CN115938540A - Scene interaction children rehabilitation training system based on cloud platform - Google Patents
Scene interaction children rehabilitation training system based on cloud platform Download PDFInfo
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Abstract
The invention provides a scene interaction children rehabilitation training system based on a cloud platform, which comprises: a user terminal; a cloud platform to: receiving and analyzing the symptom information of the user sent by the user terminal to obtain a corresponding treatment strategy; generating a treatment instruction according to the treatment strategy, and sending the treatment instruction to the scene interaction rehabilitation training module; and the scene interaction rehabilitation training module is used for receiving the treatment instruction and determining a target scene interaction strategy based on the treatment instruction. By utilizing the cloud platform to perform scene interaction, scientific and targeted rehabilitation training is performed on children, and the effect of optimizing the rehabilitation training is achieved.
Description
Technical Field
The invention relates to the technical field of rehabilitation training, in particular to a scene interaction child rehabilitation training system based on a cloud platform.
Background
At present, according to the result of the sixth census, about 5000 million children development disorder patients in China are present in 0-18 years old people in China. Wherein, about 300 million patients with autism spectrum disorder, about 2100 million patients with attention deficit hyperactivity disorder and about 1500 million patients with language and language disorders. The data show that a huge number of children with rehabilitation requirements exist in China, however, the children not only have few educational opportunities, but also bring huge economic burden to families due to long-term rehabilitation training. The family members not only spend a great deal of time and energy on nursing the children, but also bear great psychological and economic pressure. In addition, the number of children rehabilitation doctors is small in China and the development of rehabilitation medicine is in an immature stage. Various factors make the rehabilitation training effect of children unsatisfactory. How to scientifically and pertinently carry out on-line rehabilitation training on children, and the problem to be solved urgently in China is that the on-line rehabilitation training effect is improved and the pressure of parents is relieved.
Disclosure of Invention
The present invention is directed to solving, at least to some extent, one of the technical problems in the art described above. Therefore, the invention aims to provide a scene interaction children rehabilitation training system based on a cloud platform, which aims to perform scene interaction by using the cloud platform, perform scientific and targeted rehabilitation training on children and achieve the effect of optimizing the rehabilitation training.
In order to achieve the above object, an embodiment of the present invention provides a scene interaction children rehabilitation training system based on a cloud platform, which is characterized by comprising:
a user terminal;
a cloud platform to:
receiving and analyzing symptom information of a user sent by a user terminal to obtain a corresponding treatment strategy;
generating a treatment instruction according to the treatment strategy, and sending the treatment instruction to the scene interaction rehabilitation training module;
and the scene interaction rehabilitation training module is used for receiving the treatment instruction and determining a target scene interaction strategy based on the treatment instruction.
According to some embodiments of the invention, the cloud platform comprises:
the first receiving module is used for receiving the symptom information of the user sent by the user terminal;
an analysis module to:
extracting keywords from the symptom information of the user to obtain symptom keywords;
matching the symptom keywords with a plurality of preset symptom keywords in a database respectively, and determining treatment strategies corresponding to the matched preset symptom keywords;
and the first sending module is used for generating a corresponding treatment instruction based on the treatment strategy and sending the treatment instruction to the scene interaction rehabilitation training module.
According to some embodiments of the invention, the analysis module comprises:
the preprocessing module is used for acquiring a text comprising the symptom information of the user and preprocessing the text to obtain a text to be extracted;
the weight determining module is used for determining the target weight of the description keyword in the text to be extracted;
and the keyword determining module is used for sequencing the description keywords corresponding to the target weight from large to small, and selecting the description keywords with the preset number as the symptom keywords.
According to some embodiments of the invention, the pre-processing module comprises:
a first processing module to:
acquiring a text including symptom information of the user as a first text;
identifying and deleting characters matched with preset characters in the first text to obtain a second text;
a second processing module to:
utilizing a jieba word segmentation device to segment words of the second text, and spacing the obtained segmented words through blank spaces to further obtain a third text;
and carrying out duplication elimination processing on the third text to obtain a text to be extracted.
