Wearable scoliosis rehabilitation monitoring system

Abstract

The invention discloses a wearable scoliosis rehabilitation monitoring system, and aims to solve the problems that teenager idiopathic scoliosis screening is insufficient, monitoring is inconvenient, and the conservative treatment effect is difficult to quantify. The system comprises a wearable sensor module, a data processing and transmitting unit, a mobile terminal application program and a rehabilitation assisting module. The sensor module adopts a flexible angle sensor, an acceleration sensor and a gyroscope, collects three-dimensional data of the spine in real time, and calculates a Cobb angle and a trunk rotation angle ATR; the data processing unit optimizes data through Kalman filtering and supports cloud transmission; the application program provides real-time monitoring and personalized rehabilitation guidance; the rehabilitation module corrects the posture through vibration and voice feedback. Noninvasive dynamic monitoring can be achieved without X-rays, the device is light, thin, comfortable, easy and convenient to operate and low in cost, the AIS early discovery rate and treatment compliance are effectively improved, the posture of a patient is improved, spine health is promoted, and the device is suitable for schools, families and other scenes and has remarkable popularization value.

Description

Technical Field

[0001] The present invention relates to the technical field of scoliosis monitoring, and in particular to a wearable scoliosis rehabilitation monitoring system. Background Art

[0002] Adolescent idiopathic scoliosis (AIS) is a common three-dimensional spinal deformity that primarily occurs in adolescents aged 10-18 years. It is characterized by a spinal Cobb angle greater than 10°, accompanied by impaired postural control and abnormal growth and development. Without timely intervention, mild to moderate AIS (Cobb angle 10°-40°) can progress to severe (Cobb angle >40°), leading to chest deformity, impaired cardiopulmonary function (e.g., a 20%-30% decrease in vital capacity), abnormal appearance, and psychological health issues (e.g., low self-esteem and anxiety). Therefore, early screening, dynamic monitoring, and conservative treatment are crucial for controlling the progression of AIS.

[0003] Currently, the diagnosis and treatment technologies of AIS mainly include the following categories:

[0004] Traditional methods rely on physical examinations, such as the Adams flexion test combined with measurement of the ATR (Axis Trunk Rotation) angle, and X-rays to confirm the Cobb angle. Screening is typically performed in schools or medical facilities, using tools such as the Scoliometer to measure the ATR and determine whether further imaging is needed.

[0005] Problem: Screening coverage is low, especially in small and medium-sized cities and rural areas, where there is a lack of systematic screening programs. Although X-ray examinations are accurate, their frequent use poses radiation risks to adolescents (approximately 0.1-0.2 mSv each time) and cannot be monitored in real time, resulting in an early detection rate of less than 30%.

[0006] Current monitoring techniques: Regular X-ray examinations (every 3-6 months) are the primary method for monitoring AIS progression, combined with brace wear to assess treatment efficacy. Additionally, some studies have attempted to monitor spinal morphology using surface electromyography or optical scanning.

[0007] Problem: X-ray review frequency is limited and cannot capture daily posture changes or short-term progress; sEMG and Moiré equipment are expensive (approximately 50,000 to 100,000 yuan), complex to operate, and mostly static measurements, making them unsuitable for home or school use and difficult to achieve dynamic, continuous monitoring.

[0008] Non-surgical treatment: Suitable for mild to moderate AIS with a Cobb angle of 10°-40°, it includes bracing (such as the Boston brace, worn 20 hours daily), exercise therapy (such as the Schroth method, yoga), and physical therapy. Studies have shown that bracing can slow the progression of scoliosis by 40%-60%, and exercise therapy has a modest effect on mild cases (reducing the Cobb angle by approximately 2°-5°).

[0009] Surgical treatment: When the Cobb angle is >40°, minimally invasive spinal surgery (such as posterior fusion) is recommended, and the correction rate can reach 70%-80%.

[0010] Problem: The brace treatment has poor compliance (the wearing rate among adolescents is <50%), low comfort, and requires regular adjustments, and is expensive (approximately 10,000 to 20,000 yuan).

[0011] Exercise therapy lacks standardized programs and real-time feedback, and its effects vary among individuals, making it difficult to quantify and evaluate.

