Spine correction traction force control method and system

Abstract

The invention relates to the technical field of spine correction, in particular to a spine correction traction force control method and system, and the safety, effectiveness and intelligent level of spine correction treatment are improved. The method comprises the following steps: dividing a spine into at least three sub-regions according to an anatomical structure of the spine; the at least three sub-regions comprise a cervical vertebra region, a thoracic vertebra region and a lumbar vertebra region; performing biomechanical data acquisition on each sub-region to obtain a spine state feature set corresponding to each sub-region; the spine state feature set at least comprises a pressure distribution feature, a bending angle feature and a muscle tension feature; for different sub-regions, inputting the spine state feature set into a corresponding spine correction state evaluation model to obtain a spine correction state score of each sub-region; the anatomical structure and functional importance of the spine are considered, and the comprehensive influence weight of each sub-region is obtained from a preset weight database;

Description

Technical Field

[0001] The present invention relates to the technical field of spinal correction, and in particular to a spinal correction traction force control method and system. Background Art

[0002] With changes in modern lifestyles, spinal health issues are becoming increasingly prominent. Conditions such as scoliosis, herniated discs, and poor posture have become significant factors affecting people's quality of life. Spinal correction therapy, as an effective intervention, is widely used in clinical rehabilitation and health management. Spinal correction equipment (such as traction beds and correction chairs) applies traction to help restore the normal physiological curvature and mechanical balance of the spine, thereby relieving pain and improving function.

[0003] Existing spinal correction methods usually use fixed traction settings and fail to dynamically adjust according to the specific condition of the patient's spine. This can easily lead to insufficient or excessive traction, affecting the treatment effect and even causing secondary injuries. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention provides a spinal correction traction force control method and system that improves the safety, effectiveness and intelligence level of spinal correction treatment.

[0005] In a first aspect, the present invention provides a method for controlling spinal correction traction force, the method comprising:

[0006] Divide the spine into at least three sub-regions according to its anatomical structure; the at least three sub-regions include a cervical region, a thoracic region, and a lumbar region;

[0007] Biomechanical data is collected for each sub-region to obtain a spinal state feature set corresponding to each sub-region; the spinal state feature set includes at least pressure distribution features, bending angle features, and muscle tension features;

[0008] For different sub-regions, the spinal status feature set is input into the corresponding spinal correction status assessment model to obtain the spinal correction status score of each sub-region;

[0009] Considering the anatomical structure and functional importance of the spine, the comprehensive influence weight of each sub-region is obtained from the preset weight database;

[0010] Calculating a correction traction force requirement index according to the spinal correction status score of each sub-region and its corresponding comprehensive impact weight;

[0011] The correction traction force requirement index is compared with a preset threshold value. If the threshold value is exceeded, the traction force of the spinal correction device is dynamically adjusted; if the threshold value is not exceeded, the current traction force setting is maintained.

[0012] Furthermore, the method for constructing the spinal correction status assessment model includes:

[0013] Collect biomechanical data, medical imaging data, and clinical evaluation reports of patients with historical spinal diseases;

[0014] Clean the collected data, remove outliers and noise, and perform standardization;

[0015] Selecting a machine learning model as the infrastructure of the spinal correction status assessment model, the machine learning model includes support vector machine, gradient boosting tree, long short-term memory network, random forest and neural network;

[0016] Divide the processed dataset into training set, validation set and test set;

[0017] Use the training set to train the spinal correction status assessment model and continuously adjust the model parameters;

[0018] Use the validation set to evaluate the model's stability and predictive performance;

[0019] Use the test set to evaluate the accuracy and reliability of the model;

[0020] Deploy the trained model to the control system of the spinal correction device.

[0021] Furthermore, the spinal correction status assessment model calculates the spinal correction status score of each sub-region using the following formula:

[0022] S i =w pi ·F p +w ai ·F a +w mi ·F m

[0023] Among them, w pi is the weight of the pressure distribution feature, F p is the pressure distribution characteristic score, w ai is the weight of the bending angle feature, F a is the bending angle feature score, w mi is the weight of the muscle tension feature, F m is the muscle tension characteristic score.

[0024] Furthermore, the method for constructing the weight database includes:

[0025] Collect data on the importance of each subregion of the spine;

[0026] Process and analyze the collected data to extract key information for building a weighted database; processing and analysis methods include data cleaning, data standardization, statistical analysis, and expert scoring;

[0027] Determine the weight coefficient of each sub-region based on the extracted key information;

[0028] Design database structure, define database tables, fields and data types;

[0029] Enter the determined weight coefficient into the database and perform verification;

[0030] After the weight database is built, it will be regularly maintained and updated.

[0031] Furthermore, the formula for calculating the corrected traction demand index is:

[0032]

[0033] Where F represents the corrected traction demand index, S i represents the spinal correction status score of the i-th sub-region, W i represents the comprehensive impact weight of the i-th sub-region, and n represents the total number of sub-regions.

[0034] Furthermore, factors influencing the setting of the preset threshold include individual differences among patients, performance of spinal correction equipment, treatment goals and clinical practice.

