Orthopedic complete-cycle rehabilitation management system and method based on data feedback correction

Abstract

The invention relates to an orthopaedic full-cycle rehabilitation management system and method based on data feedback correction. The system comprises a central computer, a data acquisition module and a data processing and analysis module, a rehabilitation scheme making module and a feedback correction module are arranged in the central computer; the data processing and analyzing module is used for processing and analyzing the patient data received from the data acquisition module, evaluating the recovery degree of the orthopedic patient in real time, predicting the recovery process of the patient and generating an expected recovery target of the patient; the rehabilitation scheme formulating module receives an analysis result of the data processing and analyzing module and formulates a personalized rehabilitation scheme of the orthopedic patient; and the feedback correction module corrects the rehabilitation scheme of the patient in real time according to the rehabilitation state of the patient by comparing and analyzing the patient data acquired by the data acquisition module in real time and the expected recovery target output by the data processing and analysis module. Compared with the prior art, the device has the advantages of improving the rehabilitation effect, shortening the rehabilitation period and the like.

Description

Technical Field

[0001] The present invention relates to the field of orthopedic rehabilitation management, and in particular to an orthopedic full-cycle rehabilitation management system based on data feedback correction. Background Art

[0002] Orthopedic conditions are diseases affecting the musculoskeletal system, including bones, joints, muscles, ligaments, and tendons. These conditions can severely impact a patient's health and quality of life. Orthopedic rehabilitation is a series of treatments designed to help patients recover function, alleviate pain, and improve their quality of life. To assess the effectiveness of rehabilitation, patients undergo regular rehabilitation and assessments, allowing for timely adjustments to their rehabilitation plans.

[0003] The current orthopedic rehabilitation assessment mainly relies on patient self-assessment questionnaires, observation methods and direct measurement methods. However, the self-assessment questionnaires are greatly influenced by the subjective factors of the patients and the assessment is not accurate and comprehensive enough. The observation method and direct measurement method are limited by the doctor's experience and time, and it is difficult to monitor the patient's rehabilitation process in real time and dynamically. In addition, the existing orthopedic rehabilitation programs are usually standardized and do not fully consider the individual differences of patients, resulting in poor individual rehabilitation effects. Therefore, it is easy to cause the rehabilitation cycle to be extended and the rehabilitation effect to be poor.

[0004] After searching, Chinese invention patent application publication number CN117524412A discloses an orthopedic full-cycle rehabilitation management system, method and equipment based on multi-source data, including a background management system and a user mobile terminal, a medical mobile terminal and a cloud server terminal connected to the background management system. The user mobile terminal is connected to the medical mobile terminal, the cloud server terminal includes a user rehabilitation feature data monitoring library, and the background management system includes a multi-source data collection module, a data integration module, a rehabilitation program matching module and a full-cycle rehabilitation management module connected in sequence. The present invention integrates the medical mobile terminal, the user mobile terminal, the background management system and the cloud server terminal, and realizes coordinated rehabilitation management through various functional modules. It not only guides users to complete rehabilitation step by step according to the rehabilitation plan during the rehabilitation process, but also conducts real-time feedback regulation and evaluation of the rehabilitation training process, which can effectively judge the rehabilitation status of the user's rehabilitation process and realize efficient, accurate and intelligent orthopedic rehabilitation management. The existing patent application has the problem that the evaluation results are not fed back to adjust the rehabilitation plan in real time, so the rehabilitation effect is poor and the rehabilitation cycle is long.

[0005] How to achieve full-cycle rehabilitation management based on feedback mechanism to effectively improve rehabilitation effects has become a technical problem that needs to be solved. Summary of the Invention

[0006] The purpose of the present invention is to overcome the defects of the above-mentioned prior art and to provide an orthopedic full-cycle rehabilitation management system and method based on data feedback correction.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] According to one aspect of the present invention, there is provided an orthopedic full-cycle rehabilitation management system based on data feedback correction, the system comprising a central computer, a data acquisition module and a data processing and analysis module;

[0009] The central computer has built-in rehabilitation program formulation module and feedback correction module;

[0010] The data acquisition module is used to collect the physical data of orthopedic patients in real time and send the collected results to the central computer and data processing and analysis module;

[0011] The data processing and analysis module processes and analyzes the received patient data, evaluates the degree of recovery of orthopedic patients in real time, predicts the patient's recovery process, and generates the patient's expected recovery goal;

[0012] The rehabilitation program formulation module receives the analysis results of the data processing and analysis module and formulates a personalized rehabilitation program for orthopedic patients;

[0013] During the patient's rehabilitation process, the feedback correction module compares and analyzes the patient data collected in real time by the data acquisition module with the expected recovery target output by the data processing and analysis module, and corrects the patient's rehabilitation plan in real time according to the patient's rehabilitation status.

