Self-verification type child attention monitoring method

Abstract

According to the self-verification type child attention monitoring method, a rich plot database is constructed according to plot demands of children and public demands, then a child attention value is calculated according to interaction data of the children in an interaction plot, and then an attention evaluation value can be calculated in combination with a difficulty value and an attention threshold value; the attention evaluation value is used as a main basis for evaluating the attention of the child, and in the evaluation process, a self-verification mechanism is introduced, and a next section of interaction plot with different difficulty values is dynamically selected according to the attention evaluation value of the first section of interaction plot; the positive and negative correlation between the change of the attention evaluation value and the change of the difficulty value of the previous and later sections of interaction plots is calculated, different measures are taken based on the positive and negative correlation, if the positive correlation is adopted, a section of interaction plot containing olfactory stimulation can be introduced again, and the positive and negative correlation is evaluated again for self-verification; and the reliability and accuracy of the attention monitoring result are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of children's attention monitoring, and in particular to a self-verification method for monitoring children's attention. Background Art

[0002] Against the backdrop of digitization of education and the surge in demand for children's healthy growth, children's attention monitoring technology has become a research hotspot. Traditional methods of monitoring children's attention mostly rely on single-dimensional data, such as behavioral observation or simple physiological signal acquisition. They have problems such as low monitoring accuracy, susceptibility to interference from subjective factors, and lack of dynamic adaptability. For example, only recording children's distracting behavior through teacher classroom observation is prone to errors due to individual cognitive differences; the sole use of EEG signal monitoring cannot fully reflect children's attention status in complex interactive scenarios. At the same time, existing technologies lack a self-verification mechanism for monitoring results, making it difficult to ensure the reliability and validity of the data, and unable to dynamically adjust monitoring strategies and intervention measures according to children's real-time attention changes. Summary of the Invention

[0003] In view of this, the present invention proposes a self-verification method for monitoring children's attention, which can self-verify the children's attention monitoring results to ensure the accuracy of the monitoring results.

[0004] The technical solution of the present invention is achieved as follows:

[0005] A self-verified method for monitoring children's attention comprises the following steps:

[0006] Step S1: Obtaining the plot requirements of children, obtaining several different types of interactive plots based on the plot requirements and public demand, and extracting the difficulty value and attention threshold of each interactive plot;

[0007] Step S2: randomly selecting an interactive plot and pushing it to the child for interaction, collecting interaction data during the interaction process, calculating the child's attention value based on the interaction data, and calculating the attention evaluation value based on the difficulty value, the child's attention value, and the attention threshold;

[0008] Step S3: dynamically selecting the next interactive plot with different difficulty values based on the attention evaluation value, and after calculating the attention evaluation value, determining the positive or negative correlation between the change in the attention evaluation value of the two interactive plots and the change in the difficulty value;

[0009] Step S4: When the positive-negative correlation is positive, introduce olfactory stimulation into the next interactive plot, and determine the positive-negative correlation between the change in the attention evaluation value and the change in the difficulty value of the two interactive plots;

[0010] Step S5: When the positive-negative correlation is negative, the attention evaluation value calculated when the child subsequently interacts in the interactive plot is output.

[0011] Preferably, the specific steps of obtaining the child's plot needs in step S1 are:

[0012] Step S11: collecting the child's age, personality, and gender as basic attributes, collecting the child's toy preferences, game modes, and daily video viewing types as behavioral habits, and obtaining the regional characteristics of the child's area as cultural characteristics;

[0013] Step S12: Build a children's interest profile based on basic attributes, behavioral habits, and cultural characteristics, and determine the children's plot needs based on the children's interest profile.

[0014] Preferably, in step S1, a plurality of different types of interactive plots are constructed based on plot requirements and public demand, and the specific steps of presetting the corresponding attention threshold according to the difficulty value of each interactive plot are as follows:

[0015] Step S13: Preset a scenario database, wherein the scenario database contains a number of different types of interactive scenarios, each interactive scenario being marked with a difficulty value and an attention threshold;

[0016] Step S14: according to the plot requirement, searching the plot database for interactive plots of the same type as the plot requirement and outputting them, and randomly selecting other interactive plots of different types from the plot database and outputting them;

[0017] Step S15: extract the difficulty value and attention threshold of the output interactive plot.