[0012] The surgery has high risks (infection rate of about 2%-5%, risk of nerve damage of about 1%), and a long postoperative recovery period (6-12 months), which has a greater physical and mental impact on underage patients.

[0013] In recent years, wearable technology has rapidly developed in the field of health monitoring, such as smart bracelets for heart rate monitoring (accuracy ±5bpm) and wearable posture correctors for cervical spine protection. However, current wearable devices still have significant limitations for AIS monitoring and rehabilitation:

[0014] Technological gap: There is a lack of dynamic monitoring equipment specifically for AIS on the market. Existing posture correctors (such as LumoLift) only detect shoulder tilt and cannot measure Cobb angle or ATR, and their functions are limited.

[0015] Insufficient data: Existing equipment cannot provide continuous three-dimensional spinal data (such as coronal, sagittal, and transverse planes), and lacks personalized guidance combined with rehabilitation training.

[0016] Application limitations: Existing research (such as wearable electromyography systems) is mostly at the laboratory stage. The equipment is large (weight > 200g) and has high power consumption (battery life < 8 hours), making it unsuitable for daily wear.

[0017] Therefore, there is an urgent need for a wearable scoliosis rehabilitation monitoring system to solve the above problems. Summary of the Invention

[0018] The purpose of the present invention is to solve the existing technical problems raised in the above background technology and provide a wearable scoliosis rehabilitation monitoring system.

[0019] The above-mentioned object of the present invention is achieved as follows: A wearable scoliosis rehabilitation monitoring system comprises: a wearable sensor module for collecting three-dimensional angle data and posture data of the spine in real time;

[0020] a data processing and transmission unit connected to the wearable sensor module, for processing the collected data and calculating spinal deformity parameters, and transmitting the data to an external device via wireless;

[0021] a mobile terminal application, communicating with the data processing and transmission unit, for displaying monitoring results and providing personalized rehabilitation training guidance;

[0022] The rehabilitation auxiliary module is integrated into the wearable device and is used to provide posture correction and movement feedback based on the monitoring results; wherein the spinal deformity parameters include the Cobb angle θ cobb and the trunk rotation angle ATR, the Cobb angle is calculated by the following formula:

[0023]

[0024] Among them, θ Cobb is the Cobb angle, in degrees; Δy is the vertical distance between the vertices and the bottom of the scoliosis; Δx is the horizontal distance, both in millimeters, which are calculated from the coordinate data collected by the sensor module.

[0025] As a preferred technical solution of the present invention, the wearable sensor module includes multiple flexible angle sensors, acceleration sensors and gyroscopes, which are distributed along the T1-T12 thoracic vertebrae and L1-L5 lumbar vertebrae. The sensor spacing can be adjusted to adapt to users of different heights.

[0026] As a preferred technical solution of the present invention, the flexible angle sensor is used to measure the coronal plane angle of the spine, the acceleration sensor and gyroscope are used to collect sagittal thoracolumbar curvature and transverse rotation data, and the ATR is calculated by the following formula:

[0027]

[0028] Where ATR is the trunk rotation angle in degrees; ω z (t) is the Z-axis angular velocity measured by the gyroscope, in degrees per second; t0 and t1 are the start and end points of the measurement period, in seconds.

[0029] As a preferred technical solution of the present invention, the data processing and transmission unit includes an embedded microprocessor and a Bluetooth / Wi-Fi module. The microprocessor uses a Kalman filter algorithm to fuse the sensor data. The filtering formula is as follows:

[0030]

[0031] in, is the estimated value of the current state, in degrees, indicating angle data; is the predicted state value, in degrees; K k is the Kalman gain, dimensionless; z k is the measurement value, in degrees; H is the observation matrix, dimensionless.

[0032] As a preferred technical solution of the present invention, the mobile terminal application program is based on the real-time θ Cobb The ATR value is used to generate a personalized yoga training plan, and the degree of scoliosis is determined by the following thresholds:

[0033] If 5°<θ Cobb ≤10°, it is judged as mild scoliosis and observation is recommended;

[0034] If 10°<θ Cobb ≤20°, exercise therapy intervention is recommended;

[0035] If θ Cobb >20°, an alarm will sound to prompt medical attention.