[0014] Preferably, the data of the data acquisition module includes wearable device detection data, medical device detection data and patient basic data generated from electronic medical record data obtained from a medical record database, which together constitute a basic analysis data group.

[0015] More preferably, the wearable device detection data is connected to the patient through a wearable smart device to monitor the patient's vital signs data in real time;

[0016] Medical equipment testing data includes imaging examination data, joint range of motion data, and muscle strength data.

[0017] Preferably, the data processing and analysis module includes a big data analysis submodule and a rehabilitation prediction submodule; the big data analysis submodule processes and analyzes patient data using a big data analysis algorithm to generate rehabilitation quantitative indicators of joint range of motion, muscle strength recovery, and bone healing, and compares and analyzes the rehabilitation quantitative indicators with the analysis data group to evaluate the degree of recovery of orthopedic patients in real time;

[0018] The rehabilitation prediction submodule has a built-in rehabilitation prediction model based on a decision tree model, which is used to predict the patient's rehabilitation process through patient data, predict the patient's future rehabilitation trend based on the patient's current rehabilitation status, and generate the patient's expected recovery goal.

[0019] More preferably, the rehabilitation program formulation module receives the analysis results of the data processing and analysis module and generates a personalized rehabilitation program for the patient in combination with the patient's basic data;

[0020] The rehabilitation program includes a rehabilitation training part, a rehabilitation treatment part and a diet plan part.

[0021] More preferably, the rehabilitation training part includes the patient's exercise type, exercise intensity and exercise frequency, wherein the exercise type includes joint movement training, muscle strength training and balance training, the exercise intensity includes the training load, number of repetitions and duration, and the exercise frequency is the patient's weekly exercise frequency;

[0022] The rehabilitation treatment part generates treatment methods and treatment parameters for the patient based on the evaluation results of the rehabilitation prediction model;

[0023] The diet plan section formulates a diet plan for the patient based on an assessment of the patient's recovery level and in combination with the patient's nutritional intake needs.

[0024] More preferably, the feedback correction module receives real-time patient data from the data acquisition module, compares and analyzes the real-time patient data with the expected recovery target generated by the rehabilitation prediction model, and judges the recovery target based on the results of the comparison and analysis. If the patient reaches the recovery target, the patient's rehabilitation result is output to the medical monitoring terminal; if the patient does not reach the recovery target, the judgment result is sent to the rehabilitation plan formulation module.

[0025] More preferably, if the patient does not reach the recovery goal, the rehabilitation program formulation module combines real-time patient data to revise and adjust the rehabilitation program, generate a new rehabilitation program, and output the rehabilitation program to the medical monitoring terminal.

[0026] More preferably, the doctor uses the medical monitoring terminal to review and intervene in the revised rehabilitation plan based on clinical experience.

[0027] According to another aspect of the present invention, a method for an orthopedic full-cycle rehabilitation management system based on data feedback correction is provided, the method comprising:

[0028] S1, the data acquisition module collects the basic analysis data set of orthopedic patients, which includes wearable device detection data, medical device detection data and patient basic data;

[0029] S2, the data processing and analysis module analyzes the received basic analysis data set, processes and analyzes a large amount of patient data through big data analysis algorithms, compares and analyzes the generated rehabilitation quantitative indicators with the analysis data set, evaluates the orthopedic patient's recovery level in real time, predicts the patient's recovery process and future recovery trends, and generates the patient's expected recovery goal;

[0030] S3, the rehabilitation program formulation module receives the analysis results of the data processing and analysis module and combines them with the patient's basic data to formulate a personalized rehabilitation program for orthopedic patients;