[0018] Preferably, the specific steps of step S2 are:

[0019] Step S21: Randomly output an interactive plot with a medium difficulty value from the obtained multiple interactive plots, and display it on the smart terminal for children to interact with;

[0020] Step S22: directly collecting the in-game operation frequency, task completion speed, and error rate of the child during the interaction process as behavioral data through the smart terminal;

[0021] Step S23: collecting heart rate variability and galvanic skin response data as physiological data through the wearable device, and tracking eye movement frequency and frown frequency as visual data through the camera;

[0022] Step S24: normalize the behavioral data, physiological data, and visual data, and sum them after weighting to obtain the child's attention value, and calculate the attention evaluation value based on the difficulty value, the child's attention value, and the attention threshold.

[0023] Preferably, the expression of the attention evaluation value is:

[0024]

[0025] Among them, α is the difficulty value, A is the child's attention value, and B is the attention threshold.

[0026] Preferably, the specific steps of step S3 are:

[0027] Step S31: When the attention evaluation value is greater than 100%, the difficulty value of the next interactive plot selected is greater than the difficulty value of the previous interactive plot; when the attention evaluation value is less than 100%, the difficulty value of the next interactive plot selected is less than the difficulty value of the previous interactive plot;

[0028] Step S32: After calculating the attention evaluation value of the next interactive plot, subtract the attention evaluation value and difficulty value of the previous interactive plot from the attention evaluation value and difficulty value of the next interactive plot;

[0029] Step S33: When the difference between the attention evaluation value and the difficulty value has the same sign, the output is a positive correlation; otherwise, the output is a negative correlation.

[0030] Preferably, the specific steps of step S4 include:

[0031] Step S41: When the positive-negative correlation is positive and the difficulty value of the next interactive plot is less than the difficulty value of the previous interactive plot, the next interactive plot is obtained, and the specific plot content of the interactive plot is extracted, and a number of trigger nodes are set according to the specific plot content;

[0032] Step S42: Calculate the child's attention value before the triggering node when the child interacts with the interactive plot, and release the enhanced scent at the triggering node when the child's attention value is less than the attention threshold of the interactive plot;

[0033] Step S43: average the children's attention values before all trigger nodes, and again determine the positive or negative correlation between the change in the attention evaluation value of the two interactive plots and the change in the difficulty value. If it is still positively correlated, repeat step S4 based on the set number of repetitions until the positive or negative correlation is negative or the number of repetitions ends.

[0034] Preferably, the specific steps of step S4 further include:

[0035] Step S44: when the positive-negative correlation is positive, and the difficulty value of the next interactive plot is greater than the difficulty value of the previous interactive plot, obtain the next interactive plot;

[0036] Step S45: When the child interacts with the interactive plot, randomly release a distracting odor, calculate the child's attention evaluation value in the interactive plot, and again determine the positive or negative correlation between the change in the attention evaluation value and the change in the difficulty value between the two interactive plots;

[0037] Step S46: If the positive-negative correlation is still positive, the current attention evaluation value is output; otherwise, go to step S5.

[0038] Preferably, the enhanced scents include mint, citrus, rosemary, cedar, lavender and scents related to interactive plots, and the interfering scents include camphor, high-concentration perfume and incense, highly sweet and greasy scents and scents that do not match interactive plots.

