Airbag control method, medium and system for orthopedic force of scoliosis orthosis

Abstract

The present invention provides a method, medium and system for controlling the orthopedic force of a scoliosis orthosis, belonging to the technical field of scoliosis orthoses, including: adopting a method of multi-sensor data fusion to establish a contact pressure distribution model between the orthosis and the skin, a vibration model and an airbag pressure distribution model, and combining the posture characteristics of the user to establish an optimization model to maximize the correction effect, optimize the wearing comfort and minimize the energy consumption. By solving the optimization model, the optimal airbag pressure configuration scheme under different postures is obtained, and the airbag pressure is dynamically adjusted in combination with the real-time detected user posture to achieve the adaptive control of the orthopedic force of the orthosis. This system can greatly improve the correction effect and wearing comfort of the orthosis, while optimizing the energy consumption, and solves the technical problems of the existing method that the pressure adjustment mainly depends on the empirical judgment of clinicians, lacks a scientific analysis basis, has low efficiency, and is difficult to achieve precise control.

Description

Technical Field

[0001] The present invention belongs to the technical field of scoliosis orthosis, and specifically relates to a method, medium and system for controlling the orthopedic force of a scoliosis orthosis by means of an airbag. Background Art

[0002] Scoliosis is a common spinal deformity disease, the main feature of which is the spinal column presenting a lateral curvature deformation. According to statistics, the incidence rate of scoliosis is about 2%-3%, mostly occurring in adolescence, which has a serious impact on the physical and mental health and quality of life of patients. Therefore, it is crucial to take effective corrective treatment in a timely manner.

[0003] Currently, the commonly used scoliosis correction methods mainly include surgical treatment and conservative treatment. Surgical treatment means include posterior correction and fusion surgery, anterior and posterior correction and fusion surgery, etc., which can effectively correct severe scoliosis deformities. However, surgery has large trauma, a long recovery period, and there is a certain risk of surgical complications, so it is mostly used for patients with more serious conditions. In contrast, conservative treatment is more suitable for patients with milder conditions, mainly including orthosis correction, physical therapy, rehabilitation training, etc.

[0004] Among them, orthosis correction is the most common method in conservative treatment. The orthosis gradually corrects the scoliosis deformity by applying a certain corrective force and is widely used in clinical practice. For example, a rotary pressing type scoliosis orthosis disclosed in the utility model CN202210471088.X, a scoliosis orthosis disclosed in CN202023005647.3, an intelligent scoliosis orthosis disclosed in CN202023150373.7, and an intelligent orthopedic device disclosed in CN202020245828.4; common orthoses include the Boston type, Milwaukee type, Cheneau type, etc., which are mainly made of rigid materials and can provide stable corrective force. In order to improve the correction effect and wearing comfort, the orthosis often includes adjustable airbags, and the magnitude and distribution of the corrective force are regulated by adjusting the pressure inside the airbags.

[0005] However, the existing orthosis airbag pressure adjustment methods mainly rely on the empirical judgment of clinicians and lack a scientific analysis basis. Doctors usually manually adjust the airbag pressure according to the subjective feedback of patients, which is inefficient and difficult to achieve precise control. Summary of the Invention

[0006] In view of this, the present invention provides a method, medium and system for controlling the orthopedic force of a scoliosis orthosis, which can solve the technical problems that the existing method mainly relies on the empirical judgment of clinicians for pressure adjustment, lacks a scientific analysis basis, is inefficient, and is difficult to achieve precise control.

[0007] The present invention is implemented as follows:

[0008] The first aspect of the present invention provides a method for controlling the orthopedic force of a scoliosis orthosis, which includes the following steps:

[0009] S10. Obtain the pressure signals, vibration signals, and air pressure signals collected by multiple pressure sensors, multiple vibration sensors, and multiple air pressure sensors to form a pressure signal set, a vibration signal set, and an air pressure signal set;

[0010] S20. Establish a pressure distribution model of the contact surface between the orthosis and the skin according to the pressure signal set and the position of each pressure sensor;

[0011] S30. Establish a vibration model of the orthosis according to the vibration signal set and the position of each vibration sensor, which is used to evaluate the stability and comfort of the orthosis;

[0012] S40. Establish an airbag pressure distribution model according to the air pressure signal set and the position of each airbag, which is used to adjust the pressure in the airbag;

[0013] S50. Obtain the pressure distribution characteristics, vibration characteristics, and air pressure distribution characteristics of the pressure distribution model, vibration model, and airbag pressure distribution model in different postures of the user, and establish a posture-characteristic mapping relationship model, which is used to predict the orthopedic effect in different postures;

[0014] S60. Establish a multi-objective optimization model, with the maximization of the correction effect, the optimization of the wearing comfort, and the minimization of the power consumption as the objectives, with the airbag pressure as the decision variable, and the safety thresholds of pressure distribution, vibration, and air pressure as the constraints;

[0015] S70. Solve the multi-objective optimization model to obtain the optimal airbag pressure configuration scheme in different postures;

[0016] S80. According to the optimal airbag pressure configuration scheme, combined with the real-time detected posture of the user, dynamically adjust the pressure of each airbag to achieve the adaptive control of the orthopedic force of the orthosis.

[0017] Among them, the step S10 specifically includes:

[0018] Step 101. Arrange multiple pressure sensors on the contact surface between the orthosis and the skin to collect the pressure signals on the contact surface and record the position coordinate information of each pressure sensor;

[0019] Step 102. Arrange multiple vibration sensors on the outer surface of the orthosis to collect the vibration signals of the orthosis and record the position coordinate information of each vibration sensor;

[0020] Step 103: Install a pressure sensor at the air vent of the airbag to collect the air pressure signal inside the airbag;

[0021] Step 104: Respectively form a pressure signal set, a vibration signal set, and an air pressure signal set from the collected pressure signals, vibration signals, and air pressure signals.

[0022] Among them, the specific steps of step S20 include:

[0023] Step 201: Use an interpolation algorithm to construct a pressure distribution model of the orthosis-skin contact surface based on the pressure signals and their position coordinates collected by each pressure sensor. This model can describe the pressure values at any position on the contact surface;

[0024] Step 202: This pressure distribution model can be used to analyze the pressure characteristics exerted by the orthosis on the patient's skin in different postures, providing a basis for optimizing the airbag pressure configuration.