[0035] Furthermore, the method for dynamically adjusting the traction force of a spinal correction device includes:

[0036] Determine the extent to which the corrective traction demand index exceeds a preset threshold and decide the direction and magnitude of the adjustment;

[0037] Develop adjustment strategies based on the patient's historical treatment data;

[0038] Using machine learning models to predict optimal traction settings;

[0039] Take gradual, small steps to adjust the force; after each adjustment, give the patient time to adapt to the new level of traction, and then decide whether to make further adjustments based on feedback;

[0040] Continuously monitor changes in the patient's biomechanical parameters during the adjustment process and promptly revise the adjustment plan based on real-time feedback;

[0041] Record each traction adjustment process in detail and generate treatment reports regularly.

[0042] On the other hand, the present application also provides a spinal correction traction control system, the system comprising:

[0043] A spinal region division module, which divides the spinal column into at least three sub-regions according to its anatomical structure; the at least three sub-regions include a cervical region, a thoracic region, and a lumbar region;

[0044] A biomechanical data acquisition module collects biomechanical data for each sub-region to obtain a spinal state feature set corresponding to each sub-region; the spinal state feature set includes at least pressure distribution features, bending angle features, and muscle tension features;

[0045] The correction state assessment module inputs the spinal state feature set into the corresponding spinal correction state assessment model for different sub-regions to obtain the spinal correction state score of each sub-region;

[0046] The weight acquisition module considers the anatomical structure and functional importance of the spine and obtains the comprehensive influence weight of each sub-region from the preset weight database;

[0047] a correction traction force requirement index calculation module, which calculates the correction traction force requirement index according to the spinal correction status score of each sub-region and the corresponding comprehensive impact weight;

[0048] The traction force dynamic adjustment module compares the correction traction force demand index with a preset threshold value, and dynamically adjusts the traction force of the spinal correction device if the index exceeds the threshold value; if the index does not exceed the threshold value, maintains the current traction force setting.

[0049] In a third aspect, the present application provides an electronic device comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and runnable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, and the computer program implements the steps of any one of the above methods when executed by the processor.

[0050] In a fourth aspect, the present application further provides a computer-readable storage medium having a computer program stored thereon, which implements the steps in any one of the above methods when executed by a processor.

[0051] Compared with the existing technology, the present invention has the following advantages: by dividing the spine into at least three sub-regions and collecting biomechanical data for each sub-region, it can accurately consider the individual differences of patients; more closely fit the actual situation of the patient, providing a personalized treatment plan; and can dynamically adjust the traction force according to the real-time status of each sub-region, avoiding the problem of insufficient or excessive traction, thereby improving the safety and effectiveness of treatment.

[0052] By collecting biomechanical data on pressure distribution, bending angle, and muscle tension, a more comprehensive set of spinal status features is constructed, making the assessment of spinal status more accurate and comprehensive.

[0053] A spinal correction status assessment model is introduced to obtain scores for each sub-area, and the correction traction requirement index is calculated based on the comprehensive impact weight. This achieves intelligent transformation from data to decision-making, helping to improve treatment efficiency and effectiveness.

[0054] Through precise control of traction force, the risk of secondary injury caused by inappropriate traction force is reduced, ensuring the health and safety of patients;

[0055] Taking into account the differences in anatomical structure and functional importance of different parts of the spine, the comprehensive influence weight of each sub-region is obtained from the preset weight database, making the calculation of the traction demand index more scientific and reasonable;

[0056] In summary, the spinal correction traction control method significantly improves the safety, effectiveness and intelligence level of spinal correction treatment through personalized, dynamic and data-driven treatment methods. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 is a flow chart of the spinal correction traction force control method in Example 1;

[0058] Figure 2 It is a flowchart of the method for constructing a spinal correction status assessment model;

[0059] Figure 3 It is a structural diagram of the spinal correction traction control system in Example 2. DETAILED DESCRIPTION

[0060] In the description of this application, those skilled in the art should know that this application can be implemented as a method, an apparatus, an electronic device, and a computer-readable storage medium. Therefore, this application can be specifically implemented in the following forms: complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software. In addition, in some embodiments, this application can also be implemented in the form of a computer program product in one or more computer-readable storage media, wherein the computer-readable storage medium contains computer program code.

[0061] The computer-readable storage medium may be any combination of one or more computer-readable storage media. Computer-readable storage media include: electrical, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or components, or any combination thereof. More specific examples of computer-readable storage media include: portable computer disks, hard disks, random access memories, read-only memories, erasable programmable read-only memories, flash memory, optical fibers, optical disc read-only memories, optical storage devices, magnetic storage devices, or any combination thereof. In this application, a computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, device, or component.

[0062] The acquisition, storage, use, and processing of data in this application's technical solution comply with relevant national laws.

[0063] This application describes the provided methods, devices, and electronic devices through flowcharts and / or block diagrams.

