Learning disability intervention method, device, computer equipment, computer readable storage medium and computer program product for smart desk

Abstract

The present application relates to the technical field of smart desks, and in particular to methods, devices, computer equipment, computer-readable storage media, and computer program products for intervention in learning disabilities of smart desks. The present application can output corresponding types of correction prompt information when abnormal learning behaviors of users are detected; the correction prompt information is used to prompt users to correct current behaviors; users are classified into learning disability categories according to the types of correction prompt information and the corresponding number of prompts; pre-stored intervention plans are called based on the learning disability categories to which users belong, and when confirmation of the intervention plan is received, the user's behaviors are intervened according to the intervention plan, which effectively solves the problem of not being able to find the root cause of poor learning effects of users during the learning process.

Description

Technical Field

[0001] The present application relates to the technical field of smart desks, and in particular to a learning disability intervention method, device, computer equipment, computer-readable storage medium, and computer program product for smart desks. Background Art

[0002] A smart desk is a learning system that can integrate a variety of teaching resources and monitor and assist students' learning in real time. Its appearance enables students to develop good learning habits.

[0003] However, existing learning solutions based on smart desks often focus on courseware learning and are unable to discover the root causes of users' poor learning outcomes during the learning process. Summary of the invention

[0004] Based on this, it is necessary to provide a learning disability intervention method, device, computer equipment, computer-readable storage medium and computer program product for a smart desk in response to the above-mentioned technical problems.

[0005] In a first aspect, the present application provides a method for intervening in learning disabilities of a smart desk, the method comprising:

[0006] When abnormal learning behavior of the user is detected, the corresponding type of correction prompt information is output; the correction prompt information is used to prompt the user to correct the current behavior action;

[0007] Classify users’ learning disabilities according to the type of correction prompt information and the corresponding number of prompts;

[0008] A pre-stored intervention plan is called based on the learning disability category to which the user belongs. Upon receiving confirmation of the intervention plan, the user's behavioral actions are intervened according to the intervention plan.

[0009] In one embodiment, the step of outputting corresponding type of correction prompt information when abnormal learning behavior of the user is detected includes:

[0010] Collecting image frame data of user behavior actions at preset intervals, and identifying the user's head and the user's hands based on the image frame data;

[0011] A first feature point is selected on the user's head, a second feature point is selected on the user's hand, and an image area where the first feature point and the second feature point are located is determined according to a plurality of pre-divided image areas; the image area includes a first image area at a first preset distance above the desktop of the smart desk, a second image area at a second preset distance from the desktop when the user has an incorrect sitting posture, and a third image area at a third preset distance from the desktop when the user has a correct sitting posture;

[0012] In response to the second feature point in the first image area, the second image area or the third image area being alternately changed in the first preset number of adjacent image frame data, a first prompt information is output; the first prompt information is used to indicate that the user is distracted;

[0013] In response to the first feature point being continuously located in the first image area, or the first feature point and the second feature point being continuously located in the second image area in the second preset number of adjacent image frame data, outputting a second prompt message; the second prompt message is used to indicate that the user is dozing off;

[0014] In response to the fact that the first feature points in the image frame data of the second preset number of adjacent groups are continuously located in the second image area, a third prompt information is output; the third prompt information is used to indicate that the user has an improper sitting posture.

[0015] In one embodiment, the step of outputting corresponding type of correction prompt information when abnormal learning behavior of the user is detected also includes:

[0016] When the user's pronunciation exceeds a first preset time, the user's voice data is obtained and the voice data is retrieved according to a first preset similarity through a pre-stored database; the pre-stored database includes a plurality of audio learning data covering the subject content of the user's current school age;

[0017] In response to retrieving the corresponding audio data, performing an audio feature comparison between the sound data and the audio learning data according to a second preset similarity;

[0018] If there are audio features that do not match the first preset number, or if it is determined based on the audio learning data that sound data exceeding the second preset number is not a complete sentence, the first prompt message and the fourth prompt message are output; the fourth prompt message is used to indicate that the user has difficulty in reading.