According to some embodiments of the invention, the weight determination module comprises:
a first determining module to:
extracting keywords from a text to be extracted to obtain a plurality of description keywords;
clustering semantics corresponding to the description keywords to obtain a plurality of description keyword sets;
determining a clustering center corresponding to each description keyword set, and determining a target clustering center according to the clustering center corresponding to each description keyword set;
respectively calculating the distance between the description keyword set and the target clustering center to obtain corresponding distance values;
and describing the target weight of the keyword based on a preset distance-weight setting rule.
According to some embodiments of the invention, the context-interactive rehabilitation training module comprises:
a second receiving module for receiving the treatment instruction; the treatment instruction comprises the treatment strategy and an instruction for analyzing the treatment strategy;
the analysis module is used for executing the instruction for analyzing the treatment strategy and obtaining a corresponding scene interaction strategy alternative set;
and the operation module is used for receiving a selection instruction input by a user, determining a target scene interaction strategy in the scene interaction strategy alternative set and executing the target scene interaction strategy.
According to some embodiments of the invention, the parsing module comprises:
the first execution module is used for executing the instruction for analyzing the treatment strategy to obtain the treatment strategy;
a matching module to:
extracting keywords from the treatment strategy to obtain treatment keywords;
and matching the treatment keywords with a preset treatment keyword-scenario interaction association table to obtain a scenario interaction strategy alternative set.
According to some embodiments of the invention, the operating module comprises:
a third receiving module, configured to receive a selection instruction generated by a user in the scenario interaction policy candidate set due to a selection operation;
the second determining module is used for analyzing the selection instruction and determining a target scene interaction strategy;
and the second execution module is used for executing the target scenario interaction strategy.
According to some embodiments of the invention, further comprising:
the second sending module is used for sending the rehabilitation training data recorded in the target scene interaction strategy to the cloud platform;
the cloud platform is used for receiving rehabilitation training data, evaluating the rehabilitation training effect of a user based on the rehabilitation training data, and judging whether the target scene interaction strategy needs to be adjusted or not.
According to some embodiments of the invention, the cloud platform is further configured to convert the rehabilitation training data into document data and send the document data to the user terminal.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a block diagram of a context-interactive child rehabilitation training system based on a cloud platform according to the present invention;
FIG. 2 is a block diagram of a cloud platform according to one embodiment of the invention;
FIG. 3 is a block diagram of an analysis module according to one embodiment of the invention.
Detailed Description
The preferred embodiments of the present invention will be described in conjunction with the accompanying drawings, and it will be understood that they are described herein for the purpose of illustration and explanation and not limitation.
As shown in fig. 1, an embodiment of the present invention provides a scene interaction children rehabilitation training system based on a cloud platform, which is characterized by comprising:
a user terminal;
a cloud platform to:
receiving and analyzing symptom information of a user sent by a user terminal to obtain a corresponding treatment strategy;
generating a treatment instruction according to the treatment strategy, and sending the treatment instruction to the scene interaction rehabilitation training module;
and the scene interaction rehabilitation training module is used for receiving the treatment instruction and determining a target scene interaction strategy based on the treatment instruction.
The working principle of the technical scheme is as follows: a user terminal;
a cloud platform to:
receiving and analyzing the symptom information of the user sent by the user terminal to obtain a corresponding treatment strategy; accurate analysis is facilitated and reliable treatment strategies are obtained;
generating a treatment instruction according to the treatment strategy, and sending the treatment instruction to the scene interaction rehabilitation training module; the treatment strategy can be conveniently and quickly sent to the scene interaction rehabilitation training module by generating the treatment instruction, so that the rehabilitation training efficiency is improved;
the scene interaction rehabilitation training module is used for receiving the treatment instruction and determining a target scene interaction strategy based on the treatment instruction; the target scene interaction strategy applicable to the user can be determined conveniently by analyzing the received treatment instruction, and the rehabilitation training effect is improved.
The beneficial effects of the above technical scheme are as follows: the cloud platform is used for scene interaction, so that a large number of different users can perform rehabilitation training on line conveniently, the integrity of data storage generated by rehabilitation training is guaranteed, and the improvement of the rehabilitation training effect is facilitated. In addition, the treatment strategy is obtained according to accurate analysis and a treatment instruction is generated, so that the treatment strategy can be conveniently and quickly sent to the scene interaction rehabilitation training module according to the instruction, and the efficiency and the accuracy of rehabilitation training are improved. By receiving the treatment instruction and determining a target scene interaction strategy based on the treatment instruction, the targeted training of each user is ensured, and the rehabilitation training effect is improved.
