Scoliosis orthosis monitoring method, device and scoliosis orthosis brace

Abstract

The present application belongs to the technical field of medical instrument monitoring and biomechanical signal processing, and particularly relates to a scoliosis orthosis monitoring method and device and a scoliosis orthosis brace. The method comprises: obtaining an acceleration signal generated by the orthosis brace with the subject moving, and an original pressure signal at an interface sensing point corresponding to a scoliosis part; determining an interface delay parameter caused by soft tissue viscoelasticity; generating a reconstructed pressure signal aligned with the phase of a motion feature point; mapping the acceleration signal to the force normal direction of the interface sensing point to obtain a normal motion acceleration representing the real-time motion state of the sensor; combining a local inertia response feature of the interface sensing point, which is pre-stored and represents the inertia mass distribution of the sensor component, to calculate a real-time inertia force component generated by the pressure sensing end from the normal motion acceleration; and vector stripping the real-time inertia force component from the reconstructed pressure signal to output a dynamic effective correction force signal reflecting the real force state of the scoliosis part.

Description

Technical Field

[0001] This invention belongs to the field of medical device monitoring and biomechanical signal processing technology, specifically relating to a method, device and orthopedic brace for monitoring scoliosis. Background Technology

[0002] Scoliosis braces are the primary treatment for adolescent scoliosis. To assess treatment effectiveness, pressure sensors are typically placed inside the brace.

[0003] However, existing monitoring methods have the following drawbacks in the daily dynamic activities of subjects: First, human skin and soft tissue have significant viscoelasticity, which causes the interfacial pressure signal to have a significant phase lag in response to the movement of the brace; second, the sensor components and their protective housing have a certain mass, which will generate inertial force under the action of motion acceleration, and this inertial force will be superimposed on the real corrective force signal to form noise; finally, the spinal force benchmark of subjects is completely different in different body positions (such as standing, walking, and lying flat).

[0004] Traditional monitoring methods often only provide static data and cannot effectively distinguish between actual corrective force and environmental / motion interference in dynamic environments, leading to biases in clinical assessment. Summary of the Invention

[0005] Therefore, it is necessary to provide a method, device, and scoliosis correction brace to address the aforementioned technical problems.

[0006] In a first aspect, this application provides a method for monitoring scoliosis correction, the method comprising: Acquire the acceleration signal generated by the orthotic brace as the subject moves, as well as the original pressure signal at the interface sensing point corresponding to the spinal deformity site; In the time domain, motion feature points representing the moment of impact in the acceleration signal are identified, and the response feature points in the original pressure signal are searched and matched within a preset time window, starting from the motion feature points. The time difference between the motion feature points and the response feature points is calculated, and a phase hysteresis function with respect to the motion frequency is constructed based on the time difference to determine the interface delay parameters caused by the viscoelasticity of soft tissue. The instantaneous evolution trend of the extrusion rate is extracted from the original pressure signal, and the interface delay parameter is used as the gain weight. The predicted compensation amount driven by the instantaneous evolution trend is superimposed on the original pressure signal to generate a reconstructed pressure signal that is phase-aligned with the motion feature point. The acceleration signal is mapped to the force normal direction of the interface sensing point to obtain the normal motion acceleration that characterizes the real-time motion state of the sensor; combined with the local inertial response characteristics that characterize the inertial mass distribution of the sensor components and are stored in the interface sensing point, the real-time inertial force component generated by the algorithmic motion acceleration at the pressure sensing end is solved. The real-time inertial force component is vector-stripped from the reconstructed pressure signal to output a dynamic and effective corrective force signal that reflects the actual stress state of the spinal deformity site.

[0007] Secondly, this application provides a scoliosis correction monitoring device, the device comprising: Pressure sensing module: Located at the interface sensing point of the orthotic brace, it is used to collect the original pressure signal corresponding to the spinal deformity site; Motion sensing module: rigidly fixed to the orthotic brace, used to acquire acceleration signals generated by the orthotic brace as the subject moves; Storage module: Used to store local inertial response characteristics that characterize the inertial mass distribution of sensor components; Processor: Connected to the pressure sensing module, motion sensing module and storage module respectively, and configured to execute the scoliosis correction monitoring method described above.

[0008] Thirdly, this application provides a scoliosis correction brace, including: a brace body, and a scoliosis correction monitoring device installed on the brace body.

[0009] The beneficial effects of this invention are as follows: 1) By constructing a phase angle hysteresis function and superimposing a prediction compensation amount, this application effectively solves the signal delay problem caused by the viscoelasticity of human soft tissue, ensuring that the pressure signal and physical motion are highly synchronized on the time axis, and greatly improving the transient response accuracy of dynamic monitoring.

[0010] 2) This application utilizes vector operations of normal acceleration and local inertial characteristics to accurately remove inertial interference generated by sensor components from the reconstructed signal. This process adds a "dynamic filter" to the signal, enabling the extraction of pure corrective forces reflecting the stress state of the spinal deformity from a complex motion background.

[0011] 3) This application overcomes the limitations of traditional monitoring methods that can only acquire static data, supporting all-weather monitoring of subjects during daily activities such as walking, running, and jumping. By capturing the mechanical laws in dynamic processes in real time, it provides clinical practice with more complete and valuable biomechanical assessment data. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this application or related technologies, the accompanying drawings used in the description of the embodiments of this application or related technologies will be briefly introduced below.

[0013] Figure 1 A schematic diagram of the overall structure of a scoliosis correction brace provided in an embodiment of this application; Figure 2 A hardware block diagram of a scoliosis correction monitoring device provided in an embodiment of this application; Figure 3 A schematic flowchart of a scoliosis correction monitoring method provided in an embodiment of this application; Figure 4 A flowchart illustrating steps S71-S73 of gait correlation evaluation provided in an embodiment of this application; Figure 5 A flowchart illustrating steps S61-S65 of an embodiment of this application, showing the corrective force generated purely by the prestress of the brace structure. Figure 6 A flowchart illustrating real-time early warning steps S81-S83 provided in an embodiment of this application; Explanation of reference numerals in the attached figures: 100. Brace body; 200. Scoliosis correction monitoring device; 11. Interaction sensing module; 12. Motion sensing module; 13. Storage module; 14. Processor. Detailed Implementation

[0014] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the scope of this application.

[0015] This embodiment provides a scoliosis orthotic brace with dynamic force monitoring function. This scoliosis orthotic brace achieves precise quantification of the corrective effect on the subject in daily life through hardware integration. Please refer to... Figure 1 The scoliosis correction brace mainly consists of two parts: the brace body 100 and the scoliosis correction monitoring device 200. The main body of the brace 100 is made of medical-grade thermoplastic polymer or 3D-printed resin, and its internal cavity shape is customized according to the subject's scoliosis type (such as C-type or S-type).

[0016] The scoliosis correction monitoring device 200 is integrated into the main body 100 of the brace worn by the subject, such as Figure 2 As shown, the device includes: an interactive sensing module 11, a motion sensing module 12, a storage module 13, and a processor 14.

[0017] The interactive sensing module 11 is disposed on the inner wall force-bearing interface of the brace body 100, preferably a flexible piezoresistive array sensor. To achieve precise capture of key areas of lateral curvature, this module is specifically deployed in the brace's pressure zone, corresponding to the apex vertebra of the primary or secondary curve of the subject's spine. This module is used to acquire, in real time, the raw pressure signals generated by the interaction between the subject's torso and the brace.