[0025] Among them, the specific steps of step S30 include:

[0026] Step 301: Use vibration analysis techniques such as modal analysis to establish a vibration model of the orthosis based on the vibration signals and their position coordinates collected by each vibration sensor. This model can describe the vibration characteristics of the orthosis at different positions, such as amplitude, frequency, etc.;

[0027] Step 302: This vibration model can be used to evaluate the stability and wearing comfort of the orthosis. For example, identify high-amplitude regions near the resonance frequency and adjust the airbag pressure configuration to suppress these vibrations.

[0028] Among them, the specific steps of step S40 include:

[0029] Step 401: Use an interpolation algorithm to construct an airbag pressure distribution model based on the air pressure signals and their position coordinates collected by each air pressure sensor. This model can describe the air pressure values in each airbag;

[0030] Step 402: This air pressure distribution model provides a basis for adjusting the air pressure in each airbag. It can identify regions with low or high pressure according to the pressure distribution characteristics and appropriately adjust the pressure of the corresponding airbag.

[0031] Among them, the specific steps of step S50 include:

[0032] Step 501: Collect the motion signals of the user in different postures through an acceleration sensor or gyroscope set on the outer surface of the orthosis and identify different posture characteristics;

[0033] Step 502: Combine the pressure distribution model, vibration model, and air pressure distribution model established in Steps S20 - S40 to extract the pressure distribution characteristics, vibration characteristics, and air pressure distribution characteristics of each model in different postures;

[0034] Step 503: Use a supervised learning algorithm to establish an attitude - feature mapping relationship model, which can predict the corresponding pressure distribution, vibration characteristics, and air pressure distribution based on the user's posture detected in real - time.

[0035] Among them, the specific steps of Step S60 include:

[0036] Step 601: Take the correction effect, wearing comfort, and power consumption as the optimization objective functions, where the correction effect can be characterized by a pressure distribution index, the wearing comfort can be characterized by a vibration feature index, and the power consumption can be characterized by an airbag pressure index;

[0037] Step 602: Take the pressure values of each airbag as decision variables, and set safety threshold constraints for pressure distribution, vibration characteristics, and air pressure values, such as the maximum pressure does not exceed 40 kPa, the maximum vibration acceleration does not exceed 5 m / s^2, and the maximum airbag pressure does not exceed 80 kPa;

[0038] Step 603: Use a multi - objective optimization algorithm to solve this optimization model to obtain the optimal airbag pressure configuration scheme in different postures.

[0039] Among them, the specific steps of Step S70 include:

[0040] Step 701: Use a multi - objective optimization algorithm, such as a genetic algorithm or a particle swarm optimization algorithm, to solve the multi - objective optimization model established in Step S60;

[0041] Step 702: The goal of the algorithm is to maximize the correction effect, optimize the wearing comfort, and minimize the power consumption on the premise of meeting the safety constraints of pressure distribution, vibration characteristics, and air pressure;

[0042] Step 703: Through iterative optimization, obtain the optimal airbag pressure configuration scheme in different postures.

[0043] Among them, the specific steps of Step S80 include:

[0044] Step 801: Monitor the user's posture changes in real - time, and use the attitude - feature mapping relationship model established in Step S50 to predict the corresponding pressure distribution, vibration characteristics, and air pressure distribution;

[0045] Step 802: Compare the prediction results with the optimal airbag pressure configuration scheme obtained in Step S70 to determine the airbag to be adjusted and its pressure value;

[0046] Step 803: Adopt a progressive adjustment strategy to gradually adjust the pressure of each airbag to avoid discomfort caused by sudden pressure changes;

[0047] Step 804: Set up a safety monitoring mechanism. When it detects excessive pressure or severe abnormal vibration, immediately perform airbag pressure reduction treatment to ensure safe use.

[0048] Among them, the multiple pressure sensors are multiple pressure sensors arranged on the contact surface between the orthosis and the skin.

[0049] Among them, the multiple vibration sensors are multiple vibration sensors arranged on the outer surface of the orthosis.

[0050] Among them, the air pressure sensor is arranged at the air vent of the airbag for collecting the air pressure inside the airbag.

[0051] Among them, the posture of the user is detected and obtained by an acceleration sensor or a gyroscope arranged on the outer surface of the orthosis.

[0052] Among them, the posture-feature mapping relationship model adopts a multiple linear regression model.

[0053] Among them, the method for solving the multi-objective optimization model is a genetic algorithm.

[0054] Among them, when using the genetic algorithm to solve the multi-objective optimization model, the fitness function is a similarity function of the vector composed of each objective.

[0055] The second aspect of the present invention provides a computer-readable storage medium. Among them, program instructions are stored in the computer-readable storage medium. When the program instructions run, they are used to execute the above-mentioned airbag control method for the orthopedic force of a scoliosis orthosis.

[0056] The third aspect of the present invention provides an airbag control system for the orthopedic force of a scoliosis orthosis, which includes the above-mentioned computer-readable storage medium.

[0057] Compared with the prior art, the beneficial effects of the airbag control method, medium and system for the orthopedic force of a scoliosis orthosis provided by the present invention are as follows: 1. The correction effect is improved. By establishing a pressure distribution model, this method can monitor the pressure characteristics of the contact surface between the orthosis and the skin in real time, and adjust the pressure of each airbag according to the pressure distribution characteristics, effectively improving the accuracy of the correction force and the correction effect. Compared with the traditional adjustment method relying on doctors' experience, this method can achieve more refined control of the correction force.

[0058] 2. Enhanced wearing comfort. This method not only considers the pressure distribution but also establishes an orthosis vibration model to evaluate its vibration characteristics in real time. By optimizing the airbag pressure configuration, it can not only meet the requirements of the correction effect but also suppress local high-vibration areas, significantly improving the comfort of users.

[0059] 3. Reduced power consumption. This method uses a multi-objective optimization approach, minimizing power consumption as one of the optimization goals. By intelligently adjusting the pressure of each airbag, it minimizes power consumption to the greatest extent while meeting the requirements of the correction effect and comfort, significantly improving the usage efficiency.

[0060] 4. Achieved adaptive control. This method combines real-time posture detection of the user to establish a posture-feature mapping relationship model, which can predict the corresponding pressure distribution, vibration characteristics, and air pressure distribution according to different postures, and dynamically adjust the pressure of each airbag accordingly to achieve adaptive control of the orthosis correction force. This adaptive adjustment strategy greatly improves the intelligence level of the entire correction system.

