Rehabilitation nursing management system

Abstract

The invention discloses a rehabilitation nursing management system, and particularly relates to the technical field of medical rehabilitation, and the system comprises a patient intelligent evaluation module which is used for comprehensively evaluating the physiological, psychological and motor function states of a patient through multi-dimensional data collection and intelligent analysis. Physiological, psychological and motion function data of a patient are collected in a multi-dimensional mode through the patient intelligent evaluation module, rehabilitation requirements are predicted based on the data, the personalized rehabilitation plan module formulates a personalized rehabilitation plan according to an evaluation result, immersion rehabilitation guidance is provided through a virtual rehabilitation coach and AR auxiliary training, and the rehabilitation effect is improved. Meanwhile, the training intensity and effect are dynamically optimized, real-time monitoring and risk early warning are achieved through a remote and cooperation module, efficient cooperation among doctors, patients and family members is ensured, the rehabilitation progress is continuously recorded and analyzed through a data driving optimization module, optimization suggestions are provided for the doctors, rehabilitation knowledge is continuously accumulated and updated, and therefore the rehabilitation effect is comprehensively improved; and the safety and effectiveness of training are ensured.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of medical rehabilitation, and particularly relates to a rehabilitation nursing management system. BACKGROUND

[0002] The rehabilitation nursing management system is an important tool for postoperative patients, chronic disease patients and functional disorder populations in the modern medical system, which helps patients recover physical functions and improve the quality of life by integrating medical data, developing rehabilitation plans and tracking treatment effects. With the intensification of population aging and the rapid development of rehabilitation medicine, the application demand of such systems in medical institutions, communities and family scenarios is growing. The current mainstream systems are mostly based on electronic medical record management, basic training plan generation and simple progress feedback function construction, aiming to reduce the workload of medical staff and improve the standardization degree of the rehabilitation process.

[0003] However, the existing rehabilitation nursing management system has single data collection dimension, often relying only on basic physiological indicators or patient subjective description, lacking fusion analysis of multi-dimensional data such as psychological state and motor function, resulting in insufficient accuracy of rehabilitation demand prediction, rehabilitation scheme being mostly static and template design, unable to dynamically adjust the training intensity according to the real-time state of the patient, and lacking immersive interaction means, resulting in limited patient compliance and training effect, remote collaboration ability, lagging doctor-patient communication, difficulty in realizing real-time risk early warning and multi-party collaborative intervention, low data utilization efficiency, and historical rehabilitation cases failing to be effectively converted into knowledge base optimization basis, restricting the continuous improvement of personalized rehabilitation. Therefore, we provide a rehabilitation nursing management system. SUMMARY

[0004] The purpose of the present application is to solve the shortcomings in the prior art and provide a rehabilitation nursing management system.

[0005] In order to achieve the above-mentioned purpose, the present application adopts the following technical solutions:

[0006] A rehabilitation nursing management system, comprising a patient intelligent evaluation module for comprehensively evaluating the physiological, psychological and motor function state of the patient through multi-dimensional data collection and intelligent analysis, a personalized rehabilitation scheme module for customizing and dynamically adjusting the rehabilitation training plan for the patient based on the evaluation results using artificial intelligence and AR technology, a remote monitoring and collaboration module for realizing real-time interaction and collaboration of doctors, patients and family members, and a data-driven optimization module for continuously optimizing the rehabilitation scheme and improving the overall rehabilitation effect through big data analysis and machine learning.

[0007] The application is further provided with: the patient intelligent evaluation module includes a biological signal monitoring module for collecting the heart rate, blood pressure and blood oxygen physiological data of the patient in real time, a motor ability analysis module for evaluating the motor function and balance ability of the patient through sensors and AI algorithms, a cognitive function test module for evaluating the memory, attention and executive function of the patient through game interaction, an emotional state recognition module for recognizing the emotional state of the patient through facial expression and voice analysis, and a rehabilitation demand prediction module for predicting the rehabilitation demand of the patient based on historical data and current state;

[0008] The personalized rehabilitation scheme module includes an intelligent scheme generation module for automatically generating a personalized rehabilitation plan according to the evaluation results, a virtual rehabilitation coach module for providing a 3D virtual image to guide the patient to carry out rehabilitation training, an AR assisted training module for providing an immersive rehabilitation experience through augmented reality technology, an intelligent progress adjustment module for dynamically adjusting the training difficulty and intensity according to the performance of the patient, and a multi-modal feedback module for integrating visual, auditory and tactile feedback to improve the training effect.