[0039] Compared with the prior art, the present invention has the following beneficial effects:

[0040] ① Based on the different plot needs of children, a database of interactive plots is constructed. When selecting interactive plots for children to interact with, the plot needs of children can be met and their attention can be improved. At the same time, the public needs are introduced to evaluate children's attention to plots that they are not interested in, so as to comprehensively evaluate children's attention;

[0041] ② When evaluating children's attention, the child's attention value is calculated based on the child's interaction data. Then, based on the difficulty value of the interactive plot and the attention threshold combined with the child's attention value, the attention evaluation value can be calculated. This serves as the basis for evaluating children's attention. Through quantitative data, children's attention can be accurately evaluated;

[0042] ③After obtaining the attention evaluation value of the first interactive plot, the next interactive plot can be selected. Based on the positive and negative correlation between the changes in the attention evaluation values of the two previous and subsequent interactive plots and the changes in the difficulty values, the push of subsequent interactive plots can be readjusted based on the positive and negative correlation, and olfactory stimulation can be introduced for self-verification to ensure the reliability and accuracy of the attention monitoring results. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only preferred embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0044] Figure 1 A flowchart of a self-verification method for monitoring children's attention according to the present invention;

[0045] Figure 2Flowchart of step S1 of a self-verification method for monitoring children's attention according to the present invention;

[0046] Figure 3 Flowchart of step S2 of a self-verification method for monitoring children's attention according to the present invention;

[0047] Figure 4 Flowchart of step S3 of a self-verification method for monitoring children's attention according to the present invention;

[0048] Figure 5 This is a flow chart of step S4 of a self-verification method for monitoring children's attention. DETAILED DESCRIPTION

[0049] In order to better understand the technical content of the present invention, a specific embodiment is provided below, and the present invention is further described in conjunction with the accompanying drawings.

[0050] See also Figures 1 to 5 The present invention provides a self-verification method for monitoring children's attention, comprising the following steps:

[0051] Step S1: Obtaining the plot requirements of children, obtaining several different types of interactive plots based on the plot requirements and public demand, and extracting the difficulty value and attention threshold of each interactive plot;

[0052] Step S2: randomly selecting an interactive plot and pushing it to the child for interaction, collecting interaction data during the interaction process, calculating the child's attention value based on the interaction data, and calculating the attention evaluation value based on the difficulty value, the child's attention value, and the attention threshold;

[0053] Step S3: dynamically selecting the next interactive plot with different difficulty values based on the attention evaluation value, and after calculating the attention evaluation value, determining the positive or negative correlation between the change in the attention evaluation value of the two interactive plots and the change in the difficulty value;

[0054] Step S4: When the positive-negative correlation is positive, introduce olfactory stimulation into the next interactive plot, and determine the positive-negative correlation between the change in the attention evaluation value and the change in the difficulty value of the two interactive plots;

[0055] Step S5: When the positive-negative correlation is negative, the attention evaluation value calculated when the child subsequently interacts in the interactive plot is output.

[0056] The present invention employs an attention monitoring method during interaction. That is, while children are playing games, interaction data is collected to assess their attention. Before monitoring children's attention, a plot database is constructed. The plot database includes plots that the children are interested in and those that they are not interested in. After first obtaining the children's plot needs, interactive plots related to those plot needs can be searched based on the plot needs. For example, if a child likes space-themed plots, interactive plots with space environments or themes can be searched. To enrich the data volume of the plot database, interactive plots that are popular and not of interest to children are also introduced to enrich the plots. This also verifies whether children can focus on plots they are not interested in. The selected interactive plots are obtained based on current children's interactive attention training software. Each interactive plot has a preset difficulty value and an attention threshold. The greater the difficulty value, the higher the child's comprehension ability required. When interacting, children will be distracted due to excessive difficulty. The attention threshold is the minimum value. If the child's calculated attention value is lower than the attention threshold, the child is assessed as distracted; otherwise, the child is focused. By quantifying the child's attention value, the child's attention can be accurately assessed.