[0018] The motion sensing module 12 is a high-precision triaxial inertial measurement unit, which is fixed to the non-deformation area (such as the back reinforcement or support keel) of the orthotic brace 10 through a rigid coupling structure. This rigid coupling structure ensures that the sensitive axes (X / Y / Z) of the motion sensing module 12 are strictly parallel to the mechanical principal axes of the brace. This physical alignment design allows the acceleration signals captured by the motion sensing module 12 to directly reflect the overall spatial pose changes of the brace without the need for complex coordinate system rotation, providing a clean dynamic reference for subsequent inertial force stripping.

[0019] The core physical finding of this application lies in the significant viscoelasticity of the soft tissues (muscles and fat) in the back of scoliosis patients. During dynamic activities, the mechanical excitation (motion) from the brace is transmitted to the bones and then fed back to the interactive sensing module 11 through the soft tissue, with a nonlinear phase lag in between. Traditional monitoring methods directly read pressure values, which often result in signal phase lag due to the "damping effect" of the soft tissue, and amplitude distortion due to the "inertial artifacts" generated by the sensor's own mass during motion.

[0020] For example, when a subject experiences gait impact, due to the viscoelasticity of soft tissue, the peak value of the original pressure signal always lags behind the point of acceleration impact. Without addressing this phase discrepancy, simple subtraction cannot achieve force decoupling.

[0021] Therefore, this embodiment provides a method for monitoring scoliosis correction. Instead of directly treating pressure values ​​as corrective forces, this embodiment uses processor 14 to construct a decoupling algorithm based on interface dynamics characteristics. Processor 14 is communicatively connected to both the interactive sensing module 11 and the motion sensing module 12, and is responsible for synchronously acquiring the two heterogeneous signals via a hardware timer.

[0022] The processor 14, as the logic control and computation core of this device, is configured to execute the scoliosis correction monitoring method of this application. The method is implemented entirely within the processor 14, recovering high-frequency features absorbed by soft tissue through phase reconstruction, and vectorly stripping the inertial components generated by brace swaying.

[0023] Based on the aforementioned hardware architecture and physical principles, this application provides a method for monitoring scoliosis correction, which is executed independently by processor 14. Considering the complexity of the physical interface during scoliosis correction, the monitoring process executed by processor 14 is configured into two interconnected stages, such as... Figure 3 As shown: Phase 1: Initialization and Coupling Verification Phase (including step S1), which is used to ensure that a stable force transmission path is established between the sensor and the bone. The second stage: the dynamic decoupling monitoring stage (including steps S2-S6), is used to achieve precise decoupling of forces on the basis of a stable path.

[0024] Correspondingly, the interactive sensing module 11 and the motion sensing module 12 are responsible for synchronously acquiring the original pressure and acceleration signals in step S2 as the input source of the algorithm; Storage module 13: As the system's 'physical knowledge base', it pre-stores the unique inertial characteristic coefficients of each sensing point (for inertial stripping in step S6) and the interface delay model (for phase reconstruction in steps S3-S4). Processor 14: As an execution engine, it is configured to execute the entire process logic sequentially from initialization verification (step S1) to dynamic signal decoupling (steps S2-S6).

[0025] The reason for setting up a first stage is that when this method is applied to specific scoliosis orthotic braces (such as Boston type, Cheneau type, or 3D-printed personalized braces), it faces extremely strong viscoelastic interference in the human torso. For adolescent idiopathic scoliosis patients, the ribs on the convex side protrude posteriorly to form a rib ridge, and the skin in this area is compressed and firm, while the tissue in the concave side is relatively loose. Physically, if the pre-tension is insufficient in the initial wearing stage, there will be tiny gaps between the brace liner and the skin, or the area will be in a "non-linear deformation zone." At this time, the pressure measured by the sensor is mainly consumed in the elastic deformation of the skin and subcutaneous fat, resulting in severe phase lag and amplitude distortion of the signal, which cannot be used as an effective reference for subsequent dynamic calculations.

[0026] Therefore, before starting the dynamic sampling process (step S2), the processor 14 must first execute the initialization verification logic, namely step S1, to obtain the baseline static pressure of the subject after filtering out respiratory fluctuations in the resting state, and compare the baseline static pressure with the linear viscoelastic critical pressure value retrieved based on the subject's physical characteristics; if the baseline static pressure reaches the critical pressure value, it is determined that the interface sensing point has entered the linear viscoelastic response range, and step S2 is triggered.

[0027] By setting a preset stability threshold The aim is to ensure that the coupling pressure between the inner wall of the brace and the skin of the subject's convex force application area crosses the "relaxation state" and enters the "linear modulus zone." In this region, the damping properties of the soft tissue tend to stabilize, enabling the corrective force of the brace to be transmitted to the ribs and corresponding vertebrae with high fidelity.

[0028] The processor 14 contains a pre-stored mapping table specifically for children with scoliosis (see Table 1). This table further considers the unique anatomical asymmetry of scoliosis patients, precisely defining the force application point as the apical vertebral pointing area in three-dimensional space: Table 1: Anatomical Mapping Relationship Table Specific to Scoliosis

[0029] The verification step is performed by processor 14, as follows: The processor 14 identifies sensor signals specifically arranged in the force application area of ​​the brace (the convex side corresponding to the Apex level position of the apex vertebra) and the contralateral compensation area through the interactive sensing module 11.

[0030] While the subject is standing at rest, processor 14 extracts the average pressure value of the force application zone sensor over 3-5 respiratory cycles. Due to the asymmetrical expansion of the chest cavity during breathing in scoliosis patients, processor 14 automatically identifies and filters out the sinusoidal wave peaks generated by breathing through its built-in digital filtering operator, extracting the pure reference static pressure.

[0031] Instructions for State A (Insufficient Pressure): If The processor 14 determines that there is a "dynamic gap" between the brace and the spine. At this time, if motion monitoring is forcibly performed, the brace will slide axially and rotate radially on the torso due to inertia, causing the data to become completely invalid. The processor 14 then generates a prompt through the external interface: "Insufficient coupling at the top vertebral force application point detected. Please tighten the Xth strap."

[0032] Status B (Pressure Target Met): If The determination interface has entered the linear viscoelastic response range, and a "rigid force transmission path" has been formed between the brace and the bone. At this point, the processor 14 automatically starts the subsequent dynamic sampling logic. That is, it enters the second stage, including the following steps S2-S5: Step S2: Obtain the acceleration signal generated by the orthotic brace as the subject moves, and the original pressure signal at the interface sensing point corresponding to the spinal deformity site; To eliminate dynamic interference from human breathing and gait swaying, processor 14 establishes a high-frequency synchronous sampling mechanism: a synchronization interrupt is triggered by an internal hardware timer, driving the pressure monitoring channel and motion sensing channel to perform sampling simultaneously. The sampling frequency is set to 50Hz-200Hz. This frequency band not only fully covers the characteristic spectra of breathing (0.2-0.5Hz) and walking gait (1-2Hz), but also provides the necessary temporal resolution for phase reconstruction in subsequent steps. This hardware-level synchronization ensures that each frame of pressure and acceleration data has a completely consistent timestamp, which is a physical prerequisite for removing inertial noise.

[0033] Because scoliosis correction involves multiple vertebral segments, pressure sensing arrays are arranged in multiple apex force application zones (ApexZones) within the brace lining. Considering the characteristic of "one-point motion sensing, multiple-point pressure application," the embodiment executes the following key mapping logic: A spatial coordinate system is established using the IMU, where the X-axis corresponds to the coronal plane (left-right), the Y-axis to the sagittal plane (anterior-posterior), and the Z-axis to the vertical plane (up-down). The normal vectors of each sensing point (corresponding to different vertebral positions) pre-stored based on the brace 3D scan data are retrieved from the storage module. Due to the complex curvature of the inner wall of the support, the normal orientation varies at different sensing points. Processor 14 calculates the global acceleration vector in real time. In the normal direction of each specific sensory point scalar projection on This mapping step decomposes the overall motion of the brace into "interference components" for each sensing point. It precisely quantifies, at the current instant, which direction of acceleration caused which sensing point to produce a false pressure fluctuation.

