Cervical spondylosis postoperative interactive rehabilitation management system and method based on artificial intelligence

Abstract

The invention provides a cervical spondylosis postoperative interactive rehabilitation management system and method based on artificial intelligence, and relates to the technical field of artificial intelligence, and the system comprises a data collection module, a first analysis module, a second analysis module, a first judgment module, a rehabilitation plan making module and other functional modules; through cooperative operation of a plurality of functional modules, a closed loop is formed from data processing, scheme making to rehabilitation tracking, and the problems that traditional rehabilitation management is low in precision, loose in process and the like are solved.

Description

Technical Field

[0001] This invention relates to the field of artificial intelligence technology, and more specifically to an interactive rehabilitation management system and method for cervical spondylosis surgery based on artificial intelligence. Background Technology

[0002] Currently, cervical spondylosis is a series of clinical syndromes caused by degenerative and secondary changes in the cervical intervertebral discs, which irritate or compress adjacent tissues, severely affecting patients' quality of life. Anterior cervical discectomy and fusion (ACDF) is the most widely used surgical method for treating cervical spondylosis with satisfactory results. Although surgery can resolve related problems to a certain extent, it still needs to be combined with home rehabilitation exercises to achieve better treatment outcomes.

[0003] However, at present, due to various reasons such as busy work schedules, lack of reminders, and numerous daily chores, coupled with a lack of awareness of postoperative rehabilitation exercises and a lack of management systems that integrate artificial intelligence and related social software, functional exercise compliance is poor, self-management awareness is weak, and there are problems such as low rehabilitation management efficiency, loose processes, and poor results.

[0004] Therefore, how to provide an interactive rehabilitation management system for cervical spondylosis surgery that can solve the above problems is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the present invention provides an interactive rehabilitation management system and method for cervical spondylosis after surgery based on artificial intelligence. Through the collaborative operation of multiple functional modules, a closed loop is formed from data processing and plan formulation to rehabilitation tracking, which solves the problems of low accuracy and loose process in traditional rehabilitation management.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: An AI-based interactive rehabilitation management system for cervical spondylosis postoperative care includes: The data acquisition module is used to collect basic data, preoperative disease data, surgical data, and postoperative recovery data of patients after cervical spondylosis surgery. The first analysis module is connected to the data acquisition module and is used to classify the basic data, preoperative disease data, and surgical data to obtain the corresponding first classification result. The second analysis module is connected to the data acquisition module and is used to classify the basic data, surgical data and postoperative recovery data to obtain the corresponding second classification results. The first judgment module, which is connected to the first analysis module and the second analysis module, is used to generate the final classification result based on whether the first classification result and the second classification result need to be adjusted. The rehabilitation plan formulation module is connected to the first judgment module. It is used to construct a rehabilitation plan generation model and input the final classification result into the rehabilitation plan generation model for processing to obtain the corresponding postoperative rehabilitation plan for cervical spondylosis.

[0007] Preferred options also include: The rehabilitation simulation module is connected to the data acquisition module and the rehabilitation plan formulation module. It is used to establish a corresponding three-dimensional human body simulation model based on the basic data, preoperative disease data, surgical data and postoperative recovery data, and to conduct simulation training in combination with the postoperative rehabilitation plan for cervical spondylosis and the three-dimensional human body simulation model to obtain the corresponding simulated rehabilitation results.

[0008] Preferred options also include: The monitoring module is connected to the rehabilitation plan formulation module and the rehabilitation simulation module. It is used to collect monitoring data and recovery results during the patient's subsequent execution of the cervical spondylosis postoperative rehabilitation plan, and to generate corresponding actual recovery results by combining the monitoring data, recovery results and the human three-dimensional simulation model. The second judgment module, which is connected to the rehabilitation plan formulation module and the monitoring module, is used to compare the simulated rehabilitation results and the actual recovery results to determine the degree of similarity between the two.

[0009] Preferred options also include: An adjustment module, which is connected to the second judgment module and the rehabilitation simulation module, is used to adjust the postoperative rehabilitation plan for cervical spondylosis when the similarity does not meet the threshold requirement.

[0010] Preferred options also include: The prompting module is connected to the monitoring module and is used to provide a prompt when the monitoring data is missing within a preset time period.

[0011] Preferably, the first analysis module includes: A preprocessing unit, connected to the data acquisition module, is used to preprocess the basic data, preoperative disease data, surgical data, and postoperative recovery data. A classification unit, connected to the preprocessing unit, is used to perform cluster analysis based on the preprocessed basic data, preoperative disease data, and surgical data to obtain the corresponding first classification result.