[0031] S4. During the patient's rehabilitation process, the feedback correction module compares and analyzes the basic analysis data group collected in real time by the data acquisition module with the expected recovery target output by the data processing and analysis module, and corrects the patient's rehabilitation plan in real time according to the patient's rehabilitation status.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1) In the present invention, the data of orthopedic patients are acquired and monitored in real time through the data acquisition module. The data processing and analysis module evaluates the recovery degree of orthopedic patients in real time based on the patient data, predicts the patient's rehabilitation process, and generates the patient's expected recovery goal; the rehabilitation program formulation module formulates a personalized rehabilitation program for orthopedic patients based on the analysis results of the data processing and analysis module; during the patient's rehabilitation process, the feedback correction module compares and analyzes the patient data with the expected recovery goal, and corrects the patient's rehabilitation program in real time according to the patient's rehabilitation status, thereby realizing the management of the entire orthopedic rehabilitation cycle, which helps to improve the rehabilitation effect and shorten the rehabilitation cycle.

[0034] 2) The present invention uses data from multiple sources to construct a basic analysis data group, and analyzes and compares the basic analysis data group using quantitative indicators in the big data analysis submodule, thereby providing data support for the recovery degree of orthopedic patients. At the same time, the constructed rehabilitation prediction model is used to predict the patient's assessment. Compared with traditional evaluation methods, it can avoid the interference of patients' subjective factors and the limitations of doctors' experience and time, and can monitor the patient's rehabilitation process in real time and accurately, providing a reliable basis for adjusting the rehabilitation plan.

[0035] 3) The present invention combines the results of the rehabilitation program development module with the results of the data processing and analysis module and the patient's basic data to generate personalized rehabilitation programs for orthopedic patients based on their individual differences, thereby increasing the patient's orthopedic rehabilitation effect.

[0036] 4) In the present invention, the data collected from the patient in real time is input into the feedback correction module. By comparing the patient's real-time data with the expected recovery goal, the patient's rehabilitation plan is timely corrected and adjusted, and the corrected rehabilitation plan is output to the medical monitoring terminal. After the doctor's review and intervention, the plan is ensured to be safe and effective, significantly improving the rehabilitation effect and shortening the rehabilitation cycle. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a schematic diagram of the structure of the orthopedic full-cycle rehabilitation management system of the present invention;

[0038] Figure 2 Schematic diagram of the structure of the data acquisition module in the present invention;

[0039] Figure 3 Schematic diagram of the structure of the data processing and analysis module in the present invention;

[0040] Figure 4 A schematic diagram of the structure of the rehabilitation program formulation module in the present invention;

[0041] Figure 5 Schematic diagram of the structure of the feedback correction module in the present invention;

[0042] Figure 6 It is a flow chart of the orthopedic full-cycle rehabilitation management method of the present invention. DETAILED DESCRIPTION

[0043] 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 part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0044] Example 1

[0045] This embodiment relates to an orthopedic full-cycle rehabilitation management system based on data feedback correction, which aims to solve the problem raised in the above background technology that the existing orthopedic rehabilitation assessment is difficult to monitor the patient's rehabilitation progress in real time and dynamically, affecting the patient's rehabilitation cycle and rehabilitation effect.

[0046] like Figure 1 The orthopedic full-cycle rehabilitation management system based on data feedback and correction includes a central computer, a data acquisition module, a data processing and analysis module, a rehabilitation program formulation module, and a feedback correction module.

[0047] The central computer is the processing center of the system, enabling monitoring and management of the entire patient rehabilitation process. The central computer has a built-in rehabilitation program development module and a feedback correction module. The rehabilitation program development module is connected to the data processing and analysis module, and the feedback correction module is connected to the data acquisition module.

[0048] The data acquisition module and the data processing and analysis module are connected via wireless signals and together constitute the data management module.

[0049] like Figure 1 and Figure 2 The central computer is interconnected with the medical record database and connected to the data acquisition module. The central computer obtains the electronic medical record data of the patient in the medical record database to generate basic data of orthopedic patients, where the basic data of the patient includes age, gender, medical history and orthopedic condition. The basic data of the patient is input into the data acquisition module through the central computer.