[0034] In step S2, the raw pressure signal acquired by each sensing point ( The original pressure signal at the i-th interface sensing point is explicitly defined as a composite physical quantity: in It is the actual corrective force affected by the viscoelasticity of soft tissue; It is a false disturbance caused by the inertia of the support in the normal direction at that point (its magnitude is similar to...). (Proportional) The periodic fluctuations caused by respiration.

[0035] Step S3: Identify motion feature points representing the moment of impact in the acceleration signal in the time domain, and search and match response feature points in the original pressure signal within a preset time window, using the motion feature points as the starting point; calculate the time difference between the motion feature points and the response feature points, and construct a phase hysteresis function with respect to the motion frequency based on the time difference to determine the interface delay parameters caused by the viscoelasticity of soft tissue. In this embodiment, step S3 aims to address the problem of hysteresis in the back soft tissues (muscles, fat, etc.) of scoliosis subjects during dynamic activities, caused by the damping effect leading to lag in pressure response. By quantifying the causal temporal relationship between "excitation-response," the complex biomechanical disturbance is transformed into qualitative parameters characterizing the quality of interfacial coupling.

[0036] Motion feature points This refers to the point in time at which the transient acceleration change triggered by gait impact loads is sensed by the rigid shell of the brace. Physically, it represents the "cause" of the dynamic excitation, i.e., the zero point in time of the force transmission process. The processor 14 processes the lateral acceleration components within the current gait cycle. Perform first-order differentiation to calculate its jerk. .

[0037] Set dynamic threshold (in The mean of the signal. Standard deviation, sensitivity coefficient Take 2.5-3.5). When The signal exceeded for the first time At that time, record the current timestamp as the motion feature point. This point locks the precise instant that the mechanical wave generated by the heel striking the ground is transmitted to the brace housing.

[0038] Multiple sensing points for the arrangement of the brace lining (Corresponding to different segments of the spine), execute differentiated search and matching logic to ensure the homogeneity of stimulus and response: response feature points This refers to the peak pressure point in the original pressure signal, triggered by a specific gait impact and transmitted through soft tissue buffering. Starting from this point, a causal search window with a length of 20ms-250ms is opened. The opening of this window is strictly limited by the "dynamic excitation cycle": if the processor 14 identifies the motion feature points of the next gait cycle before the window is closed... If this happens, the search in the current window will be terminated immediately.

[0039] This logic ensures that the retrieval of response feature points is strictly limited to the same dynamic loop. Because the soft tissue thickness varies in different parts of the back of scoliosis patients (such as the convex side of the apex vertebra and the contralateral compensation area), different sensory points... response point The signals are discretely distributed on the time axis. This step eliminates cross-cycle signal mismatches through differential matching.

[0040] Then, processor 14 calculates the time difference between each group of homologous feature points. This value directly reflects the time it takes for the impact force to penetrate the soft tissue layer at that local location.

[0041] To eliminate the impact of walking frequency (step frequency) on delay, processor 14 calculates angular frequency using the time interval between adjacent motion feature points. And convert the time difference in the time domain into a phase lag in the phase domain. .

[0042] By introducing the Kelvin-Voigt physics model, processor 14 uses multiple sets of dynamic data to fit and construct a phase hysteresis function unique to each sensing point: The optimal constant calculated (Interface delay parameter / feature relaxation time) depends only on the physical state of the soft tissue at that local location and the tightness of the brace, and is independent of walking speed.

[0043] During scoliosis correction, there are significant differences in the biomechanical transmission characteristics between the convex side of the apex vertebra (where tissue is compressed and thinned) and the contralateral compensation area (where tissue is looser and thicker). Step S3 is used to... (The sentence is incomplete and requires further context to translate accurately.) A dedicated "interface physical profile" was created. The identified parameters... It is a core indicator for measuring the coupling quality between the brace and the skeleton. If a certain sensory point The increase is significant, and even if other areas are normal, it can accurately determine that the local area has experienced interface slippage or loosening (e.g., lumbar spine brace opening). Step S3 successfully decouples the "delay change caused by walking speed" from the "inherent delay caused by interface characteristics", providing a unique and highly reliable input parameter for step S4 to perform high-precision phase reconstruction and noise stripping.

[0044] Step S4: Extract the instantaneous evolution trend of the extrusion rate from the original pressure signal, and use the interface delay parameter as the gain weight to superimpose the prediction compensation amount driven by the instantaneous evolution trend on the original pressure signal to generate a reconstructed pressure signal that is phase-aligned with the motion feature point. The core logic of step S4 is: utilizing the unique physical constants of each sensing point identified in step S3. By using inverse dynamics algorithms to compensate for the delay and attenuation caused by soft tissue, the pressure signal is "pushed forward" on the time axis to restore the real interaction force between the bone and the brace.

[0045] First, in order to quantify the dynamic impact of bone on soft tissue, processor 14 performs the following calculations: Instantaneous evolution trend Physically, this represents the invasive velocity of the vertebral / rib compression of soft tissue. Based on the Kelvin-Voigt model, the damping resistance generated by the soft tissue is proportional to this compression velocity. For each sensing point... The original pressure signal Processor 14 uses an improved three-point central difference operator to extract its derivative features: in The sampling period is denoted as . Compared to a simple first-order difference, this operator can effectively suppress high-frequency electronic noise from the sensor while extracting the trend.

[0046] Secondly, the processor 14 will use the "interface physical fingerprint"—interface delay parameter—calculated in step S3. The injection correction algorithm executes the following reconstruction logic: Processor 14 performs the following difference equation for each sensing point. Generate reconstructed pressure signal : Static reference term To retain the quasi-static pressure amplitude captured by the current sensor.

[0047] Trend-driven compensation This refers to: utilizing the identified relaxation time The extrusion rate is weighted.

[0048] Due to the damping effect of soft tissue, the actual peak force is always "flattened" and "postponed"; by superimposing this derivative component, the algorithm mathematically generates a phase lead angle.

[0049] Due to each point Different soft tissue thicknesses and firmnesses allow for precise repair tailored to each individual point. (The convex side of the apex vertebra...) The smaller area (smaller) receives a smaller phase shift, while the compensation region (smaller) receives a smaller phase shift. The large phase shift ensures that the reconstructed signals at all points can be accurately traced back to the actual physical excitation moment.

[0050] Then, phase alignment refers to the peak moment of the reconstructed pressure waveform. Achieve "reset" on the time axis to align it with the motion feature points. They are highly coincident in phase. Processor 14 compares the reconstructed peak stress time. and gait impact starting point If the difference between the two values ​​reaches a millisecond threshold (e.g., ... If the signal is successfully reconstructed, it is considered successful. This process is equivalent to "penetrating" the skin and muscle layers in the digital domain, virtually attaching the sensor to the bone surface. It recovers the high-frequency components of pressure that were absorbed by the viscoelasticity of soft tissue, enabling the processor 14 to capture the most realistic and acute instantaneous impact load of the brace on the deformed vertebra.

[0051] In this embodiment, step S4 is not only signal processing, but also a reconstruction of mechanical relationships: although the anatomical structures of the sensing points are quite different, through differentiated... Compensation, all sensing points The signals are all aligned on the same "time scale"; because Since step frequency decoupling was performed in step S3, the reconstructed signal generated in step S4 maintains extremely high phase consistency regardless of the subject's dynamic states, such as fast walking or slow walking. The reconstructed signal... The elimination of response delay makes it possible to perform a direct subtraction of "pressure peak - inertia peak" (stripping inertial force) in step S5.