[0036] As a preferred technical solution of the present invention, the rehabilitation auxiliary module includes a micro vibrator and a voice prompt unit, which triggers feedback when a bad posture is detected. The judgment conditions for bad posture are:

[0037] |θ tilt |>θ threshold or |ATR|>ATR threshold

[0038] Among them, θ tilt The spinal inclination angle calculated by the acceleration sensor, in degrees; θ threshold is the tilt angle threshold, in degrees; ATR is the trunk rotation angle, in degrees, threshold is the ATR threshold, in degrees.

[0039] As a preferred technical solution of the present invention, the wearable sensor module is made of a flexible bonding material.

[0040] As a preferred technical solution of the present invention, the data processing and transmission unit supports cloud data storage and calculates the development trend of spinal deformity using the following formula:

[0041]

[0042] Where Δθ Cobb (t) is the rate of change of the Cobb angle; θ Cobb (t n ) and θ Cobb (t0) are the Cobb angles at the nth and initial measurements, respectively, in degrees; t n and t0 is the measurement time in days.

[0043] As a preferred technical solution of the present invention, the mobile terminal application supports multi-user authority management, allowing parents, schools and doctors to view monitoring data and evaluate the rehabilitation effect using the following formula:

[0044]

[0045] Among them, E is the percentage of rehabilitation effect; and are the Cobb angles before and after the intervention, respectively, in degrees.

[0046] As a preferred technical solution of the present invention, the system also includes a self-calibration function, which regularly calibrates the sensor deviation through the following algorithm: Where δ is the deviation value in degrees; x i is the Cobb angle value of the ith measurement, in degrees; x is the average value, in degrees; N is the number of measurements, dimensionless.

[0047] Compared with the prior art, the present invention has the following beneficial effects:

[0048] First, this invention significantly improves the early screening and dynamic monitoring of adolescent idiopathic scoliosis through a wearable sensor module. The system can acquire three-dimensional spinal data in real time and calculate the Cobb angle and the angle of trunk rotation (ATR), eliminating the need for X-rays and radiation risks. Incorporating a Kalman filter algorithm and self-calibration capabilities, it increases monitoring accuracy and stability, providing a convenient and reliable means for timely detection and intervention of AIS.

[0049] Secondly, the system enhances the effectiveness of conservative treatment for mild to moderate AIS through its rehabilitation assistance module and mobile terminal application. A vibrator and voice prompts provide real-time feedback when poor posture is detected. Combined with a personalized yoga training plan, this helps users standardize their movements and improve treatment compliance, effectively promoting spinal health recovery and improving patients' posture and quality of life.

[0050] Finally, the present invention brings wide applicability to AIS management with its portability and affordability. It is suitable for long-term wear, supports cloud-based data analysis and multi-user collaboration, and meets the needs of daily use and long-term tracking. Compared with traditional braces or surgical treatments, this system is low-cost and simple to operate, and has the potential to be promoted in schools, families, and communities, providing an efficient and practical solution for protecting adolescent spinal health. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the technical solutions in the present invention or the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0052] Figure 14 is a system block diagram of a wearable scoliosis rehabilitation monitoring system in an embodiment of the present invention. DETAILED DESCRIPTION

[0053] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the embodiments described are part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts shall fall within the scope of protection of the present invention.

[0054] The following is combined with Figure 1 , the specific implementation methods of the present invention are described in detail.

[0055] The invention proposes a wearable scoliosis rehabilitation monitoring system for early screening, dynamic monitoring and rehabilitation intervention of adolescent idiopathic scoliosis, including:

[0056] The hardware components of the wearable sensor module include: Flexible angle sensor: It uses a resistive flexible sensor (such as FlexSensor2.2) with a sensitivity of 0.1° and a measurement range of -90° to 90°, which is used to detect the coronal plane angle.

[0057] Accelerometer: A three-axis accelerometer (such as MPU-6050) with a range of ±2g and a resolution of 0.01g is used to measure the sagittal thoracolumbar curvature.

[0058] Gyroscope: Same as the MPU-6050 module, with a range of ±250° / s and a resolution of 0.008° / s, used to detect cross-sectional rotation.

[0059] The 12 sensor units are arranged along the spine, specifically at key vertebrae such as T1, T4, T7, T10, T12, L1, L3, and L5. The size of each unit is 10mm×20mm×3mm, and the total weight is approximately 45g.

