Multi-mode rehabilitation training system for children with cerebral palsy based on artificial intelligence

Abstract

The invention belongs to the technical field of artificial intelligence, and discloses a cerebral palsy child multi-mode rehabilitation training system based on artificial intelligence. The system comprises a data acquisition and preprocessing module, a multi-modal information fusion module, a personalized rehabilitation training suggestion generation module, an interaction and excitation module, a progress tracking and abnormity early warning module, a doctor and parent end APP management module and a system control and management module. According to the invention, when the interaction and excitation module and the multi-modal information fusion module are combined and applied to rehabilitation training of children with cerebral palsy, the training effect can be significantly improved, and accurate evaluation and personalized training can be realized; the child patient can be trained in a more real and attractive environment, meanwhile, the enthusiasm of the child patient is further stimulated through the gamification excitation design, and the training motivation of the child patient is enhanced through real-time feedback encouragement.

Description

Technical Field

[0001] The present invention belongs to the field of artificial intelligence technology, and specifically relates to an artificial intelligence-based multimodal rehabilitation training system for children with cerebral palsy. Background Art

[0002] The AI-based multimodal rehabilitation training system for children with cerebral palsy is designed specifically for children with cerebral palsy. It integrates advanced AI technology and aims to promote comprehensive rehabilitation through comprehensive training in multiple modalities (motor, cognitive, and language). The system utilizes AI technology for data processing and analysis, tailoring personalized training plans for each child to precisely meet their rehabilitation needs. Simultaneously, the system combines multiple training modalities to comprehensively improve children's motor function, cognitive abilities, and language expression, maximizing rehabilitation effectiveness. During training, the system monitors children's training progress and performance in real time and makes timely adjustments based on data feedback to ensure the effectiveness and targeted nature of the training. Furthermore, the system provides remote rehabilitation support, allowing doctors and therapists to monitor children's rehabilitation progress and provide remote guidance and advice through remote access. This eliminates geographical restrictions and improves the accessibility and convenience of rehabilitation services. Existing AI-based multimodal rehabilitation training systems for children with cerebral palsy face multiple challenges in their application. First, the issues of technological maturity and applicability are particularly prominent. Although artificial intelligence has made breakthroughs in the medical field, its application in the field of rehabilitation training for children with cerebral palsy is still in its early stages. In addition, most existing rehabilitation robot projects are limited to conventional auxiliary treatments, with limited applicability for younger children. There is a lack of flexible training modes and parameter adjustment methods, making it difficult to meet the specific needs of different children. Secondly, there are also deficiencies in human-computer interaction and user experience. The accuracy and stability of speech recognition and motion recognition technologies need to be improved to ensure that children can interact accurately and smoothly with the system during training. In addition, the system's user interface design and operating procedures are complex, which increases the difficulty of use for rehabilitation therapists and children, affecting the training effect. Therefore, further optimizing the maturity of the technology and improving the human-computer interaction experience are the key to promoting the widespread application of this system in rehabilitation training for children with cerebral palsy. Summary of the Invention

[0003] The purpose of the present invention is to provide a multimodal rehabilitation training system for children with cerebral palsy based on artificial intelligence to solve the problems raised in the above background technology.

[0004] To achieve the above objectives, the present invention provides the following technical solutions: an artificial intelligence-based multimodal rehabilitation training system for children with cerebral palsy, the system comprising a data acquisition and preprocessing module, a multimodal information fusion module, a personalized rehabilitation training suggestion generation module, an interaction and motivation module, a progress tracking and abnormality warning module, a doctor and parent APP management module, and a system control and management module;

[0005] The data acquisition and preprocessing module is responsible for collecting electromyographic, visual, and brain wave data, and performing cleaning, conversion, and denoising to ensure data quality;

[0006] The multimodal information fusion module is used to integrate electromyographic, visual, and brain wave data, analyze joint movements using the OpenPose algorithm, and provide a comprehensive assessment basis for children's rehabilitation training;

[0007] The personalized rehabilitation training suggestion module uses machine learning algorithms to generate training suggestions based on the patient's historical and current data, and dynamically adjusts the plan to maximize the rehabilitation effect;

[0008] The interaction and motivation module integrates AI voice assistants, VR scenarios, and gamification training to create an immersive rehabilitation experience for children, stimulate their interest, increase their participation, and provide real-time feedback and encouragement to enhance training effectiveness.

