A method and system for three-dimensional mechanical property acquisition and analysis based on pressure gradient

Abstract

The application relates to a three-dimensional mechanical characteristic acquisition and analysis method and system based on a pressure gradient, which comprises a mechanical sensing module, a motion capture module and a data processing and control module. The motion capture module and the mechanical sensing module are unified in time sequence, an operator wears a thumb matrix sensing finger sleeve on each hand, and a patient performs a sitting position knee adjusting manipulation under the motion capture module. The force size and direction of the sitting position knee adjusting manipulation under different knee joint flexion angles are collected, the pressure gradient change is obtained by using a Gaussian pressure plane reconstruction, the three-dimensional mechanical characteristics of in-vivo manipulation are measured, and the three-dimensional mechanical characteristic analysis of in-vivo manipulation is realized. Compared with the prior art, the application has the advantages of strong noise resistance, clear physical meaning, stable result, direct analysis of three-dimensional force direction of manipulation, in-vivo, real-time, non-destructive quantification, manipulation standardization and the like in a clinical environment.

Description

Technical Field

[0001] This invention relates to the field of quantitative analysis of traditional Chinese massage techniques and medical equipment technology, and in particular to a method and system for acquiring and analyzing the three-dimensional mechanical features of massage techniques based on pressure gradients. Background Technology

[0002] The prevalence of knee osteoarthritis (KOA) increases annually with patient age, primarily manifesting as knee pain and impaired joint flexion and extension, severely impacting patients' quality of life and increasing the socioeconomic burden. 61.5% of guidelines recommend manual therapy as an adjunct intervention, demonstrating its definite clinical efficacy in treating KOA. The seated knee adjustment technique, a legacy and innovation of the Ding's Massage school, has accumulated rich clinical research evidence and is widely used, exhibiting significant immediate clinical efficacy. Therefore, analyzing the seated knee adjustment technique allows for its widespread application in clinical and teaching settings, facilitating standardized research into this technique.

[0003] In research on the standardization of massage techniques, instruments such as massage technique testing devices, three-dimensional motion analysis systems, glove dynamic pressure distribution measurement systems, and wireless surface electromyography can be used for data acquisition. However, these devices cannot solve the problem of quantifying the direction of the manipulation, even though the normal force (i.e., the magnitude of the vertical force) can be measured in vivo. Currently available sensors cannot obtain directional data of the manipulation force. The limitations of existing technologies result in incomplete descriptions of the mechanical characteristics of massage techniques, hindering their objective evaluation and standardized transmission.

[0004] Chinese invention patent CN119312083A discloses a pressure mapping method and apparatus for a high-precision pressure sensor array, comprising: applying a known standard pressure to the high-precision pressure sensor array and acquiring the original pressure distribution matrix of each sensing unit; performing bicubic spline interpolation with tension coefficient compensation to obtain a continuous pressure distribution matrix; inputting a depthwise separable convolutional network for spatial feature extraction and channel feature fusion to obtain a pressure feature description matrix; performing confidence propagation iterative calculation to obtain a pressure confidence matrix; performing reliability grouping and weight coefficient calculation on the sensing units to obtain a pressure data fusion weight matrix; calculating the pressure center position and pressure gradient distribution, and outputting target pressure mapping data. The invention improves pressure mapping accuracy, reduces computational complexity, and ensures high real-time performance. However, it still suffers from problems such as high noise and unstable reconstruction results in traditional interpolation methods for thin-film pressure arrays, the inability of traditional equipment to quantify the three-dimensional direction of force applied by massage techniques, difficulty in in vivo standardization, and interference with clinical measurement operations.

[0005] In summary, there is currently a lack of a method and system for acquiring and analyzing three-dimensional mechanical features based on pressure gradients to solve or partially solve the above problems. Summary of the Invention

[0006] The purpose of this invention is to overcome the shortcomings of the existing technology by providing a method and system for acquiring and analyzing three-dimensional mechanical features of massage techniques based on pressure gradients. This addresses or partially addresses the problems of high noise and unstable reconstruction results in traditional interpolation methods using thin-film pressure arrays, the inability of traditional equipment to quantify and measure the three-dimensional direction of force applied by massage techniques, and the difficulty in in vivo standardization and interference with clinical measurements.

