Intelligent management system for comprehensive speech rehabilitation services based on mini-programs and cloud platforms

Abstract

The present invention discloses an intelligent management system for comprehensive speech rehabilitation services based on a mini-program and a cloud platform, and belongs to the technical field of service information management. The intelligent management system is used to solve the technical problems of poor overall effect of autonomous supervision and poor adaptive adjustment and optimization effect in speech rehabilitation services in existing solutions. The corresponding single response degree is obtained by digitally processing and calculating various data of each real-time response of the target, and the single response degree is analyzed for data to determine the mark corresponding to the training question of the response. The corresponding real-time response degree is obtained by real-time integration and calculation of the processing and analysis results of local single real-time responses, and the real-time response degree is analyzed for data to determine the overall training state corresponding to the target response, and the training questions of the target basic speech rehabilitation training content are adaptively and dynamically adjusted according to the analysis results.

Description

Technical Field

[0001] The present invention relates to the technical field of service information management, and in particular to an intelligent management system for comprehensive speech rehabilitation services based on mini-programs and cloud platforms. Background Art

[0002] Comprehensive speech rehabilitation service is a rehabilitation treatment method for patients with speech, language, cognitive, hearing and other communication disorders, aiming to help patients improve or restore their communication ability and cognitive function.

[0003] When implemented, the existing comprehensive speech rehabilitation service management solution cannot monitor and digitize users' real-time responses, nor can it monitor users' real-time overall training status and adaptively and dynamically adjust speech rehabilitation service content based on the monitoring results. This results in poor overall autonomous monitoring effects during speech rehabilitation services and poor adaptive adjustment and optimization effects. Summary of the invention

[0004] The purpose of the present invention is to provide an intelligent management system for comprehensive speech rehabilitation services based on mini-programs and cloud platforms, which is used to solve the technical problems of poor overall effect of autonomous supervision and poor adaptive adjustment and optimization effect in speech rehabilitation services in existing solutions.

[0005] The purpose of the present invention can be achieved through the following technical solutions:

[0006] The speech rehabilitation comprehensive service intelligent management system based on the mini program and cloud platform includes the mini program side and the cloud management platform side. The mini program side includes the speech rehabilitation test supervision module and the speech rehabilitation test service management module;

[0007] The speech rehabilitation test supervision module is used to supervise and analyze the real-time responses of the target during the speech rehabilitation training process, and to digitally process each real-time response to obtain the corresponding single response degree, and to determine the single response processing sequence of the responses corresponding to different training questions according to the single response degree; wherein the single response processing sequence includes the single response degrees corresponding to different training questions;

[0008] The speech rehabilitation test service management module is used to process and analyze the real-time response status of the target's basic speech rehabilitation training content based on a single response processing sequence, and dynamically adjust the training questions in the speech rehabilitation training content according to the analysis results; including:

[0009] Among them, when processing and analyzing the real-time response status of the target's basic speech rehabilitation training content, the single response processing sequence is traversed and data processing is performed to obtain the corresponding real-time response degree; the numerical value of the calculated real-time response degree is analyzed to obtain the response verification analysis result, and the training questions of the basic speech rehabilitation training content are dynamically adjusted according to the response verification analysis result.

[0010] Preferably, the display timestamp corresponding to the training questions in the basic speech rehabilitation training content is obtained when the mini program side displays the training questions; and the start reply timestamp when the target starts to reply and the end reply timestamp when the target ends to reply are obtained through the mini program side;

[0011] Calculate the time difference between the start reply timestamp and the display timestamp and mark it as the first time difference T1i; and calculate the time difference between the end reply timestamp and the start reply timestamp and mark it as the second time difference T2i; i=1, 2, 3, ..., n; n is a positive integer; i is a different training topic in the basic speech rehabilitation training content.

[0012] Preferably, when each real-time response of the target is digitally processed, the first time difference T1i and the second time difference T2i obtained by calculation are analyzed by the response recognition piecewise function and the single response degree corresponding to the training question is output; the single response degree includes a value of 0 or non-0;

[0013] According to the single reply degree with a value of 0, the corresponding training question is marked as a normal training question, and the single reply degree with a value other than 0 is marked as an abnormal training question;

[0014] The calculated single response degrees are sorted and combined according to the numbers of the corresponding training questions to obtain a single response processing sequence and uploaded to the cloud management platform in real time.

[0015] Preferably, the expression of the reply identification piecewise function is ; In the formula, DHi is the single response degree corresponding to the training question; Di is the response result corresponding to the training question, including a value of 0 or 1; T´1i is the standard reaction time difference corresponding to the training question, and T´2i is the standard reply time difference corresponding to the training question; α and β are different weight coefficients, and α+β=1.