[0009] The progress tracking and abnormal warning module tracks the child's training progress in real time, records key data, sets abnormal warnings, and provides a visual interface for parents and doctors to view progress and warnings;

[0010] The doctor and parent APP management module is used to remotely monitor the child's rehabilitation plan, covering training plan viewing, progress tracking, early warning reception and communication functions, helping to jointly pay attention to the child's rehabilitation progress;

[0011] The system control and management module is responsible for the operation and maintenance of the rehabilitation training system, coordinating and managing various modules, and ensuring system stability and user, authority, and data security.

[0012] Preferably, the data acquisition and preprocessing module includes a data acquisition unit, a data preprocessing unit, a data storage and management unit, and a configuration and monitoring unit;

[0013] The data acquisition unit collects rehabilitation training data in real time through the sensor interface, ensures the data is complete and real-time, records the source and time stamp, and monitors the stability of the acquisition;

[0014] The data preprocessing unit is responsible for cleaning, converting the format and denoising the raw data to ensure that the data is valid, in a unified format, and meets the quality requirements of subsequent analysis;

[0015] The data storage management unit is used to design a secure database, encrypt stored data, manage storage structure, back up and restore data, and ensure data security and accessibility;

[0016] The configuration monitoring unit is used to set interface configuration parameters, monitor acquisition preprocessing, record logs and alarms, and ensure stable operation of the system.

[0017] Preferably, the multimodal information fusion module includes a data fusion unit, a data analysis and feature extraction unit, a joint motion analysis and function evaluation unit, and a configuration and monitoring unit;

[0018] The data fusion unit is responsible for integrating multimodal data of electromyographic signals, visual images, and brain waves to ensure spatiotemporal synchronization and complementarity, and generate a comprehensive description of the rehabilitation training status;

[0019] The data analysis and feature extraction unit deeply analyzes the fused data and uses the OpenPose algorithm model to accurately extract key information on joint movement and muscle activity patterns;

[0020] The joint motion analysis unit evaluates the motor function based on the characteristics and combines rehabilitation knowledge to comprehensively evaluate the motor ability of the child;

[0021] The configuration and monitoring unit sets parameter models, monitors the entire multimodal processing process, ensures data accuracy and system stability, and records logs to warn of potential problems.

[0022] Preferably, the personalized rehabilitation training suggestion generation module includes a data integration and analysis unit, an algorithm suggestion generation unit, and a dynamic plan adjustment unit;

[0023] The data integration and analysis unit is responsible for collecting and analyzing the patient's historical and current training data;

[0024] The algorithm-generated recommendation unit generates personalized training recommendations by utilizing machine learning / deep learning algorithms;

[0025] The dynamic plan adjustment unit dynamically adjusts the training plan according to the physical condition and rehabilitation progress.

[0026] Preferably, the interaction and incentive module includes an immersive experience unit, a gamification incentive unit, and a real-time feedback encouragement unit;

[0027] The immersive experience unit is responsible for introducing AI voice assistants and VR visual scenes to create an immersive rehabilitation training environment for children;

[0028] The gamification incentive unit stimulates the patient's interest in training and improves their participation in rehabilitation training through gamification training design;

[0029] The real-time feedback encouragement unit is responsible for providing real-time feedback and encouragement to the child during the training process to enhance his or her training motivation and improve the training effect.

[0030] Preferably, the progress tracking and abnormal warning module includes a real-time progress tracking unit, a key data recording unit, and an abnormal warning response unit;

[0031] The real-time progress tracking unit is responsible for tracking the rehabilitation training progress of the child in real time to ensure that each training activity is accurately recorded;

[0032] The key data recording unit is dedicated to recording and analyzing key indicators and data during the training process, providing data support for evaluating the training effect;

[0033] The abnormal behavior detection unit detects whether the child exhibits abnormal behavior during training, including irregular movements or excessive fatigue, through a preset algorithm and model;

[0034] The abnormal warning response unit will immediately trigger the warning mechanism once abnormal behavior or data is found according to the actual situation, and notify relevant personnel to take corresponding measures to ensure the safety of the child and the training effect.