As shown in fig. 2, according to some embodiments of the invention, the cloud platform comprises:
the first receiving module is used for receiving the symptom information of the user sent by the user terminal;
an analysis module to:
extracting keywords from the symptom information of the user to obtain symptom keywords;
matching the symptom keywords with a plurality of preset symptom keywords in a database respectively, and determining treatment strategies corresponding to the matched preset symptom keywords;
and the first sending module is used for generating a corresponding treatment instruction based on the treatment strategy and sending the treatment instruction to the scene interaction rehabilitation training module.
The working principle of the technical scheme is as follows: the first receiving module is used for receiving the symptom information of the user sent by the user terminal; facilitating analysis of the symptom information;
an analysis module to:
extracting keywords from the symptom information of the user to obtain symptom keywords; the symptom of the user can be conveniently and accurately acquired, and then a reliable treatment strategy is obtained;
matching the symptom keywords with a plurality of preset symptom keywords in a database respectively, and determining treatment strategies corresponding to the matched preset symptom keywords; the treatment strategy comprises treatment time arrangement and treatment difficulty grade;
the first sending module is used for generating a corresponding treatment instruction based on the treatment strategy and sending the treatment instruction to the scene interaction rehabilitation training module; the scene interaction rehabilitation training module is convenient to carry out rehabilitation training on the user by sending the treatment instruction.
The beneficial effects of the above technical scheme are as follows: the cloud platform is used for receiving the symptom information of the user, which is sent by the user terminal, so that the symptom key words can be conveniently extracted from the text data of the symptom information, the symptom of the user can be accurately obtained, and the accuracy of the obtained treatment strategy and the individual pertinence applicability of the subsequent rehabilitation training can be guaranteed. The treatment instruction is sent to the scene interaction rehabilitation training module, so that the cloud platform and the scene interaction rehabilitation training module can be conveniently connected, and the rehabilitation training efficiency is improved.
As shown in fig. 3, according to some embodiments of the invention, the analysis module comprises:
the preprocessing module is used for acquiring a text comprising the symptom information of the user and preprocessing the text to obtain a text to be extracted;
the weight determining module is used for determining the target weight of the description keyword in the text to be extracted;
and the keyword determining module is used for sequencing the description keywords corresponding to the target weight from large to small, and selecting the description keywords with the preset number as the symptom keywords.
The working principle of the technical scheme is as follows: the preprocessing module is used for acquiring a text comprising the symptom information of the user and preprocessing the text to obtain a text to be extracted; the standard text is convenient to obtain, so that the extracted symptom keywords are more accurate and standard;
the weight determining module is used for determining the target weight of the description keyword in the text to be extracted; facilitating further narrowing in a large number of description keywords;
the keyword determining module is used for sequencing the description keywords corresponding to the target weight from large to small, and selecting the description keywords with the preset number as the symptom keywords; the method is convenient for screening out the description keywords with small symptom description effect to obtain the accurate and refined symptom keywords.
The beneficial effects of the above technical scheme are that: by preprocessing the text of the symptom information of the user, more standard text data can be obtained conveniently, the accuracy of extracting the description keywords is improved, and the extraction difficulty is reduced. By determining the weight of the description keyword, the description keyword which is fully expressed and refined can be accurately obtained and determined as the symptom keyword under the condition that a large number of description keywords exist.
According to some embodiments of the invention, the pre-processing module comprises:
a first processing module to:
acquiring a text including symptom information of the user as a first text;
identifying and deleting characters matched with preset characters in the first text to obtain a second text;
a second processing module to:
utilizing a jieba word segmentation device to segment words of the second text, and spacing the obtained segmented words through blank spaces to further obtain a third text;
and carrying out duplication elimination processing on the third text to obtain a text to be extracted.