[0016] Preferably, the single reply processing sequence is traversed and the total number of single reply degree anomalies with non-zero values ​​is counted, and the first real-time reply formula is used to calculate the total number of single reply degree anomalies. Calculate and obtain the first real-time response degree SH1 corresponding to the basic speech rehabilitation training content of the target; where A is the standard abnormal rate; N1 is the total number of abnormal questions answered by the target; and N is the total number of questions answered by the target.

[0017] Preferably, the single reply processing sequence is traversed and all single reply degrees with non-zero values ​​are obtained, and the values ​​corresponding to all single reply degrees with non-zero values ​​are obtained and marked as DH´j, j=1, 2, 3, ..., m; m is a positive integer, and m≤n; through the second real-time reply formula The second real-time recovery degree SH2 corresponding to the basic speech rehabilitation training content of the target is calculated; wherein B is the standard abnormal recovery value.

[0018] Preferably, when dynamically adjusting the training topics in the speech rehabilitation training content according to the first real-time response degree and / or the second real-time response degree;

[0019] If the value of the first real-time response degree and / or the second real-time response degree is 0, a response verification normal instruction is generated and a training question is maintained for the existing basic speech rehabilitation training content;

[0020] If the value of the first real-time response degree and / or the second real-time response degree is 1, a response verification abnormality instruction is generated and the training questions of the existing basic speech rehabilitation training content are adjusted.

[0021] Preferably, when adjusting the training questions of the existing basic speech rehabilitation training content, the historical response data corresponding to the target is obtained, and the difficulty type and training results corresponding to the training questions of the last response in the historical response data are obtained and analyzed;

[0022] If the training result is incomplete, the training topic of the basic speech rehabilitation training content is adjusted to the first adjustment training topic;

[0023] If the training result is completed, the training topic of the basic speech rehabilitation training content is adjusted to the second adjusted training topic.

[0024] Preferably, the first adjusted training topic is the last reply to other training topics of the same difficulty type; the second adjusted training topic is the last reply to other training topics of a higher difficulty type.

[0025] Compared with the existing solutions, the present invention achieves the following beneficial effects:

[0026] The present invention calculates the corresponding single response degree by digitally processing various data of each real-time response of the target, and determines the label corresponding to the training question of the response by performing data analysis on the single response degree, so as to provide reliable specific response data support for the subsequent real-time response status analysis of the target, thereby improving the diversity and availability of real-time response monitoring, processing and analysis of the target.

[0027] The present invention obtains the corresponding real-time response degree by real-time integration and calculation of the processing and analysis results of local single real-time responses, and performs data analysis on the real-time response degree to determine the overall training state corresponding to the target response, and at the same time adaptively and dynamically adjusts the training questions of the target basic speech rehabilitation training content according to the analysis results, thereby improving the overall effect of autonomous supervision of different targets during training and the adaptive adjustment and optimization effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The present invention will be further described below in conjunction with the accompanying drawings.

[0029] Figure 1 This is a module block diagram of the speech rehabilitation comprehensive service intelligent management system based on mini-programs and cloud platforms of the present invention.

[0030] Figure 2 This is a flowchart of the operation of the speech rehabilitation comprehensive service intelligent management system based on the mini-program and cloud platform of the present invention.

[0031] Figure 3 A flowchart of a single reply processing sequence in the present invention. DETAILED DESCRIPTION

[0032] 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.

[0033] Example 1: Figure 1 to Figure 2 As shown, the present invention is a speech rehabilitation comprehensive service intelligent management system based on a mini program and a cloud platform, including a mini program end and a cloud management platform end, and the mini program end includes a speech rehabilitation test supervision module and a speech rehabilitation test service management module;

[0034] The speech rehabilitation test supervision module is used to supervise and analyze the real-time responses of the target during speech rehabilitation training, and to digitally process each real-time response to obtain the corresponding single response degree, and to determine the single response processing sequence of the corresponding responses to different training questions according to the single response degree; including:

[0035] like Figure 3 As shown, when the target starts speech rehabilitation training through the mini program, a supervision instruction is generated. The target is the user who needs speech rehabilitation training, and the whole process of the target replying to the randomly generated basic speech rehabilitation training content in real time is supervised according to the supervision instruction;

[0036] Obtain the display timestamp corresponding to the training questions in the basic speech rehabilitation training content displayed on the mini program side; and obtain the start reply timestamp when the target starts to reply and the end reply timestamp when the target ends to reply through the mini program side; where the units corresponding to different types of timestamps are all seconds;