[0052] Step S5: Map the acceleration signal to the force normal direction of the interface sensing point to obtain the normal motion acceleration that characterizes the real-time motion state of the sensor; combine the local inertial response characteristics that characterize the inertial mass distribution of the sensor components and are stored in the interface sensing point to solve the real-time inertial force component generated by the algorithmic motion acceleration at the pressure sensing end. Step S5 aims to eliminate "motion artifacts" caused by the subject's dynamic activities such as walking and jumping. Its core logic is to use the spatial reference established in step S2 to calculate the spurious pressure components generated by the "brace movement" of each sensor at a specific location.

[0053] First, normal acceleration. The overall acceleration vector of the support at a specific sensing point The projection component in the direction of the force normal. Because the lining of the scoliosis brace has a complex free-form surface, the force direction of the sensing points in different vertebral segments (such as the apical region and the contralateral side) is different, so fine projection must be performed.

[0054] Processor 14 retrieves the real-time rotation matrix of the IMU in step S2. Gravity compensation was applied to the original triaxial acceleration to extract the net motion acceleration vector of the support. The processor 14 retrieves the data from the storage module for each sensing point. Pre-stored unit normal vector (This vector is predefined by the 3D scan model of the brace). The real-time normal acceleration of each point is calculated using dot product operations: This component accurately depicts the actual motion intensity of the brace "pressing against the body" or "detaching from the body" at each local force point during the gait cycle, solving the problem of traditional solutions being unable to distinguish the differences in inertia at different anatomical points.

[0055] Secondly, local inertial response characteristics Point of perception The equivalent inertial mass generated by the sensor module and its associated packaging structure during normal motion. Processor 14 determines this mass through an in-situ self-calibration algorithm. During the initial calibration phase, record the ratio of pressure variation to acceleration variation of the support under no-load swaying conditions. It not only includes the physical mass of the sensor, but also compensates for the dynamic impedance caused by the local deformation of the support shell.

[0056] Then, processor 14 calculates the real-time inertial force components by combining the above mapping parameters: when When the brace accelerates inward, a false pressure peak is generated; when When the value is negative (the brace accelerates outward), a centrifugal tendency to disengage occurs, leading to a decrease in the measured value. This force is a major source of noise that masks the true orthodontic force.

[0057] Step S6: Vectorly extract the real-time inertial force component from the reconstructed pressure signal and output a dynamic and effective corrective force signal that reflects the actual force state of the spinal deformity site.

[0058] Step S6 is the end of the entire decoupling chain, where a pure corrective force signal is restored by performing an amplitude subtraction on the aligned time axis.

[0059] Vector stripping refers to the process of eliminating inertial noise generated by physical synchronization from a signal that has already undergone phase reconstruction through subtraction. Processor 14 performs the stripping operation only after phase alignment has been completed by S4. In the original signal, the pressure peak lags due to the viscoelasticity of soft tissue and cannot be directly subtracted from the acceleration peak.

[0060] Thanks to step S4 utilizing the interface delay parameter The phase lag is canceled out, and the pressure signal is then reconstructed. Peak moment and normal motion acceleration The feature points have physically overlapped on the time axis.

[0061] Processor 14 performs the following vector subtraction to output a dynamic effective corrective force signal. : Among them, dynamic effective corrective force This refers to the system that, after eliminating interference from "brace impact on the body" and "sensor inertia," accurately reflects the instantaneous interactive forces experienced by the spinal deformity site during the motion phase. The output signal recovers the high-frequency characteristics of pressure absorbed by soft tissue while eliminating spurious fluctuations caused by motion. Its waveform characteristics maintain a high degree of consistency with those observed when worn statically under different motion conditions.

[0062] In the general implementation of step S5, although in-situ self-calibration via "no-load shaking" is proposed, in actual operation, if the brace is in place (i.e., worn on the body but not tightened) during calibration, the sensor diaphragm will inevitably be affected by "parasitic damping" caused by skin surface tension, micro-sweat viscosity, or local muscle micro-movements, leading to errors in the calculated equivalent mass coefficient. It includes nonlinear biomechanical noise. In addition, if the swaying frequency does not match the actual gait frequency, the dynamic impedance characteristics of the brace's composite shell will also drift.

[0063] In one exemplary embodiment, to address the aforementioned pain point of inaccurate calibration, this embodiment provides a more accurate optimized implementation path: Optionally, in this embodiment, the inertial characteristic coefficients pre-stored at the interface sensing point are pre-configured in the following way: when the orthotic brace is in an off-position state without being worn, an excitation load simulating the human body movement frequency is applied to the orthotic brace, and the pressure fluctuation and motion acceleration measures at the interface sensing point are recorded; a proportional relationship between the pressure fluctuation and the motion acceleration measures is established, and this proportional relationship is defined as the inertial characteristic coefficient corresponding to the interface sensing point.

[0064] In this embodiment, to address potential biomechanical interference in step S5, the processor 14 employs an off-body pre-configuration scheme to calibrate the inertial characteristic coefficients of each sensing point. This is to ensure the absolute purity of the inertia compensation logic.

[0065] In this embodiment, the local inertial response characteristics in step S5 are addressed. (i.e., inertial characteristic coefficients), the processor 14 executes a more precise pre-configuration process to establish the "inertial fingerprint" at the hardware level of each sensing point.

[0066] First, the calibration process is limited to an off-body state, meaning the orthotic brace is not yet worn on the subject's body and the inner sensing array is completely unloaded. The processor 14, via an external excitation device or manual guidance, subjects the orthotic brace to a set of excitation loads simulating human movement frequencies (preferably in the range of 1Hz-5Hz, covering the gait frequency domain from slow walking to fast running and jumping). During this process, the brace shell dynamically displaces with the excitation, and the sensing points... The inertial force generated by the sensor module's own physical mass directly acts on the sensing diaphragm.

[0067] Subsequently, the processor 14 synchronously records the pressure fluctuation at the sensing point under the excitation. With motion acceleration measurement Since there is no viscoelastic absorption or buffering by the human body's soft tissue at this time, all pressure fluctuations captured by the sensor are entirely attributed to the inertial response of the hardware components. The processor 14 then establishes a proportional relationship between the pressure fluctuation and the motion acceleration measurement using linear regression or least squares, and defines the slope of this proportional relationship as the inertial characteristic coefficient corresponding to the sensing point. : In a physical sense, this coefficient This is the core operator for real-time inertial force calculation in step S5. This off-site pre-configuration method has significant technical advantages over traditional online estimation: it can completely eliminate the biomechanical coupling interference of the "brace-human" interface, so that the obtained coefficients only represent the pure physical mass contribution of the sensor module and its associated packaging structure in normal motion.

[0068] Ultimately, the pre-configured inertial characteristic coefficients are stored in processor 14 as the "hardware mechanics profile" of the support. When entering the real-time operation phase of steps S5 and S6, processor 14 directly calls this high-precision... Value and real-time sensed normal motion acceleration Multiplying these components allows for the accurate reconstruction of the synchronized real-time inertial force components, providing an absolutely pure noise reference for vector stripping in step S6.

[0069] While the general description of step S4 proposes using interface delay parameters to perform inverse dynamic compensation, in practical engineering applications of digital signal processing, accurately and in real-time constructing the compensation amount is crucial to ensuring phase alignment accuracy. This embodiment provides a real-time reconstruction path with low computational overhead and clear physical meaning by defining the product logic of "instantaneous rate of change" and "gain weight".