[0019] In one embodiment, the step of classifying the user's learning disability according to the type of correction prompt information and the corresponding number of prompts includes:

[0020] In response to the number of times the first prompt information, the second prompt information or the third prompt information is outputted exceeds the preset number, an inattention prompt information is sent to the user's guardian, and the user is monitored for a second time after the second preset time length of sending the prompt information; if the number of times the first prompt information, the second prompt information or the third prompt information is outputted in the secondary monitoring still exceeds the preset number, a prompt information of attention deficit hyperactivity disorder to be detected is sent to the guardian.

[0021] In one embodiment, the step of classifying the user's learning disability according to the type of correction prompt information and the corresponding number of prompts further includes:

[0022] In response to the number of times the first prompt message and the fourth prompt message are outputted exceeding the preset number of times, prompt messages of inattention and dyslexia are sent to the guardian, and the user is monitored for the second time after the prompt message is sent for the third preset time period; if the number of times the fourth prompt message is outputted in the second monitoring still exceeds the preset number of times, and the number of times the first prompt message is output does not exceed the preset number of times, prompt messages of dyslexia are sent to the guardian; the third preset time period is less than the second preset time period.

[0023] In one embodiment, the steps of calling a pre-stored intervention plan based on the learning disability category to which the user belongs, and intervening in the user's behavior according to the intervention plan upon receiving confirmation of the intervention plan include:

[0024] In response to the guardian replying to the prompt information confirming the attention deficit hyperactivity disorder to be detected, calling the attention intervention strategy to guide the user; the attention intervention strategy includes an attention monitoring mechanism that gradually increases the learning time according to the first preset cycle, and triggering a reward mechanism when the learning time is completed in each cycle; the reward mechanism includes a voice message prompt reward and prompting the guardian to give the reward;

[0025] In response to the guardian replying to confirm the dyslexia prompt information, the preset follow-up reading content is called to guide the user according to the second preset period; the follow-up reading content includes content with fixed rhythm and fixed rhyme.

[0026] In a second aspect, the present application provides a learning disability intervention device for a smart desk, the device comprising:

[0027] The output module is used to output corresponding types of correction prompt information when abnormal learning behavior of the user is detected; the correction prompt information is used to prompt the user to correct the current behavior action;

[0028] A classification module, used to classify users' learning disabilities according to the type of correction prompt information and the corresponding number of prompts;

[0029] The intervention module is used to call the pre-stored intervention plan based on the learning disability category of the user, and intervene in the user's behavior according to the intervention plan when the user confirms the learning disability category.

[0030] In a third aspect, the present application provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the method provided in the first aspect of the present application are implemented.

[0031] In a fourth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the method provided in the first aspect of the present application.

[0032] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the method provided in the first aspect of the present application.

[0033] The learning disability intervention method, device, computer equipment, computer-readable storage medium and computer program product of the above-mentioned smart desk can output correction prompt information corresponding to the abnormal learning behavior when detecting that the user has abnormal learning behavior, and correct the user's abnormal learning behavior in time. If there are multiple corrections for a certain abnormal learning behavior, it indicates that the user may have a learning disability that prevents him from actively and effectively learning. Then, the correlation between the abnormal learning behavior and the corresponding learning disability category is found through the type and corresponding number of correction prompt information. Finally, based on the learning disability category to which the user belongs, with the confirmation of the guardian or the user himself, the user's behavior is intervened according to the intervention plan of the corresponding learning disability category, so that the root cause of the abnormal behavior of the user's daily learning is revealed, which effectively solves the problem of not being able to discover the root cause of the user's poor learning effect during the learning process. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related technologies, the drawings required for use in the embodiments or the related technical descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0035] Figure 1 A flowchart of the overall steps of learning disability intervention in one embodiment;