[0037] It should be explained that the basic speech rehabilitation training content includes a number of training questions of the same difficulty, and the basic speech rehabilitation training can be randomly generated according to the historical training data of the target;

[0038] The target's reply may be a voice reply or a manually selected answer reply, and the manually selected answers may be at least two; when a voice reply is made, the voice content is recognized and judged using the existing conventional voice recognition technology, and the specific recognition steps are not described in detail here;

[0039] Calculate the time difference between the start reply timestamp and the display timestamp and mark it as the first time difference T1i; and calculate the time difference between the end reply timestamp and the start reply timestamp and mark it as the second time difference T2i; i=1, 2, 3, ..., n; n is a positive integer; i is a different training topic in the basic speech rehabilitation training content;

[0040] When each real-time response of the target is digitally processed, the first time difference T1i and the second time difference T2i obtained by calculation are analyzed by the response recognition piecewise function and the single response degree corresponding to the training question is output;

[0041] Among them, the expression of the reply recognition piecewise function is ; Wherein, DHi is the single reply degree corresponding to the training question; Di is the reply result corresponding to the training question, including a value of 0 or 1; a value of 0 indicates that the reply result is correct, and a value of 1 indicates that the reply result is incorrect; T´1i is the standard reaction time difference corresponding to the training question, and T´2i is the standard reply time difference corresponding to the training question; α and β are different weight coefficients, and α+β=1, and the specific values ​​are not limited and can be customized according to the actual application situation; the standard reaction time difference and the standard reply time difference can be determined according to the median of all reaction times corresponding to all targets in history, the median of all reaction times, or according to the design requirement data corresponding to the training question;

[0042] The single reply degree contains 0 or non-zero values;

[0043] It should be noted that the single response degree is used to integrate the reaction time difference dimension data and the response time difference dimension data of each real-time response of the target to digitally represent the single response status; the larger the single response degree, the worse the single response status of the target corresponding to the training question;

[0044] According to the single reply degree with a value of 0, the corresponding training question is marked as a normal training question, and the single reply degree with a value other than 0 is marked as an abnormal training question;

[0045] The calculated single response degrees are sorted and combined according to the numbers of the corresponding training questions to obtain a single response processing sequence and uploaded to the cloud management platform in real time;

[0046] In the embodiment of the present invention, the corresponding single response degree is calculated by digitally processing various data of each real-time response of the target, and the label corresponding to the training question of the response is determined by performing data analysis on the single response degree. This can provide reliable specific response data support for subsequent real-time response status analysis of the target, thereby improving the diversity and availability of real-time response monitoring, processing and analysis of the target.

[0047] The speech rehabilitation test service management module is used to process and analyze the real-time response status of the target's basic speech rehabilitation training content based on a single response processing sequence, and dynamically adjust the training questions in the speech rehabilitation training content according to the analysis results; including:

[0048] When processing and analyzing the real-time response status of the target's basic speech rehabilitation training content, two data processing schemes are included. In actual application, the two schemes can be used either one or both;

[0049] Solution 1: Traverse the single reply processing sequence and count the total number of single reply degree anomalies with non-zero values, and use the first real-time reply formula Calculate and obtain the first real-time response degree SH1 corresponding to the basic speech rehabilitation training content of the target; where A is the standard abnormality rate, which can be determined based on the previous test data corresponding to the basic speech rehabilitation training content, or based on the median of all abnormality rates corresponding to the history of the basic speech rehabilitation training content; N1 is the total number of abnormal questions answered by the target; N is the total number of questions answered by the target;

[0050] Solution 2: Traverse the single reply processing sequence and obtain all the single reply degrees with non-zero values, and obtain the corresponding values ​​of all the single reply degrees with non-zero values ​​and mark them as DH´j, j=1, 2, 3, ..., m; m is a positive integer, and m≤n; j is the single reply degree with different non-zero values; through the second real-time reply formula Calculate and obtain the second real-time recovery degree SH2 corresponding to the basic speech rehabilitation training content of the target; where B is the standard abnormal recovery value, which can be determined based on the median of all abnormal recovery values ​​corresponding to the basic speech rehabilitation training content in history;

[0051] It should be noted that in the embodiment of the present invention, the single response degrees corresponding to different training questions of the previous target are integrated and calculated through different schemes to obtain the corresponding real-time response degrees; the real-time response degrees are used to digitally represent the overall training state when the target is subjected to speech rehabilitation training; and the single response degrees corresponding to the different training questions in the previous stage are expanded and utilized;