[0057] When a child interacts with an interactive plot, after collecting the interaction data during the interaction process, the child's attention value can be calculated based on the interaction data, and then the attention evaluation value can be calculated according to the child's attention value, difficulty value and attention threshold. The attention evaluation value can be used to evaluate whether the child is focused during the interaction process. In order to ensure the accuracy of the attention monitoring results, the self-verification function set in the present invention determines whether the child is in a focused or distracted state after calculating the attention evaluation value for the first interactive plot, and then selects the next interactive plot to push. The difficulty value of the next interactive plot will be different from that of the first interactive plot. The purpose is to determine whether the assessment of the child's attention is accurate through the difference in the interactive plot. After selecting the next interactive plot with a different difficulty value, the attention evaluation value is calculated in the same way and compared with the attention evaluation value calculated last time. At the same time, combined with the change in the difficulty value, it is determined whether the change in the attention evaluation value is positively correlated or negatively correlated with the change in the difficulty value, wherein the positive correlation includes that when the difficulty value increases, the calculated attention evaluation value also increases, and when the difficulty value decreases, the calculated attention evaluation value also increases. The attention evaluation value also decreases, and negative correlation means that the direction of change of the difficulty value of the two previous and subsequent interactive plots is opposite to the direction of change of the attention evaluation value. For example, when the difficulty decreases, the attention evaluation value increases, or when the difficulty increases, the attention evaluation value decreases. According to normal children's interaction, when the difficulty changes from high to low, the attention evaluation value should increase, and vice versa. Therefore, when the positive and negative correlation is negative, it means that attention monitoring is reasonable. Therefore, the attention evaluation value calculated in the next interactive plot can be directly output. If the positive and negative relationship is positive, for example, when the difficulty decreases, the attention evaluation value decreases instead, it means that there may be an abnormality in attention monitoring, or the child's attention is not focused enough. Therefore, non-traditional olfactory stimulation can be introduced in subsequent interactive plots to stimulate the child's attention concentration, and the positive and negative correlation can be judged again. By dynamically selecting interactive plots with different difficulty values and introducing olfactory stimulation, attention monitoring can be reasonably verified to ensure that reliable and accurate attention monitoring results can be obtained, so that parents can understand the child's concentration and thus change the training or learning plan for the child.

[0058] Preferably, the specific steps in step S1 are:

[0059] Step S11: collecting the child's age, personality, and gender as basic attributes, collecting the child's toy preferences, game modes, and daily video viewing types as behavioral habits, and obtaining the regional characteristics of the child's area as cultural characteristics;

[0060] Step S12: Build a children's interest profile based on basic attributes, behavioral habits, and cultural characteristics, and determine the children's plot needs based on the children's interest profile.

[0061] Step S13: Preset a scenario database, wherein the scenario database contains a number of different types of interactive scenarios, each interactive scenario being marked with a difficulty value and an attention threshold;

[0062] Step S14: according to the plot requirement, searching the plot database for interactive plots of the same type as the plot requirement and outputting them, and randomly selecting other interactive plots of different types from the plot database and outputting them;

[0063] Step S15: extract the difficulty value and attention threshold of the output interactive plot.

[0064] In order to improve children's attention, it is necessary to understand their interests and hobbies. The age, personality and gender differences of different children will affect their specific preferences. For example, boys may prefer engineering vehicles, the universe, monsters and other types, while girls may prefer animals, stories and other types. In addition, children's preferences can be judged based on their daily behavior, such as the types of videos they watch daily, their preferred toys and game modes, etc. In addition, the cultural symbols of some regions are more deeply rooted in the hearts of the people, so the regional characteristics of the children's area can be obtained as cultural characteristics. Then, based on basic attributes, behavioral habits and cultural characteristics, a child's interest profile can be constructed. According to the child's interest profile, the plot requirements can be determined. Then, based on the children's attention training software currently on the market, a variety of interactive plots are obtained and combined into a plot database. The interactive plots are divided into parts that are consistent with the children's plot requirements and parts that are inconsistent. Consistent interactive plots are found in the plot database, and several inconsistent interactive plots are randomly selected and output as options for children's training. At the same time, the difficulty value and attention threshold contained in the interactive plot will also be output for subsequent extraction and calculation.

[0065] Preferably, the specific steps of step S2 are:

[0066] Step S21: Randomly output an interactive plot with a medium difficulty value from the obtained multiple interactive plots, and display it on the smart terminal for children to interact with;

[0067] Step S22: directly collecting the in-game operation frequency, task completion speed, and error rate of the child during the interaction process as behavioral data through the smart terminal;

[0068] Step S23: collecting heart rate variability and galvanic skin response data as physiological data through the wearable device, and tracking eye movement frequency and frown frequency as visual data through the camera;

[0069] Step S24: normalize the behavioral data, physiological data, and visual data, and sum them after weighting to obtain the child's attention value. Calculate the attention evaluation value based on the difficulty value, the child's attention value, and the attention threshold. The expression of the attention evaluation value is:

[0070]

[0071] Among them, α is the difficulty value, A is the child's attention value, and B is the attention threshold.