[0064] It should be understood that each block in the flowchart and / or block diagram, as well as combinations of blocks in the flowchart and / or block diagram, can be implemented by computer-readable program instructions. These computer-readable program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, thereby producing a machine. These computer-readable program instructions are executed by the computer or other programmable data processing device to produce a device that implements the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0065] These computer-readable program instructions may also be stored in a computer-readable storage medium that enables a computer or other programmable data processing device to operate in a specific manner. In this way, the instructions stored in the computer-readable storage medium produce an instruction device product that implements the functions / operations specified in the blocks in the flowchart and / or block diagram.

[0066] Computer-readable program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other device, so that a series of operational steps are performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby enabling the instructions executed on the computer or other programmable data processing apparatus to provide a process that implements the functions / operations specified by the blocks in the flowchart and / or block diagram.

[0067] The present application is described below in conjunction with the accompanying drawings.

[0068] Example 1: Figures 1 to 2 As shown, a spinal correction traction force control method of the present invention specifically includes the following steps:

[0069] S1. Divide the spinal column into at least three sub-regions based on its anatomical structure; the at least three sub-regions include a cervical region, a thoracic region, and a lumbar region;

[0070] The cervical spine is located at the top of the spine and is composed of seven cervical vertebrae. The cervical spine is highly flexible, allowing the head to move in multiple directions. During spinal correction, the cervical spine requires special attention because cervical spine problems can cause severe nerve compression symptoms, such as arm numbness and neck pain.

[0071] When dividing the cervical spine into regions, it is necessary to consider its anatomical structure and functional characteristics, such as the size of the intervertebral foramen, the shape of the spinous processes, and the orientation of the transverse processes. This helps to more accurately position and manipulate the spine during subsequent spinal status assessment and corrective treatment.

[0072] The thoracic spine is located between the cervical and lumbar vertebrae and is composed of twelve thoracic vertebrae. The thoracic spine supports and protects organs within the chest cavity, such as the heart, lungs, and esophagus. The thoracic spine is relatively stable and has little flexibility, primarily providing axial support and stability to the spine.

[0073] In spinal correction, problems in the thoracic spine area include thoracic kyphosis and thoracic scoliosis. These problems can cause symptoms such as back pain and respiratory restriction. Therefore, when dividing the thoracic spine area, attention should be paid to its stability and support function to provide appropriate traction and support during subsequent correction treatment.

[0074] The lumbar region is located at the lower part of the spine and is composed of five lumbar vertebrae. The lumbar region is the part of the spine that bears the greatest load and is therefore the most susceptible to injury and degeneration. The main function of the lumbar spine is to provide flexion and rotation of the spine and support the weight of the upper body.

[0075] During spinal correction, lumbar spine problems include lumbar disc herniation, lumbar spinal stenosis, and lumbar scoliosis. These problems can lead to symptoms such as lower back pain, numbness in the lower limbs, and difficulty walking. Therefore, when dividing the lumbar spine, special attention should be paid to its load characteristics and movement function to provide appropriate traction and support during subsequent correction treatment.

[0076] The scientific basis for the division of the spine into at least three sub-regions based on its anatomical structure includes:

[0077] Physiological curvature differences: The physiological curvatures of the cervical, thoracic, and lumbar vertebrae are different, resulting in different mechanical properties and functional requirements;

[0078] Mechanical load distribution: Different areas of the spine bear different mechanical loads. The lumbar spine bears the greatest load, followed by the cervical spine, and the thoracic spine bears relatively less load.

[0079] Nerve distribution characteristics: The nerve distribution and function of different regions are different. Dividing the regions helps to protect the nerve structure in a targeted manner.

[0080] Differences in treatment needs: Spinal problems in different areas require different treatment strategies. Regional division can provide a basis for precise treatment.

[0081] In this step, by dividing the spine into three sub-regions: cervical, thoracic and lumbar according to its anatomical structure, the foundation is laid for providing each patient with a personalized correction plan. Taking into account the unique anatomical structure and functional characteristics of each sub-region, the traction force and other treatment parameters can be adjusted more accurately to meet the specific needs of different parts. In view of the high flexibility of the cervical region and the possible nerve compression symptoms, the stability of the thoracic region and its protective effect on internal organs, and the maximum load and vulnerability borne by the lumbar region, this partitioning method helps to achieve more accurate positioning and operation in subsequent spinal status assessment and correction treatment, ensuring the effectiveness and safety of the treatment. Taking into account the physiological curvature differences and mechanical load distribution of different regions, it can help to design a better adaptable Corrective devices that follow the natural shape of the spine and provide appropriate mechanical support; because different areas have different nerve distribution characteristics, reasonable zoning can reduce pressure on these sensitive nerve structures and prevent potential nerve damage; by scientifically and reasonably zoning the spine and understanding the physiological principles behind it, medical professionals can more efficiently identify problems during diagnosis and treatment and develop corresponding treatment plans; this not only improves the effectiveness of treatment, but also reduces unnecessary diagnosis and treatment time; based on all the above factors, this sophisticated zoning strategy can significantly improve the patient's recovery experience, reduce pain and other discomfort, and accelerate the process of returning to normal activity levels; in addition, it also helps prevent secondary injuries and is beneficial to maintaining good spinal health in the long run.

