A2, …, A a ,Δt] and the corresponding dependent variable Δd are input into the radial basis kernel function SVR model for training; the model parameters are continuously adjusted through the sequential minimum optimization algorithm to minimize the loss of the model based on the ε-insensitive loss function on the training set; the SVR regression model is obtained: ; where x represents the new input sample vector; x l represents the lth support vector; m represents the number of support vectors; α i and α i * represents the Lagrange multiplier determined during the model training process; K(x,x l ) represents the radial basis kernel function; b represents the bias term.

[0026] In step 3, when the user adjusts the lens power, the influencing factor information is input, the time difference is calculated, and input into the SVR regression model to obtain the recommended power difference Δd new , combined with the degree d when no adjustment is made old Calculate the recommended adjustment degree d new =d old +Δd new ; In step 4, when the user inputs a specified degree, the degree of the lens is adjusted according to the user-specified degree; when the user does not input a specified degree, the lens is adjusted according to the obtained recommended adjustment degree.

[0027] In step 5, set the minimum adjustment unit, that is, the minimum change in each adjustment, expressed as u min ; Calculate the user's sliding speed: Calculate the user's sliding speed v=s / ΔT based on the distance s that the user slides on the touchpad and the time difference ΔT between the start and end of sliding; Set the speed threshold V h , when v≤V h When the adjustment unit u=u min ; When v>V h When the adjustment unit u=u min +k(vV h ), where k is the dynamic adjustment coefficient; When the sliding direction is set to be backward, the lens power is reduced according to the adjustment unit corresponding to the sliding speed; conversely, when the sliding direction is set to be forward, the lens power is increased according to the adjustment unit corresponding to the sliding speed; the liquid in the lens is adjusted in accordance with the comparison table between the remaining liquid volume in the liquid pump and the power; In step 6, set the time period threshold T h When the user does not adjust the lens power within the time period threshold, the adjustment is considered complete, and the adjustment time and the final lens power are recorded; the adjustment time is the current time minus the time period threshold T h .

[0028] In this example: an office worker whose daily work requires him to face a computer screen for a long time, occasionally read paper documents and participate in video conferences, and browse information on his mobile phone to relax during work breaks; Data collection: Information collection of influencing factors: When the employee uses a device with adjustable lenses, the system automatically monitors factors related to his / her eye activity; user input: A1 continuously looking at the computer screen for 2 hours, A2 reading paper documents for 30 minutes, A3 using a mobile phone for 15 minutes; Time difference information collection: The staff member adjusted the lens power for the first time at 10:00 a.m. t1, and the second time at 11:30 a.m. t2, so the time difference Δt=t2-t1=1.5 hours; Power adjustment information collection: After the first adjustment, the lens power d1 is -2.00D, and after the second adjustment, d2 is -2.25D. The power difference Δd=d2-d1=-0.25D. The data is integrated into [-2 hours of watching computers, 0.5 hours of reading paper documents, 0.25 hours of using mobile phones, 1.5 hours, -0.25D], and the influencing factor data is cleaned and standardized. Model construction and training phase: construct an SVR regression model, use the collected data samples, including independent variables [time spent on the computer, time spent reading paper documents, time spent on the phone, time difference] and the corresponding dependent variable degree difference, input them into the radial basis kernel function SVR model for training, and continuously adjust the model parameters through the sequential minimum optimization algorithm to obtain the SVR regression model; Degree adjustment stage: When the employee uses glasses again, the system collects influencing factor information based on his current eye usage. He has been looking at the computer for 1.5 hours and has not performed other eye activities. After calculating the time difference, these data are input into the SVR regression model to obtain the recommended degree difference Δd new =-0.20D; the lens power before adjustment was -2.25D, so the recommended adjustment power is d new =-2.25D+(-0.20D)=-2.45D; the system makes adjustments directly; The staff found that the lens degree did not meet the requirements and chose to use the touchpad for manual fine-tuning, setting the minimum adjustment unit u min is 0.05D. Assuming that the distance s he slides on the touchpad is 10mm, and the time difference ΔT between the start and end of sliding is 2s, then the sliding speed v=s / ΔT=5mm / s; the speed threshold V h is 4mm / s, and the dynamic adjustment coefficient k is 0.02. Since v>V h , adjustment unit u=u min +k(vV h )=0.05D+0.02×(5-4)=0.07D; slide forward, increase the lens diopter according to the adjustment unit corresponding to the sliding speed, and adjust the liquid in the lens in accordance with the comparison table between the remaining liquid volume in the liquid pump and the diopter; Adjustment completion recording stage: Set time period threshold T h If the staff member fails to adjust the lens power within 30 minutes, the system considers the adjustment completed and records the adjustment time, and the current time minus the time period threshold T h , and the final lens power; these data can be used for subsequent analysis of the user's vision change trends and eye habits, in order to further optimize the model and lens adjustment strategy.