[0012] Preferably, the first determination module includes: A first judgment unit, connected to the classification unit and the second analysis module, is used to determine the similarity between the first classification result and the second classification result; The first output unit is used to output the classification result with the largest number of similarities as the final classification result when the similarity meets the preset threshold, and at the same time output the corresponding first classification label. The second output unit is used to output the union of the first classification result and the second classification result when the similarity does not meet the preset threshold, and to divide the union and output the corresponding second classification label and third classification label.

[0013] Preferably, the rehabilitation plan development module includes: A model building unit, which is used to build and train a rehabilitation plan generation model; The processing unit, which is connected to the model building unit, the first output unit, and the second output unit, is used to generate a corresponding postoperative rehabilitation plan for cervical spondylosis based on the final classification result and the rehabilitation plan generation model.

[0014] This invention also provides a method for an artificial intelligence-based interactive rehabilitation management system for cervical spondylosis after surgery, comprising the following steps: Acquire and preprocess basic data, preoperative disease data, surgical data, and postoperative recovery data of patients after cervical spondylosis surgery; The basic data, preoperative disease data, and surgical data are classified to obtain the corresponding first classification result. At the same time, the basic data, surgical data, and postoperative recovery data are classified to obtain the corresponding second classification result. Determine whether the first classification result and the second classification result need to be adjusted, and generate the final classification result; A rehabilitation plan generation model is constructed, and the final classification result is input into the rehabilitation plan generation model for processing to obtain the corresponding postoperative rehabilitation plan for cervical spondylosis.

[0015] Preferred options also include: Based on the aforementioned basic data, preoperative disease data, surgical data, and postoperative recovery data, a corresponding three-dimensional human body simulation model is established. Simulation training is then conducted using the aforementioned cervical spondylosis postoperative rehabilitation plan and the aforementioned three-dimensional human body simulation model to obtain the corresponding simulated rehabilitation results. Collect monitoring data and recovery results during the patient's subsequent implementation of the cervical spondylosis postoperative rehabilitation plan, and combine the monitoring data, recovery results, and the human body three-dimensional simulation model to generate the corresponding actual recovery results; The similarity between the simulated rehabilitation results and the actual recovery results is compared. If the similarity does not meet the threshold requirement, the postoperative rehabilitation plan for cervical spondylosis is adjusted.

[0016] As can be seen from the above technical solutions, compared with the prior art, the present invention discloses an interactive rehabilitation management system and method for cervical spondylosis surgery based on artificial intelligence, which has the following beneficial effects: 1. This invention comprehensively covers multi-dimensional information about patients with cervical spondylosis. Through multiple analysis modules and classification and judgment modules, it optimizes user classification results, generates relevant rehabilitation plans for users of the same type, and feeds back monitoring data and actual recovery status during the rehabilitation process to the system, allowing patients to know their recovery progress in real time and thus cooperate more actively with training.

[0017] 2. This invention can capture abnormalities in patient recovery in real time by setting up the linkage between the monitoring module and the adjustment module, identify problems by comparing the simulation and actual recovery results, and adjust the plan in a timely manner; In summary, the rehabilitation management system provided by this invention can automatically complete processes such as data collection, classification analysis, and plan generation. It can also predict rehabilitation effects in advance through three-dimensional simulation, reducing the workload of manual data entry, calculation, and plan deduction. This allows medical staff to focus on the diagnosis and rehabilitation guidance of patients with complex conditions, and improves the scientificity and efficiency of rehabilitation plan development. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0019] Figure 1 A structural principle block diagram of an artificial intelligence-based interactive rehabilitation management system for cervical spondylosis after surgery, provided by the present invention; Figure 2 This invention provides an overall flowchart of an interactive rehabilitation management method for cervical spondylosis surgery based on artificial intelligence. Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] See Figure 1 As shown in the figure, this invention discloses an artificial intelligence-based interactive rehabilitation management system for cervical spondylosis after surgery, wherein the system can be implemented by integrating a smart WeChat mini-program, including: Data acquisition module 1 is used to collect basic data, preoperative disease data, surgical data, and postoperative recovery data of patients after cervical spondylosis surgery. The basic data may include age, gender, height, weight, education level, body mass index (BMI), exercise habits, occupational characteristics, etc. The preoperative disease data may include preoperative imaging examination results (cervical spine X-ray, CT, MRI, and other medical imaging data), cervical disability index, SF-12 scale test results (measuring the subject's physical and mental health status), functional exercise compliance scale test results, etc. The surgical data may include surgical method and duration, intraoperative blood loss, implant type (such as fusion device, plate specifications), and immediate postoperative imaging assessment data. The postoperative recovery data may include wound healing during postoperative hospitalization, changes in pain scores, and cervical spine recovery at different stages after surgery, etc. First analysis module 2, which is connected to the data acquisition module 1, is used to classify the basic data, preoperative disease data, and surgical data to obtain the corresponding first classification result; The second analysis module 3 is connected to the data acquisition module 1 and is used to classify the basic data, surgical data and postoperative recovery data to obtain the corresponding second classification results. The first judgment module 4 is connected to the first analysis module 2 and the second analysis module 3, and is used to generate the final classification result based on whether the first classification result and the second classification result need to be adjusted. The rehabilitation plan formulation module 5 is connected to the first judgment module 4 and is used to construct a rehabilitation plan generation model. The final classification result is input into the rehabilitation plan generation model for processing to obtain the corresponding postoperative rehabilitation plan for cervical spondylosis.