[0072] When children are undergoing attention monitoring training, the difficulty level of the first interactive scenario is selected to be medium to prevent children from experiencing mood swings due to excessive difficulty, which may affect their attention monitoring. When children interact in the interactive scenario, interaction data can be collected during the interaction process. The interaction data includes behavioral data, physiological data, and visual data. For behavioral data, if the frequency of in-game operations is too high, the task completion speed is slow, and the error rate is high, it can be considered that the child's attention is poor. Similarly, wearable devices can collect heart rate variability and galvanic skin response. If the low-frequency part of heart rate variability increases or the galvanic skin response increases, it can be considered that the child's attention is reduced. The camera can collect eye movement frequency and frown frequency. If the eye movement frequency is too high and the frown frequency is high, it can be considered that the child's attention is low. After standardizing the above collected data, the weighted sum method can be used to obtain the child's attention value, and then the attention evaluation value can be calculated based on the attention evaluation value expression formula. The attention evaluation value is expressed as 100%. Greater than or equal to 100% indicates that the child is focused, and less than 100% indicates that the child is distracted.

[0073] Preferably, the specific steps of step S3 are:

[0074] Step S31: When the attention evaluation value is greater than 100%, the difficulty value of the next interactive plot selected is greater than the difficulty value of the previous interactive plot; when the attention evaluation value is less than 100%, the difficulty value of the next interactive plot selected is less than the difficulty value of the previous interactive plot;

[0075] Step S32: After calculating the attention evaluation value of the next interactive plot, subtract the attention evaluation value and difficulty value of the previous interactive plot from the attention evaluation value and difficulty value of the next interactive plot;

[0076] Step S33: When the difference between the attention evaluation value and the difficulty value has the same sign, the output is a positive correlation; otherwise, the output is a negative correlation.

[0077] When the child's attention is judged to be focused based on the attention evaluation value calculated in the first interactive plot, an interactive plot with a higher difficulty value can be selected in the next interactive plot. When it is judged to be distracted, an interactive plot with a lower difficulty value can be pushed. The purpose is to verify the accuracy of the attention monitoring results through the difference in the judgment of the child's attention in the two interactive plots. After calculating the attention evaluation value of the next interactive plot, the positive or negative correlation between the change in the attention evaluation value and the change in the difficulty value can be determined, and different verification measures can be taken based on different correlations.

[0078] Preferably, the specific steps of step S4 include:

[0079] Step S41: When the positive-negative correlation is positive and the difficulty value of the next interactive plot is less than the difficulty value of the previous interactive plot, the next interactive plot is obtained, and the specific plot content of the interactive plot is extracted, and a number of trigger nodes are set according to the specific plot content;

[0080] Step S42: Calculate the child's attention value before the triggering node when the child interacts with the interactive plot, and release the enhanced scent at the triggering node when the child's attention value is less than the attention threshold of the interactive plot;

[0081] Step S43: average the children's attention values before all trigger nodes, and again determine the positive or negative correlation between the change in the attention evaluation value of the two interactive plots and the change in the difficulty value. If it is still positively correlated, repeat step S4 based on the set number of repetitions until the positive or negative correlation is negative or the number of repetitions ends.