[0060] The sensor is fixed on a flexible silicone base (3mm thick) and connected by a retractable nylon strap. The spacing can be adjusted from 5 to 10 cm and is suitable for users with a height of 120 to 180 cm. The outer layer is covered with breathable fabric and weighs less than 50g, making it comfortable to wear for a long time. It is used to collect real-time three-dimensional spinal data, including the coronal Cobb angle (θ cobb ), sagittal curvature and transverse rotation angle ATR, sampling frequency 10Hz.

[0061] The data processing and transmission unit includes: Microprocessor: STM32F407 chip, main frequency 168MHz, integrated floating-point unit. Communication module: Bluetooth 5.0 chip (nRF52832), transmission distance 10m, rate 1Mbps.

[0062] The data processing flow is as follows: Raw data acquisition: The sensor outputs angle, acceleration and angular velocity data at a frequency of 10 Hz.

[0063] Filter the data: Use the Kalman filter algorithm to optimize the data. The formula is:

[0064]

[0065] in The current angle estimate, such as θ cobb ; Prediction value, recursively derived from the previous state. k : sensor measurement value; K k : Kalman gain, calculated by the covariance matrix, typical value is 0.1-0.5; H: observation matrix, set to 1, the angle error is reduced to ±0.5° after filtering.

[0066] Then calculate the parameters: Cobb angle:

[0067] Where Δy, Δx: calculated by the coordinates of the maximum angle difference between T1-T12, unit is mm. For example, if the Y coordinate offset at T7 is 10mm and the X coordinate is 50mm, then θ Cobb ≈11.46°.

[0068] where ω z (t): angular velocity of the gyroscope along the Z axis, t0 = 0 s, t1 = 1 s. Use numerical integration (trapezoidal method) with a step size of 0.1 s.

[0069] Finally, trend analysis: where t n -t0: monitoring period (unit: day), such as 7 days, θ Cobb The change value of .

[0070] Data transmission: Packet data per second (including θ cobb , ATR), transmit it to the mobile phone via Bluetooth, and upload it to the cloud (Alibaba Cloud Storage) simultaneously.

[0071] Mobile terminal application (APP) development environment: based on Android / iOS platform, using Flutter framework.

[0072] The functional modules of the mobile terminal application (APP) include: real-time curve display θ Cobb and (ATR), refresh rate 1H, then perform threshold judgment; the threshold judgment is specifically: 5°<θ Cobb ≤10°: prompt "mild scoliosis, please observe regularly";

[0073] 10°<θ Cobb ≤20°: Daily yoga training is recommended;

[0074] θ Cobb >20°: A pop-up alert appears: "Seek medical advice."

[0075] The rehabilitation guidance of the mobile terminal application (APP) includes: Cobb and (ATR) to generate a training plan. For example, if θ Cobb =15°, ATR=8°, recommended: Cat-Cow pose: 10 minutes, 4 sets, 10 times each set; Side plank: 15 minutes, 3 minutes each side.

[0076] Action videos (MP4 format) and timers are also available.

[0077] Effect evaluation:

[0078] Data recording: θ before and after intervention Cobb , such as from 15° to 11°, E = 26.67%.

[0079] Permission management: There are three levels of users: parents (view data), schools (batch management), and doctors (diagnostic recommendations). The data involved in permission management is encrypted using the AES-256 algorithm.

[0080] The rehabilitation assistance module includes: a micro vibrator: installed at the T7 and L3 positions; a voice module: an ISD1820 chip, which stores a 5-second voice message "Please adjust your posture."

[0081] The working mechanism is to first perform posture detection: where θ tilt : Accelerometer calculates the tilt angle, formula: a x is the X-axis acceleration (unit: m / s2), g = 9.8 m / s 2 Then feedback is given based on the threshold value: θ threshold =15°, ATR threshold =10°. Feedback trigger: If θ tilt >15° or ATR>10° for 30 seconds, the vibrator is activated for 3 seconds, and a voice message is played once, saying "Please adjust your posture."

[0082] Self-calibration function: Implementation steps: Start calibration mode every 7 days, the user stands for 5 minutes, and collects 100 θ Cobb , and then calculate the deviation: where x i :ith time θ cobb , N=100.