[0082] S2. Collect biomechanical data for each sub-region to obtain a spinal state feature set corresponding to each sub-region; the spinal state feature set includes at least pressure distribution features, bending angle features, and muscle tension features;

[0083] The method for obtaining the spinal column status feature set includes:

[0084] Pressure distribution characteristics refer to the pressure distribution of the spine and its surrounding tissues in static or dynamic states;

[0085] Using a pressure sensor array embedded in the spinal correction device, the pressure distribution at the interface between the spine and the device is monitored in real time. Three-dimensional pressure imaging technology is used to generate pressure distribution maps for each subregion of the spine.

[0086] The curvature angle characteristics refer to the changes in the curvature of the spine in the sagittal, coronal and transverse planes;

[0087] Use an optical motion capture system or inertial measurement unit sensor to monitor the movement trajectory and angle changes of the spine in real time; use 3D modeling technology to reconstruct the curvature of the spine and calculate the bending angle of each sub-region;

[0088] Muscle tone characteristics refer to the tension and activity of the muscles around the spine;

[0089] Surface electromyography sensors are attached to key muscle groups around the spine to monitor muscle electrical activity in real time; mechanical sensors are used to measure the static tension of the muscles;

[0090] A high-precision pressure sensor is used in the cervical spine area to monitor the contact pressure between the neck and the correction device; a motion capture system is used to measure the flexion, extension, and lateral bending angles of the cervical spine; and an sEMG sensor is used to monitor the tension of the neck muscles.

[0091] A pressure sensor array is used in the thoracic spine area to monitor the pressure distribution between the thoracic spine and the correction device; a motion capture system is used to measure the scoliosis and rotation angle of the thoracic spine; and a sEMG sensor is used to monitor the tension of the back muscles.

[0092] A pressure sensor is used in the lumbar spine area to monitor the contact pressure between the lumbar spine and the correction device; the flexion, extension and scoliosis angles of the lumbar spine are measured through a motion capture system; and a sEMG sensor is used to monitor the tension of the lumbar muscles.

[0093] In this step, by using advanced sensor technology and three-dimensional modeling, the pressure distribution, bending angle and muscle tension characteristics of the spine and its surrounding tissues can be accurately captured; this high-precision data collection method significantly improves the accuracy of the assessment of spinal health status, allowing doctors to more clearly understand the specific problems of each sub-area; due to differences in the anatomical structure and pathological conditions of different patients, through detailed data collection, a personalized set of spinal status characteristics can be obtained; it provides a solid foundation for the subsequent formulation of highly targeted and adaptable correction plans, which helps to improve the effect of treatment; real-time monitoring of the pressure distribution on the contact surface between the spine and the correction device, as well as changes in muscle tension, can help It helps prevent over-traction or under-traction; ensures that the traction force is within a safe range, reduces the risk of secondary injury, and improves the safety of treatment; dynamically monitors changes in the curvature angle of the spine, and combined with pressure distribution and muscle tension data, enables doctors to adjust treatment parameters in a timely manner, thereby better restoring the normal physiological curvature and mechanical balance of the spine and accelerating the recovery process; with the help of intuitive visualization tools, patients can see their spinal status and improvement more clearly, which increases their confidence in treatment and promotes a positive attitude of cooperation; through detailed biomechanical data collection, it not only enhances the scientific nature and effectiveness of spinal correction treatment, but also improves patients' sense of security and satisfaction.

[0094] S3. For different sub-regions, the spinal status feature set is input into the corresponding spinal correction status assessment model to obtain a spinal correction status score for each sub-region;

[0095] The method for constructing the spinal correction status assessment model includes:

[0096] Collect biomechanical data, medical imaging data, and clinical evaluation reports of patients with spinal diseases from a large number of clinical cases;

[0097] The collected data is cleaned to remove outliers and noise; then normalized to ensure that data from different sources can be compared on the same scale;

[0098] Selecting a machine learning model as the infrastructure of the spinal correction status assessment model, the machine learning model includes support vector machine, gradient boosting tree, long short-term memory network, random forest and neural network;

[0099] The processed dataset is divided into training set (70%), validation set (15%) and test set (15%);

[0100] Use the training set to train the spinal correction status assessment model and continuously adjust the model parameters to improve the model's prediction accuracy and generalization ability;

[0101] Use the validation set to evaluate the model's stability and predictive performance;

[0102] Use the test set to evaluate the accuracy and reliability of the model and calculate evaluation indicators such as mean square error, precision, and recall;

[0103] Deploy the trained model to the control system of the spinal correction device to achieve real-time spinal status assessment and traction control;

[0104] The spinal correction status assessment model calculates the spinal correction status score of each sub-region using the following formula:

[0105] S i =w pi ·F p +w ai ·F a +w mi ·F m

[0106] Among them, w pi is the weight of the pressure distribution feature, F p is the pressure distribution characteristic score, w ai is the weight of the bending angle feature, F a is the bending angle feature score, w mi is the weight of the muscle tension feature, F m is the muscle tension characteristic score.