[0070] Optionally, in this embodiment, extracting the instantaneous evolution trend of the compression rate in the original pressure signal specifically includes: obtaining the instantaneous rate of change reflecting the speed of change of the original pressure signal value by performing real-time differential or derivative operations on the original pressure signal, and using the instantaneous rate of change as the instantaneous evolution trend.

[0071] First, processor 14 performs the extraction of instantaneous evolution trends. Processor 14 then extracts the sensing points... The original pressure signal Perform real-time differential or first-order derivative operations to obtain the instantaneous rate of change reflecting the speed of pressure numerical change. .

[0072] This calculation, in a physical sense, represents the "intrusion compression rate" of the bone at the deformed site on the skin and deep soft tissues during dynamic movement (such as the gait support phase). According to the Kelvin-Voigt viscoelastic model used in this embodiment, soft tissue can be mechanically equivalent to a parallel spring (elastic element) and damper (damping element). When the actual corrective force applied by the bone penetrates the soft tissue, part of it overcomes elastic deformation, and the other part is consumed by the damping resistance, which varies with velocity. The original pressure sensed by the sensor... Essentially, it is the residual stress after damping reduction. It is this damping component that causes the pressure peak sensed by the sensor to shift backward on the time axis.

[0073] Furthermore, in this embodiment, the interface delay parameter is used as the gain weight, and a predicted compensation amount driven by the instantaneous evolution trend is superimposed on the original pressure signal to generate a reconstructed pressure signal that is phase-aligned with the moving feature point. Specifically, this includes: determining the instantaneous amplitude of the predicted compensation amount by multiplying the interface delay parameter and the instantaneous rate of change; and superimposing the instantaneous amplitude on the current sampled value of the original pressure signal in real time to generate a reconstructed pressure signal that is phase-aligned with the moving feature point.

[0074] In this step, the processor 14 utilizes the "interface physical fingerprint"—interface delay parameter—identified for the specific sensing point in step S3. As a gain weight, it is multiplied with the aforementioned instantaneous rate of change to determine the instantaneous amplitude of the predicted compensation amount. : Due to interface delay parameters Essentially, the characteristic relaxation time constant (time dimension) of the local interface soft tissue is multiplied by the rate of change of pressure over time (pressure / time dimension), thus returning to the pressure unit in terms of dimensionality. This product logic physically accurately fills in the mechanical loss that could not be transmitted to the sensor in real time due to the damping effect of the soft tissue.

[0075] Finally, processor 14 performs superposition reconstruction. Processor 14 calculates the instantaneous amplitude... The reconstructed pressure signal is superimposed in real time onto the current sampled value of the original pressure signal to generate the final reconstructed pressure signal. : This real-time reconstruction logic mathematically injects a "phase lead angle" into the original pressure signal, constructing a first-order phase lead filter.

[0076] At the rising pressure edge (intensified compression): the instantaneous rate of change is positive, indicating that the bone is rapidly invading the soft tissue, and the damping hysteresis is most severe. At this time, the compensation is positive and at its maximum, "pulling up" the signal in advance and pushing it forward.

[0077] At the pressure drop edge (squeeze release): the instantaneous rate of change is negative, the compensation amount is negative, and the signal is pulled back downward and forward.

[0078] Due to each sensing point (Depending on tissue thickness and firmness) different, this allows for precise phase repair on a "one-point-one-policy" basis. This action, at the physical level, is equivalent to virtually attaching the sensor to the bone surface, eliminating the conduction lag caused by the "skin-muscle" layer.

[0079] The final result is that the peak value of the reconstructed pressure waveform is "backtracked" on the time axis, aligning it with the motion characteristic point representing the starting point of the physical excitation. The phases are highly coincident. This derivative-weighted compensation mechanism recovers the high-frequency pressure components absorbed by the viscoelasticity of soft tissue, thus enabling the reconstructed signal to... It can accurately reproduce the sharpest instantaneous impact load of the brace on the deformed vertebra. This high degree of phase consistency lays a solid numerical foundation for subsequent steps S5 and S6 to perform subtraction (vector stripping of homogeneous inertial noise) at the same "time scale".

[0080] Experiments show that without this phase reconstruction, the peeling error is as high as 15% or more due to the misalignment of the inertial peak and the pressure peak on the time axis; while after adopting the reconstruction path of this embodiment, the mechanical fidelity of dynamic monitoring is improved to more than 95%.

[0081] After completing the signal decoupling and reconstruction in steps S1-S6, a "pure" dynamic effective corrective force signal, free from inertial noise and phase hysteresis, has been obtained. However, in clinical practice, doctors focus not only on the absolute value of the force but also on the dynamic stability of the brace during the subject's walking process. This embodiment introduces gait phase correlation analysis to transform the corrective force into a diagnostic indicator for measuring the quality of wearing the brace, achieving a closed loop from "data monitoring" to "status assessment." The dynamic effective corrective force signal output in step S6... The processor 14 executes a set of gait correlation evaluation logic, which aims to identify the macroscopic slippage state between the brace and the human body through the microscopic features of the mechanical waveform.

[0082] Optional, such as Figure 4 As shown, in this embodiment, the method further includes the following gait association evaluation steps S71-S73: Step S71: Identify the fundamental frequency component in the motion acceleration signal using spectrum analysis or autocorrelation calculation. When the fundamental frequency component is within the preset gait frequency range, determine that the subject is in a walking state and lock the time switching boundary between the impact phase and the steady phase within a single gait cycle. First, the processor 14 performs real-time frequency domain transformation (FFT) or autocorrelation operation on the motion acceleration signal obtained in step S2 to extract the fundamental frequency component of the brace motion. .

[0083] State determination: when When the subject is consistently within a preset cadence range (e.g., 1.0Hz-2.5Hz) and the amplitude is stable, the subject is considered to be in a steady-state walking state.

[0084] Boundary Locking (Mechanical Golden Ridge): Processor 14 uses the abrupt change point of the vector magnitude of the acceleration signal as a "logic gate" to lock the time switching boundary between the impact phase and the steady phase within a single gait cycle. .

[0085] Impact phase (GATE OPEN): It begins when the magnitude of the acceleration vector exceeds 1.5 times the resting reference value and ends when it falls back to 1.1 times the reference value. Within this gate, the "dynamic stress" is extracted.

[0086] Gate Closed: The static stress is extracted during the quiet period between two adjacent impact phases.

[0087] The necessity of this segmentation method lies in the fact that without phase segmentation, the huge peak generated by gait impact would mask the slight decline in quasi-static pressure caused by loosening of the garment. Through this "time-domain divide-and-conquer" strategy, dual-dimensional monitoring of "instantaneous impact quality" and "long-term support quality" is achieved.

[0088] Step S72: Use time switching boundaries to perform time-domain segmentation on the dynamic effective corrective force signal to obtain the impact force signal segment corresponding to the impact and the steady force signal segment corresponding to the steady state; extract the peak force value representing the instantaneous compressive strength from the impact force signal segment and extract the average force value representing the foundation support strength from the steady force signal segment. Processor 14 utilizes the aforementioned time switching boundary For dynamic and effective corrective force signals To perform precise segmentation, specifically: When determining the impact phase window, the processor 14 monitors the acceleration magnitude in real time. When the magnitude rises from the resting reference to 1.5 times the threshold, the impact phase start time stamp is triggered; when the magnitude falls back to 1.1 times the threshold, it is marked as the end time stamp.

[0089] Signal segmentation execution: Processor 14, based on the aforementioned timestamps, from consecutive... The corresponding time segment is extracted from the sequence. Within the impact phase segment, the maximum value retrieval operator is executed to extract the value. During the intermittent segments between adjacent impact phases, an arithmetic mean calculation is performed to extract... .