The working principle of the technical scheme is as follows: a first processing module to: acquiring a text including symptom information of the user as a first text; the original text data is convenient to obtain;
identifying and deleting characters matched with preset characters in the first text to obtain a second text; the preset characters comprise punctuation marks, pre-configured special characters (such as:% and the like symbols), single characters (such as 'characters' which do not have significance per se and the like);
a second processing module to:
utilizing a jieba word segmentation device to segment words of the second text, and spacing the obtained segmented words through blank spaces to further obtain a third text; text data after word segmentation can be obtained quickly by using a jieba word segmentation device conveniently;
performing duplicate removal processing on the third text to obtain a text to be extracted; more pure text data can be obtained conveniently.
The beneficial effects of the above technical scheme are that: the method has the advantages that the text of the symptom information of the user is preprocessed, so that purer text data can be obtained conveniently to serve as the text to be extracted, difficulty in extracting the description keywords is reduced, and accuracy in extracting the description keywords is improved.
According to some embodiments of the invention, the weight determination module comprises:
a first determination module to:
extracting keywords from a text to be extracted to obtain a plurality of description keywords;
clustering semantics corresponding to the description keywords to obtain a plurality of description keyword sets;
determining a clustering center corresponding to each description keyword set, and determining a target clustering center according to the clustering center corresponding to each description keyword set;
respectively calculating the distance between the description keyword set and the target clustering center to obtain corresponding distance values;
and describing the target weight of the keyword based on a preset distance-weight setting rule.
The working principle of the technical scheme is as follows: a first determining module to:
extracting keywords from a text to be extracted to obtain a plurality of description keywords; a plurality of description keywords can be obtained preliminarily;
clustering semantics corresponding to the description keywords to obtain a plurality of description keyword sets; clustering a large number of description keywords through semantics under the condition that a large number of description keywords exist, dividing the large number of description keywords, and further extracting the description keywords;
determining a clustering center corresponding to each description keyword set, and determining a target clustering center according to the clustering center corresponding to each description keyword set; determining the target weight of the description keyword according to the distance between the target clustering center and the clustering center corresponding to each description keyword set;
respectively calculating the distance between the description keyword set and the target clustering center to obtain corresponding distance values; facilitating determination of weights based on the distance values;
describing the target weight of the keyword based on a preset distance-weight setting rule; the preset distance-weight setting rule is a rule for determining a weight according to a preset correspondence between a distance value range and a weight value, and includes, for example: when the distance value ranges from 0 to 10, the corresponding weight is 5; when the distance value ranges from 10 to 20, the corresponding weight is 4; obtaining the weight through a preset distance-weight setting rule, so that the weight can be conveniently set on the corresponding description keyword;
the beneficial effects of the above technical scheme are that: clustering a large number of description keywords through semantics, so that the description keywords can be divided conveniently; by determining the target clustering center, the distance between the description keyword set and the target clustering center is calculated conveniently, the obtained distance value is subjected to a preset distance-weight setting rule to obtain the target weight of the description keyword, the description keywords corresponding to the target weight are sequenced from large to small conveniently, and the preset number of the description keywords are extracted to be used as symptom keywords.
According to some embodiments of the invention, the context-interactive rehabilitation training module comprises:
a second receiving module for receiving the treatment instruction; the treatment instruction comprises the treatment strategy and an instruction for analyzing the treatment strategy;
the analysis module is used for executing the instruction for analyzing the treatment strategy and obtaining a corresponding situation interaction strategy alternative set;
and the operation module is used for receiving a selection instruction input by a user, determining a target scenario interaction strategy in the scenario interaction strategy alternative set and executing the target scenario interaction strategy.
The working principle of the technical scheme is as follows: a second receiving module for receiving the treatment instruction; the treatment instruction comprises the treatment strategy and an instruction for analyzing the treatment strategy; treatment strategies can be obtained conveniently and quickly by analysis;
the analysis module is used for executing the instruction for analyzing the treatment strategy and obtaining a corresponding situation interaction strategy alternative set; the situation interaction strategy alternative set is obtained conveniently according to the analyzed treatment strategy preliminary matching;
the operation module is used for receiving a selection instruction input by a user, determining a target scene interaction strategy in the scene interaction strategy alternative set and executing the target scene interaction strategy; the scene interaction strategy comprises a scene interaction theme, a difficulty level, a scene interaction rule, a link setting condition, an interaction completion requirement and an interaction duration; facilitating determining a target context interaction policy to be executed further according to a user's selection;
the beneficial effects of the above technical scheme are that: by receiving the treatment instructions, the safety integrity of the treatment strategy included in the received treatment instructions is ensured. By analyzing the treatment strategy, the situation interaction strategy adapted to the user can be obtained preliminarily, and a choice is provided for the user to finally determine the target situation interaction strategy, which is beneficial to improving the user friendliness.