[0035] Preferably, the doctor and parent APP management module includes a user authentication and authority management unit, a training plan and progress viewing unit, an early warning information receiving and processing unit, and an online communication and collaboration unit;

[0036] The user authentication and authority management unit is responsible for ensuring that only legitimate doctors and parents can log in to the APP, and assigning corresponding viewing and management permissions based on roles;

[0037] The training plan and progress viewing unit is responsible for providing doctors and parents with the function of remotely viewing the child's rehabilitation training plan and its execution progress, ensuring that both parties have a clear understanding of the training situation;

[0038] The warning information receiving and processing unit is responsible for receiving warning information from the progress tracking and abnormal warning module in real time, and pushing notifications to doctors and parents through the APP so that they can take timely response measures;

[0039] The online communication and collaboration unit is responsible for establishing an instant messaging channel between doctors and parents within the APP, facilitating communication, discussion and collaboration between both parties on the child's recovery progress.

[0040] Preferably, the system control and management module includes a system operation and maintenance unit, a module coordination unit, a user management unit, a permission management unit, and a data security unit;

[0041] The system operation and maintenance unit is responsible for the daily operation and maintenance of the entire rehabilitation training system to ensure the stable operation of the system;

[0042] The module coordination unit is used to coordinate and manage various functional modules to ensure smooth interaction and data flow between them;

[0043] The user management unit is used to provide user registration, login, and information modification management functions to ensure the accuracy and security of user information;

[0044] The authority management unit is responsible for assigning corresponding system permissions according to user roles, ensuring that users can only access and operate content within their authority range;

[0045] The data security unit is responsible for data encryption, backup, and recovery security measures to ensure the security and reliability of system data.

[0046] The beneficial effects of the present invention are as follows:

[0047] The present invention combines the interaction and motivation module with the multimodal information fusion module for rehabilitation training of children with cerebral palsy, which can significantly improve the training effect and realize accurate evaluation and personalized training. Through the AI ​​voice assistant and VR visual scene introduced by the immersive experience unit, children can train in a more realistic and attractive environment. At the same time, the gamification incentive design further stimulates their enthusiasm, and real-time feedback encouragement enhances their training motivation. On the other hand, the multimodal information fusion module integrates a variety of biological signals and image data to provide children with a comprehensive description of their rehabilitation training status, and through in-depth data analysis and feature extraction, accurately evaluates their joint movement and muscle activity patterns, provides doctors and therapists with a comprehensive understanding of the actual rehabilitation situation, supports the formulation of personalized training plans, and configures and monitors units to ensure the accuracy and stability of the entire processing process, providing reliable technical support for rehabilitation training, thereby jointly promoting the efficiency and accuracy of the rehabilitation process of children with cerebral palsy. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 A framework diagram for use with the control module of the present invention. DETAILED DESCRIPTION

[0049] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. 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 making creative efforts are within the scope of protection of the present invention.

[0050] As shown in the figure, an embodiment of the present invention provides an artificial intelligence-based multimodal rehabilitation training system for children with cerebral palsy. The system includes a data acquisition and preprocessing module, a multimodal information fusion module, a personalized rehabilitation training suggestion generation module, an interaction and motivation module, a progress tracking and abnormality warning module, a doctor and parent APP management module, and a system control and management module.

[0051] The data acquisition and preprocessing module is responsible for collecting electromyographic, visual, and brain wave data, and performing cleaning, conversion, and denoising to ensure data quality;

[0052] The multimodal information fusion module is used to integrate electromyographic, visual, and brain wave data, analyze joint movements using the OpenPose algorithm, and provide a comprehensive assessment basis for children's rehabilitation training;

[0053] The personalized rehabilitation training suggestion module uses machine learning algorithms to generate training suggestions based on the patient's historical and current data, and dynamically adjusts the plan to maximize the rehabilitation effect;

[0054] The interaction and motivation module integrates AI voice assistants, VR scenarios, and gamification training to create an immersive rehabilitation experience for children, stimulate their interest, increase their participation, and provide real-time feedback and encouragement to enhance training effectiveness.

[0055] The progress tracking and abnormal warning module tracks the child's training progress in real time, records key data, sets abnormal warnings, and provides a visual interface for parents and doctors to view progress and warnings;

[0056] The doctor and parent APP management module is used to remotely monitor the child's rehabilitation plan, covering training plan viewing, progress tracking, early warning reception and communication functions, helping to jointly pay attention to the child's rehabilitation progress;

[0057] The system control and management module is responsible for the operation and maintenance of the rehabilitation training system, coordinating and managing various modules, and ensuring system stability and user, authority, and data security.