[0036] Figure 2 A flowchart of steps for identifying abnormal user learning behavior based on image frame data in one embodiment;

[0037] Figure 3 A flowchart of steps for identifying abnormal user learning behavior based on pronunciation in one embodiment;

[0038] Figure 4 The figure is a framework diagram of a learning disability intervention device of a smart desk in one embodiment. DETAILED DESCRIPTION

[0039] In order to make the above-mentioned purposes, features and advantages of the present application more obvious and easy to understand, the specific implementation methods of the present application are described in detail below in conjunction with the accompanying drawings. In the following description, many specific details are set forth to facilitate a full understanding of the present application. However, the present application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar improvements without violating the connotation of the present application, so the present application is not limited by the specific embodiments disclosed below.

[0040] In addition, the terms "first" and "second" are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of the features. In the description of this application, "plurality" means at least two, such as two, three, etc., unless otherwise clearly and specifically defined.

[0041] In an exemplary embodiment, Figure 1 As shown, the present application provides a method for intervening learning disabilities in a smart desk, the method comprising the following steps S12 to S16. Among them:

[0042] Step S12, outputting corresponding type of correction prompt information when abnormal learning behavior of the user is detected; the correction prompt information is used to prompt the user to correct the current behavior.

[0043] Among them, abnormal learning behaviors may include dozing off, distraction, reading difficulties, and improper sitting posture.

[0044] Specifically, abnormal learning behavior is usually easy to correct, but it needs to be corrected continuously. Guardians cannot follow up and correct for a long time, which causes users to gradually form bad learning habits. Therefore, corresponding types of correction prompt information can be output by setting voice prompts or display prompts to correct users in time.

[0045] Step S14, classifying the user's learning disability according to the type of correction prompt information and the corresponding number of prompts.

[0046] Specifically, when multiple corrections still fail to improve the user's abnormal learning behavior, it indicates that the user may have a learning disability in the direction of physical and mental health that causes the user to be unable to effectively control himself. At this time, it is necessary to conduct an in-depth analysis of the abnormal learning behavior and associate the abnormal learning behavior with the type of learning disability according to preset rules to determine the type of learning disability.

[0047] Step S16, calling a pre-stored intervention plan based on the learning disability category to which the user belongs, and upon receiving confirmation of the intervention plan, intervening on the user's behavior according to the intervention plan.

[0048] Specifically, the user's learning disabilities can be corrected through a preset intervention plan, which may include measures corresponding to the type of learning disabilities to guide, motivate and punish the user in accordance with preset scientific guidance methods.

[0049] Specifically, in order to further clarify the feasibility of the intervention plan, the intervention plan can be implemented in advance through confirmation by the user himself or the guardian to avoid incorrect implementation or implementation at an inappropriate time.

[0050] Furthermore, the situation of incorrect implementation includes abnormal learning behavior caused by the user for some special reason.

[0051] The embodiment of the present application provides a learning disability intervention method for a smart desk. The method can output correction prompt information corresponding to the abnormal learning behavior when it is detected that the user has abnormal learning behavior, and correct the user's abnormal learning behavior in time. If there are multiple corrections for a certain abnormal learning behavior, it indicates that the user may have a learning disability that makes it impossible to actively and effectively learn. Then, the correlation between the abnormal learning behavior and the corresponding learning disability category is found through the type of correction prompt information and the corresponding number of times. Finally, based on the learning disability category to which the user belongs, with the confirmation of the guardian or the user himself, the user's behavior is intervened according to the intervention plan of the corresponding learning disability category, thereby revealing the root cause of the abnormal behavior of the user through daily learning, and effectively solving the problem of not being able to discover the root cause of the user's poor learning effect during the learning process.

[0052] In an exemplary embodiment, Figure 2 As shown, the step of outputting corresponding types of correction prompt information when abnormal learning behavior of the user is detected includes the following steps S122a to S126a. Among them:

[0053] Step S122a, collecting image frame data of the user's behavior actions at preset intervals, and identifying the user's head and the user's hands based on the image frame data.