[0107] In this step, by collecting and analyzing biomechanical data, medical imaging data, and clinical evaluation reports from a large number of clinical cases, we ensure that the basis of model training is a large amount of real-world data, thereby improving the accuracy and reliability of model predictions; each sub-region has its own unique anatomical structure and functional characteristics, and the use of an evaluation model specific to each sub-region can provide a more personalized score, providing a scientific basis for doctors to formulate targeted treatment plans; deploying the trained model to the control system of the spinal correction equipment can achieve real-time spinal status assessment; this allows the traction force to be dynamically adjusted according to the patient's immediate response during treatment, avoiding excessive or insufficient traction, reducing the risk of secondary injury, and improving the treatment effect; through continuous Adjusting model parameters to improve prediction accuracy and generalization ability ensures that the model can adapt to the specific conditions of different patients and further enhances the safety and effectiveness of treatment; displaying the evaluation results of the model through visualization tools can help patients more intuitively understand their own conditions and improvements, and increase their confidence and cooperation in treatment; adopting standardized data processing procedures and scoring systems ensures that data from different sources can be compared on the same scale, and also makes the scores of different patients comparable, which facilitates doctors to conduct comprehensive evaluations and comparative studies; step S3 constructs a scientific and reasonable spinal correction status assessment model, which not only improves the accuracy, safety and effectiveness of spinal correction treatment, but also promotes the development of medical technology and the improvement of user experience.

[0108] S4. Considering the anatomical structure and functional importance of the spine, the comprehensive influence weight of each sub-region is obtained from the preset weight database;

[0109] The method for constructing the weight database includes:

[0110] Collect data on the importance of each subregion of the spine by reviewing relevant literature, clinical data, expert opinions, and other means. The collected data should cover people of different age groups, genders, and disease types.

[0111] Process and analyze the collected data to extract key information for building a weighted database; processing and analysis methods include data cleaning, data standardization, statistical analysis, and expert scoring;

[0112] Determine the weight coefficient: Determine the weight coefficient of each sub-region based on its performance in the importance assessment indicators and the expert scoring results;

[0113] Design the database structure to store, query and update weight coefficients; including defining database tables, fields, data types, etc.;

[0114] Enter the determined weight coefficient into the database and verify it to ensure the accuracy and completeness of the data;

[0115] After the weight database is built, it will be regularly maintained and updated, including data updates, database optimization, and user feedback.

[0116] In this step, data on the importance of each sub-region of the spine are collected through various channels such as consulting relevant literature, clinical data, and expert opinions to ensure the accuracy of weight setting; the data covers people of different age groups, genders, disease types, etc., so that the weight coefficient can be applied to a wide range of patient groups, improving the versatility and applicability of the model; the weight coefficient fully considers the anatomical position and functional characteristics of each sub-region in the spine, provides a scientific basis for personalized traction adjustment, and helps to improve the effect and safety of treatment; it not only relies on quantitative data analysis, but also combines qualitative expert scoring to ensure that the weight setting is in line with scientific principles and close to actual clinical needs; the weight database can be integrated into the control system of the spinal correction equipment to achieve real-time call and update; this enables doctors to dynamically adjust traction settings based on the latest evaluation results, optimize treatment plans, and improve treatment efficiency; through precise weight setting, excessive or insufficient traction is avoided, the risk of secondary injury caused by improper treatment is reduced, and the overall quality of treatment is improved; the use of unified data processing and analysis methods ensures that data from different sources can be compared on the same scale, and the weight coefficients of different patients are comparable, which is convenient for doctors to conduct comprehensive evaluations and comparative studies; the process of determining the weight coefficient is open and transparent, and easy to understand and explain, which enhances the trust of doctors and patients in treatment plans; regular maintenance and updates ensure that the weight database can continuously adapt to new medical discoveries and technological advances, and always maintain its advanced nature and applicability.

[0117] S5. Calculate a correction traction force requirement index based on the spinal correction status score of each sub-region and its corresponding comprehensive impact weight;

[0118] The comprehensive impact weight reflects the importance of different spinal subregions in overall spinal health and function. For each subregion, its spinal correction status score is multiplied by the corresponding comprehensive impact weight to obtain the local traction force requirement contribution value of the subregion.

[0119] The total corrective traction requirement index is calculated by adding up the local traction requirement contributions of all sub-areas. The calculated corrective traction requirement index is a comprehensive value that reflects the current degree of traction requirement of the entire spine.

[0120] To ensure the accuracy and comparability of the corrected traction demand index, the calculated index needs to be normalized. This process involves converting the index to a specific range of values ​​or comparing it to a benchmark value to obtain a relative value. This helps simplify the logic and decision-making process for subsequent traction adjustment.