[0058] The data acquisition and preprocessing module includes a data acquisition unit, a data preprocessing unit, a data storage and management unit, and a configuration and monitoring unit;

[0059] The data acquisition unit collects rehabilitation training data in real time through the sensor interface, ensures the data is complete and real-time, records the source and time stamp, and monitors the stability of the acquisition;

[0060] The data preprocessing unit is responsible for cleaning, converting the format and denoising the raw data to ensure that the data is valid, in a unified format, and meets the quality requirements of subsequent analysis;

[0061] The data storage management unit is used to design a secure database, encrypt stored data, manage storage structure, back up and restore data, and ensure data security and accessibility;

[0062] The configuration monitoring unit is used to set interface configuration parameters, monitor acquisition preprocessing, record logs and alarms, and ensure stable operation of the system.

[0063] The data acquisition unit is responsible for collecting raw data to ensure the real-time and integrity of the data; the data preprocessing unit cleans, converts the format and denoises the collected data to improve data quality; the data storage and management unit securely stores the processed data and provides data backup and recovery functions; the configuration and monitoring unit is responsible for configuring system parameters, monitoring data acquisition, preprocessing and storage processes, and providing logging and alarm functions to ensure stable system operation. The units transmit and share information through data interfaces and communication protocols to jointly support the processing and analysis of rehabilitation training data.

[0064] Among them, the multimodal information fusion module includes a data fusion unit, a data analysis and feature extraction unit, a joint motion analysis and function evaluation unit, and a configuration and monitoring unit.

[0065] The data fusion unit is responsible for integrating multimodal data such as electromyographic signals, visual images, and brain waves to ensure spatiotemporal synchronization and complementarity, and generate a comprehensive description of the rehabilitation training status;

[0066] The data analysis and feature extraction unit deeply analyzes the fused data and uses algorithm models such as OpenPose to accurately extract key information such as joint movement and muscle activity patterns;

[0067] The joint motion analysis unit evaluates the motor function based on the characteristics and combines rehabilitation knowledge to comprehensively evaluate the motor ability of the child;

[0068] The configuration and monitoring unit sets parameter models, monitors the entire multimodal processing process, ensures data accuracy and system stability, and records logs to warn of potential problems.

[0069] The data fusion unit integrates multimodal data to provide comprehensive information for the analysis unit; the analysis unit extracts features to support motion analysis; the analysis unit evaluates functions and gives evaluations based on rehabilitation knowledge; the configuration and monitoring unit runs through the entire process to ensure that parameters are correct and the process is stable, and records logs and warns of problems.

[0070] The personalized rehabilitation training suggestion generation module includes a data integration and analysis unit, an algorithm generation suggestion unit, and a dynamic adjustment plan unit;

[0071] The data integration and analysis unit is responsible for collecting and analyzing the patient's historical and current training data;

[0072] The algorithm-generated recommendation unit generates personalized training recommendations by utilizing machine learning / deep learning algorithms;

[0073] The dynamic plan adjustment unit dynamically adjusts the training plan according to the physical condition and rehabilitation progress.

[0074] As a source of information, the data integration and analysis unit comprehensively collects and processes the multi-channel training data of the children, providing an accurate and comprehensive information basis for the algorithm-generated recommendation unit. Based on these data, the algorithm-generated recommendation unit uses advanced machine learning or deep learning algorithms to generate personalized training recommendations that meet the individual characteristics and rehabilitation goals of the children. These recommendations provide initial guidance for the dynamic adjustment plan unit, enabling it to dynamically adjust the training plan based on real-time data to ensure that the training always keeps pace with the child's rehabilitation progress. At the same time, the data integration and analysis unit also provides the dynamic adjustment plan unit with insights into rehabilitation trends and potential problems through in-depth analysis of historical data, helping it to formulate more accurate and effective training plans to accelerate the child's rehabilitation process.