[0007] The objective of this invention can be achieved through the following technical solutions: According to one aspect of the present invention, a method for acquiring and analyzing three-dimensional mechanical features based on pressure gradients is provided, specifically including: S1. Establish a two-dimensional rectangular coordinate system based on the center-to-center spacing of the target pressure array, define the physical coordinates of the manual pressure array, obtain the measured pressure value on the physical coordinates of each manual pressure array, and preprocess the measured pressure value. S2. Based on the preprocessed measured pressure values, construct an objective function with the goal of minimizing the sum of squared residuals; S3. Initialize the parameters of the constructed objective function, iteratively solve the objective function using a nonlinear least squares algorithm until the sum of squared residuals converges, obtain the optimal parameters, and verify the effectiveness of the optimal parameters; S4. Substitute the optimal parameters into the Gaussian plane formula to reconstruct the Gaussian pressure plane, generate a continuous pressure distribution plane, and obtain manual pressure gradient information; S5. Based on the obtained pressure gradient information of the manipulation technique, calculate the three-dimensional mechanical characteristics of the manipulation technique, which include the pressure center and tangential force, thereby realizing the acquisition and analysis of the three-dimensional mechanical characteristics of the manipulation technique based on the pressure gradient.

[0008] As a preferred technical solution, the preprocessing includes removing outliers and eliminating zero drift from the obtained measured pressure values.

[0009] As a preferred technical solution, the objective function is expressed as follows: in, For the sum of squared residuals, The amplitude is a Gaussian distribution. The coordinates of the center of the Gaussian distribution are: The standard deviation is a Gaussian distribution. For base pressure, For the first Measured pressure values ​​on the physical coordinates of each pressure element. The x-coordinate of the physical coordinates of the pressure array. The vertical axis represents the physical coordinates of the pressure array. This represents the number of pressure array elements.

[0010] As a preferred technical solution, the parameter initialization includes determining the initial value of each parameter based on the maximum pressure point of the measured pressure value.

[0011] As a preferred technical solution, the validity verification includes verifying that the obtained parameters are within a preset parameter range.

[0012] As a preferred technical solution, the optimal parameters include the amplitude of the Gaussian distribution, the coordinates of the center of the Gaussian distribution, the standard deviation of the Gaussian distribution, and the base pressure.

[0013] As a preferred technical solution, the Gaussian pressure plane reconstruction obtains the pressure values ​​of each coordinate within the physical coordinate range of the manual pressure array through gridded calculation, thereby completing the transition from discrete points to a continuous plane and generating a continuous pressure distribution plane.

[0014] As a preferred technical solution, the pressure center coordinates are obtained by fitting an objective function, the torque of the pressure center is calculated based on the torque balance of the Gaussian pressure plane, and the tangential force is calculated by combining the collected material elastic layer thickness.

[0015] According to another aspect of the present invention, a system for acquiring and analyzing three-dimensional mechanical features based on pressure gradient is provided. The system is used to execute the aforementioned method for acquiring and analyzing three-dimensional mechanical features based on pressure gradient. The system includes a mechanical sensing module, a motion capture module, and a data processing and control module. The mechanical sensing module is installed on a matrix-type flexible thin-film pressure sensor finger sleeve that can be worn on the operator's thumb. The sensing area of ​​each finger sleeve forms a pressure point matrix, which is used to collect two-dimensional pressure distribution data of the contact surface with the patient's body surface in real time during the manipulation. The motion capture module is used to capture and record the movement trajectory and posture data of the operator's thumb and / or the patient's knee joint in three-dimensional space in real time. The data processing and control module is used to solve for the optimal model parameters by minimizing the residual between the measured values ​​and the model prediction values ​​using the least squares method based on a two-dimensional Gaussian distribution model, thereby obtaining a continuous pressure distribution plane reconstructed from the Gaussian pressure plane.