[0052] When dynamically adjusting the training questions in the speech rehabilitation training content according to the first real-time response degree and / or the second real-time response degree;

[0053] If the value of the first real-time response degree and / or the second real-time response degree is 0, a response verification normal instruction is generated and a training question is maintained for the existing basic speech rehabilitation training content;

[0054] If the value of the first real-time response degree and / or the second real-time response degree is 1, a response verification abnormality instruction is generated and the training questions of the existing basic speech rehabilitation training content are adjusted;

[0055] In the embodiment of the present invention, by identifying and analyzing the real-time response degree, the training content of the dynamic target can be adaptively adjusted in a timely and efficient manner according to the analysis result, thereby improving the reliability of autonomous identification of speech rehabilitation training and the flexibility of adaptive adjustment;

[0056] Specifically, when adjusting the training questions of the existing basic speech rehabilitation training content, the historical response data corresponding to the target is obtained, and the difficulty type and training results corresponding to the training questions of the last response in the historical response data are obtained and analyzed;

[0057] Among them, the training questions of the basic speech rehabilitation training content can be randomly generated according to the difficulty type corresponding to the training question of the last reply in the historical reply data, including but not limited to the same difficulty type, a lower difficulty type and a higher difficulty type, for consolidating and improving the historical training content;

[0058] If the training result is incomplete, the training questions of the basic speech rehabilitation training content are adjusted to the first adjusted training questions; the first adjusted training questions are other training questions of the same difficulty type as the last reply; the difficulty types include but are not limited to elementary difficulty, lower-intermediate difficulty, intermediate difficulty, upper-intermediate difficulty, and advanced difficulty; the voice reply corresponding to the training question can also be adjusted to a manual answer selection reply, and the manual answer selection reply can be adjusted to a voice reply;

[0059] If the training result is completed, the training questions of the basic speech rehabilitation training content are adjusted to the second adjusted training questions; wherein the second adjusted training questions are other training questions of a higher difficulty level corresponding to the last reply.

[0060] In the embodiment of the present invention, the corresponding real-time response degree is obtained by real-time integration and calculation of the processing and analysis results of the local single real-time response, and the real-time response degree is subjected to data analysis to determine the overall training state corresponding to the target response. At the same time, the training questions of the target basic speech rehabilitation training content are adaptively and dynamically adjusted according to the analysis results, thereby improving the overall effect of autonomous supervision of different targets during training and the adaptive adjustment and optimization effect.

[0061] Embodiment 2: Based on the technical solution of embodiment 1, it also includes a speech rehabilitation test content supervision module;

[0062] The speech rehabilitation test content supervision module is used to supervise the overall initial training allocation status corresponding to the basic speech rehabilitation training content for different targets, and dynamically and adaptively adjust the initial training allocation plan of subsequent basic speech rehabilitation training content according to the supervision results; including:

[0063] Count the total number of times Nf of the initial training allocation corresponding to the basic speech rehabilitation training content, and the total number of times Nt of adjustments corresponding to the abnormal reply verification instructions for the basic speech rehabilitation training content with different goals, and use the formula Calculate and obtain the implementation status SZ of the basic speech rehabilitation training content corresponding to the initial training allocation; where C is the standard implementation status value; it can be determined based on the design requirement data corresponding to the basic speech rehabilitation training content;

[0064] If the implementation state degree is not greater than 0, a normal instruction for training allocation is generated and the initial training allocation plan of the existing basic speech rehabilitation training content is maintained;

[0065] Otherwise, a training allocation abnormality instruction is generated and the initial training allocation plan of the existing basic speech rehabilitation training content is adjusted; wherein the specific content of the initial training allocation plan is adjusted according to the actual initial training allocation rule;

[0066] In an embodiment of the present invention, the speech rehabilitation test content supervision module further supervises and analyzes the initial training allocation status of the basic speech rehabilitation training content from an overall dimension, and dynamically and adaptively adjusts the basic speech rehabilitation training content according to the analysis results, thereby improving the supervision effect and adaptive adjustment optimization effect of the training question dimension.

[0067] In addition, the formulas involved in the above are all dimensionless and numerical calculations. They are a formula that is closest to the actual situation obtained by collecting a large amount of data and simulating it with simulation software.

[0068] In the several embodiments provided by the present invention, it should be understood that the disclosed system can be implemented in other ways. For example, the above-described embodiments of the invention are only illustrative, for example, the division of modules is only a logical function division, and there may be other division methods in actual implementation.

[0069] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0070] In addition, each functional module in each embodiment of the present invention may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of hardware plus software functional modules.