[0121] The formula for calculating the corrected traction demand index is:

[0122]

[0123] Where F represents the corrected traction demand index, S i represents the spinal correction status score of the i-th sub-region, W i represents the comprehensive impact weight of the i-th sub-region, and n represents the total number of sub-regions.

[0124] In this step, by considering the anatomical structure and functional importance of different spinal sub-regions, as well as their current status scores, this method can provide each patient with a personalized correction plan; make the treatment more tailored to individual needs, and improve the effectiveness and pertinence of the treatment; use the overall correction traction demand index obtained by adding the local traction demand contribution values ​​to achieve precise control of the traction force; ensure sufficient correction force to achieve the treatment purpose, and avoid the risks of excessive traction; this method not only focuses on the situation of a single sub-region, but also takes the importance of each part into consideration through comprehensive influence weights, thereby providing a more comprehensive and accurate overall assessment; in addition, it supports dynamic adjustment based on real-time monitoring data to increase It enhances the safety and flexibility of treatment; standardizes the calculated corrective traction demand index so that it falls within a specific numerical range or is converted into a relative value, which facilitates the comparison of data between different patients and is easier for clinicians to understand and apply; at the same time, it simplifies the logic and decision-making process of subsequent traction adjustment, thereby improving treatment efficiency; by scientifically quantifying and integrating the needs of each sub-area, it helps to establish a systematic and standardized treatment process, reduces the influence of human factors, and promotes the consistency and stability of treatment quality; based on a detailed analysis of the spinal status and appropriate weight distribution, this method can effectively prevent secondary injuries caused by improper traction while ensuring therapeutic efficacy, thereby protecting the health and safety of patients.

[0125] S6. Comparing the correction traction force requirement index with a preset threshold value, and dynamically adjusting the traction force of the spinal correction device if the correction force requirement index exceeds the threshold value; and maintaining the current traction force setting if the correction force requirement index does not exceed the threshold value.

[0126] The factors affecting the setting of the preset threshold include:

[0127] Individual patient differences: Patients of different ages and genders have different tolerance and responses to traction. The patient's weight and body shape will affect the load on the spine and the distribution of traction. Heavier patients may require greater traction to achieve therapeutic effects, but may also be more susceptible to excessive traction. The patient's spinal history, such as scoliosis and herniated disc, will affect their response and tolerance to traction. Therefore, for patients with specific spinal histories, more detailed thresholds may need to be set.

[0128] Performance of spinal correction devices: Different models of spinal correction devices have different traction force ranges. When setting the threshold, the device's maximum and minimum traction forces need to be considered to ensure that the adjusted traction force remains within the device's performance range. The device's precision and stability determine the accuracy and reliability of traction force adjustment. These performance parameters of the device need to be considered when setting the threshold to ensure that the adjusted traction force can be accurately and stably applied to the patient.

[0129] Treatment goals: Treatment goals and patient responses may vary at different stages of spinal correction; therefore, different thresholds need to be set based on the treatment stage; different treatment goals may require different thresholds to optimize treatment outcomes;

[0130] Clinical practice: Propose recommendations or consensus on threshold setting based on clinical experience and research data;

[0131] A method for dynamically adjusting the traction force of a spinal correction device, comprising:

[0132] Determine the extent to which the corrected traction demand index exceeds the preset threshold and decide the direction and magnitude of the adjustment. If the demand index is significantly higher than the threshold, it means that the current traction is insufficient and needs to be increased appropriately. Conversely, if it is close to or slightly exceeds the threshold, only minor adjustments are required.

[0133] Combine the patient's historical treatment data, consider the previous adjustment effects, and formulate an adjustment strategy;

[0134] Utilize machine learning models to predict optimal traction settings; these models can provide precise adjustment recommendations based on the patient's real-time status profile, past treatment records, and clinical guidelines.

[0135] To avoid discomfort or risks caused by sudden and drastic changes in traction force, gradual adjustments in small steps are used. After each adjustment, the patient is given time to adapt to the new traction force level, and further adjustments are decided based on feedback.

[0136] During the adjustment process, the patient's biomechanical parameters are continuously monitored, and the adjustment plan is promptly modified based on real-time feedback. At the same time, patients or medical staff are allowed to provide subjective feelings as an auxiliary basis for adjustment.

[0137] To prevent the traction force from exceeding the safe range, set a maximum traction force limit on the hardware to ensure that excessive traction will not occur due to system failure or misoperation;

[0138] Develop software protection mechanisms to prompt medical staff for confirmation before making drastic adjustments, or set up automatic rollback functions to immediately revert to safe settings when an abnormality is detected;

[0139] Record each traction adjustment process in detail, including the time point, reason, specific parameter changes, etc.

[0140] Generate treatment reports regularly to summarize adjustments made over a period of time and their corresponding effects, so that doctors can evaluate the effectiveness of the treatment plan and make necessary adjustments accordingly.