[0009] The application is further provided with: the remote monitoring and collaboration module includes a remote video guidance module for supporting doctors to remotely guide the rehabilitation training of the patient in real time, an intelligent risk warning module for warning abnormal physiological indicators and training risks in real time, a multi-terminal data synchronization module for realizing seamless connection of data of hospitals, families and mobile devices, a rehabilitation team collaboration module for providing a case discussion and scheme optimization collaboration space for a rehabilitation team, and a family member participation interface module for enabling family members to understand the progress of the patient and provide support;

[0010] The data-driven optimization module includes a rehabilitation effect tracking module for tracking and recording the rehabilitation progress and effect of the patient in the long term, a big data analysis module for mining the rules and best practices in the rehabilitation process, an intelligent report generation module for automatically generating detailed rehabilitation progress reports, a scheme optimization suggestion module for providing scheme optimization suggestions for doctors based on data analysis, and a knowledge base updating module for continuously updating the rehabilitation knowledge and best practice case library.

[0011] The application is further provided with: the intelligent progress adjustment module includes a physiological signal acquisition module for acquiring key physiological indicators such as heart rate, blood pressure and blood oxygen in real time, a motor data analysis module for analyzing the movement trajectory, speed and strength output of the patient, a rehabilitation phenotype evaluation module for comprehensively evaluating the training completion degree and quality of the patient, and a stress state determination module for determining the stress state of the patient based on physiological signals and motor data.

[0012] The application is further provided with: the physiological signal acquisition module provides health data for the motion data analysis module by real-time monitoring of key physiological indicators; the motion data analysis module provides quantitative motion for the rehabilitation performance evaluation module by analyzing the motion characteristics of the patient; the rehabilitation performance evaluation module provides comprehensive evaluation results for the stress state determination module by analyzing the training completion degree and quality; the stress state determination module provides stress state classification for subsequent intelligent adjustment decisions by integrating physiological signals and motion data analysis results.

[0013] The application is further provided with: the biological signal monitoring module provides basic health indicators for the motion ability analysis module by real-time acquisition of physiological data; the motion ability analysis module provides body state reference for the cognitive function test module by evaluating motion function; the cognitive function test module provides cognitive ability data for the emotional state recognition module by evaluating results of game-like interaction; the emotional state recognition module provides psychological state information for the rehabilitation demand prediction module by analyzing emotional state.

[0014] The application is further provided with: the intelligent scheme generation module provides training schemes for the virtual rehabilitation coach module by automatically generating rehabilitation plans; the virtual rehabilitation coach module provides motion standards for the AR assisted training module by 3D virtual image guidance; the AR assisted training module provides training data for the intelligent progress adjustment module by augmented reality technology; the intelligent progress adjustment module provides optimization suggestions for the multi-modal feedback module by dynamically adjusting training parameters.

[0015] The application is further provided with: the remote video guidance module provides training site information for the intelligent risk early warning module by real-time guidance; the intelligent risk early warning module provides safety warning data for the multi-terminal data synchronization module by anomaly detection; the multi-terminal data synchronization module provides complete case information for the rehabilitation team collaboration module by data integration; the rehabilitation team collaboration module provides professional suggestions for the family participation interface module by team discussion results.

[0016] The application is further provided with: the rehabilitation effect tracking module provides historical data for the big data analysis module by long-term tracking and recording; the big data analysis module provides analysis results for the intelligent report generation module by data mining; the intelligent report generation module provides decision basis for the scheme optimization suggestion module by automatically generating reports; the scheme optimization suggestion module provides practical cases for the knowledge base update module by optimization suggestions.