[0029] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A lens power adjustment system based on touch technology, characterized in that: The system includes an input module, an analysis module, a database module, a control module and a regulation module; The input module is used for users to input influencing factor information and specify the adjustment degree; the analysis module is used to build an SVR regression model based on historical influencing factors, time and degree adjustment information to analyze new data and recommend adjustment degrees; the database module is used to provide historical influencing factor information, time information and degree adjustment information and store new data; the control module is used to adjust the lens degree according to the recommended adjustment degree or the specified adjustment degree input by the user; the adjustment module is used for the user to control the touch panel to adjust the lens degree; The specific method of adjustment is as follows: the lens is made of elastic polymer material, and the liquid in the lens is optical liquid; when the volume of the liquid in the lens is different, the lens is deformed and has different curvatures and refractive indices, and the degree of the lens at this time is determined according to the different refractive indices and curvatures, and a comparison table between the remaining volume of liquid in the liquid pump and the degree is formed, and the liquid corresponding to the adjusted degree in the liquid pump is controlled to be pushed or extracted to achieve the adjustment of the lens degree; The output end of the input module is connected to the input ends of the analysis module and the adjustment module; the output end of the analysis module is connected to the input end of the adjustment module; the output end of the database module is connected to the input end of the analysis module; the control module is connected to the adjustment module; the output end of the adjustment module is connected to the input end of the database module.

2. The lens power adjustment system based on touch technology according to claim 1, characterized in that: The influencing factors refer to factors related to eye activities and have a direct or indirect relationship with vision changes.

3. The lens power adjustment system based on touch technology according to claim 2, characterized in that: The analysis module includes a data collection unit, a regression model unit and a degree recommendation unit; The data collection unit is used to collect influencing factor information, time difference information and degree adjustment information when the user adjusts the lens degree; the regression model unit is used to construct an SVR regression model to fit the relationship between the influencing factor and the lens degree change; The degree recommendation unit is used to use a regression model to give a degree adjustment recommendation according to the influencing factors input by the user; The output end of the data collection unit is connected to the input end of the regression model unit; The output end of the regression model unit is connected to the input end of the degree recommendation unit; the output end of the degree recommendation unit is connected to the input end of the adjustment module.

4. The lens power adjustment system based on touch technology according to claim 3, characterized in that: The control module includes a comparison table unit, a control unit and a unit adjustment unit; The comparison table unit is used to store the comparison relationship between the remaining liquid volume in the liquid pump and the degree; the control unit is used to control the pushing or extraction of the liquid corresponding to the adjusted degree in the liquid pump to adjust the degree of the lens; the unit adjustment unit is used to set the degree adjustment unit according to the user's sliding speed; The comparison table unit is connected to the control unit; the output end of the unit adjustment unit is connected to the input end of the control unit; the output end of the control unit is connected to the input end of the adjustment module.

5. The lens power adjustment system based on touch technology according to claim 4, characterized in that: The adjustment module includes a preliminary adjustment unit, a secondary adjustment unit and an adjustment completion unit; The primary adjustment unit is used to adjust the lens according to the degree specified by the user or the recommended adjustment degree; the secondary adjustment unit is used for the user to adjust the degree of the lens using the touch panel; The adjustment completion unit is used to set a time period threshold. When the user does not adjust the lens power within the time period threshold, it is considered that the adjustment is completed. The output end of the preliminary adjustment unit is connected to the input end of the secondary adjustment unit and the adjustment completion unit; the output end of the secondary adjustment unit is connected to the input end of the adjustment completion unit and the control module; the output end of the adjustment completion unit is connected to the input end of the database module.

6. A method for adjusting lens power based on touch technology, characterized in that: The method comprises the following steps: Step 1, collecting influencing factor information, time difference information and degree adjustment information when the user adjusts the lens degree; Step 2, construct an SVR regression model to fit the relationship between the influencing factors and the change of lens power; Step 3: Use the regression model to give a degree adjustment recommendation based on the impact factor input by the user; Step 4: Adjust the lens according to the degree specified by the user or the recommended degree; Step 5: When the user uses the touchpad to adjust the lens degree, the degree adjustment unit is set according to the user's sliding speed, and the lens degree is adjusted in combination with the sliding direction; Step 6: Set a time period threshold. When the user does not adjust the lens power within the time period threshold, the adjustment is considered complete, and the adjustment time and the final lens power are recorded.