According to some embodiments of the invention, the parsing module comprises:
the first execution module is used for executing the instruction for analyzing the treatment strategy to obtain the treatment strategy;
a matching module to:
extracting keywords from the treatment strategy to obtain treatment keywords;
and matching the treatment keywords with a preset treatment keyword-scenario interaction association table to obtain a scenario interaction strategy alternative set.
The working principle of the technical scheme is as follows: the first execution module is used for executing the instruction for analyzing the treatment strategy to obtain the treatment strategy; complete and complete treatment strategies are conveniently obtained;
a matching module to: extracting keywords from the treatment strategy to obtain treatment keywords; facilitating interaction strategies based on the obtained treatment keywords and the matching scenarios;
matching the treatment keywords with a preset treatment keyword-scenario interaction association table to obtain a scenario interaction strategy alternative set; the preset treatment keyword-context interaction association table is a relationship table established according to an association relationship between preset treatment keywords and context interaction policies, for example: the treatment keyword is autism, and the scene interaction strategy M01, the scene interaction strategy M02 and the scene interaction strategy M03 are obtained according to the association relationship between the preset treatment keyword and the scene interaction strategy.
The beneficial effects of the above technical scheme are that: by extracting the keywords from the analyzed treatment strategy, the situation interaction strategy alternative set can be obtained conveniently by quickly and accurately matching the extracted treatment keywords with a preset treatment keyword-situation interaction association table, and the rehabilitation training efficiency is improved.
According to some embodiments of the invention, the operation module comprises:
a third receiving module, configured to receive a selection instruction generated by a user due to a selection operation in the scenario interaction policy candidate set;
the second determining module is used for analyzing the selection instruction and determining a target scene interaction strategy;
and the second execution module is used for executing the target scenario interaction strategy.
The working principle of the technical scheme is as follows: a third receiving module, configured to receive a selection instruction generated by a user in the scenario interaction policy candidate set due to a selection operation; the target scenario strategy for execution is finally determined according to the selection instruction;
the second determining module is used for analyzing the selection instruction and determining a target scene interaction strategy; the selection instruction comprises a scene interaction strategy name; the target scene interaction strategy is conveniently and rapidly determined according to the scene interaction strategy name obtained by analyzing the selection instruction;
the second execution module is used for executing the target scene interaction strategy; the method is convenient for executing the most adaptive situation interaction strategy of the user to carry out rehabilitation training, and improves the rehabilitation training effect.
The beneficial effects of the above technical scheme are that: the target scene interaction strategy is determined by receiving a selection instruction of a user, so that the user friendliness is improved conveniently. The rehabilitation training is carried out according to the target scene interaction strategy, so that the rehabilitation training is facilitated for the user according to a scientific and most targeted scene interaction strategy, and the rehabilitation training effect is improved.
According to some embodiments of the invention, further comprising:
the second sending module is used for sending the rehabilitation training data recorded in the target scene interaction strategy to the cloud platform;
the cloud platform is used for receiving rehabilitation training data, evaluating the rehabilitation training effect of a user based on the rehabilitation training data and judging whether the target scene interaction strategy needs to be adjusted or not;
the working principle of the technical scheme is as follows: the second sending module is used for sending the rehabilitation training data recorded in the target scene interaction strategy to the cloud platform; the rehabilitation training data can be conveniently stored and processed;
the cloud platform is used for receiving rehabilitation training data, evaluating the rehabilitation training effect of a user based on the rehabilitation training data and judging whether the target scene interaction strategy needs to be adjusted or not; the rehabilitation training effect of the user is evaluated through rehabilitation training data, and a target scene interaction strategy is adjusted in time, so that the rehabilitation training effect is kept in an optimal state all the time;
the cloud platform, comprising:
the fourth receiving module is used for receiving the rehabilitation training data;
a data analysis module to:
preprocessing the rehabilitation training data to obtain processed data; the preprocessing comprises outlier rejection and data standardization;
counting the processing data based on a preset counting method to obtain four groups of statistical data; the four sets of statistical data include: the first group of data is statistical data of the time consumption of each link in single training, the second group of data is statistical data of the total time consumption of the single training, the third group of data is statistical data of the completion degree of each link in the single training at a preset link time threshold, and the fourth group of data is statistical data of the total completion degree of the single training at a preset total time threshold; the preset statistical method comprises a statistical table and a broken line statistical chart;
respectively acquiring change data between the latest data and the initial data of each group of statistical data based on the four groups of statistical data; whether the target scene interaction strategy needs to be adjusted or not is judged conveniently according to the change data;
comparing the change data with corresponding change thresholds respectively, and determining that the target scene interaction strategy needs to be adjusted when any change data meets the change thresholds; the rehabilitation training effect is improved by enabling the target scene interaction strategy to be always kept in the most suitable state.