[0016] As a preferred technical solution, the system also includes a real-time visualization interface and a storage module. The real-time visualization interface displays the thumb movement trajectory and the real-time updated three-dimensional force vector, and the storage module stores the raw data and analysis results in the database in a time-synchronized manner for subsequent offline analysis.

[0017] Compared with the prior art, the present invention has at least one of the following beneficial effects: (1) This invention uses a two-dimensional Gaussian distribution that conforms to the physical laws of elastic contact as the basic model, minimizes the residual between the measured value and the model prediction value by the least squares method, solves the optimal model parameters, and realizes the reconstruction from discrete pressure points to a continuous Gaussian plane. This solves the problems of high noise and unstable reconstruction results of traditional interpolation method for thin film pressure arrays, and realizes high-precision reconstruction from discrete pressure points to a continuous pressure plane. It has strong noise resistance, clear physical meaning, stable results, and can be adapted to low-resolution arrays.

[0018] (2) This invention analyzes the pressure gradient field obtained by analyzing the two-dimensional pressure distribution data collected by the matrix pressure sensor, analyzes the three-dimensional direction of the force applied by the massage technique, and uses the physical property that the pressure gradient vector naturally points to the direction of the fastest increase in pressure as the key mathematical physical quantity for inverting the direction of the lateral force and resultant force of the massage technique. This solves the problem that traditional equipment cannot quantify and measure the three-dimensional direction of the force applied by the massage technique, and realizes the technical effect of directly analyzing the three-dimensional force direction of the massage technique.

[0019] (3) This invention constructs a complete three-dimensional mechanical feature acquisition and analysis system for manual techniques by constructing a system that can synchronously record the dynamic changes of three-dimensional force vectors, pressure distribution and joint movement angles under manual operation, and constructs a complete three-dimensional force feature time curve of knee joint flexion angle. It can be operated in real clinical environment in vivo and in real time without interfering with the normal manual procedure. It solves the problem that traditional Chinese massage techniques are difficult to standardize in vivo and that clinical measurement interferes with operation. It achieves the technical effect of in vivo, real-time, non-destructive quantification and manual standardization in clinical environment. Attached Figure Description

[0020] Figure 1 This is a flowchart of the method of the present invention. Detailed Implementation

[0021] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0022] Example 1 To address the problems existing in the aforementioned prior art, this embodiment provides a method for acquiring and analyzing three-dimensional mechanical features based on pressure gradients, such as... Figure 1 As shown, it specifically includes: S1. Establish a two-dimensional rectangular coordinate system based on the center-to-center spacing of the target pressure array, define the physical coordinates of the manual pressure array, obtain the measured pressure value on the physical coordinates of each manual pressure array, and preprocess the measured pressure value.

[0023] For a 5×3 thin-film pressure array, a two-dimensional rectangular coordinate system is established based on the center-to-center spacing of the units, with the center-to-center spacing set to 4mm, to define the physical coordinates of each sensor unit. , ),in 1, 2, 3, 1, 2, 3, 4, 5 correspond to AO units.

[0024] The measured pressure values ​​on the physical coordinates of each pressure array are preprocessed to remove outliers, such as extreme values ​​exceeding the sensor's range, and to eliminate zero drift, such as by subtracting the baseline value when there is no pressure, thus obtaining the effective measured pressure values. ,in 1,2,…,15.

[0025] S2. Based on the preprocessed measured pressure values, construct an objective function with the goal of minimizing the sum of squared residuals.

[0026] in, For the sum of squared residuals, The amplitude is a Gaussian distribution. The coordinates of the center of the Gaussian distribution are: The standard deviation is a Gaussian distribution. For base pressure, For the first Measured pressure values ​​on the physical coordinates of each pressure element. The x-coordinate of the physical coordinates of the pressure array. The vertical axis represents the physical coordinates of the pressure array. The number of pressure array elements needs to be minimized. In order to find the optimal parameters.

