Intelligent rehabilitation treatment management system and method based on big data

Abstract

The invention discloses an intelligent rehabilitation treatment management system and method based on big data, and relates to the technical field of intelligent management. During operation of the system, rehabilitation-related data of an orthopedic patient is collected, real-time data is obtained through intelligent wearable equipment and a sensor, the pain and fatigue state of the patient is monitored, preprocessing is carried out, and the patient is subjected to rehabilitation treatment; the method comprises the following steps: analyzing collected data, monitoring the rehabilitation progress of a patient in real time, calculating to obtain a comprehensive rehabilitation progress evaluation index Etotal, comparing the comprehensive rehabilitation progress evaluation index Etotal with a preset state threshold value M and a second preset state threshold value N to generate a personalized rehabilitation scheme, and remotely monitoring rehabilitation data of the patient by a doctor so as to obtain a personalized rehabilitation scheme. According to the method, the rehabilitation plan and the training progress of a patient can be checked through a mobile phone APP, the rehabilitation plan, the training progress and real-time feedback are fed back, intelligent reminding is obtained, and through rehabilitation video or voice guidance, the patient can share experience, exchange rehabilitation experience and obtain psychological support and encouragement.

Description

Technical Field

[0001] The present invention relates to the field of intelligent management technology, and in particular to an intelligent rehabilitation treatment management system and method based on big data. Background Art

[0002] For orthopedic rehabilitation treatment, the traditional rehabilitation management method mainly relies on the experience of doctors and the consciousness of patients. The rehabilitation process is relatively simple and difficult to monitor in real time. This method not only lacks dynamic adjustment of personalized treatment plans, but also cannot evaluate the rehabilitation effect in time, resulting in a long rehabilitation cycle for patients and insufficient rehabilitation quality. In recent years, with the rapid development of big data technology, wearable devices and Internet of Things technology, intelligent rehabilitation treatment management has gradually become a research hotspot in the field of orthopedic rehabilitation. Traditional rehabilitation management methods often rely on regular offline diagnosis and treatment, and it is difficult for doctors to track the rehabilitation progress of patients in real time, resulting in delayed adjustment of rehabilitation plans. Secondly, the rehabilitation training of patients depends on personal consciousness, lacks accurate real-time data support, and cannot automatically feedback and make necessary optimizations during the training process. Thirdly, the traditional rehabilitation method lacks unified data analysis, making it difficult to scientifically evaluate the progress and effect of rehabilitation.

[0003] In the traditional orthopedic rehabilitation management model, rehabilitation progress depends on the doctor's clinical experience and the patient's subjective feedback, but lacks real-time and objective data information. This situation leads to blindness and lag in the rehabilitation process. Once the rehabilitation plan cannot be adjusted in time or the patient's rehabilitation training is not effective, it may cause secondary injury or prolong the rehabilitation cycle, increasing the patient's treatment costs and pain. Especially in terms of pain and fatigue management, traditional methods are difficult to provide effective monitoring and adjustment, which makes it easy for patients to become overly tired or have increased pain during the rehabilitation process, thus affecting the rehabilitation effect. These shortcomings highlight the urgent need for a more intelligent management system that can optimize the rehabilitation plan through data-driven, evaluate the rehabilitation progress in real time, reduce the occurrence of abnormal rehabilitation phenomena, and ensure the safety and effectiveness of the rehabilitation process. Summary of the invention

[0004] In view of the deficiencies in the prior art, the present invention provides an intelligent rehabilitation treatment management system and method based on big data, which solves the problems mentioned in the background technology.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent rehabilitation treatment management system based on big data, including a data acquisition module, a data processing module, an intelligent analysis module, a remote monitoring module, a patient interaction module and a rehabilitation guidance module; The data acquisition module is used to collect rehabilitation-related data of orthopedic patients, including joint range of motion, bone healing progress, muscle strength and gait information, obtain real-time data through smart wearable devices and sensors, and monitor the pain and fatigue status of patients; The data processing module is used to store the collected orthopedic rehabilitation data in the big data platform and perform data cleaning and standardization processing; The intelligent analysis module is used to monitor the patient's rehabilitation progress in real time by analyzing the collected data, and calculate and obtain the comprehensive rehabilitation progress evaluation index E according to the joint range of motion, muscle strength and pain score data. total , through the comprehensive rehabilitation progress assessment index E total Compare with the preset state threshold M and the second preset state threshold N, generate a personalized rehabilitation plan, obtain the evaluation plan and transmit it to the remote monitoring module; The remote monitoring module is used to accept the evaluation plan, and the doctor remotely monitors the patient's rehabilitation data, understands the rehabilitation progress, and promptly makes suggestions or adjusts the rehabilitation plan to ensure that the patient can receive efficient rehabilitation treatment at home or outside the clinic; The patient interaction module is used for patients to view rehabilitation plans, training progress and real-time feedback through mobile phone APP, obtain intelligent reminders, and ensure that rehabilitation training is completed in the correct way through rehabilitation video or voice guidance; The rehabilitation guidance module is used to provide standardized rehabilitation training video guidance to help patients complete professional rehabilitation training. Through the patient community interactive platform, patients can share experiences and exchange rehabilitation insights and obtain psychological support and encouragement.