[0050] The data acquisition module uses a variety of devices to collect real-time data of orthopedic patients. Figure 2 The data of the data acquisition module includes three parts: wearable device detection data, medical device detection data, and basic patient data generated from electronic medical record data obtained from the medical record database. Wearable device detection data is connected to the patient through a wearable smart device to monitor the patient's heart rate, number of steps, and exercise duration in real time, constituting the patient's vital signs data. Medical device detection data includes imaging examination data, joint range of motion data, and muscle strength data. Imaging examination data is obtained by connecting to medical imaging equipment, joint range of motion data is obtained by measuring with a joint range of motion meter, and muscle strength data is obtained by measuring with an electronic muscle strength tester. The wearable device detection data, medical device detection data, and electronic medical record data obtained by the data acquisition module together constitute the basic analysis data group.

[0051] The data processing and analysis module assists orthopedic patients in rehabilitation management by analyzing patient data. The data processing and analysis module receives the basic analysis data group from the data acquisition module and performs analysis and processing to provide data support for the patient's orthopedic rehabilitation management. Figure 3The data processing and analysis module includes a big data analysis submodule and a rehabilitation prediction submodule. The big data analysis submodule processes and analyzes a large amount of patient data through a big data analysis algorithm to generate rehabilitation quantitative indicators of joint mobility, muscle strength recovery, and bone healing. By comparing and analyzing the rehabilitation quantitative indicators and analysis data groups, the recovery degree of orthopedic patients can be evaluated in real time. The rehabilitation prediction submodule has a built-in rehabilitation prediction model based on a decision tree model, which is used to predict the patient's rehabilitation process through patient data, predict the patient's future rehabilitation trend based on the patient's current rehabilitation status, generate the patient's expected recovery goal, and provide data support for the formulation and adjustment of rehabilitation plans.

[0052] like Figure 4 As shown, the rehabilitation program formulation module generates a personalized rehabilitation program for the patient by analyzing the patient's data. The rehabilitation program formulation module receives the analysis results of the data processing and analysis module, and generates a personalized rehabilitation program for the patient in combination with the patient's basic data. The rehabilitation program includes a rehabilitation training part, a rehabilitation treatment part, and a diet plan part. The rehabilitation training part includes the patient's exercise type, exercise intensity, and exercise frequency, where the exercise type includes joint movement training, muscle strength training, and balance training, the exercise intensity includes the training load, number of repetitions, and duration, and the exercise frequency is the patient's weekly exercise times. The rehabilitation treatment part generates the patient's treatment methods and treatment parameters based on the evaluation results of the rehabilitation prediction model. The diet plan part formulates the patient's diet plan based on the patient's recovery degree assessment by the big data analysis submodule in the data processing and analysis module, combined with the patient's nutritional intake needs.

[0053] like Figure 4 As shown, the rehabilitation program development module receives the analysis results of the data processing and analysis module and combines them with the patient's basic data to develop a personalized rehabilitation training plan for orthopedic patients. This includes exercise types, including joint range of motion training, muscle strength training, and balance training. It also determines exercise intensity, including training load, number of repetitions and duration, as well as exercise frequency. The rehabilitation treatment component generates treatment plans based on the evaluation results of the rehabilitation prediction model, such as hot compresses, massage, electrical stimulation, magnetic therapy, and other treatment methods. The diet plan component develops a diet plan for the patient based on the patient's recovery level assessed by the big data analysis submodule and the patient's nutritional intake needs.

[0054] The feedback correction module compares and analyzes the patient's real-time data with the expected recovery goals, and corrects the patient's rehabilitation plan in real time according to the patient's recovery status. Figure 5As shown, the feedback correction module receives the patient basic analysis data set from the data acquisition module in real time, compares and analyzes the patient's real-time data (i.e., the patient basic analysis data set received in real time) with the expected recovery target generated by the rehabilitation prediction model, and judges the recovery target based on the results of the comparison analysis. If the patient reaches the recovery target, the patient's rehabilitation result is output to the medical monitoring terminal; if the patient does not reach the recovery target, the real-time patient basic analysis data set is re-input into the rehabilitation program formulation module, and the rehabilitation program is corrected and adjusted using a computer correction algorithm. A new rehabilitation program is generated and output to the medical monitoring terminal. The medical monitoring terminal reviews and intervenes in the revised rehabilitation program based on clinical experience to ensure the safety and effectiveness of the program.