[0054] Specifically, a recognition model may be constructed in advance through image recognition and feature training, so as to recognize the user's head and the user's hands according to the recognition model corresponding to the image frame data.

[0055] Furthermore, by identifying the user's head and hands, the user's current action can be effectively determined to judge abnormal learning behavior.

[0056] Step S124a, select a first feature point on the user's head and a second feature point on the user's hand, and determine the image area where the first feature point and the second feature point are located based on multiple pre-divided image areas; the image area includes a first image area at a first preset distance above the desktop of the smart desk, a second image area at a second preset distance from the desktop when the user is sitting in an incorrect posture, and a third image area at a third preset distance from the desktop when the user is sitting in a correct posture.

[0057] The selection of the first feature point and the second feature point is used to avoid cross-image area distribution caused by a larger area of ​​the user's head or the user's hand, and the image area where the user's head and the user's hand are located cannot be effectively determined.

[0058] Specifically, the first preset distance is smaller than the second preset distance; and the second preset distance is smaller than the third preset distance.

[0059] Exemplarily, the first feature point may be the intersection of the line connecting the user's eyes and the perpendicular bisector, and the second feature point may be the center point of the back of the user's hand.

[0060] It is understandable that if the third image area is selected just above the neck of the user in the correct sitting position, then when the user's chest, back, and waist are bent, the first feature point cannot remain in the third image area, but moves to the second image area and the first image area. When the first feature point and the second feature point remain in the first image area for a long time, it indicates that the user may be dozing off, so the division of the image area can effectively distinguish whether the user's current behavior is abnormal learning behavior.

[0061] Step S126a, in response to the second feature point in the first image area, the second image area or the third image area being alternately changed in the first preset number of adjacent image frame data, outputting a first prompt message; the first prompt message is used to indicate that the user is distracted;

[0062] In response to the first feature point being continuously located in the first image area, or the first feature point and the second feature point being continuously located in the second image area in the second preset number of adjacent image frame data, outputting a second prompt message; the second prompt message is used to indicate that the user is dozing off;

[0063] In response to the fact that the first feature points in the image frame data of the second preset number of adjacent groups are continuously located in the second image area, a third prompt information is output; the third prompt information is used to indicate that the user has an improper sitting posture.

[0064] Specifically, in a normal learning situation, the user's hand movement should be to maintain in the first image area, while the occurrence of alternating movements indicates that the user is playing.

[0065] During the specific implementation process, it was found that when the human body needs to fall asleep, it usually needs to lean on something. Therefore, when the first feature point and the second feature point are continuously located in the second image area, it indicates that the user's head is leaning on the user's hand. If it is maintained for a long time, it means that the user is dozing off.

[0066] In an exemplary embodiment, Figure 3 As shown, the step of outputting corresponding types of correction prompt information when abnormal learning behavior of the user is detected also includes the following steps S122b to S126b. Among them:

[0067] Step S122b, when the user's pronunciation exceeds a first preset duration, the user's voice data is obtained and the voice data is searched through a pre-stored database according to a first preset similarity; the pre-stored database includes multiple audio learning data covering the user's current school subject content.

[0068] Specifically, when the user's pronunciation exceeds the first preset duration, the audio learning data of the subject can be retrieved through the first preset similarity with a lower similarity to determine whether the user is reading aloud. The first preset similarity is set mainly to help the user find the corresponding sentence. If the similarity is set higher, the corresponding sentence in the audio learning data may not be searched because the user has reading difficulties.

[0069] Exemplarily, school-age subject content may include Chinese and English.

[0070] Step S124b, in response to retrieving the corresponding audio data, performing audio feature comparison between the sound data and the audio learning data according to a second preset similarity.

[0071] Specifically, when the corresponding audio data is searched, the audio features are compared by setting a second preset similarity threshold with a higher similarity to determine whether the user's pronunciation is accurate and whether the reading is complete.