[0006] Preferably, the data acquisition module includes a physiological data acquisition unit, a bone healing monitoring unit and a pain fatigue status monitoring unit; The physiological data acquisition unit is used to collect the patient's joint activity and muscle strength through wearable devices or implantable sensors to obtain: the current joint activity θ now 、The theoretical maximum range of motion of the joint θ max ; The bone healing monitoring unit is used to monitor the bone healing progress of patients with fractures or after surgery, collect bone density changes and bone imaging data, and obtain: the current bone healing status D now , Bone healing status value D in the early postoperative period surgery and the status value D when fully healed max ; The pain fatigue status monitoring unit is used to detect the patient's subjective assessment of pain intensity, pain duration, pain location, pain type and muscle fatigue through patient feedback or pain monitoring equipment, and obtain: muscle strength recovery status M t .

[0007] Preferably, the data processing module includes a data storage unit and a data preprocessing unit; The data storage unit is used to store the collected orthopedic rehabilitation data in the big data platform; The data preprocessing unit is used to clean the collected data, remove noise data and outliers, standardize the processed data, ensure that sensor data from different sources are analyzed consistently, and prepare to be input into the intelligent analysis module.

[0008] Preferably, the intelligent analysis module includes a rehabilitation progress analysis unit and a state threshold comparison unit; The rehabilitation progress analysis unit is used to evaluate the rehabilitation progress based on the pre-processed joint range of motion, muscle strength and bone healing data using a formula to obtain the following comprehensive rehabilitation progress evaluation index E total , Joint range of motion recovery rate A t and Progress in Bone Healing t ; The rehabilitation progress assessment index E total Calculated by the following formula: ; Among them, E total A is the comprehensive rehabilitation progress assessment index. t is the recovery rate of joint range of motion, B t For bone healing progress, M t is the muscle strength recovery, w1, w2 and w3 are the corresponding weight coefficients.

[0009] Preferably, the joint range of motion recovery rate At is calculated by the following formula: ; Among them, A t Indicates the current joint range of motion recovery rate. is the current range of motion of the joint, is the theoretical maximum range of motion of the joint; The bone healing progress Bt is calculated by the following formula: ; Among them, B t For bone healing progress, D now is the current bone healing status, D surgery D is the initial bone healing status after surgery. max The state when it is fully healed.

[0010] Preferably, the state threshold comparison unit is used to compare the rehabilitation progress assessment index E totalCompare with the first preset state threshold M and the second preset state threshold N to determine whether the patient's rehabilitation progress meets the standard, generate a rehabilitation assessment plan based on the rehabilitation progress analysis and threshold comparison results, and transmit the results to the remote monitoring module; When the rehabilitation progress evaluation index E total <The first preset state threshold M, the first level of rehabilitation state is obtained, indicating that the rehabilitation progress is less than 30% below the expected level, the patient's recovery speed is slow, and there are obstacles such as insufficient rehabilitation training, pain or fatigue. The frequency of daily rehabilitation training is gradually increased, and it is recommended to increase the training time by 20-30%; When the first preset state threshold M≤rehabilitation progress assessment index E total ≤ the second preset state threshold N, the second level rehabilitation state is obtained, the rehabilitation progress is in line with expectations, the patient's recovery speed is within the normal range, and the current rehabilitation program is continued to maintain the frequency, intensity and duration of the current training; When the rehabilitation progress evaluation index E total >The second preset state threshold N, the rehabilitation progress exceeds expectations by more than 25%, the patient recovers quickly, and there is the potential to further accelerate the rehabilitation progress. The system recommends gradually increasing the intensity and difficulty of training.

[0011] Preferably, the remote monitoring module includes a rehabilitation data monitoring unit and a program adjustment unit; The rehabilitation data monitoring unit is used to display the patient's rehabilitation data in real time, so that the doctor can remotely monitor and understand the patient's rehabilitation status; The program adjustment unit is used to receive the rehabilitation assessment program transmitted from the intelligent analysis module, display the rehabilitation progress, and provide suggestions. The doctor uses this unit to remotely adjust the rehabilitation program according to the patient's rehabilitation progress, modify the frequency and intensity of rehabilitation training, or add new rehabilitation items.

[0012] Preferably, the patient interaction module includes a rehabilitation plan display unit, a real-time feedback unit and an intelligent reminder unit; The rehabilitation plan display unit is used to display the rehabilitation training plan to the patient, including daily training tasks, training time and target progress; The real-time feedback unit is used to display the patient's rehabilitation data and training completion status in real time, and provide real-time feedback to help the patient understand the rehabilitation effect; The intelligent reminder unit is used to automatically remind patients to perform rehabilitation training according to the rehabilitation plan, and provide personalized rehabilitation suggestions to help patients complete training tasks on time.