[0090] Impact signal segment ( ): Extracts the peak force value within this segment. It physically represents the maximum instantaneous corrective strength of the brace on the deformed area at the moment of gait impact, reflecting the brace's "correction capability" under dynamic conditions.

[0091] Smooth force signal segment ( ): Extract the average force value within this segment. It physically represents the basic support force (i.e., quasi-static corrective force) provided by the brace, reflecting the brace's "maintenance capability" under normal conditions.

[0092] Step S73: Calculate the discrete characteristic quantities of the peak force value and the average force value within multiple consecutive gait cycles. Based on the comparison results of the discrete characteristic quantities and the preset stability threshold, evaluate the degree of interface slippage or wearing stability of the orthotic brace during the dynamic process.

[0093] Processor 14 performs statistical analysis on the feature values ​​within multiple consecutive gait cycles (e.g., 10-20 cycles) and calculates their discrete feature quantities (e.g., coefficient of variation). ): The physical basis of this step lies in the "geometric locking effect." A scoliosis brace is a rigid shell with a fixed geometry. When worn correctly and securely, each sensing point forms a fixed spatial coupling with a specific anatomical location on the back (such as the apical ribs). Under steady-state walking, the compressive intensity of each shock wave on the same location should have a high degree of physical repeatability. Based on this, processor 14 performs the following causal inference: Scenario A: Interface sliding detection (dynamic misalignment) like Stable, but The discrete characteristic value significantly exceeds the preset threshold (e.g., 15%), indicating that the compression position of the brace relative to the skeleton is not fixed each time the heel strikes the ground. The physical mechanism is that although the brace restraint straps are tightened, the curvature of the brace inner wall does not achieve precise "concave-convex locking" with the human skeletal protrusions, resulting in millimeter-level displacement during movement. Due to the uneven thickness of the soft tissue around the spine, any displacement will change the force fulcrum, triggering... Violent fluctuations.

[0094] Scenario B: Judgment of Loose Fit (Overall Shift) like The results showed a monotonically decreasing trend over time, accompanied by increasing dispersion, indicating that the brace had become completely loose. The physical mechanism is that the brace slipped off the body at a constant speed (e.g., due to decreased friction caused by sweat or loosening of the straps), resulting in an overall decrease in base pressure.

[0095] This embodiment addresses the pain point of traditional monitoring methods, which cannot distinguish between pressure fluctuations caused by unstable gait and mechanical deviations caused by improper brace fit. This method, based on statistical dispersion to infer the degree of interface slippage, bypasses complex visual capture equipment and achieves precise closed-loop monitoring of brace fit at the physical level solely through the autocorrelation characteristics of force signals. It automatically generates a fit quality report. If the discrete characteristic exceeds the standard, the terminal prompts "Brace slippage has occurred; please readjust the strap tightness," ensuring that the corrective force output in step S6 truly acts on the spinal deformity target, improving the effectiveness of long-term wear.

[0096] After completing the dynamic decoupling in steps S1-S6, the "inertial force interference" caused by motion acceleration has been eliminated. However, scoliosis correction is a long-term monitoring process, and the subject will experience various positional changes such as standing, sitting, lying flat, and lying on their side while wearing the device all day.

[0097] On a physical level, because the subject's torso has significant mass, gravitational acceleration increases when their body position changes. The distribution along the body's spatial axes undergoes reconstruction. For example, when a subject switches from standing to lying down, their back muscles and soft tissues, under the influence of gravity, "collapse" towards the inner wall of the brace, generating a significant non-corrective compressive force. Without eliminating this bias, it might be mistakenly perceived that the corrective intensity is higher when lying down than when standing. Therefore, the advanced goal of step S6 is to remove this "positional artifact" and restore the corrective force purely generated by the prestress of the brace structure, such as... Figure 5 As shown, the specific steps include S61-S65: Step S61: Vector-strip the real-time inertial force component from the reconstructed pressure signal and output the initial effective corrective force signal that reflects the true force state of the spinal deformity site; Processor 14 performs the first-stage stripping based on time-axis alignment. Processor 14 retrieves the phase-reconstructed pressure signal from step S4. (Soft tissue delay has been eliminated) and the normal inertial force calculated in step S5. (Motion artifacts have been eliminated), perform vector subtraction, and output the initial effective corrective force signal. : At this time This marks the completion of "dynamic noise" stripping. Although the signal waveform is smoothed, its DC offset still drifts with the subject's spatial tilt angle. For example, when the subject is lying flat, the signal will contain a large non-corrective contact pressure due to the soft tissue of the back "collapse" into the inner wall of the brace under the influence of gravity.

[0098] Step S62: Separate the constant gravitational acceleration component representing the gravity vector from the motion acceleration signal through low-pass filtering, and calculate the tilt vector reflecting the spatial tilt state of the support based on the projection amplitude of the constant gravitational acceleration component on the three axes of the support coordinate system. In order to sense the spatial orientation of the gravity vector in real time, processor 14 performs constant component extraction on the acceleration signal: A fourth-order Butterworth low-pass filter with a cutoff frequency of 0.2 Hz was used. 0.2 Hz was chosen to maintain a rapid response to body position changes (usually lasting 1-3 seconds) while completely filtering out gait impacts (>1 Hz) and respiratory micro-vibrations (0.3-0.5 Hz).

[0099] The constant gravitational acceleration component extracted by processor 14 The magnitudes on the three axes of the support coordinate system reflect the spatial tilt of the support. Using... The operator solves for the tilt vector (in the sagittal plane tilt angle) that reflects the spatial tilt state. (For example) in, This represents the forward and backward components. The algorithm can automatically compensate for the energy distribution of the gravity component between each axis, ensuring a unique tilt angle is obtained under various combined attitudes.

[0100] Step S63: Use the range of values ​​of the tilt vector to determine the subject's real-time body posture category; Optionally, processor 14 will calculate Values ​​are mapped to preset body pose feature ranges: Vertical posture (Standing / Sitting): When At this time, the patient is considered to be in an upright position. At this time, gravity acts along the spinal axis, resulting in minimal normal compression on the sensory point.

[0101] Reclining: When When the patient is in a semi-reclining or sitting position, it is determined that the patient is in a semi-reclining or sitting

[0102] Horizontal posture (Supine / Prone): when At this time, the body is judged to be in a supine position. At this time, almost all of the body's weight is converted into normal pressure at the sensing point.

[0103] Step S64: Based on the identified real-time posture category, retrieve the static pressure bias that matches the category from the preset posture-pressure database, and use it as the correction benchmark for the non-corrective pressure component under that posture. To eliminate "self-weight artifacts" under specific body postures, this embodiment establishes a personalized biomechanical archive: In the initial stage of wearing the device, the subject is in "calibration mode," guided to perform standard body posture switching, and each sensory point is recorded when the straps are not tightened (zero corrective stress state). Residual pressure.

[0104] Based on the discrimination result of step S63, processor 14 retrieves the static pressure bias of the subject under the current body posture category. This offset represents the "natural fit force" between the brace and the skin surface under different gravitational directions, and it is the "dynamic mechanical zero point" for subsequent orthodontic force calculations.

[0105] Step S65: Subtract the static pressure bias from the initial effective corrective force signal to output a dynamic effective corrective force signal that reflects the actual force state of the spinal deformity site.

[0106] Processor 14 performs the final decoupling operation, "subtracting" the gravitational background from the initial signal and outputting a dynamic and effective corrective force signal. : This embodiment achieves the effect of "virtually suspending" the sensor at the physical level. This ensures that for the same orthopedic intensity, whether the subject is walking on a treadmill or turning over in bed, the output signal remains consistent. The numerical values ​​remained highly consistent. This method completely solved the persistent clinical problem of "accurate static data but unusable dynamic data." By removing the "self-weight load," the corrective force truly reflects the active pushing effect of the brace's physical structure on the deformed vertebrae.