[0082] Specifically, when the positive-negative relationship is positively correlated, and the difficulty value of the next interactive plot is less than that of the previous interactive plot, it indicates that when the difficulty value decreases, the child's attention assessment value decreases synchronously. The possible reason is that the child's attention changes or the attention monitoring mechanism fails. In order to verify the accuracy of the attention monitoring results, after selecting the next interactive plot, the specific plot content of the interactive plot is extracted, and several trigger nodes in the plot are obtained. The interactive plot is divided into stages based on the trigger nodes. Then, when the child interacts, the plot segment before each trigger node will calculate the child's attention value and compare it with the attention threshold of the current interactive plot. When the child pays attention, the child's attention value is calculated. When the concentration value is less than the attention threshold, it is judged that the child is distracted. At this time, an enhanced scent, such as mint, citrus, rosemary, cedar, lavender, and scents related to the interactive plot can be released at the trigger node to improve the child's concentration. When the entire interactive plot is completed, the child's attention value of each plot segment is averaged, and the attention evaluation value is calculated, and the positive and negative correlation is judged again with the previous interactive plot. If it is still positively correlated, step S4 can be repeated based on the set number of repetitions until the positive and negative correlation is negative or the number of repetitions ends. If it is still positively correlated at the end of the repetition number, it can be basically determined that there is an abnormality in the child monitoring function and the relevant parameters need to be adjusted.

[0083] Preferably, the specific steps of step S4 further include:

[0084] Step S44: when the positive-negative correlation is positive, and the difficulty value of the next interactive plot is greater than the difficulty value of the previous interactive plot, obtain the next interactive plot;

[0085] Step S45: When the child interacts with the interactive plot, randomly release a distracting odor, calculate the child's attention evaluation value in the interactive plot, and again determine the positive or negative correlation between the change in the attention evaluation value and the change in the difficulty value between the two interactive plots;

[0086] Step S46: If the positive-negative correlation is still positive, the current attention evaluation value is output; otherwise, go to step S5.

[0087] When the positive and negative correlation is positive, and the difficulty value of the next interactive plot is greater than that of the previous interactive plot, it indicates that as the difficulty increases, the child's attention evaluation value also increases, indicating that the child's concentration is high. At this time, when interacting in the next interactive plot, interfering odors such as camphor, high-concentration perfume and incense, highly sweet and greasy odors, and odors that do not match the interactive plot can be released to distract the child. Then, the attention evaluation value in this interactive plot is calculated, and the positive and negative correlation between the change in the attention evaluation value of the two interactive plots and the change in the difficulty value is calculated. If it is still positively correlated, it means that the interfering odor has no effect on the child and the child is more focused. At this time, the current attention evaluation value can be output as a basis for evaluating the child's attention.

[0088] If the positive-negative correlation is negative, it means that the interfering odor has played a role and affected the child's attention. At this time, an interactive plot can be randomly pushed, and then the attention evaluation value calculated during the interactive plot can be output.

[0089] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A self-verified method for monitoring children's attention, characterized in that: The following steps are involved: Step S1: Obtaining the plot requirements of children, obtaining several different types of interactive plots based on the plot requirements and public demand, and extracting the difficulty value and attention threshold of each interactive plot; Step S2: randomly selecting an interactive plot and pushing it to the child for interaction, collecting interaction data during the interaction process, calculating the child's attention value based on the interaction data, and calculating the attention evaluation value based on the difficulty value, the child's attention value, and the attention threshold; Step S3: dynamically selecting the next interactive plot with different difficulty values based on the attention evaluation value, and after calculating the attention evaluation value, determining the positive or negative correlation between the change in the attention evaluation value of the two interactive plots and the change in the difficulty value; Step S4: When the positive-negative correlation is positive, introduce olfactory stimulation into the next interactive plot, and determine the positive-negative correlation between the change in the attention evaluation value and the change in the difficulty value of the two interactive plots; Step S5: When the positive-negative correlation is negative, the attention evaluation value calculated when the child subsequently interacts in the interactive plot is output.

2. A self-verification method for monitoring children's attention according to claim 1, characterized in that: The specific steps of obtaining the plot requirements of the children in step S1 are: Step S11: collecting the child's age, personality, and gender as basic attributes, collecting the child's toy preferences, game modes, and daily video viewing types as behavioral habits, and obtaining the regional characteristics of the child's area as cultural characteristics; Step S12: Build a children's interest profile based on basic attributes, behavioral habits, and cultural characteristics, and determine the children's plot needs based on the children's interest profile.