[0013] Preferably, the rehabilitation guidance module includes a rehabilitation training guidance unit and a psychological support unit; The rehabilitation training guidance unit is used to provide professional rehabilitation training videos to help patients correctly complete various training tasks according to the rehabilitation plan, including joint range of motion training and strength training; The psychological support unit is used for patients to interact with other rehabilitation patients, share rehabilitation experiences and insights, enhance rehabilitation confidence, provide psychological counseling resources and methods, help patients cope with psychological challenges in the rehabilitation process, and ensure mental health during the rehabilitation process.

[0014] An intelligent rehabilitation treatment management method based on big data comprises the following steps: Step 1: Collect rehabilitation-related data of orthopedic patients, including joint range of motion, bone healing progress, muscle strength and gait information, obtain real-time data through smart wearable devices and sensors, and monitor the patient's pain and fatigue status; Step 2: Store the collected orthopedic rehabilitation data in the big data platform and perform data cleaning and standardization; Step 3: Analyze the collected data to monitor the patient's rehabilitation progress in real time, and calculate and obtain the comprehensive rehabilitation progress evaluation index E based on the joint range of motion, muscle strength, and pain score data. total , through the comprehensive rehabilitation progress assessment index E total Compare with the preset state threshold M and the second preset state threshold N, generate a personalized rehabilitation plan, obtain the evaluation plan and transmit it to the remote monitoring module; Step 4: Accept the assessment plan, the doctor remotely monitors the patient's rehabilitation data, understands the rehabilitation progress, and promptly makes suggestions or adjusts the rehabilitation plan to ensure that the patient can receive efficient rehabilitation treatment at home or outside the clinic; Step 5: The patient can check the rehabilitation plan, training progress and real-time feedback through the mobile phone APP, get smart reminders, and receive rehabilitation video or voice guidance to ensure that the rehabilitation training is completed in the correct way; Step 6: Provide standardized rehabilitation training video guidance to help patients complete professional rehabilitation training. Through the patient community interactive platform, patients can share experiences and exchange rehabilitation experiences and receive psychological support and encouragement.

[0015] The present invention provides an intelligent rehabilitation treatment management system and method based on big data, which has the following beneficial effects: (1) When the system is running, it collects rehabilitation-related data of orthopedic patients, obtains real-time data through smart wearable devices and sensors, monitors the pain and fatigue status of patients, performs preprocessing, analyzes the collected data, monitors the rehabilitation progress of patients in real time, and obtains the comprehensive rehabilitation progress evaluation index E after calculation. total , through the comprehensive rehabilitation progress assessment index E totalBy comparing with the preset state threshold M and the second preset state threshold N, a personalized rehabilitation plan is generated. The doctor remotely monitors the patient's rehabilitation data and makes timely suggestions or adjusts the rehabilitation plan. The patient can view the rehabilitation plan, training progress and real-time feedback through the mobile phone APP, obtain intelligent reminders, and through rehabilitation video or voice guidance, the patient can share experiences and exchange rehabilitation insights, and obtain psychological support and encouragement.

[0016] (2) The intelligent rehabilitation treatment management system based on big data realizes the comprehensive management of the rehabilitation process of orthopedic patients through the collaborative work of six modules. The data acquisition module obtains real-time rehabilitation data through wearable devices and sensors, including joint range of motion, muscle strength, bone healing progress, etc. These data are cleaned and standardized by the data processing module and then enter the intelligent analysis module. The intelligent analysis module calculates the comprehensive rehabilitation progress evaluation index E through the rehabilitation progress evaluation formula. total , and generates personalized rehabilitation plans based on preset thresholds. The remote monitoring module provides doctors with the opportunity to understand the patient's rehabilitation progress at any time and adjust the rehabilitation plan in a timely manner. The patient interaction module and rehabilitation guidance module help patients perform rehabilitation training efficiently in their daily lives through intelligent reminders, real-time feedback and standardized rehabilitation training videos, ensuring the accurate implementation of the rehabilitation plan.

[0017] (3) Through real-time data collection and analysis, the system effectively solves the problems of lack of dynamic monitoring, insufficient personalization, and delayed assessment of rehabilitation progress in the traditional rehabilitation process. Compared with current technical means, the system introduces big data analysis and intelligent algorithms, which can monitor the patient's rehabilitation progress in real time and automatically adjust the rehabilitation plan according to changes in data. In addition, patients and doctors can obtain rehabilitation advice and feedback in real time through remote monitoring and interactive functions, avoiding the problem of rehabilitation delays caused by regular follow-up visits in traditional methods. The pain and fatigue monitoring function provides patients with a safer rehabilitation experience, reduces the risk of secondary injuries, and improves patients' rehabilitation effects and compliance.