[0061] Generally speaking, the adaptive control method proposed in the present invention makes full use of multidisciplinary cross-cutting technical means, including sensing technology, signal processing, optimization algorithms, etc. It comprehensively considers the correction effect, wearing comfort, and power consumption, and solves the technical problems of the existing methods that the pressure adjustment mainly depends on the empirical judgment of clinicians, lacks scientific analysis basis, is inefficient, and is difficult to achieve precise control. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments of the present invention. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0063] Figure 1 is the flowchart of the method provided by the present invention; DETAILED DESCRIPTION OF THE EMBODIMENTS

[0064] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the drawings in the embodiments of the present invention.

[0065] As Figure 1 shown, it is the flowchart of an airbag control method for the correction force of a scoliosis orthosis provided by the present invention. This method includes the following steps:

[0066] S10. Obtain the pressure signals, vibration signals, and air pressure signals collected by multiple pressure sensors, multiple vibration sensors, and multiple air pressure sensors to form a pressure signal set, a vibration signal set, and an air pressure signal set;

[0067] S20. Establish a pressure distribution model of the contact surface between the orthosis and the skin according to the pressure signal set and the position of each pressure sensor;

[0068] S30. Establish a vibration model of the orthosis according to the vibration signal set and the position of each vibration sensor, which is used to evaluate the stability and comfort of the orthosis;

[0069] S40. Establish an airbag pressure distribution model according to the air pressure signal set and the position of each airbag, which is used to adjust the pressure in the airbag;

[0070] S50. Obtain the pressure distribution characteristics, vibration characteristics, and air pressure distribution characteristics of the pressure distribution model, vibration model, and airbag pressure distribution model in different postures of the user, and establish a posture-characteristic mapping relationship model, which is used to predict the orthopedic effect in different postures;

[0071] S60. Establish a multi-objective optimization model, with the maximization of the correction effect, the optimization of the wearing comfort, and the minimization of the power consumption as the objectives, with the airbag pressure as the decision variable, and with the safety thresholds of pressure distribution, vibration, and air pressure as the constraint conditions;

[0072] S70. Solve the multi-objective optimization model to obtain the optimal airbag pressure configuration scheme in different postures;

[0073] S80. According to the optimal airbag pressure configuration scheme, combined with the real-time detected posture of the user, dynamically adjust the pressure of each airbag to achieve the adaptive control of the orthopedic force of the orthosis.

[0074] The specific implementation manners of the above steps are described in detail below:

[0075] Step S10: Obtain the pressure signals, vibration signals, and air pressure signals collected by multiple pressure sensors, multiple vibration sensors, and multiple air pressure sensors to form a pressure signal set, a vibration signal set, and an air pressure signal set.

[0076] The specific implementation manner is as follows:

[0077] 1. Deploy multiple pressure sensors on the contact surface between the orthosis and the skin to collect the pressure signals on the contact surface. The position coordinate information of each pressure sensor also needs to be recorded.

[0078] 2. Deploy multiple vibration sensors on the outer surface of the orthosis to collect the vibration signals of the orthosis. The position coordinate information of each vibration sensor also needs to be recorded.

[0079] 3. A pressure sensor is arranged at the air vent of the airbag to collect the air pressure signal inside the airbag.

[0080] 4. The collected pressure signals, vibration signals, and air pressure signals are respectively formed into a pressure signal set, a vibration signal set, and an air pressure signal set. These signal sets provide basic data for establishing a pressure distribution model, a vibration model, and an air pressure distribution model in the subsequent steps.

[0081] Step S20: According to the pressure signal set and the position of each pressure sensor, establish a pressure distribution model of the contact surface between the orthosis and the skin.

[0082] The specific implementation method is as follows:

[0083] 1. Adopt an interpolation algorithm, such as bilinear interpolation or adaptive spline interpolation, etc., and construct a pressure distribution model of the contact surface between the orthosis and the skin according to the pressure signals collected by each pressure sensor and their position coordinates. This model can describe the pressure value at any position on the contact surface.

[0084] 2. This pressure distribution model can be used to analyze the pressure characteristics exerted by the orthosis on the patient's skin in different postures, providing a basis for optimizing the airbag pressure configuration. For example, local high-pressure areas can be identified according to the pressure distribution characteristics, and the pressure of the corresponding airbag can be adjusted accordingly.

[0085] Step S30: According to the vibration signal set and the position of each vibration sensor, establish a vibration model of the orthosis to evaluate the stability and comfort of the orthosis.

[0086] The specific implementation method is as follows:

[0087] 1. Adopt vibration analysis techniques such as modal analysis, and establish a vibration model of the orthosis according to the vibration signals collected by each vibration sensor and their position coordinates. This model can describe the vibration characteristics of the orthosis at different positions, such as amplitude, frequency, etc.

[0088] 2. This vibration model can be used to evaluate the stability and wearing comfort of the orthosis. For example, high-amplitude areas near the resonance frequency can be identified according to the vibration characteristics, and the airbag pressure configuration can be adjusted to suppress these vibrations, improving the stability of the orthosis and the comfort of the user.

[0089] Step S40: According to the air pressure signal set and the position of each airbag, establish an airbag pressure distribution model to adjust the air pressure inside the airbag.

[0090] The specific implementation method is as follows:

[0091] 1. An interpolation algorithm, such as bilinear interpolation or adaptive spline interpolation, etc., is adopted to construct an airbag pressure distribution model based on the air pressure signals and their position coordinates collected by each air pressure sensor. This model can describe the pressure values in each airbag.

[0092] 2. This air pressure distribution model provides a basis for adjusting the pressure in each airbag. For example, the areas with lower pressure can be identified according to the pressure distribution characteristics, and the pressure of the corresponding airbag can be appropriately increased, or the areas with too high pressure can be identified and the pressure of the corresponding airbag can be appropriately reduced to achieve the goal of overall pressure optimization.

[0093] Step S50: Obtain the pressure distribution characteristics, vibration characteristics, and air pressure distribution characteristics of the pressure distribution model, vibration model, and airbag pressure distribution model in different postures of the user, and establish a posture-characteristic mapping relationship model for predicting the orthopedic effect in different postures.

[0094] The specific implementation method is as follows:

[0095] 1. The motion signals of the user in different postures are collected through the acceleration sensors or gyroscopes set on the outer surface of the orthosis, and different posture characteristics are identified.

[0096] 2. Combining the pressure distribution model, vibration model, and air pressure distribution model established in steps S20 - S40, extract the pressure distribution characteristics, vibration characteristics, and air pressure distribution characteristics of each model in different postures.