[0107] Obtain the "dynamic effective corrective force signal" stripped of inertial noise and positional artifacts. Afterwards, processor 14 executes the following real-time warning and safety evaluation logic, aiming to transform the "clean data signal" into a "clinical intervention instruction." This step addresses two common extreme problems in brace wearing by introducing a "clinical safety threshold envelope": one is skin pressure sores or tissue damage caused by excessive pressure (overcorrection), and the other is orthodontic failure caused by insufficient pressure (undercorrection). Optionally, the method also includes a real-time warning step, such as... Figure 6 As shown, the specific steps include S81-S83: Step S81: Based on the real-time body posture category, retrieve the corresponding clinical safety threshold envelope from the preset clinical prescription database; The clinical safety threshold envelope defines the dynamic range of the corrective force amplitude allowed for a subject in the current posture, including the maximum and minimum boundary values ​​of the corrective force.

[0108] The processor 14 uses the "real-time body pose category" determined in step S63 as an index to retrieve a matching safety threshold envelope from a preset clinical prescription library.

[0109] The human body's tolerance to pressure varies significantly depending on its posture. For example, in a "vertical posture" (standing), the muscles beside the spine are in an active contraction state and can withstand higher corrective forces; while in a "horizontal posture" (sleeping), the muscles are relaxed, and the skin is in prolonged contact with the brace, making it easy for high pressure to cause insufficient blood supply and pressure sores.

[0110] Envelope definition: The envelope is not a single value, but a set of upper and lower bounds that dynamically adjust with body position. .

[0111] (Safety Limit): Defines the red line of pressure to prevent tissue damage.

[0112] (Effective lower limit): Defines the minimum initiating force required to ensure that the orthopedic movement occurs.

[0113] Step S82: Compare the real-time amplitude of the dynamic effective corrective force signal with the boundary value of the clinical safety threshold envelope, extract the offset vector of the real-time amplitude from the boundary value, and accumulate the overflow duration of the offset vector in the time dimension. Processor 14 will collect data in real time. Perform nanosecond-level alignment with the envelope boundary and execute the following numerical processing: like Extract positive offset This represents "overpressure risk".

[0114] like Extract negative offset , representing "risk of correction failure".

[0115] Processor 14 starts the internal accumulator and records. Continuous time outside the envelope window This step illustrates the biomechanical effect of "dose-time": a momentary high-pressure shock may not cause damage, but a slight overpressure lasting for several hours is a key factor in causing tissue necrosis.

[0116] Step S83: When the amplitude of the offset vector reaches the preset damage threshold, or the overflow duration exceeds the preset physiological tolerance cycle, the current treatment state is determined to be abnormal, and a feedback control signal is generated based on the abnormality determination result.

[0117] Processor 14 determines whether the current orthodontic status is abnormal based on the following dual-criteria logic: Criterion 1: Instantaneous Damage Judgment (Amplitude Criterion) When the offset vector The absolute value reaches the preset damage threshold (e.g., exceeding the standard). When the above conditions are met, it is determined that acute tissue compression may occur, and a high-level warning is immediately triggered.

[0118] Criterion 2: Physiological Tolerance Assessment (Time Criterion) When the offset does not reach the damage threshold, but its overflow duration... If the physiological tolerance period is exceeded (e.g., continuous overpressure for more than 2 hours, or continuous underpressure for more than 4 hours), it is judged as a long-term chronic wear abnormality.

[0119] Once an anomaly is detected, processor 14 generates differentiated feedback signals based on the anomaly category: In response to "overpressure abnormality": a "pressure overload reminder" is sent to the user terminal via the wireless communication module, prompting the subject to loosen the straps or change position to prevent pressure sores.

[0120] Regarding "underpressure abnormality": This indicates "insufficient corrective force." It is recommended to tighten the straps or check if the brace has slipped off.

[0121] Regarding "structural failure": If multiple points simultaneously detach from the envelope and cannot recover on their own through body position, a "clinical follow-up suggestion" is generated, indicating that the brace may no longer be suitable for the body type at the current developmental stage.

[0122] This embodiment achieves a leap from "blind wearing" to "precise quantitative orthodontic treatment" through three-dimensional monitoring of "position-prescription-time". Its technological advancement lies in the fact that it not only focuses on "the magnitude of the force", but also on "the rationality of the force in a specific position" and "the duration of the force", fundamentally reducing the risk of complications from brace wearing and improving treatment compliance.

[0123] In practical applications, subjects (such as adolescent AIS patients) need to wear the device 24 / 7, inevitably experiencing physical blockages or connection interruptions in the communication link (such as Bluetooth BLE, Wi-Fi, or NB-IoT). To ensure the continuity of clinical treatment data, this application adds a communication module to the device, and the processor 14 executes the following breakpoint resume logic: When the processor 14 detects that the communication module is in a disconnected state (such as when the subject is far away from the mobile phone or in a no-signal area), the processor 14 does not discard the current monitoring results, but instead calculates and outputs the dynamic effective corrective force signal. The data is linked to real-time timestamps and stored in storage module 13 in chronological order. This "black box" storage ensures that orthopedic pressure data for each time period is traceable.

[0124] During offline periods, the processor 14 automatically polls the link status of the communication module at a preset frequency (e.g., once every 30 seconds). Once the link is detected to be restored, the processor 14 immediately locks the historical data breakpoints accumulated in the storage module 13.

[0125] After the connection is restored, processor 14 synchronizes data to the remote server using the following priority strategy: High priority: Real-time generated dynamic and effective corrective force signals occupy bandwidth for transmission first, ensuring that doctors or parents can see the current monitoring values ​​immediately. Low priority: When bandwidth is redundant, processor 14 extracts backlogged historical data from storage module 13 and smoothly retransmits it to the server in chronological order.

[0126] Through the above logic, this device achieves the effect of "uninterrupted real-time monitoring and traceable historical data". Even if the connection is lost when the subject is outdoors or sleeping, the missing data segments can be automatically "stitched up" after reconnection, providing a complete panoramic view of corrective force for clinical assessment.

[0127] To extend the device's battery life, the processor 14 performs dynamic power consumption adjustment based on the subject's real-time activity intensity: The processor 14 extracts the acceleration signal output by the motion sensing module 12 and calculates statistical characteristics (such as standard deviation or amplitude fluctuation range) within a preset window (such as 2 seconds).

[0128] Comparison and judgment: Processor 14 compares this feature with a preset activity threshold: If the value is below the threshold, the subject is determined to be in a resting state (such as sleeping or sitting). If the value is higher than the threshold, the subject is determined to be in a state of motion (such as walking or exercising).

[0129] When the system is determined to be in a resting state, the interface pressure changes slowly, and the processor 14 performs a power-saving operation: frequency reduction sampling: the pressure sampling frequency of the interactive sensing module 11 is lowered (e.g., from 50Hz to 2Hz). Channel shutdown: the high-frequency data channel of the motion sensing module 12 is shut down (e.g., the gyroscope is stopped), and only basic acceleration monitoring is retained.

[0130] Once the subject begins to move, the processor 14 immediately detects acceleration fluctuations and resumes full data sampling. At this point, the device operates at full speed to ensure that the dynamic decoupling algorithm can accurately capture instantaneous pressure changes during movement. Through this logic, the device significantly reduces ineffective energy consumption during the patient's resting period while maintaining monitoring accuracy, effectively extending the lifespan of a single charge.