[0018] (4) By introducing intelligent analysis technology based on big data, the system significantly improves the personalization and accuracy of rehabilitation treatment. Compared with traditional rehabilitation methods that rely on doctor experience and subjective feedback, the intelligent rehabilitation system can more scientifically evaluate the patient's rehabilitation progress and formulate a rehabilitation plan that is more in line with the patient's actual situation, thereby accelerating the rehabilitation progress and reducing the rehabilitation cycle. At the same time, the real-time pain and fatigue monitoring function optimizes the patient's training intensity and avoids the problem of rehabilitation delay caused by overtraining. Ultimately, the application of the intelligent rehabilitation treatment management system not only improves the efficiency and safety of rehabilitation treatment, but also provides new technological breakthroughs in the field of orthopedic rehabilitation, effectively improving the patient's rehabilitation experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 This is a block diagram of an intelligent rehabilitation treatment management system based on big data in the present invention; Figure 2 This is a schematic diagram of the steps of an intelligent rehabilitation treatment management method based on big data of the present invention. DETAILED DESCRIPTION

[0020] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] Example 1 The present invention provides an intelligent rehabilitation treatment management system based on big data. Figure 1 , including data acquisition module, data processing module, intelligent analysis module, remote monitoring module, patient interaction module and rehabilitation guidance module; The data acquisition module is used to collect rehabilitation-related data of orthopedic patients, including joint range of motion, bone healing progress, muscle strength and gait information, obtain real-time data through smart wearable devices and sensors, and monitor the pain and fatigue status of patients; The data processing module is used to store the collected orthopedic rehabilitation data in the big data platform and perform data cleaning and standardization processing; The intelligent analysis module is used to monitor the patient's rehabilitation progress in real time by analyzing the collected data, and calculate and obtain the comprehensive rehabilitation progress evaluation index E according to the joint range of motion, muscle strength and pain score data. total , through the comprehensive rehabilitation progress assessment index E total Compare with the preset state threshold M and the second preset state threshold N, generate a personalized rehabilitation plan, obtain the evaluation plan and transmit it to the remote monitoring module; The remote monitoring module is used to accept the evaluation plan, and the doctor remotely monitors the patient's rehabilitation data, understands the rehabilitation progress, and promptly makes suggestions or adjusts the rehabilitation plan to ensure that the patient can receive efficient rehabilitation treatment at home or outside the clinic; The patient interaction module is used for patients to view rehabilitation plans, training progress and real-time feedback through mobile phone APP, obtain intelligent reminders, and ensure that rehabilitation training is completed in the correct way through rehabilitation video or voice guidance; The rehabilitation guidance module is used to provide standardized rehabilitation training video guidance to help patients complete professional rehabilitation training. Through the patient community interactive platform, patients can share experiences and exchange rehabilitation insights and obtain psychological support and encouragement.

[0022] In this embodiment, rehabilitation-related data of orthopedic patients, including joint range of motion, bone healing progress, muscle strength and gait information, are collected, real-time data is obtained through smart wearable devices and sensors, and the pain and fatigue status of patients are monitored. The collected orthopedic rehabilitation data are stored in a big data platform, and data cleaning and standardization are performed. By analyzing the collected data, the rehabilitation progress of patients is monitored in real time, and based on the joint range of motion, muscle strength, and pain score data, the following comprehensive rehabilitation progress evaluation index E is calculated: total , through the comprehensive rehabilitation progress assessment index E total Compare with the preset state threshold M and the second preset state threshold N, generate a personalized rehabilitation plan, obtain the evaluation plan and transmit it to the remote monitoring module, accept the evaluation plan, the doctor remotely monitors the patient's rehabilitation data, understands the rehabilitation progress, and promptly makes suggestions or adjusts the rehabilitation plan to ensure that the patient can receive efficient rehabilitation treatment at home or outside the clinic. The patient can view the rehabilitation plan, training progress and real-time feedback through the mobile phone APP, obtain intelligent reminders, and use rehabilitation video or voice guidance to ensure that the rehabilitation training is completed in the correct way. Standardized rehabilitation training video guidance is provided to help patients complete professional rehabilitation training. Through the patient community interactive platform, patients can share experiences and exchange rehabilitation experiences and obtain psychological support and encouragement.

[0023] Example 2 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the data acquisition module includes a physiological data acquisition unit, a bone healing monitoring unit and a pain fatigue status monitoring unit; The physiological data acquisition unit is used to collect the patient's joint activity and muscle strength through wearable devices or implantable sensors to obtain: the current joint activity θ now 、The theoretical maximum range of motion of the joint θ max ; The bone healing monitoring unit is used to monitor the bone healing progress of patients with fractures or after surgery, collect bone density changes and bone imaging data, and obtain: the current bone healing status D now , Bone healing status value D in the early postoperative period surgery and the status value D when fully healed max ; The pain fatigue status monitoring unit is used to detect the patient's subjective assessment of pain intensity, pain duration, pain location, pain type and muscle fatigue through patient feedback or pain monitoring equipment, and obtain: muscle strength recovery status M t .

[0024] The data processing module includes a data storage unit and a data preprocessing unit; The data storage unit is used to store the collected orthopedic rehabilitation data in the big data platform; The data preprocessing unit is used to clean the collected data, remove noise data and outliers, standardize the processed data, ensure that sensor data from different sources are analyzed consistently, and prepare to be input into the intelligent analysis module.