[0097] 3. A supervised learning algorithm, such as multiple linear regression or neural network, is adopted to establish a posture-characteristic mapping relationship model. This model can predict the corresponding pressure distribution, vibration characteristics, and air pressure distribution according to the real-time detected posture of the user, so as to predict the orthopedic effect in different postures.

[0098] Step S60: Establish a multi-objective optimization model with the maximization of the correction effect, the optimization of the wearing comfort, and the minimization of the power consumption as the objectives, the airbag pressure as the decision variable, and the safety thresholds of the pressure distribution, vibration, and air pressure as the constraints.

[0099] The specific implementation method is as follows:

[0100] 1. Take the correction effect, wearing comfort, and power consumption as the optimization objective functions. Among them, the correction effect can be characterized by the pressure distribution index, the wearing comfort can be characterized by the vibration characteristic index, and the power consumption can be characterized by the airbag pressure index.

[0101] 2. Take the pressure values of each airbag as the decision variables. The pressure distribution, vibration characteristics, and air pressure values need to meet certain safety threshold constraints, for example:

[0102] - The maximum value of the pressure distribution does not exceed 40 kPa

[0103] - The maximum value of the vibration acceleration does not exceed 5 m / s^2

[0104] - The maximum value of the airbag pressure does not exceed 80 kPa

[0105] 3. Use a multi-objective optimization algorithm, such as a genetic algorithm or a particle swarm optimization algorithm, to solve this multi-objective optimization model and obtain the optimal airbag pressure configuration scheme under different postures. This scheme can take into account the optimization of the correction effect, wearing comfort, and power consumption.

[0106] Step S70: Solve the multi-objective optimization model to obtain the optimal airbag pressure configuration scheme under different postures.

[0107] The specific implementation method is as follows:

[0108] 1. Use a multi-objective optimization algorithm, such as a genetic algorithm or a particle swarm optimization algorithm, to solve the multi-objective optimization model established in step S60.

[0109] 2. The goal of the algorithm is to maximize the correction effect, optimize the wearing comfort, and minimize the power consumption on the premise of meeting the pressure distribution, vibration characteristics, and air pressure safety constraints.

[0110] 3. Through iterative optimization, the optimal airbag pressure configuration scheme under different postures can be obtained. This scheme provides the best reference basis for subsequent dynamic adjustment of the airbag pressure.

[0111] Step S80: According to the optimal airbag pressure configuration scheme, combined with the real-time detected posture of the user, dynamically adjust the pressure of each airbag to achieve the adaptive control of the orthosis correction force.

[0112] The specific implementation method is as follows:

[0113] 1. Monitor the posture change of the user in real time, and predict the corresponding pressure distribution, vibration characteristics, and air pressure distribution through the posture-feature mapping relationship model established in step S50.

[0114] 2. Compare the prediction results with the optimal airbag pressure configuration scheme obtained in step S70 to determine the airbags that need to be adjusted and their pressure values.

[0115] 3. Adopt a progressive adjustment strategy to gradually adjust the pressure of each airbag to avoid discomfort caused by sudden pressure changes.

[0116] 4. At the same time, set up a safety monitoring mechanism. When it is detected that the pressure is too high or the vibration is severely abnormal, immediately perform airbag decompression to ensure safe use.

[0117] 5. By dynamically adjusting the airbag pressure, the adaptive control of the orthotic force of the orthosis is realized to improve the correction effect, enhance the wearing comfort, and reduce the power consumption.

[0118] In summary, the patent claim describes an adaptive control method for a scoliosis orthosis based on airbag pressure. Through the modeling and analysis of pressure, vibration, and air pressure signals, a multi-objective optimization model is established, and dynamic airbag pressure adjustment is realized in combination with real-time posture detection, thereby improving the correction effect, wearing comfort, and power utilization efficiency. This method integrates multidisciplinary knowledge, including sensing technology, signal processing, mechanical vibration, optimization algorithms, etc., providing an innovative solution for the intelligent control of scoliosis orthoses.

[0119] The second aspect of the present invention provides a computer-readable storage medium, wherein program instructions are stored in the computer-readable storage medium, and when the program instructions run, they are used to execute the above-mentioned airbag control method for the orthotic force of a scoliosis orthosis.

[0120] The third aspect of the present invention provides an airbag control system for the orthotic force of a scoliosis orthosis, which includes the above-mentioned computer-readable storage medium.

[0121] To better understand and implement the present invention, the following provides a detailed description of the specific implementation manner of the present invention in combination with formulas. Of course, this detailed description can also be directly used in a computer program as the specific implementation manner of the present invention in a computer-readable storage medium, or in a computer, single-chip microcomputer, control chip, and other electronic devices. The specific description is as follows:

[0122] Step S10: Obtain the pressure signals, vibration signals, and air pressure signals collected by a plurality of pressure sensors, a plurality of vibration sensors, and a plurality of air pressure sensors to form a pressure signal set, a vibration signal set, and an air pressure signal set.

[0123] The specific implementation manner is as follows:

[0124] 1. Pressure signal acquisition: Assume that there are n pressure sensors on the contact surface between the orthosis and the skin, and the position coordinates of each sensor are (x i , y i ), i = 1, 2,..., n. The pressure signal collected by the i-th pressure sensor is denoted as P i (t), then the pressure signal set can be expressed as:

[0125] P = {P 1 (t), P 2 (t),..., P n (t)}

[0126] where P i(t) represents the pressure value collected by the i-th pressure sensor at time t. The position coordinates (x i , y i ) of each pressure sensor also need to be recorded for subsequent establishment of the pressure distribution model.

[0127] 2. Vibration signal acquisition: Suppose there are m vibration sensors on the outer surface of the orthosis, and the position coordinates of each sensor are (x j , y j ), where j = 1, 2,..., m. The vibration signal collected by the j-th vibration sensor is denoted as V j (t), then the vibration signal set can be expressed as:

[0128] V = {V 1 (t), V 2 (t),..., V m (t)}

[0129] Among them, V j (t) represents the vibration value collected by the j-th vibration sensor at time t. The position coordinates (x j , y j ) of each vibration sensor also need to be recorded for subsequent establishment of the vibration model.