[0075] The interaction and incentive module includes an immersive experience unit, a gamification incentive unit, and a real-time feedback encouragement unit;

[0076] The immersive experience unit is responsible for introducing AI voice assistants and VR visual scenes to create an immersive rehabilitation training environment for children;

[0077] The gamification incentive unit stimulates the patient's interest in training and improves their participation in rehabilitation training through gamification training design;

[0078] The real-time feedback encouragement unit is responsible for providing real-time feedback and encouragement to the child during the training process to enhance his or her training motivation and improve the training effect.

[0079] The AI ​​voice assistant and VR visual scenes are the core of the interaction and motivation module, together creating an immersive rehabilitation training experience. The AI ​​voice assistant communicates in real time to guide children to complete tasks, while the VR scenes simulate real-life environments, allowing children to immerse themselves in challenges and fun. The gamified training design unit combines the AI ​​voice assistant's task instructions with the visual feast of VR to stimulate children's interest and increase their participation. Real-time feedback and encouragement are the key to enhancing training effectiveness. The AI ​​voice assistant provides positive feedback based on performance, such as "Keep it up" or "You can do it," which enhances children's confidence and sense of accomplishment, prompting them to actively participate in training. The three elements complement each other, not only making training more interesting and interactive, but also significantly improving children's participation and involvement, thereby optimizing rehabilitation results.

[0080] The progress tracking and abnormal warning module includes a real-time progress tracking unit, a key data recording unit, and an abnormal warning response unit;

[0081] The real-time progress tracking unit is responsible for tracking the rehabilitation training progress of the child in real time to ensure that each training activity is accurately recorded;

[0082] The key data recording unit is dedicated to recording and analyzing key indicators and data during the training process, providing data support for evaluating the training effect;

[0083] The abnormal behavior detection unit detects whether the child has abnormal behavior during training, including irregular movements or excessive fatigue, through a preset algorithm and model;

[0084] The abnormal warning response unit will immediately trigger the warning mechanism once abnormal behavior or data is found according to the actual situation, and notify relevant personnel to take corresponding measures to ensure the safety of the child and the training effect.

[0085] The Real-Time Progress Tracking Unit monitors and records the patient's training activities, providing baseline data for the Key Data Recording Unit, which collects, organizes, and analyzes key indicators, assesses training effectiveness, and provides input for anomaly detection. The Abnormal Behavior Detection Unit uses algorithms and models to deeply analyze data, detecting abnormal behaviors such as irregular movements and excessive fatigue, and immediately transmits warnings to the Abnormal Warning Response Unit, which quickly triggers the warning mechanism to notify key personnel such as rehabilitation therapists and parents to ensure the patient's safety and promptly adjust the training plan to optimize training results. These four units work together to ensure the safety and efficiency of children's rehabilitation training.

[0086] The doctor and parent APP management module includes a user authentication and authority management unit, a training plan and progress viewing unit, a warning information receiving and processing unit, and an online communication and collaboration unit.

[0087] The user authentication and permission management unit is responsible for ensuring that only legitimate doctors and parents can log in to the APP, and assigning corresponding viewing and management permissions based on their roles;

[0088] The training plan and progress viewing unit is responsible for providing doctors and parents with the function of remotely viewing the child's rehabilitation training plan and its execution progress, ensuring that both parties have a clear understanding of the training situation;

[0089] The warning information receiving and processing unit is responsible for receiving warning information from the progress tracking and abnormal warning module in real time, and pushing notifications to doctors and parents through the APP so that they can take timely response measures;

[0090] The online communication and collaboration unit is responsible for establishing an instant messaging channel between doctors and parents within the APP, facilitating communication, discussion and collaboration between both parties on the child's recovery progress.

[0091] The user authentication and permission management unit lays the foundation for the doctor and parent app management modules, ensuring that legitimate users log in and are assigned corresponding permissions. On this basis, the training plan and progress viewing unit provides real-time and accurate information, allowing doctors and parents to remotely understand the rehabilitation training status of their children. The early warning information reception and processing unit are closely connected to ensure that early warning information is accurately pushed to authorized users, facilitating timely response. At the same time, the online communication and collaboration unit establishes an instant messaging platform to promote communication and collaboration between doctors and parents on the rehabilitation progress of their children, enhance interaction, and improve the practicality and efficiency of the module.