[0022] Specifically, the rehabilitation plan may include the following: (1) Popular science knowledge related to cervical spondylosis rehabilitation: Patients can choose according to their needs. Popular science knowledge can be displayed in items and corresponding voice functions can be added. (2) Intelligent Exercise Video: This embodiment of the invention, through literature retrieval and expert database analysis, has created a set of cervical spine exercises suitable for postoperative patients with cervical spondylosis. Patients can see their own exercises on a visual exercise interface, and there will be reminders of overexertion to prevent cervical spine damage caused by overexertion. In addition to the video display, a cartoon character image is added to the lower right corner of the video page for voice guidance. The cartoon character is cute, lively, and brightly colored, easily attracting people's attention. The cervical spine exercises include two parts: ① Neck muscle stretching and relaxation exercises: forward flexion, backward extension, left flexion, right flexion, left rotation, right rotation. Try to do each movement to the maximum extent possible, based on your own comfort, and hold for 3 seconds. You can do 2-3 sets per day. ② Shoulder and back muscle stretching and relaxation exercises: activate the scapular muscles and do shoulder rotation exercises 10 times. Strengthen the scapular muscles, straighten your chest and squeeze your back, hold for 30 seconds, 5 times per set. We recommend that patients perform the cervical spine exercises twice a day, based on their comfort. The neck exercises should be performed on the first day after ACDF surgery, after the patient gets out of bed or sits beside the bed. (3) Sharing and interaction: The WeChat mini program will add a reward function for completing the goal. Patients who complete the task every day can participate in the lottery and share with friends to achieve the effect of peer support. (4) Smart reminders: If the number of daily exercises is not met, a message will be pushed to ensure that the exercise for the day is completed.

[0023] In one specific embodiment, it also includes: The rehabilitation simulation module 6 is connected to the data acquisition module 1 and the rehabilitation plan formulation module 5. It is used to establish a corresponding three-dimensional human body simulation model based on the basic data, preoperative disease data, surgical data and postoperative recovery data, and to conduct simulation training in combination with the postoperative rehabilitation plan for cervical spondylosis and the three-dimensional human body simulation model to obtain the corresponding simulated rehabilitation results.

[0024] In one specific embodiment, it also includes: The monitoring module 7 is connected to the rehabilitation plan formulation module 5 and the rehabilitation simulation module 6. It is used to collect monitoring data and recovery results during the subsequent execution of the cervical spondylosis postoperative rehabilitation plan by the patient, and to generate corresponding actual recovery results by combining the monitoring data, recovery results and the human three-dimensional simulation model. The second judgment module 8 is connected to the rehabilitation plan formulation module 5 and the monitoring module 7, and is used to compare the simulated rehabilitation results and the actual recovery results to determine the degree of similarity between the two.

[0025] In one specific embodiment, it also includes: The adjustment module 9 is connected to the second judgment module 8 and the rehabilitation simulation module 6, and is used to adjust the postoperative rehabilitation plan for cervical spondylosis when the similarity does not meet the threshold requirements.

[0026] In one specific embodiment, it also includes: The prompting module 10 is connected to the monitoring module 7 and is used to provide a prompt when the monitoring data is missing within a preset time period.

[0027] In one specific embodiment, the first analysis module 2 includes: Preprocessing unit 21, which is connected to data acquisition module 1, is used to preprocess the basic data, preoperative disease data, surgical data and postoperative recovery data. The preprocessing process may include abnormal and irrelevant data removal and normalization. Meanwhile, the second analysis module 3 can share the standardized data obtained by preprocessing unit 21. Classification unit 22, which is connected to preprocessing unit 21, is used to perform cluster analysis based on the preprocessed basic data, preoperative disease data, and surgical data to obtain the corresponding first classification result.