[0025] In this embodiment, the data acquisition module realizes the comprehensive collection of multiple key parameters in the orthopedic rehabilitation process through the collaborative work of the physiological data acquisition unit, the bone healing monitoring unit and the pain and fatigue status monitoring unit. This not only includes physiological data such as joint range of motion and muscle strength, but also monitors the progress of bone healing through changes in bone density and imaging data, and comprehensively evaluates pain and fatigue status through patient feedback and monitoring equipment. The data processing module ensures that the data collected by different devices can be analyzed consistently through data cleaning and standardization, and effectively removes noise and abnormal data, making the data more accurate and reliable. The storage function of the big data platform provides high-quality basic data for system analysis, ensuring the accuracy and real-time performance of subsequent processing by the intelligent analysis module. The design of this module not only improves the integrity and availability of the data, but also provides a solid foundation for the generation of personalized rehabilitation plans.

[0026] Example 3 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the intelligent analysis module includes a rehabilitation progress analysis unit and a state threshold comparison unit; The rehabilitation progress analysis unit is used to evaluate the rehabilitation progress based on the pre-processed joint range of motion, muscle strength and bone healing data using a formula to obtain the following comprehensive rehabilitation progress evaluation index E total , Joint range of motion recovery rate A t and Progress in Bone Healing t ; The rehabilitation progress assessment index E total Calculated by the following formula: ; Among them, E total A is the comprehensive rehabilitation progress assessment index. t is the recovery rate of joint range of motion, B t For bone healing progress, M t is the muscle strength recovery, w1, w2 and w3 are the corresponding weight coefficients.

[0027] The joint range of motion recovery rate At is calculated by the following formula: ; Among them, A tIndicates the current joint range of motion recovery rate. is the current range of motion of the joint, is the theoretical maximum range of motion of the joint; The bone healing progress Bt is calculated by the following formula: ; Among them, B t For bone healing progress, D now is the current bone healing status, D surgery D is the initial bone healing status after surgery. max The state when it is fully healed.

[0028] The state threshold comparison unit is used to compare the rehabilitation progress assessment index E total Compare with the first preset state threshold M and the second preset state threshold N to determine whether the patient's rehabilitation progress meets the standard, generate a rehabilitation assessment plan based on the rehabilitation progress analysis and threshold comparison results, and transmit the results to the remote monitoring module; When the rehabilitation progress evaluation index E total <The first preset state threshold M, the first level of rehabilitation state is obtained, indicating that the rehabilitation progress is less than 30% below the expected level, the patient's recovery speed is slow, there are obstacles such as insufficient rehabilitation training, pain or fatigue, and the frequency of daily rehabilitation training is gradually increased. It is recommended to increase the training time by 20-30%, and appropriately increase the training intensity, but avoid excessively aggravating the patient's pain or fatigue. For example, if the patient is doing strength training, resistance or weight can be increased, but physiological data must be monitored to ensure that it is within a safe range. If pain is the main cause of delayed rehabilitation, it is recommended to strengthen pain management, adjust analgesics or add auxiliary physical therapy methods, such as ice compresses, massage or low-intensity physical therapy (such as ultrasonic physical therapy). After each training, the system monitors the patient's recovery time (such as the time it takes for the heart rate to return to normal) to help doctors determine whether more rest time is needed or the training intensity is reduced; When the first preset state threshold M≤rehabilitation progress assessment index E total ≤ the second preset state threshold N, obtain the second level rehabilitation state, the rehabilitation progress is in line with expectations, the patient's recovery speed is within the normal range, continue to implement the current rehabilitation plan, maintain the current training frequency, intensity and duration, the system should regularly monitor the rehabilitation progress to ensure that the patient maintains a good rehabilitation state, and on the basis of maintaining the existing training intensity, gradually add new rehabilitation items, such as balance training, flexibility training or gait optimization training, to improve the comprehensiveness of rehabilitation, and increase the monitoring of fatigue status when the rehabilitation progress is normal. If fatigue accumulates or the patient complains of increased fatigue, the training intensity can be appropriately adjusted or the rest time can be increased to prevent excessive delays in rehabilitation progress; When the rehabilitation progress evaluation index E total>The second preset state threshold N, the rehabilitation progress exceeds expectations by more than 25%, the patient recovers quickly, and has the potential to further accelerate the rehabilitation progress. The system recommends gradually increasing the intensity and difficulty of training, increasing the range and load in joint mobility training, or adding obstacles and speed requirements in gait training. While ensuring that the patient's body can withstand it, the training interval can be appropriately shortened and the daily training frequency can be increased to speed up the recovery. More strength training programs can be added, especially for major muscle groups, such as the muscles around the thigh and hip joints, to improve the patient's motor function and joint stability.