[0017] The application has the following beneficial effects:

[0018] The present application collects physiological, psychological and motor function data of patients through the patient intelligent evaluation module, and predicts rehabilitation needs based on these data, and the individualized rehabilitation program module formulates individualized rehabilitation plans according to the evaluation results, and provides immersive rehabilitation guidance through virtual rehabilitation coaches and AR assisted training, dynamically optimizes training intensity and effect, realizes real-time monitoring and risk early warning through the remote and collaborative module, ensures efficient cooperation among doctors, patients and family members, continuously records and analyzes rehabilitation progress through the data-driven optimization module, provides optimization suggestions for doctors, and continuously accumulates and updates rehabilitation knowledge, thereby comprehensively improving rehabilitation effect and ensuring safety and effectiveness of training. BRIEF DESCRIPTION OF DRAWINGS

[0019] Figure 1 The figure is a schematic diagram of the rehabilitation nursing management system in the present application.

[0020] Figure 2 The figure is a schematic diagram of the intelligent progress adjustment module in the rehabilitation nursing management system in the present application. DETAILED DESCRIPTION

[0021] In order to make the technical problems to be solved by the present application, the technical solutions and beneficial effects more clear and explicit, the present application will be further described in detail below in combination with the drawings and embodiments. It should be understood that the described embodiments are only part of the embodiments of the present application, not all the embodiments, and the specific embodiments described herein are only used to explain the present application, and are not used to limit the present application. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative labor fall within the scope of protection of the present application.

[0022] It needs to be further explained that the drawings and embodiments of the present application mainly describe and explain the concept of the present application, and on the basis of the concept, the specific forms and settings of some connection relationships, position relationships, power mechanisms, power supply systems, hydraulic systems and control systems may not be completely described, but those of ordinary skill in the art can realize the above-mentioned specific forms and settings by using well-known ways on the premise of understanding the concept of the present application.

[0023] When an element is referred to as being "fixed" or "set" on another element, it can be directly on the other element or indirectly on the other element. When an element is referred to as being "connected" to another element, it can be directly connected to the other element or indirectly connected to the other element.

[0024] The terms "inner", "outer", "length", "width", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", and the like, indicate directions or positions in accordance with the directions or positions shown in the drawings, and are used only for the purpose of facilitating the description of the present application and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application.

[0025] For the convenience of description, spatial relative terms such as "above", "upper", "upper surface", "upper", etc. can be used herein to describe the spatial positional relationship of one device or feature with respect to other devices or features as shown in the drawings. It should be understood that the spatial relative terms are intended to include different orientations in use or operation in addition to the orientation of the device described in the drawings. For example, if the device in the drawings is inverted, the device described as "above" or "above" other devices or structures will be positioned "below" or "below" other devices or structures. Thus, the exemplary term "above" can include both "above" and "below" orientations. The device can also be positioned in other different ways, and the spatial relative description used herein is interpreted accordingly.

[0026] The terms "first", "second", are used only for descriptive purposes, and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined with "first", "second" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "multiple" is two or more, and the meaning of "several" is one or more, unless otherwise explicitly specified.

[0027] Now a rehabilitation nursing management system provided by the present application will be described.

[0028] Embodiment 1

[0029] As shown in Figure 1 A rehabilitation nursing management system, comprising a patient intelligent assessment module for comprehensively assessing the physiological, psychological and motor function status of the patient through multi-dimensional data acquisition and intelligent analysis, a personalized rehabilitation program module for tailoring and dynamically adjusting the rehabilitation training plan for the patient based on the assessment results using artificial intelligence and AR technology, a remote monitoring and collaboration module for realizing real-time interaction and collaboration between doctors, patients and family members, and a data-driven optimization module for continuously optimizing the rehabilitation program and improving the overall rehabilitation effect through big data analysis and machine learning;

[0030] The patient intelligent assessment module includes a biological signal monitoring module for real-time collection of physiological data of the patient's heart rate, blood pressure, and blood oxygen, a motor function analysis module for assessing the patient's motor function and balance ability through sensors and AI algorithms, a cognitive function test module for assessing the patient's memory, attention, and executive function through gamified interaction, an emotional state recognition module for recognizing the patient's emotional state through facial expression and voice analysis, and a rehabilitation demand prediction module for predicting the patient's rehabilitation needs based on historical data and current state;