3. A self-verification method for monitoring children's attention according to claim 1, characterized in that: In step S1, a number of different types of interactive plots are constructed based on plot requirements and public demand, and the specific steps of presetting the corresponding attention threshold according to the difficulty value of each interactive plot are as follows: Step S13: Preset a scenario database, wherein the scenario database contains a number of different types of interactive scenarios, each interactive scenario being marked with a difficulty value and an attention threshold; Step S14: according to the plot requirement, searching the plot database for interactive plots of the same type as the plot requirement and outputting them, and randomly selecting other interactive plots of different types from the plot database and outputting them; Step S15: extract the difficulty value and attention threshold of the output interactive plot.

4. A self-verification method for monitoring children's attention according to claim 1, characterized in that: The specific steps of step S2 are: Step S21: Randomly output an interactive plot with a medium difficulty value from the obtained multiple interactive plots, and display it on the smart terminal for children to interact with; Step S22: directly collecting the in-game operation frequency, task completion speed, and error rate of the child during the interaction process as behavioral data through the smart terminal; Step S23: collecting heart rate variability and galvanic skin response data as physiological data through the wearable device, and tracking eye movement frequency and frown frequency as visual data through the camera; Step S24: normalize the behavioral data, physiological data, and visual data, and sum them after weighting to obtain the child's attention value, and calculate the attention evaluation value based on the difficulty value, the child's attention value, and the attention threshold.

5. A self-verification method for monitoring children's attention according to claim 1 or 4, characterized in that: The expression of the attention evaluation value is: Among them, α is the difficulty value, A is the child's attention value, and B is the attention threshold.

6. A self-verification method for monitoring children's attention according to claim 1, characterized in that: The specific steps of step S3 are: Step S31: When the attention evaluation value is greater than 100%, the difficulty value of the next interactive plot selected is greater than the difficulty value of the previous interactive plot; when the attention evaluation value is less than 100%, the difficulty value of the next interactive plot selected is less than the difficulty value of the previous interactive plot; Step S32: After calculating the attention evaluation value of the next interactive plot, subtract the attention evaluation value and difficulty value of the previous interactive plot from the attention evaluation value and difficulty value of the next interactive plot; Step S33: When the difference between the attention evaluation value and the difficulty value has the same sign, the output is a positive correlation; otherwise, the output is a negative correlation.

7. A self-verification method for monitoring children's attention according to claim 1, characterized in that: The specific steps of step S4 include: Step S41: When the positive-negative correlation is positive and the difficulty value of the next interactive plot is less than the difficulty value of the previous interactive plot, the next interactive plot is obtained, and the specific plot content of the interactive plot is extracted, and a number of trigger nodes are set according to the specific plot content; Step S42: Calculate the child's attention value before the triggering node when the child interacts with the interactive plot, and release the enhanced scent at the triggering node when the child's attention value is less than the attention threshold of the interactive plot; Step S43: average the children's attention values before all trigger nodes, and again determine the positive or negative correlation between the change in the attention evaluation value of the two interactive plots and the change in the difficulty value. If it is still positively correlated, repeat step S4 based on the set number of repetitions until the positive or negative correlation is negative or the number of repetitions ends.

8. A self-verification method for monitoring children's attention according to claim 7, characterized in that: The specific steps of step S4 also include: Step S44: when the positive-negative correlation is positive, and the difficulty value of the next interactive plot is greater than the difficulty value of the previous interactive plot, obtain the next interactive plot; Step S45: When the child interacts with the interactive plot, randomly release a distracting odor, calculate the child's attention evaluation value in the interactive plot, and again determine the positive or negative correlation between the change in the attention evaluation value and the change in the difficulty value between the two interactive plots; Step S46: If the positive-negative correlation is still positive, the current attention evaluation value is output; otherwise, go to step S5.

9. A self-verification method for monitoring children's attention according to claim 8, characterized in that: The enhanced scents include mint, citrus, rosemary, cedar, lavender, and scents related to interactive plots, and the interfering scents include camphor, high-concentration perfume and incense, highly sweet and greasy scents, and scents that do not match the interactive plots.

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