[0029] In this embodiment, the intelligent analysis module can accurately evaluate the patient's rehabilitation progress based on the pre-processed joint range of motion, muscle strength and bone healing data through the collaboration of the rehabilitation progress analysis unit and the state threshold comparison unit. The comprehensive rehabilitation progress evaluation index E calculated by the formula total , the system can determine in real time whether the rehabilitation progress is up to standard. This module can not only provide personalized rehabilitation assessment plans according to different stages of rehabilitation progress, but also accurately classify rehabilitation status through state threshold comparison, and formulate corresponding improvement strategies for patients with lagging, normal and exceeding rehabilitation progress, such as increasing training frequency, adjusting training intensity, etc. Compared with traditional rehabilitation methods that rely on subjective judgment, the intelligent analysis module provides a more scientific and accurate rehabilitation assessment and adjustment mechanism, which significantly improves the personalization and flexibility of rehabilitation plans, and helps patients recover faster and safer.

[0030] Example 4 This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the remote monitoring module includes a rehabilitation data monitoring unit and a program adjustment unit; The rehabilitation data monitoring unit is used to display the patient's rehabilitation data in real time, so that the doctor can remotely monitor and understand the patient's rehabilitation status; The program adjustment unit is used to receive the rehabilitation assessment program transmitted from the intelligent analysis module, display the rehabilitation progress, and provide suggestions. The doctor uses this unit to remotely adjust the rehabilitation program according to the patient's rehabilitation progress, modify the frequency and intensity of rehabilitation training, or add new rehabilitation items.

[0031] The patient interaction module includes a rehabilitation plan display unit, a real-time feedback unit and an intelligent reminder unit; The rehabilitation plan display unit is used to display the rehabilitation training plan to the patient, including daily training tasks, training time and target progress; The real-time feedback unit is used to display the patient's rehabilitation data and training completion status in real time, and provide real-time feedback to help the patient understand the rehabilitation effect; The intelligent reminder unit is used to automatically remind patients to perform rehabilitation training according to the rehabilitation plan, and provide personalized rehabilitation suggestions to help patients complete training tasks on time.

[0032] The rehabilitation guidance module includes a rehabilitation training guidance unit and a psychological support unit; The rehabilitation training guidance unit is used to provide professional rehabilitation training videos to help patients correctly complete various training tasks according to the rehabilitation plan, including joint range of motion training and strength training; The psychological support unit is used for patients to interact with other rehabilitation patients, share rehabilitation experiences and insights, enhance rehabilitation confidence, provide psychological counseling resources and methods, help patients cope with psychological challenges in the rehabilitation process, and ensure mental health during the rehabilitation process.

[0033] In this embodiment, the combination of the remote monitoring module, the patient interaction module and the rehabilitation guidance module realizes comprehensive remote management and personalized guidance of the rehabilitation process. Through the rehabilitation data monitoring unit of the remote monitoring module, the doctor can view the patient's rehabilitation status in real time, find problems in time, and remotely optimize the rehabilitation plan through the program adjustment unit, thereby improving the response speed and accuracy of the rehabilitation program. The patient interaction module helps patients to grasp the rehabilitation progress at any time, obtain personalized training suggestions, and ensure the effective implementation of rehabilitation training through rehabilitation plan display, real-time feedback and intelligent reminders. The professional training videos and psychological support resources provided by the rehabilitation guidance module not only enhance the patient's rehabilitation effect, but also help patients overcome the psychological challenges they may encounter during the rehabilitation process through community interaction and psychological counseling. The integration of these functions significantly improves the implementation effect of the rehabilitation program, enhances the patient's participation and compliance, and reduces the problems of insufficient or overtraining that may occur during the rehabilitation process.

[0034] Example 5 A smart rehabilitation treatment management method based on big data, please refer to Figure 2 , specifically: including the following steps: Step 1: Collect rehabilitation-related data of orthopedic patients, including joint range of motion, bone healing progress, muscle strength and gait information, obtain real-time data through smart wearable devices and sensors, and monitor the patient's pain and fatigue status; Step 2: Store the collected orthopedic rehabilitation data in the big data platform and perform data cleaning and standardization; Step 3: Analyze the collected data to monitor the patient's rehabilitation progress in real time, and calculate and obtain the comprehensive rehabilitation progress evaluation index E based on the joint range of motion, muscle strength, and pain score data. total , through the comprehensive rehabilitation progress assessment index E totalCompare with the preset state threshold M and the second preset state threshold N, generate a personalized rehabilitation plan, obtain the evaluation plan and transmit it to the remote monitoring module; Step 4: Accept the assessment plan, the doctor remotely monitors the patient's rehabilitation data, understands the rehabilitation progress, and promptly makes suggestions or adjusts the rehabilitation plan to ensure that the patient can receive efficient rehabilitation treatment at home or outside the clinic; Step 5: The patient can check the rehabilitation plan, training progress and real-time feedback through the mobile phone APP, get smart reminders, and receive rehabilitation video or voice guidance to ensure that the rehabilitation training is completed in the correct way; Step 6: Provide standardized rehabilitation training video guidance to help patients complete professional rehabilitation training. Through the patient community interactive platform, patients can share experiences and exchange rehabilitation experiences and receive psychological support and encouragement.