The beneficial effects of the above technical scheme are that: through with rehabilitation training data send to the cloud platform, the cloud platform of being convenient for is saved and is handled a large amount of rehabilitation training data. The cloud platform can timely adjust the target scene interaction strategy by counting the rehabilitation training data and evaluating the rehabilitation training effect of the user, so that the rehabilitation training effect is always kept in the best state.
According to some embodiments of the invention, the cloud platform is further configured to convert the rehabilitation training data into document data and send the document data to the user terminal.
The working principle and the beneficial effects of the technical scheme are as follows: and converting the rehabilitation training data into document data and sending the document data to the user terminal. The user can conveniently acquire the rehabilitation training data through the user terminal, and the recovery condition of the user can be known in time by knowing the progress and effect of the rehabilitation training.
According to some embodiments of the invention, the cloud platform further comprises:
a task scheduling module to:
scheduling different evaluation tasks triggered by rehabilitation training data of different users; each evaluation task is allocated with at least one process;
based on the number of processes assigned to the evaluation tasks, the completion time of a single evaluation task at the scheduling stage s is calculated:
wherein t1 is the completion time of a single evaluation task in the scheduling stage s; j. the design is a square s The number of processes allocated in the scheduling stage s; j is the jth process; Δ t is the time of execution of each process;
thus, the completion time of all the evaluation tasks in the current scheduling stage s is obtained:
wherein t2 is the completion time of the current all the evaluation task numbers N; n is the nth evaluation task;
based on the t2, obtaining the throughput rate of the current scheduling stage s:
wherein L is s The throughput rate in the scheduling stage s of the current evaluation task; i is a trigger node included in a scheduling stage s of the current evaluation task; i is the ith trigger node;
based on throughput rate L in scheduling phase s of the current evaluation task s And obtaining the throughput rate of the complete currently executed evaluation task:
wherein, L is the throughput rate of the complete currently executed evaluation task;
and comparing the throughput rate of the complete currently executed evaluation task with a preset throughput rate threshold, adjusting the scheduling of the current evaluation task when the throughput rate of the complete currently executed evaluation task is smaller than the preset throughput rate threshold, and sending an alarm prompt.
The working principle of the technical scheme is as follows: a task scheduling module to:
scheduling different evaluation tasks triggered by rehabilitation training data of different users; each evaluation task is allocated with at least one process;
based on the number of the processes, calculating the completion time of a single evaluation task in a scheduling stage s;
thus, the completion time of all the evaluation tasks in the current scheduling stage s is obtained;
obtaining the throughput rate in the current scheduling stage s based on the completion time of all the evaluation tasks in the current scheduling stage s;
obtaining the complete throughput rate of the currently executed evaluation task based on the throughput rate in the scheduling stage s of the current evaluation task;
comparing the throughput rate of the complete currently executed evaluation task with a preset throughput rate threshold, when the throughput rate of the complete currently executed evaluation task is smaller than the preset throughput rate threshold, adjusting the scheduling of the current evaluation task, and sending an alarm prompt; the method and the device facilitate the judgment of the current evaluation task quantity through the complete throughput rate of the current evaluation task.