[0141] In this step, by comprehensively considering the individual differences of patients, the most appropriate traction setting can be tailored for each patient; ensuring a high degree of personalization of the treatment plan, improving the effectiveness and safety of the treatment, and reducing the discomfort or risks caused by universal settings; combining the performance parameters of the spinal correction device, a reasonable preset threshold can be set, and ensuring that the adjusted traction is accurately and stably applied to the patient; not only enhances the safety of the treatment, but also improves the consistency of the treatment effect; according to different treatment goals and treatment stages, dynamic adjustment of traction can better meet the treatment needs of each period; help to accelerate the rehabilitation process, improve patient satisfaction and quality of life; use machine learning models to analyze the patient's real-time status feature set, past treatment records and clinical guidelines, providing scientific data support, making each adjustment more accurate and reliable; this data-based approach also allows for continuous improvement and optimization Optimized treatment strategy; gradual small-step adjustments are adopted to avoid the discomfort or risks that may be caused by sudden and drastic changes in traction; patients are given enough time to adapt to the new settings after each adjustment, which helps reduce their anxiety and promotes better treatment effects; changes in biomechanical parameters are continuously monitored during the adjustment process, and fine-tuning is performed based on the subjective feelings of patients or medical staff, ensuring flexibility and responsiveness during the treatment process; the real-time feedback mechanism enables doctors to respond to any adverse reactions of patients in a timely manner, ensuring the safety of treatment; the maximum traction force limit in hardware and the software protection mechanism effectively prevent excessive traction or other potential risks, further ensuring the safety and reliability of treatment; the process of each traction adjustment is recorded in detail, and treatment reports are generated regularly to facilitate doctors to track treatment progress and evaluate the effects; these records also provide valuable data support for subsequent research and improvements.

[0142] Example 2: Figure 3 As shown, a spinal correction traction control system of the present invention specifically includes the following modules:

[0143] A spinal region division module, which divides the spinal column into at least three sub-regions according to its anatomical structure; the at least three sub-regions include a cervical region, a thoracic region, and a lumbar region;

[0144] A biomechanical data acquisition module collects biomechanical data for each sub-region to obtain a spinal state feature set corresponding to each sub-region; the spinal state feature set includes at least pressure distribution features, bending angle features, and muscle tension features;

[0145] The correction state assessment module inputs the spinal state feature set into the corresponding spinal correction state assessment model for different sub-regions to obtain the spinal correction state score of each sub-region;

[0146] The weight acquisition module considers the anatomical structure and functional importance of the spine and obtains the comprehensive influence weight of each sub-region from the preset weight database;

[0147] a correction traction force requirement index calculation module, which calculates the correction traction force requirement index according to the spinal correction status score of each sub-region and the corresponding comprehensive impact weight;

[0148] The traction force dynamic adjustment module compares the correction traction force demand index with a preset threshold value, and dynamically adjusts the traction force of the spinal correction device if the index exceeds the threshold value; if the index does not exceed the threshold value, maintains the current traction force setting.

[0149] By dividing the spine into multiple sub-regions and collecting and evaluating independent biomechanical data for each region, the system can accurately analyze the patient's spinal condition and provide personalized correction plans, avoiding the discomfort that may be caused by traditional fixed traction settings.

[0150] The dynamic traction adjustment module can automatically adjust the traction force based on the real-time calculated corrective traction demand index, ensuring that the most appropriate traction force is always maintained during treatment, thereby improving the safety and effectiveness of treatment and reducing the risk of secondary injury.

[0151] The biomechanical data acquisition module acquires multi-dimensional features such as pressure distribution, bending angle, and muscle tension. Combined with the correction status assessment model, the system can more comprehensively assess the patient's spinal condition, providing a scientific basis for formulating correction plans.

[0152] The system uses comprehensive influence weights from a pre-set weight database to make intelligent decisions, taking into account not only the anatomical characteristics of different sub-regions but also their functional importance, making the correction process more rational and efficient. Because the system can accurately locate and address the specific areas requiring correction, while dynamically adjusting traction to suit different treatment stages, it helps accelerate the recovery process and improve the overall treatment effect.

[0153] Dynamic adjustment mechanism and threshold comparison can help prevent over-traction or under-traction, ensuring the treatment process is safe and effective;

[0154] In summary, this system not only improves the professional level and technical content of spinal correction treatment, but also brings patients a safer and more effective treatment experience.

[0155] The various variations and specific embodiments of the spinal correction traction force control method in the aforementioned embodiment 1 are also applicable to the spinal correction traction force control system of this embodiment. Through the aforementioned detailed description of the spinal correction traction force control method, those skilled in the art can clearly understand the implementation method of the spinal correction traction force control system of this embodiment. Therefore, for the sake of brevity of the specification, it will not be described in detail here.

[0156] In addition, the present application also provides an electronic device, including a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and runnable on the processor. The transceiver, the memory, and the processor are respectively connected via a bus. When the computer program is executed by the processor, each process of the above-mentioned method embodiment for controlling output data is implemented, and the same technical effect can be achieved. To avoid repetition, it will not be described here.