[0031] The personalized rehabilitation scheme module includes an intelligent scheme generation module for automatically generating a personalized rehabilitation plan based on the assessment results, a virtual rehabilitation coach module for providing a 3D virtual avatar to guide the patient in rehabilitation training, an AR-assisted training module for providing an immersive rehabilitation experience through augmented reality technology, an intelligent progress adjustment module for dynamically adjusting the training difficulty and intensity based on the patient's performance, and a multi-modal feedback module for integrating visual, auditory, and tactile feedback to improve training effectiveness;

[0032] The remote monitoring and collaboration module includes a remote video guidance module for supporting doctors in remotely guiding the patient's rehabilitation training in real time, an intelligent risk warning module for real-time warning of abnormal physiological indicators and training risks, a multi-end data synchronization module for seamless data connection between hospitals, families, and mobile devices, a rehabilitation team collaboration module for providing a case discussion and scheme optimization collaboration space for the rehabilitation team, and a family involvement interface module for enabling family members to understand the patient's progress and provide support;

[0033] The data-driven optimization module includes a rehabilitation effect tracking module for long-term tracking of the patient's rehabilitation progress and effect, a big data analysis module for mining patterns and best practices in the rehabilitation process, an intelligent report generation module for automatically generating detailed rehabilitation progress reports, a scheme optimization suggestion module for providing doctors with scheme optimization suggestions based on data analysis, and a knowledge base update module for continuously updating the rehabilitation knowledge and best practice case library;

[0034] The biological signal monitoring module provides basic health indicators for the motor function analysis module by collecting physiological data in real time; the motor function analysis module provides body state references for the cognitive function test module by assessing motor function; the cognitive function test module provides cognitive ability data for the emotional state recognition module through the assessment results of gamified interaction; the emotional state recognition module provides psychological state information for the rehabilitation demand prediction module by analyzing the emotional state;

[0035] The intelligent scheme generation module provides a training scheme for the virtual rehabilitation coach module by automatically generating a rehabilitation plan; the virtual rehabilitation coach module provides action standards for the AR assisted training module through 3D virtual image guidance; the AR assisted training module provides training data for the intelligent progress adjustment module through augmented reality technology; the intelligent progress adjustment module provides optimization suggestions for the multi-modal feedback module by dynamically adjusting training parameters;

[0036] The remote video guidance module provides training site information for the intelligent risk early warning module through real-time guidance; the intelligent risk early warning module provides safety warning data for the multi-end data synchronization module through anomaly detection; the multi-end data synchronization module provides complete case information for the rehabilitation team collaboration module through data integration; the rehabilitation team collaboration module provides professional suggestions for the family participation interface module through team discussion results;

[0037] The rehabilitation effect tracking module provides historical data for the big data analysis module through long-term tracking records; the big data analysis module provides analysis results for the intelligent report generation module through data mining; the intelligent report generation module provides decision-making basis for the scheme optimization suggestion module by automatically generating reports; the scheme optimization suggestion module provides practical cases for the knowledge base update module through optimization suggestions.

[0038] In the above embodiment, through the biological signal monitoring module, the motor ability analysis module, the cognitive function test module and the emotional state recognition module in the patient intelligent assessment module, the physiological, psychological and motor function data of the patient are collected in multiple dimensions, and the rehabilitation needs are predicted based on these data; then, the individualized rehabilitation scheme module formulates an individualized rehabilitation plan through the intelligent scheme generation module according to the evaluation results, and provides immersive rehabilitation guidance by the virtual rehabilitation coach module and the AR assisted training module, while the intelligent progress adjustment module and the multi-modal feedback module dynamically optimize the training intensity and effect;

[0039] In this process, the remote monitoring and collaboration module realizes real-time monitoring and risk early warning through the remote video guidance module and the intelligent risk early warning module, and ensures efficient collaboration among doctors, patients and family members through the multi-end data synchronization module, the rehabilitation team collaboration module and the family participation interface module; finally, the data-driven optimization module continuously records and analyzes the rehabilitation progress through the rehabilitation effect tracking module and the big data analysis module, uses the intelligent report generation module and the scheme optimization suggestion module to provide optimization suggestions for doctors, and continuously accumulates and updates rehabilitation knowledge through the knowledge base update module, thereby comprehensively improving the rehabilitation effect.