[0035] In this embodiment, through the above steps, the intelligent rehabilitation treatment management method based on big data realizes comprehensive and efficient management of orthopedic rehabilitation. First, the data collection and processing steps ensure the real-time collection and accurate processing of patient rehabilitation related data, providing a reliable basis for subsequent analysis. total The system can accurately generate personalized rehabilitation plans through calculation and analysis, and through the remote monitoring module, ensure timely intervention by doctors and remote adjustment of rehabilitation plans, thus improving the flexibility and effectiveness of rehabilitation management. Patients can obtain intelligent reminders, real-time feedback and rehabilitation guidance videos through mobile phone APP to help them complete rehabilitation training correctly and on time, and obtain psychological support through community interaction, which enhances the precise control and optimization of rehabilitation enthusiasm, significantly shortens the rehabilitation cycle and improves the rehabilitation effect.

[0036] Although 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 the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent rehabilitation treatment management system based on big data, characterized by: It includes data acquisition module, data processing module, intelligent analysis module, remote monitoring module, patient interaction module and rehabilitation guidance module; The data acquisition module is used to collect rehabilitation-related data of orthopedic patients, including joint range of motion, bone healing progress, muscle strength and gait information, obtain real-time data through smart wearable devices and sensors, and monitor the pain and fatigue status of patients; The data processing module is used to store the collected orthopedic rehabilitation data in the big data platform and perform data cleaning and standardization processing; The intelligent analysis module is used to monitor the patient's rehabilitation progress in real time by analyzing the collected data, and calculate and obtain the comprehensive rehabilitation progress evaluation index E according to the joint range of motion, muscle strength and pain score data. total , through the comprehensive rehabilitation progress assessment index E total Compare with the preset state threshold M and the second preset state threshold N, generate a personalized rehabilitation plan, obtain the evaluation plan and transmit it to the remote monitoring module; The remote monitoring module is used to accept the evaluation plan, and the doctor remotely monitors the patient's rehabilitation data, understands the rehabilitation progress, and promptly makes suggestions or adjusts the rehabilitation plan to ensure that the patient can receive efficient rehabilitation treatment at home or outside the clinic; The patient interaction module is used for patients to view rehabilitation plans, training progress and real-time feedback through mobile phone APP, obtain intelligent reminders, and ensure that rehabilitation training is completed in the correct way through rehabilitation video or voice guidance; The rehabilitation guidance module is used to provide standardized rehabilitation training video guidance to help patients complete professional rehabilitation training. Through the patient community interactive platform, patients can share experiences and exchange rehabilitation insights and obtain psychological support and encouragement.

2. According to the big data-based intelligent rehabilitation treatment management system of claim 1, it is characterized by: The data acquisition module includes a physiological data acquisition unit, a bone healing monitoring unit and a pain fatigue status monitoring unit; The physiological data acquisition unit is used to collect the patient's joint activity and muscle strength through wearable devices or implantable sensors to obtain: the current joint activity θ now 、The theoretical maximum range of motion of the joint θ max ; The bone healing monitoring unit is used to monitor the bone healing progress of patients with fractures or after surgery, collect bone density changes and bone imaging data, and obtain: the current bone healing status D now , Bone healing status value D in the early postoperative period surgery and the status value D when fully healed max ; The pain fatigue status monitoring unit is used to detect the patient's subjective assessment of pain intensity, pain duration, pain location, pain type and muscle fatigue through patient feedback or pain monitoring equipment, and obtain: muscle strength recovery status M t .

3. The intelligent rehabilitation treatment management system based on big data according to claim 1 is characterized by: The data processing module includes a data storage unit and a data preprocessing unit; The data storage unit is used to store the collected orthopedic rehabilitation data in the big data platform; The data preprocessing unit is used to clean the collected data, remove noise data and outliers, standardize the processed data, ensure that sensor data from different sources are analyzed consistently, and prepare to be input into the intelligent analysis module.

4. The intelligent rehabilitation treatment management system based on big data according to claim 1 is characterized by: The intelligent analysis module includes a rehabilitation progress analysis unit and a state threshold comparison unit; The rehabilitation progress analysis unit is used to evaluate the rehabilitation progress based on the pre-processed joint range of motion, muscle strength and bone healing data using a formula to obtain the following comprehensive rehabilitation progress evaluation index E total , Joint range of motion recovery rate A t and Progress in Bone Healing t ; The rehabilitation progress assessment index E total Calculated by the following formula: ； Among them, E total A is the comprehensive rehabilitation progress assessment index. t is the recovery rate of joint range of motion, B t For bone healing progress, M t is the muscle strength recovery, w1, w2 and w3 are the corresponding weight coefficients.

5. The intelligent rehabilitation treatment management system based on big data according to claim 4 is characterized in that: The joint range of motion recovery rate At is calculated by the following formula: ； Among them, A t Indicates the current joint range of motion recovery rate. is the current range of motion of the joint, is the theoretical maximum range of motion of the joint; The bone healing progress Bt is calculated by the following formula: ； Among them, B t For bone healing progress, D now is the current bone healing status, D surgery D is the initial bone healing status after surgery. max The state when it is fully healed.