[0157] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for controlling spinal correction traction force, characterized in that: The method comprises: Divide the spine into at least three sub-regions according to its anatomical structure; the at least three sub-regions include a cervical region, a thoracic region, and a lumbar region; Biomechanical data is collected for each sub-region to obtain a spinal state feature set corresponding to each sub-region; the spinal state feature set includes at least pressure distribution features, bending angle features, and muscle tension features; For different sub-regions, the spinal status feature set is input into the corresponding spinal correction status assessment model to obtain the spinal correction status score of each sub-region; Considering the anatomical structure and functional importance of the spine, the comprehensive influence weight of each sub-region is obtained from the preset weight database; Calculating a correction traction force requirement index according to the spinal correction status score of each sub-region and its corresponding comprehensive impact weight; The correction traction force requirement index is compared with a preset threshold value. If the threshold value is exceeded, the traction force of the spinal correction device is dynamically adjusted; if the threshold value is not exceeded, the current traction force setting is maintained.

2. The spinal correction traction force control method according to claim 1, characterized in that: The method for constructing the spinal correction status assessment model includes: Collect biomechanical data, medical imaging data, and clinical evaluation reports of patients with historical spinal diseases; Clean the collected data, remove outliers and noise, and perform standardization; Selecting a machine learning model as the infrastructure of the spinal correction status assessment model, the machine learning model includes support vector machine, gradient boosting tree, long short-term memory network, random forest and neural network; Divide the processed dataset into training set, validation set and test set; Use the training set to train the spinal correction status assessment model and continuously adjust the model parameters; Use the validation set to evaluate the model's stability and predictive performance; Use the test set to evaluate the accuracy and reliability of the model; Deploy the trained model to the control system of the spinal correction device.

3. The spinal correction traction force control method according to claim 2, characterized in that: The spinal correction status assessment model calculates the spinal correction status score of each sub-region using the following formula: S i =w pi ·F p +w ai ·F a +w mi ·F m Among them, w pi is the weight of the pressure distribution feature, F p is the pressure distribution characteristic score, w ai is the weight of the bending angle feature, F a is the bending angle feature score, w mi is the weight of the muscle tension feature, F m is the muscle tension characteristic score.

4. The spinal correction traction force control method according to claim 1, characterized in that: The method for constructing the weight database includes: Collect data on the importance of each subregion of the spine; Process and analyze the collected data to extract key information for building a weighted database; processing and analysis methods include data cleaning, data standardization, statistical analysis, and expert scoring; Determine the weight coefficient of each sub-region based on the extracted key information; Design database structure, define database tables, fields and data types; Enter the determined weight coefficient into the database and perform verification; After the weight database is built, it will be regularly maintained and updated.

5. The spinal correction traction force control method according to claim 1, characterized in that: The formula for calculating the corrected traction demand index is: Where F represents the corrected traction demand index, S i represents the spinal correction status score of the i-th sub-region, W i represents the comprehensive impact weight of the i-th sub-region, and n represents the total number of sub-regions.

6. The spinal correction traction force control method according to claim 1, characterized in that: Factors influencing the setting of the preset threshold include individual differences among patients, performance of spinal correction equipment, treatment goals and clinical practice.

7. The spinal correction traction force control method according to claim 1, characterized in that: A method for dynamically adjusting the traction force of a spinal correction device, comprising: Determine the extent to which the corrective traction demand index exceeds a preset threshold and decide the direction and magnitude of the adjustment; Develop adjustment strategies based on the patient's historical treatment data; Using machine learning models to predict optimal traction settings; Take gradual, small steps to adjust the force; after each adjustment, give the patient time to adapt to the new level of traction, and then decide whether to make further adjustments based on feedback; Continuously monitor changes in the patient's biomechanical parameters during the adjustment process and promptly revise the adjustment plan based on real-time feedback; Record each traction adjustment process in detail and generate treatment reports regularly.

8. A spinal correction traction control system, characterized in that: The system comprises: A spinal region division module, which divides the spinal column into at least three sub-regions according to its anatomical structure; the at least three sub-regions include a cervical region, a thoracic region, and a lumbar region; A biomechanical data acquisition module collects biomechanical data for each sub-region to obtain a spinal state feature set corresponding to each sub-region; the spinal state feature set includes at least pressure distribution features, bending angle features, and muscle tension features; The correction state assessment module inputs the spinal state feature set into the corresponding spinal correction state assessment model for different sub-regions to obtain the spinal correction state score of each sub-region; The weight acquisition module considers the anatomical structure and functional importance of the spine and obtains the comprehensive influence weight of each sub-region from the preset weight database; a correction traction force requirement index calculation module, which calculates the correction traction force requirement index according to the spinal correction status score of each sub-region and the corresponding comprehensive impact weight; The traction force dynamic adjustment module compares the correction traction force demand index with a preset threshold value, and dynamically adjusts the traction force of the spinal correction device if the index exceeds the threshold value; if the index does not exceed the threshold value, maintains the current traction force setting.

9. An electronic device for controlling spinal correction traction force, comprising a bus, a transceiver, a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the transceiver, the memory, and the processor are connected via the bus, and characterized in that: When the computer program is executed by the processor, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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