[0092] The system control and management module includes a system operation and maintenance unit, a module coordination unit, a user management unit, a permission management unit, and a data security unit;

[0093] The system operation and maintenance unit is responsible for the daily operation and maintenance of the entire rehabilitation training system to ensure the stable operation of the system;

[0094] The module coordination unit is used to coordinate and manage various functional modules to ensure smooth interaction and data flow between them;

[0095] The user management unit is used to provide management functions such as user registration, login, information modification, etc. to ensure the accuracy and security of user information;

[0096] The authority management unit is responsible for assigning corresponding system permissions according to user roles, ensuring that users can only access and operate content within their authority range;

[0097] The data security unit is responsible for data encryption, backup, recovery and other security measures to ensure the security and reliability of system data.

[0098] As the core of the rehabilitation training system, the System Operation and Maintenance Unit is responsible for daily operation and maintenance, ensuring the system's ability to provide services continuously and stably, laying a solid foundation for the normal operation of all other units. The Module Coordination Unit relies on the stable environment provided by the System Operation and Maintenance Unit to efficiently coordinate and manage the various functional modules, ensuring smooth interaction and data flow between them, thereby promoting the perfect implementation of the system's overall functionality. The User Management Unit and the Permission Management Unit work closely together, jointly responsible for the system's user information and permission allocation. The User Management Unit focuses on managing basic user information, while the Permission Management Unit precisely assigns system permissions based on user roles. Together, they ensure that users can only access and operate content within their authority scope, effectively ensuring system security. Furthermore, the Data Security Unit, as the security guardian of the entire system, is committed to implementing security measures such as data encryption, backup, and recovery to ensure the security and reliability of system data and provide a solid security barrier for other units.

[0099] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0100] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. An artificial intelligence-based multimodal rehabilitation training system for children with cerebral palsy, characterized by: The system includes data acquisition and preprocessing module, multimodal information fusion module, personalized rehabilitation training suggestion generation module, interaction and motivation module, progress tracking and abnormal warning module, doctor and parent APP management module, and system control and management module. The data acquisition and preprocessing module is responsible for collecting electromyographic, visual, and brain wave data, and performing cleaning, conversion, and denoising to ensure data quality; The multimodal information fusion module is used to integrate electromyographic, visual, and brain wave data, analyze joint movements using the OpenPose algorithm, and provide a comprehensive assessment basis for children's rehabilitation training; The personalized rehabilitation training suggestion module uses machine learning algorithms to generate training suggestions based on the patient's historical and current data, and dynamically adjusts the plan to maximize the rehabilitation effect; The interaction and motivation module integrates AI voice assistants, VR scenarios, and gamification training to create an immersive rehabilitation experience for children, stimulate their interest, increase their participation, and provide real-time feedback and encouragement to enhance training effectiveness. The progress tracking and abnormal warning module tracks the child's training progress in real time, records key data, sets abnormal warnings, and provides a visual interface for parents and doctors to view progress and warnings; The doctor and parent APP management module is used to remotely monitor the child's rehabilitation plan, covering training plan viewing, progress tracking, early warning reception and communication functions, helping to jointly pay attention to the child's rehabilitation progress; The system control and management module is responsible for the operation and maintenance of the rehabilitation training system, coordinating and managing various modules, and ensuring system stability and user, authority, and data security.

2. The multimodal rehabilitation training system for children with cerebral palsy based on artificial intelligence according to claim 1, characterized in that: The data acquisition and preprocessing module includes a data acquisition unit, a data preprocessing unit, a data storage and management unit, and a configuration and monitoring unit; The data acquisition unit collects rehabilitation training data in real time through the sensor interface, ensures the data is complete and real-time, records the source and time stamp, and monitors the stability of the acquisition; The data preprocessing unit is responsible for cleaning, converting the format and denoising the raw data to ensure that the data is valid, in a unified format, and meets the quality requirements of subsequent analysis; The data storage management unit is used to design a secure database, encrypt stored data, manage storage structure, back up and restore data, and ensure data security and accessibility; The configuration monitoring unit is used to set interface configuration parameters, monitor acquisition preprocessing, record logs and alarms, and ensure stable operation of the system.