[0072] Step S126b, if there are a first preset number of audio features that do not match, or if it is determined based on the audio learning data that the sound data exceeding the second preset number is not a complete sentence, the first prompt message and the fourth prompt message are output; the fourth prompt message is used to indicate that the user has difficulty in reading.

[0073] Specifically, the first preset number of audio features do not match, indicating that the user has non-standard pronunciation, and the second preset number of sound data are not complete sentences, which is used to indicate that the user has difficulty in reading and cannot complete reading or is distracted and has intermittent reading.

[0074] Furthermore, the second preset amount of sound data that is not a complete sentence can be compared with audio features, using the audio learning data as a standard to determine whether the user's current sound data is a complete sentence.

[0075] In an exemplary embodiment, the step of classifying the user's learning disability according to the type of correction prompt information and the corresponding number of prompts includes:

[0076] In response to the number of times the first prompt information, the second prompt information or the third prompt information is outputted exceeds the preset number, an inattention prompt information is sent to the user's guardian, and the user is monitored for a second time after the second preset time length of sending the prompt information; if the number of times the first prompt information, the second prompt information or the third prompt information is outputted in the secondary monitoring still exceeds the preset number, a prompt information of attention deficit hyperactivity disorder to be detected is sent to the guardian.

[0077] Specifically, when the smart desk is unable to correct the user, it may be because the user does not pay enough attention to the prompt information of the smart desk, so the guardian is notified to draw the user's attention.

[0078] Specifically, the second preset time period can be set longer so that a second monitoring can be conducted after the guardian leaves, to prevent interference from the guardian resulting in an inability to clearly identify the category of the learning disability.

[0079] Furthermore, if the number of times the first prompt information, the second prompt information or the third prompt information is output through the secondary monitoring corrected by the guardian still exceeds the preset number, it indicates that the user cannot achieve effective autonomous control and may have attention deficit hyperactivity disorder.

[0080] In an exemplary embodiment, the step of classifying the user's learning disability according to the type of correction prompt information and the corresponding number of prompts further includes:

[0081] In response to the number of times the first prompt message and the fourth prompt message are outputted exceeding the preset number of times, prompt messages of inattention and dyslexia are sent to the guardian, and the user is monitored for the second time after the prompt message is sent for the third preset time period; if the number of times the fourth prompt message is outputted in the second monitoring still exceeds the preset number of times, and the number of times the first prompt message is output does not exceed the preset number of times, prompt messages of dyslexia are sent to the guardian; the third preset time period is less than the second preset time period.

[0082] Specifically, when the number of times the first prompt information and the fourth prompt information are output simultaneously exceeds the preset number, it means that the user may have hyperactivity or dyslexia, and thus a judgment is made through guardian intervention. If after the guardian intervenes, the number of times the fourth prompt information is output still exceeds the preset number, and the number of times the first prompt information is output does not exceed the preset number, it means that the user has dyslexia and the preset intervention cannot be achieved, otherwise it means that attention deficit hyperactivity disorder may exist.

[0083] Furthermore, the third preset time length can be set shorter, and monitoring can be performed without the guardian leaving, so that the guardian's intervention in attention deficit is effective, thereby making a judgment on dyslexia.

[0084] In an exemplary embodiment, the steps of calling a pre-stored intervention plan based on the learning disability category to which the user belongs, and intervening in the user's behavior according to the intervention plan upon receiving confirmation of the intervention plan include:

[0085] In response to the guardian replying to the prompt information confirming the attention deficit hyperactivity disorder to be detected, calling the attention intervention strategy to guide the user; the attention intervention strategy includes an attention monitoring mechanism that gradually increases the learning time according to the first preset cycle, and triggering a reward mechanism when the learning time is completed in each cycle; the reward mechanism includes a voice message prompt reward and prompting the guardian to give the reward;

[0086] In response to the guardian replying to confirm the dyslexia prompt information, the preset follow-up reading content is called to guide the user according to the second preset period; the follow-up reading content includes content with fixed rhythm and fixed rhyme.