[0040] Embodiment 2

[0041] As Figures 1-2As shown, a rehabilitation nursing management system, the intelligent progress adjustment module includes a physiological signal acquisition module for real-time acquisition of heart rate, blood pressure, blood oxygen key physiological indicators, a motion data analysis module for analyzing the motion trajectory, speed and force output of the patient, a rehabilitation phenotype evaluation module for comprehensive evaluation of the patient's training completion degree and quality, and a stress state determination module for determining the stress state of the patient based on physiological signals and motion data;

[0042] The physiological signal acquisition module provides health data for the motion data analysis module by real-time monitoring of key physiological indicators; the motion data analysis module provides quantitative motion for the rehabilitation performance evaluation module by analyzing the motion characteristics of the patient; the rehabilitation performance evaluation module provides a comprehensive evaluation result for the stress state determination module by analyzing the training completion degree and quality; the stress state determination module provides stress state classification for subsequent intelligent adjustment decisions by integrating physiological signal and motion data analysis results.

[0043] In the above embodiment, the physiological signal acquisition module monitors the patient's heart rate, blood pressure, blood oxygen and other key physiological indicators in real time to provide health data support for the motion data analysis module; then, the motion data analysis module analyzes the patient's motion trajectory, speed and force output and other motion characteristics, and transmits the quantized motion data to the rehabilitation performance evaluation module; the rehabilitation performance evaluation module comprehensively evaluates the patient's training completion degree and quality, generates a comprehensive evaluation result and transmits it to the stress state determination module; finally, the stress state determination module integrates physiological signal and motion data analysis results to classify the patient's stress state, providing a basis for subsequent intelligent adjustment decisions, thereby dynamically optimizing the difficulty and intensity of rehabilitation training, ensuring the safety and effectiveness of training.

[0044] The determination branch of the stress state determination module includes the following four:

[0045] High pressure state:

[0046] Dynamic difficulty adjustment: reduce the training difficulty;

[0047] High-intensity training: maintain the current intensity but shorten the training time;

[0048] Medium pressure state:

[0049] Training intensity optimization: fine-tune training parameters;

[0050] Medium-intensity training: maintain the current training plan;

[0051] Low pressure state:

[0052] Rehabilitation rhythm control: appropriately increase the training intensity;

[0053] Low-intensity training: extend the training time or increase the training volume;

[0054] Abnormal state:

[0055] Safety intervention: Immediately suspend training;

[0056] Emergency pause: Start emergency handling process and notify medical staff.

[0057] Working principle: When using the present rehabilitation nursing management system, through multi-dimensional data collection and intelligent analysis, the physiological, psychological and motor function state of the patient is comprehensively evaluated, and based on the evaluation results, the patient is tailored and dynamically adjusted by artificial intelligence and AR technology. The rehabilitation training plan. The system first collects the patient's heart rate, blood pressure, blood oxygen and other physiological data through the biological signal monitoring module, motor ability analysis module, cognitive function test module and emotional state recognition module in the patient intelligent evaluation module, evaluates the patient's motor function, balance ability, cognitive function and emotional state, and predicts the rehabilitation needs. Subsequently, the individualized rehabilitation program module formulates individualized rehabilitation plans according to the evaluation results through the intelligent scheme generation module, and provides immersive rehabilitation guidance by the virtual rehabilitation coach module and the AR assisted training module, while the intelligent progress adjustment module and the multi-modal feedback module dynamically optimize the training intensity and effect, ensuring the safety and effectiveness of the training.

[0058] During the rehabilitation training process, the remote monitoring and collaboration module realizes real-time monitoring and risk warning through the remote video guidance module and the intelligent risk warning module, ensuring the safety of the patient during the training process. The multi-terminal data synchronization module seamlessly connects the data of hospitals, families and mobile devices, and the rehabilitation team collaboration module provides a collaborative space for doctors and rehabilitation teams to discuss cases and optimize schemes, and the family participation interface module allows family members to understand the patient's progress and provide support. This multi-party collaboration mechanism ensures the efficiency and continuity of rehabilitation training, while enhancing the sense of participation of patients and family members.