[0083] Example: If x=10°, x i The mean is 10.2°, so δ = 0.2°.

[0084] This is then corrected: subsequent measurements are subtracted from δ.

[0085] Implementation steps: The user puts the device on the back, adjusts the position from T1 to L5, fixes the nylon strap, turns on the power (3.7V lithium battery, capacity 500mAh), and connects the APP to Bluetooth. At this time, data collection is carried out, the sensor is activated, and the microprocessor calculates θ Cobb and (ATR), the app displays results, recommends training, the rehabilitation module provides posture feedback, records data weekly, evaluates results after 6 weeks, and calibrates regularly.

[0086] Example 1: School screening application;

[0087] In a middle school in Jiaojiang District, Taizhou City, 50 students aged 12-16 were screened for scoliosis for 5 days.

[0088] The device includes: 10 sensor module units (T1, T4, T7, T10, T12, L1, L2, L3, L4, L5); lithium battery; and an app installed on the teacher's mobile phone.

[0089] Implementation process:

[0090] 1. Students wear devices for continuous monitoring during class (8:00-12:00).

[0091] Example: Student A (14 years old, female): The coordinate shift at T7 is Δy=12mm, Δx=50mm.

[0092]

[0093] (ATR):ω z (t) average 0.6% / s, integrated for 1s to obtain ATR = 0.6°.

[0094] 2. Data processing: Kalman filter: initial noise 0.8°, after filtering θ Cobb =13.45°(error±0.5°), APP judgment: 10°<θ Cobb ≤20° indicates "mild scoliosis, exercise intervention is recommended."

[0095] 3. Feedback: Student A sits in an inclined position (θ tilt =18°) for more than 30 seconds, the vibrator is triggered for 3 seconds and a voice prompt "Please adjust your posture" is given.

[0096] 4. Results: Within 5 days, 6 students θ Cobb >10° (positive rate 12%), of which 2 patients exceeded 15°, and the APP recommended X-ray examination to parents.

[0097] Data trend: Student A's θ on the 5th day Cobb =13.60°,

[0098] Technical verification: high screening accuracy, self-calibration δ=0.1°, and stable system.

[0099] Example 2: Rehabilitation intervention trial;

[0100] 10 students diagnosed with mild AIS (θ Cobb 10°-20°), aged 13-15 years, 6-week intervention trial.

[0101] Grouping: Experimental group (5 people): use this system + yoga. Control group (5 people): yoga only, no feedback.

[0102] Device Configuration: Experimental Group: 12 sensors, including two vibrators (T7 and L3), voice module, 48-hour battery life. App: Daily training plan with videos.

[0103] Implementation process:

[0104] 1. Experimental group: Student B (13 years old, male):

[0105] initial: ATR = 7.8°;

[0106] Training: 30 minutes daily, cat-cow pose (10 minutes, 4 sets, 12 reps each, 0.5 Hz), side plank (10 minutes each side);

[0107] Feedback: θ tilt =17°, vibrate for 3 seconds, trigger 120 times in 6 weeks, after 6 weeks: Development Trends:

[0108] 2. Control group: Student C (14 years old, female): Initial:

[0109] Training: Same as above, no feedback; 6 weeks later: E=12.03%

[0110] Results: The average E in the experimental group was 24.8%, while that in the control group was 11.9%, with significant difference (P<0.05).

[0111] This specific implementation method includes detailed hardware design (such as 12 flexible sensor units and an STM32F407 microprocessor), algorithm implementation (such as Kalman filtering and Cobb angle calculation), and a complete operational process (from wearing to effect evaluation). Example 1 verifies the high accuracy and portability of the system in school screening, and Example 2 demonstrates its significant effect in rehabilitation intervention (the improvement rate in the experimental group increased by about one-fold), proving the practical value and promotion potential of the system in early monitoring and conservative treatment of AIS.

[0112] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present invention.