The beneficial effects of the above technical scheme are that: the throughput rate of the currently executed evaluation task is obtained by calculating the throughput rate in the scheduling stage s of the currently executed evaluation task, and the currently executed evaluation task amount is conveniently judged based on the throughput rate of the currently executed evaluation task, so that the data processing resources of the cloud platform are fully and reasonably utilized, the full scheduling of the evaluation task is ensured, and the execution efficiency of the evaluation task is improved. By means of the alarm prompt, the scheduling of the current evaluation task can be adjusted conveniently and timely, and the scheduling efficiency of the evaluation task is improved.
It will be apparent to those skilled in the art that various changes and modifications may be made in the present invention without departing from the spirit and scope of the invention. Thus, if such modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include such modifications and variations.
Claims (10)
1. The utility model provides a scene interaction children rehabilitation training system based on cloud platform which characterized in that includes:
a user terminal;
a cloud platform to:
receiving and analyzing symptom information of a user sent by a user terminal to obtain a corresponding treatment strategy;
generating a treatment instruction according to the treatment strategy, and sending the treatment instruction to the scene interaction rehabilitation training module;
and the scene interaction rehabilitation training module is used for receiving the treatment instruction and determining a target scene interaction strategy based on the treatment instruction.
2. The cloud platform based scene interaction children rehabilitation training system of claim 1, wherein the cloud platform comprises:
the first receiving module is used for receiving the symptom information of the user sent by the user terminal;
an analysis module to:
extracting keywords from the symptom information of the user to obtain symptom keywords;
matching the symptom keywords with a plurality of preset symptom keywords in a database respectively, and determining treatment strategies corresponding to the matched preset symptom keywords;
and the first sending module is used for generating a corresponding treatment instruction based on the treatment strategy and sending the treatment instruction to the scene interaction rehabilitation training module.
3. The cloud platform based scene interaction children rehabilitation training system according to claim 2, wherein the analysis module comprises:
the preprocessing module is used for acquiring a text comprising the symptom information of the user and preprocessing the text to obtain a text to be extracted;
the weight determining module is used for determining the target weight of the description keyword in the text to be extracted;
and the keyword determining module is used for sequencing the description keywords corresponding to the target weight from large to small, and selecting the description keywords with the preset number as the symptom keywords.
4. The cloud platform based context-interactive children rehabilitation training system of claim 3, wherein the preprocessing module comprises:
a first processing module to:
acquiring a text including symptom information of the user as a first text;
identifying and deleting characters matched with preset characters in the first text to obtain a second text;
a second processing module to:
utilizing a jieba word segmentation device to segment words of the second text, and spacing the obtained segmented words through blank spaces to further obtain a third text;
and carrying out duplication elimination processing on the third text to obtain a text to be extracted.
5. The cloud platform based context-interactive children rehabilitation training system of claim 3, wherein the weight determination module comprises:
a first determining module to:
extracting keywords from a text to be extracted to obtain a plurality of description keywords;
clustering semantics corresponding to the description keywords to obtain a plurality of description keyword sets;
determining a clustering center corresponding to each description keyword set, and determining a target clustering center according to the clustering center corresponding to each description keyword set;
respectively calculating the distance between the description keyword set and the target clustering center to obtain corresponding distance values;
and describing the target weight of the keyword based on a preset distance-weight setting rule.
6. The cloud platform-based context-interactive child rehabilitation training system of claim 1, wherein the context-interactive rehabilitation training module comprises:
a second receiving module for receiving the treatment instruction; the treatment instruction comprises the treatment strategy and an instruction for analyzing the treatment strategy;
the analysis module is used for executing the instruction for analyzing the treatment strategy and obtaining a corresponding situation interaction strategy alternative set;
and the operation module is used for receiving a selection instruction input by a user, determining a target scene interaction strategy in the scene interaction strategy alternative set and executing the target scene interaction strategy.
7. The cloud platform based scene interaction children rehabilitation training system according to claim 6, wherein the parsing module comprises:
the first execution module is used for executing the instruction for analyzing the treatment strategy to obtain the treatment strategy;
a matching module to:
extracting keywords from the treatment strategy to obtain treatment keywords;
and matching the treatment keywords with a preset treatment keyword-scenario interaction association table to obtain a scenario interaction strategy alternative set.