6. The intelligent rehabilitation treatment management system based on big data according to claim 4 is characterized in that: The state threshold comparison unit is used to compare the rehabilitation progress assessment index E total Compare with the first preset state threshold M and the second preset state threshold N to determine whether the patient's rehabilitation progress meets the standard, generate a rehabilitation assessment plan based on the rehabilitation progress analysis and threshold comparison results, and transmit the results to the remote monitoring module; When the rehabilitation progress evaluation index E total <The first preset state threshold M, the first level of rehabilitation state is obtained, indicating that the rehabilitation progress is less than 30% below the expected level, the patient's recovery speed is slow, and there are obstacles such as insufficient rehabilitation training, pain or fatigue. The frequency of daily rehabilitation training is gradually increased, and it is recommended to increase the training time by 20-30%; When the first preset state threshold M≤rehabilitation progress assessment index E total ≤ the second preset state threshold N, the second level rehabilitation state is obtained, the rehabilitation progress is in line with expectations, the patient's recovery speed is within the normal range, and the current rehabilitation program is continued to maintain the frequency, intensity and duration of the current training; When the rehabilitation progress evaluation index E total >The second preset state threshold N, the rehabilitation progress exceeds expectations by more than 25%, the patient recovers quickly, and there is the potential to further accelerate the rehabilitation progress. The system recommends gradually increasing the intensity and difficulty of training.

7. The intelligent rehabilitation treatment management system based on big data according to claim 1 is characterized by: The remote monitoring module includes a rehabilitation data monitoring unit and a program adjustment unit; The rehabilitation data monitoring unit is used to display the patient's rehabilitation data in real time, so that the doctor can remotely monitor and understand the patient's rehabilitation status; The program adjustment unit is used to receive the rehabilitation assessment program transmitted from the intelligent analysis module, display the rehabilitation progress, and provide suggestions. The doctor uses this unit to remotely adjust the rehabilitation program according to the patient's rehabilitation progress, modify the frequency and intensity of rehabilitation training, or add new rehabilitation items.

8. The intelligent rehabilitation treatment management system based on big data according to claim 1 is characterized by: The patient interaction module includes a rehabilitation plan display unit, a real-time feedback unit and an intelligent reminder unit; The rehabilitation plan display unit is used to display the rehabilitation training plan to the patient, including daily training tasks, training time and target progress; The real-time feedback unit is used to display the patient's rehabilitation data and training completion status in real time, and provide real-time feedback to help the patient understand the rehabilitation effect; The intelligent reminder unit is used to automatically remind patients to perform rehabilitation training according to the rehabilitation plan, and provide personalized rehabilitation suggestions to help patients complete training tasks on time.

9. The intelligent rehabilitation treatment management system based on big data according to claim 1, characterized in that: The rehabilitation guidance module includes a rehabilitation training guidance unit and a psychological support unit; The rehabilitation training guidance unit is used to provide professional rehabilitation training videos to help patients correctly complete various training tasks according to the rehabilitation plan, including joint range of motion training and strength training; The psychological support unit is used for patients to interact with other rehabilitation patients, share rehabilitation experiences and insights, enhance rehabilitation confidence, provide psychological counseling resources and methods, help patients cope with psychological challenges in the rehabilitation process, and ensure mental health during the rehabilitation process.

10. An intelligent rehabilitation treatment management method based on big data, applied to an intelligent rehabilitation treatment management system based on big data as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Collect rehabilitation-related data of orthopedic patients, including joint range of motion, bone healing progress, muscle strength and gait information, obtain real-time data through smart wearable devices and sensors, and monitor the patient's pain and fatigue status; Step 2: Store the collected orthopedic rehabilitation data in the big data platform and perform data cleaning and standardization; Step 3: Analyze the collected data to monitor the patient's rehabilitation progress in real time, and calculate and obtain the comprehensive rehabilitation progress evaluation index E based on the joint range of motion, muscle strength, and pain score data. total , through the comprehensive rehabilitation progress assessment index E total Compare with the preset state threshold M and the second preset state threshold N, generate a personalized rehabilitation plan, obtain the evaluation plan and transmit it to the remote monitoring module; Step 4: Accept the assessment plan, the doctor remotely monitors the patient's rehabilitation data, understands the rehabilitation progress, and promptly makes suggestions or adjusts the rehabilitation plan to ensure that the patient can receive efficient rehabilitation treatment at home or outside the clinic; Step 5: The patient can check the rehabilitation plan, training progress and real-time feedback through the mobile phone APP, get smart reminders, and receive rehabilitation video or voice guidance to ensure that the rehabilitation training is completed in the correct way; Step 6: Provide standardized rehabilitation training video guidance to help patients complete professional rehabilitation training. Through the patient community interactive platform, patients can share experiences and exchange rehabilitation experiences and receive psychological support and encouragement.

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