[0028] In one specific embodiment, the first determining module 4 includes: The first judgment unit 41 is connected to the classification unit 22 and the second analysis module 3, and is used to determine the similarity between the first classification result and the second classification result; The first output unit 42 is used to output the classification result with the largest number as the final classification result when the similarity meets the preset threshold, and at the same time output the corresponding first classification label. The process of outputting the first label may include: (1) directly outputting the combined classification label (such as medium-risk rehabilitation), (2) if there is a slight difference between the two classification results but the similarity meets the standard, outputting the classification dimension result with a higher proportion. The second output unit 43 is used to output the union of the first classification result and the second classification result when the similarity does not meet the preset threshold, and to divide the union and output the corresponding second classification label and third classification label. Specifically, it includes: labeling the same and different parts of the first classification result and the second classification result respectively, such as outputting high-risk rehabilitation group and rapid recovery type.

[0029] In one specific embodiment, the rehabilitation plan development module 5 includes: Model building unit 51, which is used to build and train a rehabilitation plan generation model, wherein the rehabilitation plan generation model can be; The processing unit 52 is connected to the model building unit 51, the first output unit 42, and the second output unit 43, and is used to generate a corresponding postoperative rehabilitation plan for cervical spondylosis based on the final classification result and the rehabilitation plan generation model.

[0030] Specifically, the rehabilitation plan development module 5 may include: Model optimization unit 53 is connected to adjustment module 9 and model construction unit 51. It is used to optimize the rehabilitation plan generation model based on the obtained adjustment results to improve model performance. The rehabilitation plan database unit 54 is connected to the model building unit 51 and the model optimization unit 53. It is used to input new rehabilitation case data into the model training library in real time, continuously optimize model performance, and enrich the diversity of rehabilitation programs.

[0031] See Figure 2 As shown, this embodiment of the invention also provides a method for an artificial intelligence-based interactive rehabilitation management system for cervical spondylosis surgery, comprising the following steps: Acquire and preprocess basic data, preoperative disease data, surgical data, and postoperative recovery data of patients after cervical spondylosis surgery; The basic data, preoperative disease data, and surgical data are classified to obtain the corresponding first classification result. At the same time, the basic data, surgical data, and postoperative recovery data are classified to obtain the corresponding second classification result. Determine whether the first classification result and the second classification result need to be adjusted, and generate the final classification result; A rehabilitation plan generation model is constructed, and the final classification result is input into the rehabilitation plan generation model for processing to obtain the corresponding postoperative rehabilitation plan for cervical spondylosis.

[0032] In one specific embodiment, it also includes: Based on the aforementioned basic data, preoperative disease data, surgical data, and postoperative recovery data, a corresponding three-dimensional human body simulation model is established. Simulation training is then conducted using the aforementioned cervical spondylosis postoperative rehabilitation plan and the aforementioned three-dimensional human body simulation model to obtain the corresponding simulated rehabilitation results. Collect monitoring data and recovery results during the patient's subsequent implementation of the cervical spondylosis postoperative rehabilitation plan, and combine the monitoring data, recovery results, and the human body three-dimensional simulation model to generate the corresponding actual recovery results; The similarity between the simulated rehabilitation results and the actual recovery results is compared. If the similarity does not meet the threshold requirement, the postoperative rehabilitation plan for cervical spondylosis is adjusted.

[0033] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0034] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. An artificial intelligence-based interactive rehabilitation management system for cervical spondylosis postoperative care, characterized in that, include: The data acquisition module (1) is used to collect basic data, preoperative disease data, surgical data and postoperative recovery data of patients after cervical spondylosis surgery; The first analysis module (2) is connected to the data acquisition module (1) and is used to classify the basic data, preoperative disease data and surgical data to obtain the corresponding first classification result; The second analysis module (3) is connected to the data acquisition module (1) and is used to classify the basic data, surgical data and postoperative recovery data to obtain the corresponding second classification results. The first judgment module (4) is connected to the first analysis module (2) and the second analysis module (3) and is used to generate the final classification result based on whether the first classification result and the second classification result need to be adjusted. The rehabilitation plan formulation module (5) is connected to the first judgment module (4) and is used to construct a rehabilitation plan generation model. The final classification result is input into the rehabilitation plan generation model for processing to obtain the corresponding postoperative rehabilitation plan for cervical spondylosis.

2. The interactive rehabilitation management system for cervical spondylosis surgery based on artificial intelligence according to claim 1, characterized in that, Also includes: The rehabilitation simulation module (6) is connected to the data acquisition module (1) and the rehabilitation plan formulation module (5). It is used to establish a corresponding three-dimensional human body simulation model based on the basic data, preoperative disease data, surgical data and postoperative recovery data, and to conduct simulation training in combination with the postoperative rehabilitation plan for cervical spondylosis and the three-dimensional human body simulation model to obtain the corresponding simulated rehabilitation results.