[0055] Example 2

[0056] This embodiment also relates to an orthopedic full-cycle rehabilitation management method based on data feedback correction, the method comprising:

[0057] S1, the data acquisition module collects the basic analysis data set of orthopedic patients to provide data support for subsequent analysis; the basic analysis data set includes wearable device detection data, medical device detection data and patient basic data;

[0058] S2, the data processing and analysis module, analyzes the received basic analysis data set. Using big data analysis algorithms, it processes and analyzes large amounts of patient data to generate quantitative rehabilitation indicators for joint range of motion, muscle strength recovery, and bone healing. By comparing and analyzing the rehabilitation quantitative indicators with the analysis data set, the orthopedic patient's recovery level is assessed in real time. The data processing and analysis module's built-in rehabilitation prediction model uses patient data to predict the patient's recovery progress and future recovery trends based on their current recovery status. This generates the patient's expected recovery goal, providing data support for the development and adjustment of rehabilitation plans.

[0059] S3, the rehabilitation program formulation module receives the analysis results of the data processing and analysis module, and combines them with the patient's basic data to formulate a personalized rehabilitation program for orthopedic patients, including rehabilitation training, rehabilitation treatment and diet plan, to improve the recovery speed of different orthopedic patients.

[0060] During the patient's recovery process, the feedback correction module compares the basic analysis data collected in real time by the data acquisition module with the expected recovery goals output by the data processing and analysis module. It then adjusts the patient's rehabilitation plan in real time based on the patient's recovery status. If the recovery goal is not achieved, the rehabilitation plan is revised and adjusted, and the plan is dynamically optimized through the medical monitoring terminal after review and intervention by the doctor.

[0061] Example 3

[0062] The electronic device of the present invention includes a central processing unit (CPU), which can perform various appropriate actions and processes according to computer program instructions stored in a read-only memory (ROM) or loaded from a storage unit into a random access memory (RAM). In the RAM, various programs and data required for device operation can also be stored. The CPU, ROM, and RAM are connected to each other via a bus. An input / output (I / O) interface is also connected to the bus.

[0063] Many components in a device are connected to the I / O interface, including: input units, such as a keyboard and mouse; output units, such as various types of displays and speakers; storage units, such as magnetic disks and optical disks; and communication units, such as network cards, modems, and wireless communication transceivers. The communication unit allows the device to exchange information / data with other devices via computer networks such as the Internet and / or various telecommunication networks.

[0064] The processing unit performs the various methods and processes described above. For example, in some embodiments, the method can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit. In some embodiments, part or all of the computer program can be loaded and / or installed on the device via a ROM and / or a communication unit. When the computer program is loaded into RAM and executed by the CPU, one or more steps of the method described above can be performed. Alternatively, in other embodiments, the CPU can be configured to execute the method in any other appropriate manner (e.g., by means of firmware).

[0065] The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, and without limitation, exemplary types of hardware logic components that may be used include: field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chip (SOCs), complex programmable logic devices (CPLDs), and the like.

[0066] The program code for implementing the method of the present invention can be written in any combination of one or more programming languages. Such program code can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device so that when the program code is executed by the processor or controller, the functions / operations specified in the flow chart and / or block diagram are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0067] In the context of the present invention, machine-readable medium can be a tangible medium that can contain or store a program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. Machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0068] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and such modifications or substitutions are intended to be within the scope of protection of the present invention. Therefore, the scope of protection of the present invention shall be subject to the scope of protection of the claims.

Claims

1. An orthopedic full-cycle rehabilitation management system based on data feedback correction, characterized in that: The system includes a central computer, a data acquisition module and a data processing and analysis module; The central computer has built-in rehabilitation program formulation module and feedback correction module; The data acquisition module is used to collect the physical data of orthopedic patients in real time and send the collected results to the central computer and data processing and analysis module; The data processing and analysis module processes and analyzes the received patient data, evaluates the degree of recovery of orthopedic patients in real time, predicts the patient's recovery process, and generates the patient's expected recovery goal; The rehabilitation program formulation module receives the analysis results of the data processing and analysis module and formulates a personalized rehabilitation program for orthopedic patients; During the patient's rehabilitation process, the feedback correction module compares and analyzes the patient data collected in real time by the data acquisition module with the expected recovery target output by the data processing and analysis module, and corrects the patient's rehabilitation plan in real time according to the patient's rehabilitation status.

2. The orthopedic full-cycle rehabilitation management system based on data feedback correction according to claim 1 is characterized in that: The data collected by the data acquisition module includes wearable device detection data, medical device detection data, and basic patient data generated from electronic medical record data obtained from the medical record database, which together constitute the basic analysis data group.