Claims

1. A wearable scoliosis rehabilitation monitoring system, characterized in that: include: Wearable sensor module for collecting three-dimensional angle and posture data of the spine in real time; a data processing and transmission unit connected to the wearable sensor module, for processing the collected data and calculating spinal deformity parameters, and transmitting the data to an external device via wireless; a mobile terminal application, communicating with the data processing and transmission unit, for displaying monitoring results and providing personalized rehabilitation training guidance; The rehabilitation auxiliary module is integrated into the wearable device and is used to provide posture correction and movement feedback based on the monitoring results; wherein the spinal deformity parameters include the Cobb angle θ cobb and the trunk rotation angle ATR, the Cobb angle is calculated by the following formula: Among them, θ Cobb is the Cobb angle, in degrees; Δy is the vertical distance between the vertices and the bottom of the scoliosis; Δx is the horizontal distance, both in millimeters, which are calculated from the coordinate data collected by the sensor module.

2. The wearable scoliosis rehabilitation monitoring system according to claim 1, characterized in that: The wearable sensor module includes multiple flexible angle sensors, acceleration sensors and gyroscopes, which are distributed along the T1-T12 thoracic vertebrae and L1-L5 lumbar vertebrae, and the sensor spacing is adjustable.

3. The wearable scoliosis rehabilitation monitoring system according to claim 2, characterized in that: The flexible angle sensor is used to measure the coronal plane angle of the spine, the acceleration sensor and gyroscope are used to collect sagittal thoracolumbar curvature and transverse rotation data, and the ATR is calculated using the following formula: Where ATR is the trunk rotation angle in degrees; ω z (t) is the Z-axis angular velocity measured by the gyroscope, in degrees per second; t0 and t1 are the start and end points of the measurement period, in seconds.

4. The wearable scoliosis rehabilitation monitoring system according to claim 1, characterized in that: The data processing and transmission unit includes an embedded microprocessor and a Bluetooth / Wi-Fi module. The microprocessor uses a Kalman filter algorithm to fuse the sensor data. The filtering formula is as follows: in, is the estimated value of the current state, in degrees, indicating angle data; is the predicted state value, in degrees; K k is the Kalman gain, dimensionless; z k is the measurement value, in degrees; H is the observation matrix, dimensionless.

5. The wearable scoliosis rehabilitation monitoring system according to claim 1, characterized in that: The mobile terminal application is based on real-time Cobb The ATR value is used to generate a personalized yoga training plan, and the degree of scoliosis is determined by the following thresholds: If 5°<θ Cobb ≤10°, it is judged as mild scoliosis and observation is recommended; If 10°<θ Cobb ≤20°, exercise therapy intervention is recommended; If θ Cobb >20°, an alarm will sound to prompt medical attention.

6. The wearable scoliosis rehabilitation monitoring system according to claim 1, characterized in that: The rehabilitation assistance module includes a micro vibrator and a voice prompt unit, which triggers feedback when a bad posture is detected. The judgment conditions for bad posture are: |θ tilt |>θ threshold or |ATR|>ATR threshold Among them, θ tilt The spinal inclination angle calculated by the acceleration sensor, in degrees; θ threshold is the tilt angle threshold, in degrees; ATR is the trunk rotation angle, in degrees, threshold is the ATR threshold, in degrees.

7. The wearable scoliosis rehabilitation monitoring system according to claim 2, characterized in that: The wearable sensor module is made of flexible bonding material.

8. The wearable scoliosis rehabilitation monitoring system according to claim 4, characterized in that: The data processing and transmission unit supports cloud data storage and calculates the progression trend of spinal deformity using the following formula: Where Δθ Cobb (t) is the rate of change of the Cobb angle; θ Cobb (t n ) and θ Cobb (t0) are the Cobb angles at the nth and initial measurements, respectively, in degrees; t n and t0 is the measurement time in days.

9. The wearable scoliosis rehabilitation monitoring system according to claim 5, characterized in that: The mobile terminal application supports multi-user permission management, allowing parents, schools and doctors to view monitoring data and evaluate rehabilitation effects using the following formula: Among them, E is the percentage of rehabilitation effect; and are the Cobb angles before and after the intervention, respectively, in degrees.

10. The wearable scoliosis rehabilitation monitoring system according to claim 1, characterized in that: The system also includes a self-calibration function that regularly calibrates sensor deviations using the following algorithm: Where δ is the deviation value in degrees; x i is the Cobb angle value of the ith measurement, in degrees; x is the average value, in degrees; N is the number of measurements, dimensionless.

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