3. The interactive rehabilitation management system for cervical spondylosis surgery based on artificial intelligence according to claim 1, characterized in that, Also includes: The monitoring module (7) is connected to the rehabilitation plan formulation module (5) and the rehabilitation simulation module (6) to collect monitoring data and recovery results during the subsequent execution of the cervical spondylosis postoperative rehabilitation plan by the patient, and to generate corresponding actual recovery results by combining the monitoring data, recovery results and the human three-dimensional simulation model. The second judgment module (8) is connected to the rehabilitation plan formulation module (5) and the monitoring module (7) and is used to compare the simulated rehabilitation results and the actual recovery results to determine the degree of similarity between the two.

4. The interactive rehabilitation management system for cervical spondylosis surgery based on artificial intelligence according to claim 3, characterized in that, Also includes: The adjustment module (9) is connected to the second judgment module (8) and the rehabilitation simulation module (6) and is used to adjust the postoperative rehabilitation plan for cervical spondylosis when the similarity does not meet the threshold requirements.

5. The interactive rehabilitation management system for cervical spondylosis surgery based on artificial intelligence according to claim 3, characterized in that, Also includes: The prompting module (10) is connected to the monitoring module (7) and is used to provide a prompt when the monitoring data is missing within a preset time period.

6. The interactive rehabilitation management system for cervical spondylosis surgery based on artificial intelligence according to claim 1, characterized in that, The first analysis module (2) includes: The preprocessing unit (21) is connected to the data acquisition module (1) and is used to preprocess the basic data, preoperative disease data, surgical data and postoperative recovery data. The classification unit (22) is connected to the preprocessing unit (21) and is used to perform cluster analysis based on the preprocessed basic data, preoperative disease data and surgical data to obtain the corresponding first classification result.

7. The interactive rehabilitation management system for cervical spondylosis surgery based on artificial intelligence according to claim 6, characterized in that, The first judgment module (4) includes: The first judgment unit (41) is connected to the classification unit (22) and the second analysis module (3) to determine the similarity between the first classification result and the second classification result; The first output unit (42) is used to output the classification result with the largest number as the final classification result when the similarity meets the preset threshold, and at the same time output the corresponding first classification label. The second output unit (43) is used to output the union of the first classification result and the second classification result when the similarity does not meet the preset threshold, and to divide the union and output the corresponding second classification label and third classification label.

8. The artificial intelligence-based interactive rehabilitation management system for cervical spondylosis surgery according to claim 7, characterized in that, The rehabilitation plan development module (5) includes: Model building unit (51), which is used to build and train a rehabilitation plan generation model; The processing unit (52) is connected to the model building unit (51), the first output unit (42), and the second output unit (43) and is used to generate a corresponding postoperative rehabilitation plan for cervical spondylosis based on the final classification result and the rehabilitation plan generation model.

9. A method for using the artificial intelligence-based interactive rehabilitation management system for cervical spondylosis surgery as described in any one of claims 1-8, characterized in that, Includes the following steps: Acquire and preprocess basic data, preoperative disease data, surgical data, and postoperative recovery data of patients after cervical spondylosis surgery; The basic data, preoperative disease data, and surgical data are classified to obtain the corresponding first classification result. At the same time, the basic data, surgical data, and postoperative recovery data are classified to obtain the corresponding second classification result. Determine whether the first classification result and the second classification result need to be adjusted, and generate the final classification result; A rehabilitation plan generation model is constructed, and the final classification result is input into the rehabilitation plan generation model for processing to obtain the corresponding postoperative rehabilitation plan for cervical spondylosis.

10. The method according to claim 9, characterized in that, Also includes: Based on the aforementioned basic data, preoperative disease data, surgical data, and postoperative recovery data, a corresponding three-dimensional human body simulation model is established. Simulation training is then conducted using the aforementioned cervical spondylosis postoperative rehabilitation plan and the aforementioned three-dimensional human body simulation model to obtain the corresponding simulated rehabilitation results. Collect monitoring data and recovery results during the patient's subsequent implementation of the cervical spondylosis postoperative rehabilitation plan, and combine the monitoring data, recovery results, and the human body three-dimensional simulation model to generate the corresponding actual recovery results; The similarity between the simulated rehabilitation results and the actual recovery results is compared. If the similarity does not meet the threshold requirement, the postoperative rehabilitation plan for cervical spondylosis is adjusted.

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