[0059] The data-driven optimization module tracks the patient's rehabilitation progress and effect through the rehabilitation effect tracking module for a long time, and uses the big data analysis module to mine the rules and best practices in the rehabilitation process. The intelligent report generation module automatically generates detailed rehabilitation progress reports for doctors to provide decision-making basis, and the scheme optimization suggestion module provides scheme optimization suggestions for doctors based on data analysis. The knowledge base updating module continuously updates the rehabilitation knowledge and best practice case library, ensuring that the system can continuously accumulate and optimize the rehabilitation scheme, thereby comprehensively improving the rehabilitation effect.

[0060] The intelligent progress adjustment module monitors the patient's heart rate, blood pressure, blood oxygen and other key physiological indicators in real time through the physiological signal acquisition module, providing health data support for the exercise data analysis module. The exercise data analysis module analyzes the patient's exercise trajectory, speed and strength output, and transmits the quantified exercise data to the rehabilitation performance evaluation module. The rehabilitation performance evaluation module comprehensively evaluates the patient's training completion and quality, generates a comprehensive evaluation result and transmits it to the stress state determination module. The stress state determination module integrates physiological signals and exercise data analysis results, classifies the patient's stress state, and dynamically adjusts the training difficulty and intensity according to different stress states (high pressure, medium pressure, low pressure, abnormality), ensuring the safety and effectiveness of training. For example, in a high pressure state, the system will reduce the training difficulty or shorten the training time; in a low pressure state, the system will appropriately increase the training intensity or extend the training time; and in an abnormal state, the system will immediately suspend training and start an emergency handling process, notifying medical staff to intervene.

[0061] The above merely provides the preferred embodiments of the present application, but is not intended to limit the present application. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present application shall fall within the scope of protection of the present application.

[0062] It is to be noted that the terms used herein are only for describing specific embodiments and are not intended to limit the exemplary embodiments according to the present application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprise" and / or "include" when used in this specification, specify the presence of stated features, steps, operations, devices, components and / or combinations thereof.

[0063] The relative arrangement of the components and steps, numerical expressions, and numerical values set forth in these embodiments do not limit the scope of the present application unless specifically stated otherwise. It should be understood that the sizes of the various portions shown in the drawings are not drawn to scale for ease of description. Techniques, methods, and devices known to those of ordinary skill in the relevant art can not be discussed in detail, but should be considered as part of the authorized description where appropriate. In all examples shown and discussed herein, any specific values should be interpreted as merely exemplary, and not as limiting. Therefore, other examples of the exemplary embodiments can have different values. It should be noted that similar reference numbers and letters represent similar items in the following drawings, and therefore, once an item is defined in one drawing, it need not be further discussed in subsequent drawings.

Claims

1. A rehabilitation nursing management system, characterized in that, It includes a patient intelligent assessment module for comprehensively evaluating patients' physiological, psychological, and motor function status through multi-dimensional data collection and intelligent analysis; a personalized rehabilitation program module for tailoring and dynamically adjusting rehabilitation training plans for patients based on assessment results using artificial intelligence and AR technology; a remote monitoring and collaboration module for enabling real-time interaction and collaboration among doctors, patients, and their families; and a data-driven optimization module for continuously optimizing rehabilitation programs and improving overall rehabilitation outcomes through big data analysis and machine learning.

2. The rehabilitation nursing management system according to claim 1, characterized in that, The patient intelligent assessment module includes a biosignal monitoring module for real-time collection of patients' heart rate, blood pressure, and blood oxygen physiological data; a motor ability analysis module for assessing patients' motor function and balance ability through sensors and AI algorithms; a cognitive function testing module for assessing patients' memory, attention, and executive function through gamified interaction; an emotion state recognition module for identifying patients' emotional state through facial expressions and voice analysis; and a rehabilitation need prediction module for predicting patients' rehabilitation needs based on historical data and current state. The personalized rehabilitation program module includes an intelligent program generation module for automatically generating personalized rehabilitation plans based on assessment results, a virtual rehabilitation coach module for providing 3D virtual avatars to guide patients in rehabilitation training, an AR-assisted training module for providing an immersive rehabilitation experience through augmented reality technology, an intelligent progress adjustment module for dynamically adjusting the difficulty and intensity of training based on patient performance, and a multimodal feedback module for integrating visual, auditory, and tactile feedback to improve training effectiveness.