[0071] It is obvious to a person skilled in the art that the present invention is not limited to the details of the exemplary embodiments described above, and that the present invention can be implemented in other specific forms without departing from the essential characteristics of the present invention.

[0072] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the spirit and scope of the technical solution of the present invention.

Claims

1. An intelligent management system for comprehensive speech rehabilitation services based on mini-programs and cloud platforms, characterized by: It includes the mini program side and the cloud management platform side. The mini program side includes the speech rehabilitation test supervision module and the speech rehabilitation test service management module; The speech rehabilitation test supervision module is used to supervise and analyze the real-time responses of the target during the speech rehabilitation training process, and to digitally process each real-time response to obtain the corresponding single response degree, and to determine the single response processing sequence of the responses corresponding to different training questions according to the single response degree; wherein, the corresponding display timestamp when the mini program side displays the training questions in the basic speech rehabilitation training content is obtained; and the start response timestamp when the target starts to respond and the end response timestamp when the target ends to respond are obtained through the mini program side; Calculate the time difference between the start reply timestamp and the display timestamp and mark it as the first time difference T1i; and calculate the time difference between the end reply timestamp and the start reply timestamp and mark it as the second time difference T2i; i=1, 2, 3, ..., n; n is a positive integer; i is a different training topic in the basic speech rehabilitation training content; When each real-time response of the target is digitally processed, the first time difference T1i and the second time difference T2i obtained by calculation are analyzed by the response recognition piecewise function and the single response degree corresponding to the training question is output; the single response degree includes a value of 0 or non-0; According to the single reply degree with a value of 0, the corresponding training question is marked as a normal training question, and the single reply degree with a value other than 0 is marked as an abnormal training question; The calculated single response degrees are sorted and combined according to the numbers of the corresponding training questions to obtain a single response processing sequence and uploaded to the cloud management platform in real time; The speech rehabilitation test service management module is used to process and analyze the real-time response status of the target's basic speech rehabilitation training content based on a single response processing sequence, and dynamically adjust the training questions in the speech rehabilitation training content according to the analysis results; When the real-time response status of the target's basic speech rehabilitation training content is processed and analyzed, the single response processing sequence is traversed and the total number of single response degree anomalies with non-zero values ​​is counted, and the first real-time response formula is used to calculate the number of abnormal single response degrees. Calculate and obtain the first real-time response degree SH1 corresponding to the basic speech rehabilitation training content of the target; where A is the standard abnormal rate; N1 is the total number of abnormal questions answered by the target; N is the total number of questions answered by the target; And, traverse the single reply processing sequence and obtain all the single reply degrees whose values ​​are not 0, and obtain the values ​​corresponding to all the single reply degrees whose values ​​are not 0 and mark them as DH´j, j=1, 2, 3, ..., m; m is a positive integer, and m≤n; through the second real-time reply formula Calculate and obtain the second real-time recovery degree SH2 corresponding to the basic speech rehabilitation training content of the target; where B is the standard abnormal recovery value; When dynamically adjusting the training questions in the speech rehabilitation training content according to the first real-time response degree and / or the second real-time response degree; If the value of the first real-time response degree and / or the second real-time response degree is 0, a response verification normal instruction is generated and a training question is maintained for the existing basic speech rehabilitation training content; If the value of the first real-time response degree and / or the second real-time response degree is 1, a response verification abnormality instruction is generated and the training questions of the existing basic speech rehabilitation training content are adjusted; When adjusting the training questions of the existing basic speech rehabilitation training content, obtain the historical response data corresponding to the target, and obtain and analyze the difficulty type and training results corresponding to the training questions of the last response in the historical response data; If the training result is incomplete, the training topic of the basic speech rehabilitation training content is adjusted to the first adjustment training topic; If the training result is completed, the training topic of the basic speech rehabilitation training content is adjusted to the second adjusted training topic.

2. The speech rehabilitation comprehensive service intelligent management system based on mini-programs and cloud platforms according to claim 1 is characterized in that: The expression for the piecewise function of the reply identification is ; Where DHi is the single response degree corresponding to the training question; Di is the response result corresponding to the training question, including a value of 0 or 1; T´1i is the standard reaction time difference corresponding to the training question, and T´2i is the standard reply time difference corresponding to the training question; α and β are different weight coefficients, and α+β=1.

3. The speech rehabilitation comprehensive service intelligent management system based on mini-programs and cloud platforms according to claim 1 is characterized in that: The first adjustment training topic is the last reply to other training topics of the same difficulty type; the second adjustment training topic is the last reply to other training topics of a higher difficulty type.

Images