[0130] 3. Air pressure signal acquisition: Suppose there are k airbags on the orthosis, and a pressure sensor is provided at the air vent of each airbag. The air pressure signal collected by the l-th pressure sensor is denoted as G l (t), then the air pressure signal set can be expressed as:

[0131] G = {G 1 (t), G 2 (t), …, G k (t)}

[0132] Among them, G l (t) represents the air pressure value collected by the l-th pressure sensor at time t. The position information of each pressure sensor also needs to be recorded for subsequent establishment of the air pressure distribution model.

[0133] Through the above steps, the pressure signal set P, the vibration signal set V, and the air pressure signal set G can be obtained, providing basic data for subsequent establishment of various distribution models.

[0134] Step S20: Establish a pressure distribution model of the contact surface between the orthosis and the skin according to the pressure signal set and the position of each pressure sensor.

[0135] The specific implementation method is as follows:

[0136] Let the pressure distribution function be P(x, y, t), where (x, y) represents the arbitrary position coordinates on the contact surface and t represents time. A two-dimensional interpolation algorithm, such as bilinear interpolation or adaptive spline interpolation, can be used to fit the pressure distribution function P(x, y, t) according to the pressure values P i (t) of each sensor in the pressure signal set P and their position coordinates (x i , y i ), that is:

[0137] P(x, y, t) = f(P 1 (t), P 2 (t),..., P n (t); x 1 , y 1 , x 2 , y 2 ,..., x n , y n )

[0138] where f represents the interpolation algorithm. This pressure distribution model can be used to analyze the pressure characteristics exerted by the orthosis on the patient's skin in different postures, providing a basis for subsequent optimization of the airbag pressure configuration. For example, local high-pressure areas can be identified based on the pressure distribution characteristics to adjust the pressure of the corresponding airbag accordingly.

[0139] Step S30: Establish a vibration model of the orthosis according to the vibration signal set and the position of each vibration sensor, which is used to evaluate the stability and comfort of the orthosis.

[0140] The specific implementation is as follows:

[0141] Vibration analysis techniques such as modal analysis can be used to establish a vibration model of the orthosis according to the vibration values V j (t) of each sensor in the vibration signal set V and their position coordinates (x j , y j ). The vibration model can be expressed as:

[0142]

[0143] where M is the mass matrix, C is the damping matrix, K is the stiffness matrix, x(t) is the displacement vector, is the velocity vector, is the acceleration vector, and F(t) is the external load vector. By solving this vibration equation, the vibration characteristics of the orthosis at the positions of each vibration sensor, such as amplitude and frequency, can be obtained.

[0144] This vibration model can be used to evaluate the stability and wearing comfort of the orthosis. For example, high-amplitude regions near the resonance frequency can be identified based on the vibration characteristics, and the airbag pressure configuration can be adjusted to suppress these vibrations, improving the stability of the orthosis and the comfort of the user.

[0145] Step S40: Establish an airbag pressure distribution model based on the air pressure signal set and the position of each airbag for adjusting the pressure inside the airbag.

[0146] The specific implementation is as follows:

[0147] Let the air pressure distribution function be G(x, y, t), where (x, y) represents the airbag position coordinates and t represents time. Similarly, a two-dimensional interpolation algorithm can be used to fit the air pressure distribution function G(x, y, t) according to the air pressure values G l (t) of each sensor in the air pressure signal set G and their position coordinates (x l , y l ), that is:

[0148] G(x, y, t) = g(G 1 (t), G 2 (t), …, G k (t); x 1 , y 1 , x 2 , y 2 , …, x k , y k )

[0149] where g represents the interpolation algorithm. This air pressure distribution model provides a basis for adjusting the pressure in each airbag. For example, regions with lower pressure can be identified based on the pressure distribution characteristics, and the pressure of the corresponding airbag can be appropriately increased, or regions with too high pressure can be identified and the pressure of the corresponding airbag can be appropriately reduced to achieve the goal of overall pressure optimization.

[0150] Step S50: Obtain the pressure distribution characteristics, vibration characteristics, and air pressure distribution characteristics of the pressure distribution model, vibration model, and airbag pressure distribution model under different postures of the user, and establish a posture-characteristic mapping relationship model for predicting the orthopedic effect under different postures.

[0151] The specific implementation is as follows:

[0152] 1. By using the acceleration sensors or gyroscopes set on the outer surface of the orthosis, the motion signals of the user in different postures can be collected, and pattern recognition algorithms such as principal component analysis or Gaussian mixture model can be used to identify different posture characteristics. Let the identified posture characteristic vector be a(t) = [a 1 (t), a 2 (t),... ap (t)] T , where p is the dimension of the pose feature.

[0153] 2. Combining the pressure distribution model P(x, y, t), vibration model and air pressure distribution model G(x, y, t) established in steps S20 - S40, characteristic indexes of each model under different poses can be extracted, such as:

[0154] The pressure distribution feature vector p(t) = [p 1 (t), p 2 (t),..., p q (t)] T , where q is the dimension of the pressure feature

[0155] The vibration feature vector v(t) = [v 1 (t), v 2 (t),..., v r (t)] T , where r is the dimension of the vibration feature

[0156] The air pressure distribution feature vector g(t) = [g 1 (t), g 2 (t),..., g s (t)] T , where s is the dimension of the air pressure feature

[0157] 3. Next, a supervised learning algorithm, such as multiple linear regression or neural network, can be used to establish a pose - feature mapping relationship model:

[0158] p(t) = f p (a(t))

[0159] v(t) = f v (a(t))

[0160] g(t) = f g (a(t))

[0161] where f p , f v , f g are mapping functions. This model can predict the corresponding pressure distribution feature p(t), vibration feature v(t) and air pressure distribution feature g(t) according to the real - time detected user pose a(t), so as to predict the orthopedic effect under different poses.

[0162] Step S60: Establish a multi-objective optimization model with the maximization of the correction effect, the optimization of the wearing comfort, and the minimization of the power consumption as the objectives, the airbag pressure as the decision variable, and the pressure distribution, vibration, and safety thresholds of the air pressure as the constraints.