[0027] S3. Initialize the parameters of the constructed objective function, use a nonlinear least squares algorithm to iteratively solve the objective function until the sum of squared residuals converges, obtain the optimal parameters, and verify the effectiveness of the optimal parameters.

[0028] The initial value is initially determined based on the maximum pressure point from the measured data, such as... Take the coordinates of the element with the maximum pressure. Take the maximum pressure value. Take 1-2 times the spacing between array cells. Take the minimum measured pressure value.

[0029] Nonlinear least squares algorithms, such as the Levenberg-Marquardt algorithm and the LM algorithm, are used to iteratively solve the objective function until the sum of squared residuals is reached. Convergence, such as The change is less than 10 -6 ), to obtain the optimal parameters ( , , , , ).

[0030] The optimal parameters are validated for effectiveness. Within a reasonable range, such as 1-10mm, >0 ensures that the fitting results conform to physical meaning.

[0031] S4. Substitute the optimal parameters into the Gaussian plane formula to reconstruct the Gaussian pressure plane, generate a continuous pressure distribution plane, and obtain the manual pressure gradient information.

[0032] By performing gridded calculations, such as calculations with a step size of 0.1 mm, the pressure value at any coordinate within the array range can be obtained, thus completing the transition from discrete points to a continuous plane and generating a continuous pressure distribution plane.

[0033] S5. Based on the obtained pressure gradient information of the manipulation technique, calculate the three-dimensional mechanical characteristics of the manipulation technique. The three-dimensional mechanical characteristics of the manipulation technique include the pressure center and tangential force, realizing the acquisition and analysis of the three-dimensional mechanical characteristics of the manipulation technique based on the pressure gradient.

[0034] Obtained by fitting the objective function This provides stable pressure center coordinates, avoiding the noise interference problem of traditional weighted average COP. Based on the moment balance of the Gaussian pressure plane, the moment about the pressure center is calculated. , Combined with the thickness of the elastic layer of the collected material Tangential force is obtained: ， in, , .

[0035] Ultimately, a method for acquiring and analyzing three-dimensional mechanical features based on pressure gradients was achieved.

[0036] Example 2 In view of the aforementioned embodiment of the method for acquiring and analyzing three-dimensional mechanical features based on pressure gradient, this embodiment provides a system for acquiring and analyzing three-dimensional mechanical features based on pressure gradient, used to execute the aforementioned method for acquiring and analyzing three-dimensional mechanical features based on pressure gradient. The system includes a mechanical sensing module, a motion capture module, a data processing and control module, and dedicated analysis software.

[0037] 1. The mechanical sensing module is installed on a matrix-type flexible thin-film pressure sensor finger sleeve that can be worn on the operator's thumb. Each finger sleeve has a 3-row × 5-column flexible thin-film pressure sensor matrix, which is used to collect two-dimensional pressure distribution data of the contact surface with the patient's body surface in real time during the manipulation.

[0038] The pressure sensor matrix consists of 15 independent sensing units. The middle units are spaced 1mm apart and are composed of 3×3mm squares; the top and bottom sensing units are composed of 5×3mm rectangles and two irregularly shaped fan-shaped units. The overall effective sensing area is approximately 27mm×15mm, which can completely cover the main contact surface of an adult's thumb pad.

[0039] Each sensing unit has a range of 0-100N and a resolution of ≤0.1N. The overall sampling baud rate for the finger sleeve is 9600, 19200, 38400, 57600, 74800, 115200, and 230400, with a default sampling baud rate of 115200 to ensure stable and real-time uploading of pressure data to the data processing and control module, meeting the requirements for dynamic feature acquisition of manipulation techniques. It communicates with the data processing and control module via Bluetooth and has a continuous working time of ≥4 hours.

[0040] The pressure matrix sensor's outer casing is composed of an adhesive PE film. The subject first wears a finger cot, then the PE film is adhered to the finger cot to fit the operator's thumb. The receiver box is secured to the wrist with a strap. The raw voltage signal is acquired by a 24-bit analog-to-digital converter (ADC) built into the finger cot and transmitted via Bluetooth to the data processing and control module. The host driver software first converts the voltage value into a pressure value (unit: N) and reconstructs it into a pressure matrix P(t) for each frame according to a 5×3 spatial arrangement.