8. The cloud platform based scene interaction children rehabilitation training system according to claim 6, wherein the operation module comprises:
a third receiving module, configured to receive a selection instruction generated by a user in the scenario interaction policy candidate set due to a selection operation;
the second determining module is used for analyzing the selection instruction and determining a target scene interaction strategy;
and the second execution module is used for executing the target scenario interaction strategy.
9. The cloud platform based scene interaction children rehabilitation training system of claim 1, further comprising:
the second sending module is used for sending the rehabilitation training data recorded in the target scene interaction strategy to the cloud platform;
the cloud platform is used for receiving rehabilitation training data, evaluating the rehabilitation training effect of a user based on the rehabilitation training data, and judging whether the target scene interaction strategy needs to be adjusted or not.
10. The cloud platform based scene interaction children rehabilitation training system of claim 9, wherein the cloud platform is further configured to convert the rehabilitation training data into document data and send the document data to a user terminal.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110504031A (en) * | 2019-08-28 | 2019-11-26 | 首都医科大学 | Cloud for Health behavior Intervention manages database building method and system |
| CN110931103A (en) * | 2019-11-01 | 2020-03-27 | 深圳市迈步机器人科技有限公司 | Control method and system of rehabilitation equipment |
| WO2021071971A1 (en) * | 2019-10-11 | 2021-04-15 | Healthpointe Solutions, Inc. | System and method for steering care plan actions by detecting tone, emotion, and/or health outcome |
| CN113101134A (en) * | 2021-04-02 | 2021-07-13 | 上海交通大学医学院附属新华医院 | Children lower limb movement auxiliary rehabilitation system based on power exoskeleton |
| CN113270187A (en) * | 2021-07-21 | 2021-08-17 | 奥罗科技(天津)有限公司 | Intelligent remote autism rehabilitation training system |
| CN114334070A (en) * | 2022-01-05 | 2022-04-12 | 上海良方健康科技有限公司 | Auxiliary prescription system based on medical big data |
| CN114388089A (en) * | 2021-12-31 | 2022-04-22 | 姜海霞 | Personal health management method and system based on artificial intelligence |
| CN114783560A (en) * | 2022-04-11 | 2022-07-22 | 广州晓康医疗科技有限公司 | Recovered line system of wisdom |
| CN114898832A (en) * | 2022-05-30 | 2022-08-12 | 安徽法罗适医疗技术有限公司 | Rehabilitation training remote control system, method, device, equipment and medium |
-
2022
- 2022-12-14 CN CN202211605904.8A patent/CN115938540B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110504031A (en) * | 2019-08-28 | 2019-11-26 | 首都医科大学 | Cloud for Health behavior Intervention manages database building method and system |
| WO2021071971A1 (en) * | 2019-10-11 | 2021-04-15 | Healthpointe Solutions, Inc. | System and method for steering care plan actions by detecting tone, emotion, and/or health outcome |
| CN110931103A (en) * | 2019-11-01 | 2020-03-27 | 深圳市迈步机器人科技有限公司 | Control method and system of rehabilitation equipment |
| CN113101134A (en) * | 2021-04-02 | 2021-07-13 | 上海交通大学医学院附属新华医院 | Children lower limb movement auxiliary rehabilitation system based on power exoskeleton |
| CN113270187A (en) * | 2021-07-21 | 2021-08-17 | 奥罗科技(天津)有限公司 | Intelligent remote autism rehabilitation training system |
| CN114388089A (en) * | 2021-12-31 | 2022-04-22 | 姜海霞 | Personal health management method and system based on artificial intelligence |
| CN114334070A (en) * | 2022-01-05 | 2022-04-12 | 上海良方健康科技有限公司 | Auxiliary prescription system based on medical big data |
| CN114783560A (en) * | 2022-04-11 | 2022-07-22 | 广州晓康医疗科技有限公司 | Recovered line system of wisdom |
| CN114898832A (en) * | 2022-05-30 | 2022-08-12 | 安徽法罗适医疗技术有限公司 | Rehabilitation training remote control system, method, device, equipment and medium |
Non-Patent Citations (1)
| Title |
|---|
| 李强: "《云计算及其应用》", 武汉大学出版社, pages: 183 - 185 * |
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