7. The method for adjusting the lens power based on touch technology according to claim 6, characterized in that: In step 1, the specific method of adjustment is as follows: when the volume of liquid in the lens is different, the lens has different curvatures and refractive indices, the degree of the lens at this time is determined according to the different refractive indices and curvatures, a comparison table between the remaining volume of liquid in the liquid pump and the degree is formed, and the liquid volume corresponding to the adjusted degree in the liquid pump is controlled to be pushed or extracted to control the adjustment of the lens degree; The influencing factors refer to factors related to eye activities, which are directly or indirectly related to vision changes; The impact factor is expressed as: [A1, A2, …, A a ]; where a is a positive integer, indicating the number of impact factors, A1~A a Represent the 1st to ath impact factors respectively; The time difference information is represented by the time difference Δt between a certain degree adjustment corresponding moment and the previous degree adjustment corresponding moment; wherein Δt=t n -t n-1 ; n is a positive integer, indicating the degree adjustment frequency sequence, t n Indicates the time corresponding to the nth degree adjustment, t n-1 Indicates the time corresponding to the (n-1)th degree adjustment; The degree adjustment information is represented by the degree difference Δd between the corresponding degree after a certain degree adjustment is completed and the corresponding degree after the previous degree adjustment is completed; wherein Δd=d n -d n-1 ;d n Indicates the corresponding degree after the nth degree adjustment is completed, d n-1 Indicates the corresponding degree after the (n-1)th degree adjustment is completed; Integrate the collected data: [A1,A2,…,A a ,Δt,Δd]; clean and standardize the influencing factor data.

8. The method for adjusting the lens power based on touch technology according to claim 7, characterized in that: In step 2, the SVR regression model is constructed: the radial basis kernel function is expressed as: K(x i ,x j )=exp(-γ||x i -x j || 2 ), where i, j are positive integers, representing the data sample sequence; x i =[A1,A2,…,A a ,Δt] i , represents the feature vector of the i-th sample, x j =[A1,A2,…,Aa,Δt] j , represents the feature vector of the jth sample; γ represents the kernel width parameter; Determine the parameters: the insensitive parameter ε is used to define the error tolerance interval in the insensitive loss function; the ε-insensitive loss function is expressed as: ; Regularization parameter C controls the degree of penalty for samples beyond the ε-insensitivity band; where y represents the actual degree difference; f(x) represents the predicted degree difference; ε represents the error range; cross-validation combined with grid search is used to determine the parameters γ, C and ε; Model training: Use the collected data samples, including independent variables [A1, A2, …, A a ,Δt] and the corresponding dependent variable Δd are input into the radial basis kernel function SVR model for training; the model parameters are continuously adjusted through the sequential minimum optimization algorithm to minimize the loss of the model based on the ε-insensitive loss function on the training set; the SVR regression model is obtained: ; where x represents the new input sample vector; x l represents the lth support vector; m represents the number of support vectors; α i and α i * represents the Lagrange multiplier determined during the model training process; K(x,x l ) represents the radial basis kernel function; b represents the bias term.

9. The method for adjusting the lens power based on touch technology according to claim 8, characterized in that: In step 3, when the user adjusts the lens power, the influencing factor information is input, the time difference is calculated, and input into the SVR regression model to obtain the recommended power difference Δd new , combined with the degree d when no adjustment is made old Calculate the recommended adjustment degree d new =d old +Δd new ; In step 4, when the user inputs a specified degree, the degree of the lens is adjusted according to the user-specified degree; when the user does not input a specified degree, the lens is adjusted according to the obtained recommended adjustment degree.

10. The method for adjusting lens power based on touch technology according to claim 9, characterized in that: In step 5, set the minimum adjustment unit, that is, the minimum change in each adjustment, expressed as u min ; Calculate the user's sliding speed: Calculate the user's sliding speed v=s / ΔT based on the distance s that the user slides on the touchpad and the time difference ΔT between the start and end of sliding; Set the speed threshold V h , when v≤V h When the adjustment unit u=u min ; When v>V h When the adjustment unit u=u min +k(vV h ), where k is the dynamic adjustment coefficient; When the sliding direction is set to be backward, the lens power is reduced according to the adjustment unit corresponding to the sliding speed; conversely, when the sliding direction is set to be forward, the lens power is increased according to the adjustment unit corresponding to the sliding speed; the liquid in the lens is adjusted in accordance with the comparison table between the remaining liquid volume in the liquid pump and the power; In step 6, set the time period threshold T h When the user does not adjust the lens power within the time period threshold, the adjustment is considered complete, and the adjustment time and the final lens power are recorded; the adjustment time is the current time minus the time period threshold T h .

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