[0163] The specific implementation is as follows:

[0164] 1. Take the correction effect F 1 , the wearing comfort F 2 , and the power consumption F 3 as the optimization objective functions. Among them:

[0165] The correction effect F 1 can be characterized by the weighted average of the pressure distribution, i.e., F 1 = ∫∫w(x, y)P(x, y, t)dxdy, where w(x, y) is the weight function

[0166] The wearing comfort F 2 can be characterized by the weighted average of the vibration acceleration, i.e., where u(x, y) is the weight function

[0167] The power consumption F 3 can be characterized by the weighted average of the airbag pressure, i.e., where v l is the weight coefficient

[0168] 2. Take the pressure values G l (t), l = 1, 2,..., k of each airbag as the decision variables. The pressure distribution, vibration characteristics, and air pressure values need to meet certain safety threshold constraints. For example:

[0169] The maximum value of the pressure distribution does not exceed P max = 40 kPa

[0170] The maximum value of the vibration acceleration does not exceed

[0171] The maximum value of the airbag pressure does not exceed G max = 80 kPa

[0172] Based on the above, the following multi-objective optimization model can be established:

[0173] min{-F 1 , -F 2 , F 3}

[0174] s.t. P(x, y, t) ≤ P max

[0175]

[0176] G l F(t) ≤ G max , l = 1, 2, ..., k

[0177] where the decision variable is the pressure value G of each airbag l F(t). A multi-objective optimization algorithm, such as a genetic algorithm or a particle swarm optimization algorithm, can be used to solve this optimization model to obtain the optimal airbag pressure configuration scheme under different postures. This scheme can take into account the optimization of the correction effect, wearing comfort, and power consumption.

[0178] Step S70: Solve the multi-objective optimization model to obtain the optimal airbag pressure configuration scheme under different postures.

[0179] The specific implementation is as follows:

[0180] 1. Use a multi-objective optimization algorithm, such as a genetic algorithm or a particle swarm optimization algorithm, to solve the multi-objective optimization model established in step S60.

[0181] 2. The goal of the algorithm is to maximize the correction effect F 1 while satisfying the pressure distribution, vibration characteristics, and air pressure safety constraints, and optimize the wearing comfort F 2 , and minimize the power consumption F 3 .

[0182] 3. Through iterative optimization, the optimal airbag pressure configuration scheme under different postures can be obtained This scheme provides the best reference basis for subsequent dynamic adjustment of the airbag pressure.

[0183] Step S80: According to the optimal airbag pressure configuration scheme, combined with the real-time detected posture of the user, dynamically adjust the pressure of each airbag to achieve adaptive control of the orthosis correction force.

[0184] The specific implementation is as follows:

[0185] 1. Real-time monitor the posture change of the user, and predict the corresponding pressure distribution feature vector p(t), vibration feature vector v(t), and air pressure distribution feature vector g(t) through the posture-feature mapping relationship model established in step S50.

[0186] 2. Compare the prediction results with the optimal airbag pressure configuration scheme obtained in step S70 to determine the airbag to be adjusted and its pressure value. The specific adjustment strategy is as follows:

[0187]

[0188] where K p, K d are the proportional and derivative adjustment coefficients, and Δt is the adjustment period. This formula adopts the proportional-derivative control strategy, which can achieve the progressive adjustment of the airbag pressure and avoid the discomfort caused by sudden pressure changes.

[0189] 3. At the same time, set up a safety monitoring mechanism. When it is detected that the maximum value max{P(x, y, t)} of the pressure distribution exceeds P max = 40 kPa, or the maximum value of the vibration acceleration exceeds , immediately perform the airbag decompression process to ensure the use safety.

[0190] 4. By dynamically adjusting the airbag pressure, achieve the adaptive control of the orthosis orthopedic force to improve the correction effect F 1 , enhance the wearing comfort F 2 , and reduce the power consumption F 3 .

[0191] In summary, the patent claim describes an adaptive control method for a scoliosis orthosis based on airbag pressure. Through the modeling and analysis of pressure, vibration, and air pressure signals, a multi-objective optimization model is established, and the dynamic airbag pressure adjustment is realized by combining real-time posture detection, thereby improving the correction effect, wearing comfort, and power utilization efficiency. This method integrates multidisciplinary knowledge, including sensing technology, signal processing, mechanical vibration, optimization algorithms, etc., and provides an innovative solution for the intelligent control of scoliosis orthoses.

[0192] The whole specific implementation involves a large number of mathematical formulas and algorithm principles, including:

[0193] 1. Use the two-dimensional interpolation algorithm to construct the pressure distribution model P(x, y, t) and the air pressure distribution model G(x, y, t).

[0194] 2. Adopt vibration analysis technology to establish the vibration model of the orthosis

[0195] 3. Use the supervised learning algorithm to establish the posture-feature mapping relationship models p(t) = f p (a(t)), v(t) = f v (a(t)), g(t) = f g (a(t)).

[0196] 4. Adopt the multi-objective optimization algorithm to solve the multi-objective optimization model of pressure distribution, vibration characteristics, and air pressure.

[0197] 5. Use the proportional-derivative control strategy to realize the dynamic adjustment of the airbag pressure.

[0198] Specifically, the principle of the present invention is as follows: By establishing a pressure distribution model, a vibration model, and an air pressure distribution model, combined with the real-time posture information of the user, and adopting a multi-objective optimization method, the pressure of each airbag is dynamically adjusted, so as to achieve the coordinated optimization of the correction effect, wearing comfort, and power consumption. This idea conforms to the following principles and logic:

[0199] 1. The establishment of the pressure distribution model provides a basis for accurately controlling the correction force. The scoliosis orthosis corrects spinal deformities by applying a certain correction force. The magnitude and distribution of the correction force directly determine the correction effect. Therefore, accurately describing the pressure distribution characteristics on the contact surface between the orthosis and the skin is the basis for achieving precise correction control. The present invention uses an interpolation algorithm to construct a pressure distribution model based on the signals of multiple pressure sensors on the contact surface, which can predict the pressure values at any position and provide a basis for adjusting the airbag pressure.

[0200] 2. The establishment of the vibration model helps to improve the use comfort. In addition to the correction force, the orthosis will also generate a certain amount of vibration during use. Excessive vibration will cause discomfort to the user and reduce the wearing comfort. The present invention uses vibration analysis technology to establish a vibration model of the orthosis, which can predict the vibration characteristics of each area and adjust the airbag pressure accordingly to suppress local high vibration, thereby improving the overall use comfort.

[0201] 3. The establishment of the air pressure distribution model lays a foundation for power optimization. The airbag pressure adjustment of the orthosis directly affects the power consumption. The present invention also establishes an air pressure distribution model, which can accurately predict the pressure state of each airbag, provide a basis for multi-objective optimization, and minimize the overall power consumption on the premise of meeting the requirements of the correction effect and comfort.