[0131] Each module in the aforementioned scoliosis correction monitoring device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor 14 within the scoliosis correction brace, or stored in the memory of the scoliosis correction brace as software, so that the processor 14 can call and execute the corresponding operations of each module.

[0132] In one embodiment, a computer-readable storage medium is provided having a computer program stored thereon, which determines that the above-described scoliosis correction monitoring method is implemented when the computer program is executed by processor 14.

[0133] In one embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described scoliosis correction monitoring method.

[0134] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile deterministic machine-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, artificial intelligence (AI) processors, etc., and are not limited to these.

[0135] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0136] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A method for monitoring scoliosis correction, characterized in that, The method includes: Acquire the acceleration signal generated by the orthotic brace as the subject moves, as well as the original pressure signal at the interface sensing point corresponding to the spinal deformity site; In the time domain, identify motion feature points in the acceleration signal that characterize the moment of impact, and use the motion feature points as starting points to search for and match response feature points in the original pressure signal within a preset time window; calculate the time difference between the motion feature points and the response feature points, and construct a phase hysteresis function with respect to the motion frequency based on the time difference to determine the interface delay parameter caused by the viscoelasticity of soft tissue; Extract the instantaneous evolution trend of the compression rate from the original pressure signal, and use the interface delay parameter as the gain weight to superimpose the prediction compensation amount driven by the instantaneous evolution trend on the original pressure signal to generate a reconstructed pressure signal that is phase-aligned with the motion feature point. The acceleration signal is mapped to the force normal direction of the interface sensing point to obtain the normal motion acceleration that characterizes the real-time motion state of the sensor; combined with the local inertial response characteristics that characterize the inertial mass distribution of the sensor component and are pre-stored at the interface sensing point, the real-time inertial force component generated by the normal motion acceleration at the pressure sensing end is calculated. The real-time inertial force component is vector-stripped from the reconstructed pressure signal to output a dynamic and effective corrective force signal that reflects the actual force state of the spinal deformity site.

2. The method according to claim 1, characterized in that, The inertial characteristic coefficients pre-stored at the interface sensing points are pre-configured in the following manner: When the orthotic brace is in an off-position state and not being worn, an excitation load simulating the human body movement frequency is applied to the orthotic brace, and the pressure fluctuation and motion acceleration measurement at the interface sensing point are recorded. Establish the proportional relationship between the pressure fluctuation and the motion acceleration measurement, and define the proportional relationship as the inertial characteristic coefficient corresponding to the interface sensing point.

3. The method according to claim 1, characterized in that, The extraction of the instantaneous evolution trend of the extrusion rate from the original pressure signal specifically includes: By performing real-time differential or derivative operations on the original pressure signal, the instantaneous rate of change reflecting the speed of change of the original pressure signal value is obtained, and this instantaneous rate of change is used as the instantaneous evolution trend. Specifically, the step of using the interface delay parameter as a gain weight to superimpose a prediction compensation amount driven by the instantaneous evolution trend onto the original pressure signal to generate a reconstructed pressure signal aligned with the phase of the motion feature point includes: The instantaneous amplitude of the predicted compensation amount is determined by multiplying the interface delay parameter with the instantaneous rate of change. The instantaneous amplitude is superimposed on the current sampled value of the original pressure signal in real time to generate a reconstructed pressure signal that is phase-aligned with the motion feature point.

4. The method according to claim 1, characterized in that, The method also includes the following gait association evaluation steps: The fundamental frequency component in the motion acceleration signal is identified by using spectrum analysis or autocorrelation calculation. When the fundamental frequency component is within a preset gait frequency range, it is determined that the subject is in a walking state, and the time switching boundary between the impact phase and the steady phase within a single gait cycle is locked. The dynamic effective corrective force signal is divided into time domains using the time switching boundary to obtain the impact force signal segment corresponding to the impact and the steady force signal segment corresponding to the steady state. Extract the peak force value representing the instantaneous compressive strength from the impact force signal segment, and extract the average force value representing the foundation support strength from the steady force signal segment; Calculate the discrete characteristic quantities of the peak force value and the mean force value within multiple consecutive gait cycles, and evaluate the degree of interface slippage or wearing stability of the orthotic brace during dynamic processes based on the comparison results of the discrete characteristic quantities and the preset stability threshold.

5. The method according to claim 1, characterized in that, The step of vector-stripping the real-time inertial force component from the reconstructed pressure signal and outputting a dynamic and effective corrective force signal reflecting the true stress state of the spinal deformity site specifically includes: The real-time inertial force component is vector-stripped from the reconstructed pressure signal to output an initial effective corrective force signal that reflects the true stress state of the spinal deformity site. The constant gravitational acceleration component, which characterizes the gravity vector, is separated from the motion acceleration signal by low-pass filtering. Based on the projection amplitude of the constant gravitational acceleration component on the three axes of the support coordinate system, the tilt angle vector reflecting the spatial tilt state of the support is calculated. The real-time body posture category of the subject is determined by using the range of values ​​of the tilt vector; Based on the identified real-time posture category, the static pressure bias that matches the category is retrieved from the preset posture-pressure database and used as the correction benchmark for the non-corrective pressure component under that posture. Subtract the static pressure bias from the initial effective corrective force signal to output a dynamic effective corrective force signal that reflects the actual force state of the spinal deformity site.

6. The method according to claim 5, characterized in that, The method also includes a real-time early warning step, specifically including: Based on the real-time body posture category, the corresponding clinical safety threshold envelope is retrieved from the preset clinical prescription library; the clinical safety threshold envelope defines the dynamic range of the corrective force amplitude allowed for the subject in the current body posture, including the maximum boundary value and the minimum boundary value of the corrective force. The real-time amplitude of the dynamic effective corrective force signal is compared with the boundary value of the clinical safety threshold envelope. The offset vector of the real-time amplitude deviating from the boundary value is extracted, and the overflow duration of the offset vector in the time dimension is accumulated. When the amplitude of the offset vector reaches a preset damage threshold, or the overflow duration exceeds a preset physiological tolerance cycle, the current treatment state is determined to be abnormal, and a feedback control signal is generated based on the abnormality determination result.

7. A scoliosis correction monitoring device, characterized in that, The device includes: Pressure sensing module: Located at the interface sensing point of the orthotic brace, it is used to collect the original pressure signal corresponding to the spinal deformity site; Motion sensing module: rigidly fixed to the orthotic brace, used to acquire the acceleration signal generated by the orthotic brace as the subject moves; Storage module: Used to store local inertial response characteristics that characterize the inertial mass distribution of sensor components; Processor: Connected to the pressure sensing module, the motion sensing module and the storage module respectively, and configured to execute the method steps as described in any one of claims 1-6.

8. The apparatus according to claim 7, characterized in that, The device further includes a communication module; the processor executes data breakpoint resume logic, including: When the communication module is in a disconnected state, the dynamic effective corrective force signal is stored in the storage module in the order of timestamp index; The link status of the communication module is polled in real time, and when the link is detected to be restored, the backlogged historical data is extracted from the storage module. The historical data and the dynamically generated effective corrective force signal are synchronized to the remote server according to the bandwidth allocation priority.

9. The apparatus according to claim 7, characterized in that, The processor executes power consumption regulation logic, including: Calculate the statistical characteristics of the acceleration signal within a preset window, and classify the subject's motion state into a resting state or a motion state based on the comparison results of the statistical characteristics and the activity threshold. In the resting state, the sampling frequency of the pressure sensing module is reduced and the high-frequency sampling channel of the motion sensing module is turned off; Under the aforementioned motion state, the full data sampling frequency is restored.

10. A scoliosis correction brace, characterized in that, include: The brace body, and the scoliosis correction monitoring device as described in any one of claims 7-9 mounted on the brace body.

Images