3. The multimodal rehabilitation training system for children with cerebral palsy based on artificial intelligence according to claim 1, characterized in that: The multimodal information fusion module includes a data fusion unit, a data analysis and feature extraction unit, a joint motion analysis and function evaluation unit, and a configuration and monitoring unit; The data fusion unit is responsible for integrating multimodal data of electromyographic signals, visual images, and brain waves to ensure spatiotemporal synchronization and complementarity, and generate a comprehensive description of the rehabilitation training status; The data analysis and feature extraction unit deeply analyzes the fused data and uses the OpenPose algorithm model to accurately extract key information on joint movement and muscle activity patterns; The joint motion analysis unit evaluates the motor function based on the characteristics and combines rehabilitation knowledge to comprehensively evaluate the motor ability of the child; The configuration and monitoring unit sets parameter models, monitors the entire multimodal processing process, ensures data accuracy and system stability, and records logs to warn of potential problems.

4. The artificial intelligence-based multimodal rehabilitation training system for children with cerebral palsy according to claim 1, characterized in that: The personalized rehabilitation training suggestion generation module includes a data integration and analysis unit, an algorithm generation suggestion unit, and a dynamic adjustment plan unit; The data integration and analysis unit is responsible for collecting and analyzing the patient's historical and current training data; The algorithm-generated recommendation unit generates personalized training recommendations by utilizing machine learning / deep learning algorithms; The dynamic plan adjustment unit dynamically adjusts the training plan according to the physical condition and rehabilitation progress.

5. The multimodal rehabilitation training system for children with cerebral palsy based on artificial intelligence according to claim 1, characterized in that: The interaction and incentive module includes an immersive experience unit, a gamification incentive unit, and a real-time feedback encouragement unit; The immersive experience unit is responsible for introducing AI voice assistants and VR visual scenes to create an immersive rehabilitation training environment for children; The gamification incentive unit stimulates the patient's interest in training and improves their participation in rehabilitation training through gamification training design; The real-time feedback encouragement unit is responsible for providing real-time feedback and encouragement to the child during the training process to enhance his or her training motivation and improve the training effect.

6. The multimodal rehabilitation training system for children with cerebral palsy based on artificial intelligence according to claim 1, characterized in that: The progress tracking and abnormal warning module includes a real-time progress tracking unit, a key data recording unit, and an abnormal warning response unit; The real-time progress tracking unit is responsible for tracking the rehabilitation training progress of the child in real time to ensure that each training activity is accurately recorded; The key data recording unit is dedicated to recording and analyzing key indicators and data during the training process, providing data support for evaluating the training effect; The abnormal behavior detection unit detects whether the child exhibits abnormal behavior during training, including irregular movements or excessive fatigue, through a preset algorithm and model; The abnormal warning response unit will immediately trigger the warning mechanism once abnormal behavior or data is found according to the actual situation, and notify relevant personnel to take corresponding measures to ensure the safety of the child and the training effect.

7. The artificial intelligence-based multimodal rehabilitation training system for children with cerebral palsy according to claim 1, characterized in that: The doctor and parent APP management module includes a user authentication and authority management unit, a training plan and progress viewing unit, a warning information receiving and processing unit, and an online communication and collaboration unit; The user authentication and authority management unit is responsible for ensuring that only legitimate doctors and parents can log in to the APP, and assigning corresponding viewing and management permissions based on roles; The training plan and progress viewing unit is responsible for providing doctors and parents with the function of remotely viewing the child's rehabilitation training plan and its execution progress, ensuring that both parties have a clear understanding of the training situation; The warning information receiving and processing unit is responsible for receiving warning information from the progress tracking and abnormal warning module in real time, and pushing notifications to doctors and parents through the APP so that they can take timely response measures; The online communication and collaboration unit is responsible for establishing an instant messaging channel between doctors and parents within the APP, facilitating communication, discussion and collaboration between both parties on the child's recovery progress.

8. The artificial intelligence-based multimodal rehabilitation training system for children with cerebral palsy according to claim 1, characterized in that: The system control and management module includes a system operation and maintenance unit, a module coordination unit, a user management unit, a permission management unit, and a data security unit; The system operation and maintenance unit is responsible for the daily operation and maintenance of the entire rehabilitation training system to ensure the stable operation of the system; The module coordination unit is used to coordinate and manage various functional modules to ensure smooth interaction and data flow between them; The user management unit is used to provide user registration, login, and information modification management functions to ensure the accuracy and security of user information; The authority management unit is responsible for assigning corresponding system permissions according to user roles, ensuring that users can only access and operate content within their authority range; The data security unit is responsible for data encryption, backup, and recovery security measures to ensure the security and reliability of system data.

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