[0202] 4. The establishment of the posture-feature mapping model realizes adaptive control. When the human body is in different postures, the shape and force-bearing conditions of the spine will change, which will in turn affect the pressure distribution, vibration characteristics, and air pressure distribution of the orthosis. The present invention establishes a posture-feature mapping model by real-time monitoring of the user's posture changes, which can predict the pressure, vibration, and air pressure characteristics in different postures, provide a basis for dynamically adjusting the airbag pressure, and realize adaptive control.

[0203] 5. The solution of multi-objective optimization takes into account the correction effect, comfort, and power. The present invention maximizes the correction effect, optimizes the wearing comfort, and minimizes the power consumption, and sets it as a multi-objective optimization problem. Through the solution of the multi-objective optimization algorithm, the optimal airbag pressure configuration scheme in different postures is obtained, which can not only meet the correction requirements, but also improve the comfort and reduce the power consumption, reflecting a systematic optimization design idea.

[0204] In summary, the technical solution of the adaptive control method of the present invention closely focuses on the key performance indicators of the scoliosis orthosis, makes full use of advanced sensing technologies, signal processing, and optimization algorithms, establishes multiple key models, and integrates them into the dynamic airbag pressure regulation, thereby achieving the coordinated optimization of the correction effect, wearing comfort, and power consumption, meeting the technical requirements for the intelligent development of scoliosis orthoses.

[0205] To better understand the present invention, an embodiment of a specific application scenario of the present invention is provided below:

[0206] The orthopedics department of a certain hospital diagnosed a 15-year-old female patient, Xiaohong, with scoliosis. After preliminary examinations, the doctor diagnosed that Xiaohong had mild scoliosis, and the vertebral rotation angle was approximately 20°. After communicating with Xiaohong and her family, it was decided to adopt conservative treatment with a scoliosis orthosis.

[0207] Based on basic information such as Xiaohong's height and weight, the doctor customized a Cheneau-style orthosis for her. The orthosis is made of polypropylene material and has 5 adjustable airbags, which are distributed in the thoracic, lumbar, and pelvic regions of the orthosis. To achieve the intelligent control of the orthosis, the doctor decided to adopt the adaptive control method based on airbag pressure proposed by the present invention.

[0208] 1. Acquisition of pressure, vibration, and air pressure signals

[0209] First, during the production process of the orthosis, the doctor installed sensors at the following positions:

[0210] (1) A total of 12 pressure sensors were installed on the contact surface between the orthosis and the skin, distributed in the thoracic, lumbar, and pelvic regions. The position coordinate information of each pressure sensor was recorded on the design drawing of the orthosis.

[0211] (2) A total of 8 vibration sensors were installed on the outer surface of the orthosis, distributed at key positions. The position coordinates of each vibration sensor were also recorded.

[0212] (3) One air pressure sensor was installed at the air vent of each of the 5 airbags to monitor the pressure changes inside the airbags in real time.

[0213] In addition, the doctor also installed an integrated inertial measurement unit (IMU) on the outer surface of the orthosis, which includes a three-axis acceleration sensor and a three-axis gyroscope, to detect the patient's motion posture in real time.

[0214] During the process of wearing the orthosis for Xiaohong, each sensor collected pressure signals, vibration signals, and air pressure signals in real time, and transmitted these raw data wirelessly via Bluetooth to a nearby control terminal device for storage and analysis. At the same time, the IMU also monitored the posture changes of Xiaohong during different movements in real time. Through 10 minutes of data collection, the doctor obtained a preliminary set of pressure signals P, vibration signals V, and air pressure signals G, as well as the corresponding posture characteristics a(t).

[0215] 2. Establishment of the pressure distribution model

[0216] Based on the data of 12 pressure sensors recorded in the pressure signal set P and their specific position coordinates on the orthosis, the doctor used the bilinear interpolation algorithm to construct a pressure distribution model P(x, y, t) of the contact surface between the orthosis and the skin. This model can predict the pressure value at any position (x, y) on the contact surface at time t.

[0217] The doctor conducted a preliminary analysis of the pressure distribution model and found that when Xiaohong was standing upright, there were two local high-pressure areas in the thoracic and lumbar regions of the orthosis, with the pressure value reaching about 35 kPa, while the pressure in the pelvic region was relatively low, about 20 kPa. This indicates that the pressure distribution of the orthosis needs to be further optimized and adjusted to achieve a more uniform state.

[0218] 3. Establishment of the vibration model

[0219] Based on the data of 8 vibration sensors recorded in the vibration signal set V and combined with their position coordinates on the orthosis, the doctor used the modal analysis method to establish a vibration model of the orthosis. This model describes the vibration characteristics of the orthosis at different positions, including amplitude and frequency, etc.

[0220] The analysis results show that when Xiaohong walks slowly, the local vibration of the orthosis is relatively intense, especially in the thoracic region, and the vibration acceleration reaches a maximum of 4.5 m / s^2. These high-vibration areas may have an adverse impact on the wearing comfort of the user.

[0221] 4. Establishment of the air pressure distribution model

[0222] The doctor further analyzed the data of 5 air pressure sensors recorded in the air pressure signal set G and combined with their position information on the orthosis, and used the bilinear interpolation algorithm to construct an airbag pressure distribution model G(x, y, t). This model can predict the pressure value at any airbag position (x, y) at time t.

[0223] Preliminary results show that when Xiaohong stands upright, the pressure distribution of the five airbags is relatively uniform, about 60 kPa. However, when Xiaohong walks slowly, the pressure of some airbags fluctuates significantly, reaching a maximum of 75 kPa, while the pressure of some other airbags is relatively low, only about 50 kPa. This uneven pressure distribution may reduce the stability and wearing comfort of the orthosis.

[0224] 5. Establishment of the posture-feature mapping relationship model

[0225] The doctor further analyzed the posture data a(t) collected by the IMU and found that the pressure distribution model P(x, y, t), vibration model and air pressure distribution model G(x, y, t) all changed significantly under different postures such as standing upright, walking slowly, and walking uphill.

[0226] To achieve adaptive control, the doctor adopted a multiple linear regression algorithm to establish a posture-feature mapping relationship model:

[0227] p(t) = f p (a(t))

[0228] v(t) = f v (a(t))

[0229] g(t) = f g (a(t))

[0230] Through this model, the doctor can predict the corresponding pressure distribution characteristics p(t), vibration characteristics v(t), and air pressure distribution characteristics g(t) based on the real-time detected user posture a(t), providing a basis for subsequent airbag pressure optimization.