3. The orthopedic full-cycle rehabilitation management system based on data feedback correction according to claim 2 is characterized in that: Wearable device detection data is connected to the patient through wearable smart devices to monitor the patient's vital signs data in real time; Medical equipment testing data includes imaging examination data, joint range of motion data, and muscle strength data.

4. The orthopedic full-cycle rehabilitation management system based on data feedback correction according to claim 1 is characterized in that: The data processing and analysis module includes a big data analysis submodule and a rehabilitation prediction submodule; the big data analysis submodule processes and analyzes patient data using a big data analysis algorithm to generate rehabilitation quantitative indicators for joint range of motion, muscle strength recovery, and bone healing. By comparing and analyzing the rehabilitation quantitative indicators with the analysis data group, the recovery degree of orthopedic patients is evaluated in real time; The rehabilitation prediction submodule has a built-in rehabilitation prediction model based on a decision tree model, which is used to predict the patient's rehabilitation process through patient data, predict the patient's future rehabilitation trend based on the patient's current rehabilitation status, and generate the patient's expected recovery goal.

5. The orthopedic full-cycle rehabilitation management system based on data feedback correction according to claim 2 is characterized in that: The rehabilitation program formulation module receives the analysis results of the data processing and analysis module and generates a personalized rehabilitation program for the patient based on the patient data; The rehabilitation program includes a rehabilitation training part, a rehabilitation treatment part and a diet plan part.

6. The orthopedic full-cycle rehabilitation management system based on data feedback correction according to claim 5, characterized in that: The rehabilitation training part includes the patient's exercise type, exercise intensity and exercise frequency, wherein the exercise type includes joint movement training, muscle strength training and balance training, the exercise intensity includes the training load, number of repetitions and duration, and the exercise frequency is the patient's weekly exercise frequency; The rehabilitation treatment part generates treatment methods and treatment parameters for the patient based on the evaluation results of the rehabilitation prediction model; The diet plan section formulates a diet plan for the patient based on an assessment of the patient's recovery level and in combination with the patient's nutritional intake needs.

7. The orthopedic full-cycle rehabilitation management system based on data feedback correction according to claim 4 is characterized in that: The feedback correction module receives the patient's real-time data from the data acquisition module, compares and analyzes the patient's real-time data with the expected recovery target generated by the rehabilitation prediction model, and judges the recovery target based on the results of the comparison and analysis. If the patient reaches the recovery target, the patient's rehabilitation result is output to the medical monitoring terminal; if the patient does not reach the recovery target, the judgment result is sent to the rehabilitation plan formulation module.

8. The orthopedic full-cycle rehabilitation management system based on data feedback and correction according to claim 7 is characterized in that: If the patient fails to achieve the recovery goal, the rehabilitation plan formulation module will combine real-time patient data to revise and adjust the rehabilitation plan, generate a new rehabilitation plan, and output the rehabilitation plan to the medical monitoring terminal.

9. The orthopedic full-cycle rehabilitation management system based on data feedback correction according to claim 8, characterized in that: Doctors use medical monitoring terminals to review and intervene in the revised rehabilitation plan based on clinical experience.

10. A method for an orthopedic full-cycle rehabilitation management system based on data feedback correction using any one of claims 1 to 9, characterized in that: The method includes: S1, the data acquisition module collects the basic analysis data set of orthopedic patients, which includes wearable device detection data, medical device detection data and patient basic data; S2, the data processing and analysis module analyzes the received basic analysis data set, processes and analyzes a large amount of patient data through big data analysis algorithms, compares and analyzes the generated rehabilitation quantitative indicators with the analysis data set, evaluates the orthopedic patient's recovery level in real time, predicts the patient's recovery process and future recovery trends, and generates the patient's expected recovery goal; S3, the rehabilitation program formulation module receives the analysis results of the data processing and analysis module and combines them with the patient's basic data to formulate a personalized rehabilitation program for orthopedic patients; S4. During the patient's rehabilitation process, the feedback correction module compares and analyzes the basic analysis data group collected in real time by the data acquisition module with the expected recovery target output by the data processing and analysis module, and corrects the patient's rehabilitation plan in real time according to the patient's rehabilitation status.

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