[0087] Specifically, attention deficit hyperactivity disorder can be gradually improved through behavioral intervention. Therefore, by gradually increasing the learning time within the first preset period for correction, it is ensured that users can effectively improve their attention. During the learning period, a reward mechanism is set up to encourage users to concentrate, which is in line with the guidance method for attention deficit hyperactivity disorder.

[0088] Furthermore, in the case that users have reading difficulties, the users can be trained to read through guiding content with unchanged rhythm and rhyme, thereby improving their reading ability.

[0089] It should be understood that, although the steps in the flowcharts involved in the above embodiments are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence according to the order indicated by the arrows. Unless there is a clear explanation in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a part of the steps in the flowcharts involved in the above embodiments may include multiple steps or multiple stages, and these steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily carried out in sequence, but can be executed in turn or alternately with other steps or at least a part of the steps or stages in other steps.

[0090] Based on the same inventive concept, the embodiment of the present application also provides a learning disability intervention device for a smart desk for implementing the learning disability intervention method for a smart desk involved above. The implementation scheme for solving the problem provided by the device is similar to the implementation scheme recorded in the above method, so the specific limitations in the embodiments of the learning disability intervention device for one or more smart desks provided below can refer to the limitations of the learning disability intervention method for a smart desk above, and will not be repeated here.

[0091] Second, as Figure 4 As shown, the present application also provides a learning disability intervention device 400 for a smart desk, the device comprising:

[0092] The output module 401 is used to output corresponding type of correction prompt information when abnormal learning behavior of the user is detected; the correction prompt information is used to prompt the user to correct the current behavior action;

[0093] Classification module 402, used to classify the learning disability of the user according to the type of correction prompt information and the corresponding number of prompts;

[0094] The intervention module 403 is used to call a pre-stored intervention plan based on the learning disability category to which the user belongs, and intervene in the user's behavior according to the intervention plan when the user confirms the learning disability category.

[0095] In a third aspect, the present application also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the steps of the learning disability intervention method for a smart desk as described above are implemented.

[0096] In a fourth aspect, the present application also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of a learning disability intervention method for a smart desk as described above.

[0097] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps of the learning disability intervention method for a smart desk as described above.

[0098] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to the memory, database or other medium used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetoresistive random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. As an illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The database involved in each embodiment provided in this application may include at least one of a relational database and a non-relational database. Non-relational databases may include distributed databases based on blockchains, etc., but are not limited to this. The processor involved in each embodiment provided in this application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, etc., but are not limited to this.

[0099] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0100] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the present application shall be subject to the attached claims.

Claims

1. A learning disability intervention method for a smart desk, characterized in that: The method comprises: When it is detected that the user has abnormal learning behavior, a corresponding type of correction prompt information is output; the correction prompt information is used to prompt the user to correct the current behavior action; the step of outputting the corresponding type of correction prompt information when it is detected that the user has abnormal learning behavior includes: collecting image frame data of the user's behavior action at a preset interval, and identifying the user's head and the user's hand according to the image frame data; selecting a first feature point on the user's head and a second feature point on the user's hand, and determining the image area where the first feature point and the second feature point are located based on a plurality of pre-divided image areas; the image area includes a first image area that is a first preset distance above the desktop of the smart desk, a second image area that is a second preset distance from the desktop of the smart desk when the user has an incorrect sitting posture, and a second image area that is a second preset distance from the desktop of the smart desk when the user has a correct sitting posture. a third image area at a third preset distance from the desktop; in response to the second feature point alternating in the first image area, the second image area or the third image area in the image frame data adjacent to the first preset number, a first prompt information is output; the first prompt information is used to indicate that the user is distracted; in response to the first feature point continuously being located in the first image area, or the first feature point and the second feature point continuously being located in the second image area in the image frame data adjacent to the second preset number, a second prompt information is output; the second prompt information is used to indicate that the user is dozing; in response to the first feature point continuously being located in the second image area in the image frame data adjacent to the second preset number, a third prompt information is output; the third prompt information is used to indicate that the user is sitting in an improper posture; Classifying the user's learning disability according to the type of the correction prompt information and the corresponding number of prompts; A pre-stored intervention plan is called based on the learning disability category to which the user belongs, and upon receiving confirmation of the intervention plan, the user's behavior is intervened in accordance with the intervention plan; the categories of learning disabilities include attention deficit hyperactivity disorder and dyslexia.