[0231] 6. Establishment and solution of the multi-objective optimization model

[0232] With the above various models as the basis, the doctor then established a multi-objective optimization model, taking maximizing the correction effect, optimizing the wearing comfort, and minimizing the power consumption as the three objective functions:

[0233] min{-F 1 , -F 2 , F 3}

[0234] s.t.P(x, y, t) ≤ P max = 40 kPa

[0235]

[0236] G l (t) ≤ G max= 80 kPa, l = 1, 2, ..., 5

[0237] Among them, the correction effect F 1 is characterized by the weighted average of the pressure distribution, and the wearing comfort F 2 is characterized by the weighted average of the vibration acceleration, and the power consumption F 3 is characterized by the weighted average of the airbag pressure. The pressure values G l (t) of the 5 airbags are used as decision variables and are constrained by the safety thresholds of the pressure distribution, vibration characteristics, and air pressure.

[0238] To solve this multi-objective optimization problem, the doctor selected the genetic algorithm. Through iterative optimization, the optimal airbag pressure configuration scheme under different postures was finally obtained.

[0239] 7. Adaptive adjustment of dynamic airbag pressure

[0240] With the optimal airbag pressure configuration scheme as a reference, the doctor then implemented the dynamic adjustment control of the orthosis airbag pressure. The specific process is as follows:

[0241] (1) Real-time monitor the change of Xiaohong's motion posture a(t), and predict the corresponding pressure distribution characteristics p(t), vibration characteristics v(t), and air pressure distribution characteristics g(t) through the posture-characteristic mapping relationship model.

[0242] (2) Compare the prediction results with the optimal airbag pressure configuration scheme to determine the airbags that need to be adjusted and their pressure values. The following proportional-derivative control strategy is used for pressure adjustment:

[0243]

[0244] where Δt is the adjustment period, and K p , K d are the proportional and derivative adjustment coefficients. This strategy can achieve the progressive adjustment of the airbag pressure and avoid the discomfort caused by sudden changes.

[0245] (3) At the same time, a safety monitoring mechanism is set up. When it is detected that the maximum value max{P(x, y, t)} of the pressure distribution exceeds P max = 40 kPa, or the maximum value of the vibration acceleration exceeds , the airbag is immediately decompressed to ensure safe use.

[0246] Through the above dynamic adjustment strategy, the orthosis can adaptively adjust the pressure configuration of each airbag according to Xiaohong's real-time motion posture, which not only meets the requirements of the correction effect, but also improves the wearing comfort and reduces the power consumption.

[0247] 8. Analysis of Clinical Application Effect

[0248] During the 3 - month treatment process, the doctor closely monitored the correction of Xiaohong's spinal deformity. Through regular follow - up examinations with X - ray films, it was found that the vertebral rotation angle of Xiaohong gradually corrected from the initial 20° to 12°, approaching the normal level. At the same time, Xiaohong reported feeling relatively comfortable when using the orthosis and was able to wear it for a long time without obvious fatigue. The doctor calculated the energy consumption of the orthosis system and found that compared with the traditional manual adjustment method, the power consumption decreased by about 30%.

[0249] As mentioned above, the above is only the specific implementation manner of the present invention, but the protection scope of the present invention is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present invention can easily think of changes or substitutions, which should be covered within the protection scope of the present invention.

Claims

1. An airbag control system for the corrective force of a scoliosis orthosis, characterized in that: The invention comprises a computer-readable storage medium, wherein the computer-readable storage medium stores program instructions, and when the program instructions are executed, the method for controlling the corrective force of a scoliosis orthosis with an airbag is used to execute the method, wherein the method for controlling the corrective force of a scoliosis orthosis with an airbag specifically comprises the following steps: S10, acquiring pressure signals, vibration signals, and air pressure signals collected by multiple pressure sensors, multiple vibration sensors, and multiple air pressure sensors to form a pressure signal set, a vibration signal set, and an air pressure signal set; S20, establishing a pressure distribution model of the contact surface between the orthosis and the skin according to the pressure signal set and the position of each pressure sensor; S30, establishing a vibration model of the orthosis according to the vibration signal set and the position of each vibration sensor, for evaluating the stability and comfort of the orthosis; S40, establishing an airbag pressure distribution model according to the air pressure signal set and the position of each airbag, so as to adjust the pressure in the airbag; S50, obtaining pressure distribution characteristics, vibration characteristics and air pressure distribution characteristics of the pressure distribution model, vibration model and airbag pressure distribution model under different postures of the user, and establishing a posture-feature mapping relationship model for predicting the orthopedic effect under different postures; S60, establishing a multi-objective optimization model, with the objectives of maximizing the correction effect, optimizing the wearing comfort and minimizing the power consumption, with the airbag pressure as the decision variable, and with the pressure distribution, vibration and air pressure safety threshold as the constraint conditions; S70, solving the multi-objective optimization model to obtain the optimal airbag pressure configuration scheme under different postures; S80, dynamically adjusting the pressure of each airbag according to the optimal airbag pressure configuration scheme and in combination with the user's posture detected in real time, so as to achieve adaptive control of the orthotic force of the orthosis.

2. The airbag control system for the corrective force of a scoliosis orthosis according to claim 1, characterized in that: The multiple pressure sensors are multiple pressure sensors arranged on the contact surface between the orthosis and the skin.

3. The airbag control system for the corrective force of a scoliosis orthosis according to claim 1, characterized in that: The plurality of vibration sensors are a plurality of vibration sensors arranged on the outer surface of the orthosis.

4. The airbag control system for the corrective force of a scoliosis orthosis according to claim 1, characterized in that: The air pressure sensor is arranged at the vent of the airbag and is used to collect the air pressure in the airbag.

5. The airbag control system for the corrective force of a scoliosis orthosis according to claim 1, characterized in that: The user's posture is detected and acquired by an acceleration sensor or a gyroscope arranged on the outer surface of the orthosis.

6. The airbag control system for the corrective force of a scoliosis orthosis according to claim 1, characterized in that: The posture-feature mapping relationship model adopts a multivariate linear regression model.

7. The airbag control system for the corrective force of a scoliosis orthosis according to claim 1, characterized in that: The method used to solve the multi-objective optimization model is a genetic algorithm.

8. The airbag control system for the corrective force of a scoliosis orthosis according to claim 1, characterized in that: When a genetic algorithm is used to solve the multi-objective optimization model, the fitness function is a similarity function of a vector composed of each objective.

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