3. The rehabilitation nursing management system according to claim 1, characterized in that, The remote monitoring and collaboration module includes a remote video guidance module for supporting doctors to remotely guide patients' rehabilitation training in real time, an intelligent risk warning module for real-time early warning of abnormal physiological indicators and training risks, a multi-terminal data synchronization module for achieving seamless data connection between hospitals, homes and mobile devices, a rehabilitation team collaboration module for providing rehabilitation teams with a collaborative space for case discussion and plan optimization, and a family participation interface module for enabling family members to understand the patient's progress and provide support. The data-driven optimization module includes a rehabilitation effect tracking module for long-term tracking and recording of patients' rehabilitation progress and effects, a big data analysis module for mining patterns and best practices in the rehabilitation process, an intelligent report generation module for automatically generating detailed rehabilitation progress reports, a plan optimization suggestion module for providing doctors with plan optimization suggestions based on data analysis, and a knowledge base update module for continuously updating rehabilitation knowledge and best practice case libraries.

4. The rehabilitation nursing management system according to claim 2, characterized in that, The intelligent progress adjustment module includes a physiological signal acquisition module for real-time collection of key physiological indicators such as heart rate, blood pressure, and blood oxygen; a motion data analysis module for analyzing the patient's movement trajectory, speed, and force output; a rehabilitation phenotype assessment module for comprehensively evaluating the patient's training completion and quality; and a stress state determination module for judging the patient's stress state based on physiological signals and motion data.

5. A rehabilitation nursing management system according to claim 4, characterized in that, The physiological signal acquisition module provides health data to the exercise data analysis module by monitoring key physiological indicators in real time; the exercise data analysis module provides quantitative exercise data to the rehabilitation performance assessment module by analyzing the patient's exercise characteristics; the rehabilitation performance assessment module provides comprehensive assessment results to the stress state determination module by comprehensively analyzing training completion and quality; and the stress state determination module provides stress state classification for subsequent intelligent adjustment decisions by integrating physiological signals and exercise data analysis results.

6. A rehabilitation nursing management system according to claim 2, characterized in that, The biosignal monitoring module provides basic health indicators for the motor ability analysis module by collecting physiological data in real time; the motor ability analysis module provides a physical status reference for the cognitive function testing module by assessing motor function; the cognitive function testing module provides cognitive ability data for the emotion state recognition module by evaluating the results through gamified interaction; and the emotion state recognition module provides psychological state information for the rehabilitation needs prediction module by analyzing emotional states.

7. A rehabilitation nursing management system according to claim 2, characterized in that, The intelligent solution generation module provides training plans for the virtual rehabilitation coach module by automatically generating rehabilitation plans; the virtual rehabilitation coach module provides movement standards for the AR-assisted training module by providing guidance through 3D virtual images; the AR-assisted training module provides training data for the intelligent progress adjustment module by using augmented reality technology; and the intelligent progress adjustment module provides optimization suggestions for the multimodal feedback module by dynamically adjusting training parameters.

8. A rehabilitation nursing management system according to claim 3, characterized in that, The remote video guidance module provides training site information to the intelligent risk warning module through real-time guidance; the intelligent risk warning module provides security warning data to the multi-terminal data synchronization module through anomaly detection. The multi-terminal data synchronization module provides complete case information to the rehabilitation team collaboration module through data integration; the rehabilitation team collaboration module provides professional advice to the family participation interface module based on the results of team discussions.

9. A rehabilitation nursing management system according to claim 3, characterized in that, The rehabilitation effect tracking module provides historical data to the big data analysis module through long-term tracking records; the big data analysis module provides analysis results to the intelligent report generation module through data mining; and the intelligent report generation module provides decision-making basis for the plan optimization suggestion module by automatically generating reports. The optimization suggestion module provides practical examples for the knowledge base update module through optimization suggestions.

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