2. The method according to claim 1, characterized in that The step of outputting corresponding type of correction prompt information when abnormal learning behavior of the user is detected also includes: When the user's pronunciation exceeds a first preset time, obtaining the user's voice data and searching the voice data according to a first preset similarity through a pre-stored database; the pre-stored database includes a plurality of audio learning data covering the subject content of the user's current school age; In response to retrieving the corresponding audio learning data, performing audio feature comparison between the sound data and the audio learning data according to a second preset similarity; If there are a first preset number of audio features that do not match, or if it is determined based on the audio learning data that the sound data exceeding a second preset number is not a complete sentence, the first prompt information and the fourth prompt information are output; the fourth prompt information is used to indicate that the user has difficulty in reading.

3. The method according to claim 2, characterized in that The step of classifying the user's learning disability according to the type of the correction prompt information and the corresponding number of prompts includes: In response to the number of times the first prompt information, the second prompt information or the third prompt information is outputted exceeds the preset number of times, a prompt information of inattention is sent to the user's guardian, and the user is monitored for a second time after the second preset time length of time of sending the prompt information; if the number of times the first prompt information, the second prompt information or the third prompt information is outputted in the secondary monitoring still exceeds the preset number of times, a prompt information of attention deficit hyperactivity disorder to be detected is sent to the guardian.

4. The method according to claim 3, characterized in that The step of classifying the user's learning disability according to the type of the correction prompt information and the corresponding number of prompts also includes: In response to the number of times the first prompt message and the fourth prompt message are outputted exceeding the preset number of times, prompt messages of inattention and dyslexia are sent to the guardian, and the user is monitored for a second time after the prompt message is sent for a third preset time period; if the number of times the fourth prompt message is output in the second monitoring still exceeds the preset number of times, and the number of times the first prompt message is output does not exceed the preset number of times, prompt messages of dyslexia are sent to the guardian; the third preset time period is less than the second preset time period.

5. The method according to claim 4, characterized in that The step of calling a pre-stored intervention plan based on the learning disability category to which the user belongs, and intervening in the user's behavior according to the intervention plan upon receiving confirmation of the intervention plan includes: In response to the guardian replying to confirm the prompt information of the attention deficit hyperactivity disorder to be detected, calling an attention intervention strategy to guide the user; the attention intervention strategy includes an attention monitoring mechanism that gradually increases the learning time according to a first preset cycle, and triggering a reward mechanism when the learning time is completed in each cycle; the reward mechanism includes a voice message prompt reward and prompting the guardian to give the reward; In response to the guardian replying and confirming the dyslexia prompt information, the preset follow-up reading content is called to guide the user according to a second preset period; the follow-up reading content includes content with a fixed rhythm and a fixed rhyme.

6. A learning disability intervention device for a smart desk, characterized in that: Based on the method according to any one of claims 1 to 5, the device comprises: An output module, used to output corresponding type of correction prompt information when abnormal learning behavior of the user is detected; the correction prompt information is used to prompt the user to correct the current behavior action; A classification module, used to classify the learning disabilities of users according to the type of correction prompt information and the corresponding number of prompts; The intervention module is used to call a pre-stored intervention plan based on the learning disability category to which the user belongs, and intervene in the user's behavior according to the intervention plan when the user confirms the learning disability category.

7. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 5 are implemented.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

9. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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