[0041] 2. The motion capture module employs a high-precision motion capture system based on infrared optics principles. This includes 19 infrared cameras (100Hz sampling frequency), 4 planar force platforms (1000Hz sampling frequency), an 80-channel digital-to-analog converter, 2 HD high-speed cameras, and computer systems such as Cortex 5.5.0 data acquisition software and Visual3D biomechanical analysis software.

[0042] Optical reflective markers are applied around the patient's knee joint to calculate the knee flexion angle in real time.

[0043] The motion capture module generates a TTL pulse signal as a global synchronization clock source, which is directly connected to the data acquisition card of the data processing and control module, simultaneously triggering the acquisition frame of pressure data. All data streams are tagged with microsecond-level timestamps based on this hardware clock. During data processing, precise matching is performed using these timestamps to ensure strict synchronization between mechanical and motion data.

[0044] In the motion capture module, to overcome the shortcomings of conventional gait analysis marker point schemes, which are only applicable to walking and cannot be coupled with manual biomechanical characteristics in real time, this invention designs a manual-guided lower limb marker point layout and a real-time knee flexion angle calculation method, specifically tailored to the characteristics of in-vivo manipulation of seated knee adjustment techniques. Specifically, the marker points are not simply applied using the complete marker set from gait analysis. Instead, after biomechanical transmission path analysis and redundant point removal, only anatomical locations strongly correlated with the knee flexion angle during manual force application are selected, including the affected side anterior superior iliac spine, the lateral knee joint point, the tibial tuberosity, and the ankle joint. This reduces computational complexity and improves the specificity of angle measurements.

[0045] In the angle calculation process, the thigh vector is first constructed based on the global three-dimensional coordinates of the aforementioned marked points. With calf vector Then, the two vectors are projected onto the sagittal plane, ignoring the frontal axis component to eliminate non-sagittal plane oscillation interference that may occur during the manipulation, and the angle between the projected vectors is calculated: in, This represents a two-dimensional vector projected onto the sagittal plane from the thigh vector. This represents the two-dimensional vector projected onto the sagittal plane from the lower leg vector, and the thigh vector... The vector representing the direction from the anterior superior iliac spine to the lateral aspect of the knee joint, representing the lower leg vector. This represents the vector pointing from the outer side of the knee joint to the ankle joint.

[0046] To suppress high-frequency noise caused by patient muscle tremors or skin artifacts, a Kalman filter was used to smooth the original angle sequence in real time, resulting in θfiltered. Before each manipulation, the patient's knee joint was passively fully extended, and the angle at this point was recorded as the zero offset θoffset. The real-time flexion angle is then: θ(t) = θfiltered(t) - θoffset All angle data are timestamped to the microsecond level via TTL pulses from the motion capture system and strictly synchronized with each frame of data acquired by the pressure array, thereby constructing an angle-mechanical characteristic coupling curve with the knee flexion angle as the abscissa and the pressure center trajectory and tangential force as the ordinate. This method not only achieves in vivo, real-time analysis of joint angles during manual manipulation but also provides a synchronous spatiotemporal benchmark for subsequent standardized evaluation and quantitative transmission of manual techniques.

[0047] 3. The data processing and control module is implemented using a Gaussian plane model. The Gaussian plane, i.e., a two-dimensional Gaussian distribution, is a classic physical model that conforms to the distribution of elastic contact pressure. Its core expression is: in, coordinates The pressure value at that location, The amplitude is a Gaussian distribution. Centered by the Gaussian distribution Let be the standard deviation of the Gaussian distribution. This is the base pressure.

[0048] 4. Dedicated analysis software includes a real-time visualization interface and data storage management.

[0049] The thumb movement trajectory and the real-time updated 3D force vector are displayed through a 3D scene view. The thumb movement trajectory is represented by a directional arrow, and the real-time updated 3D force vector is represented by a colored arrow. The color and length represent the magnitude of the force.

[0050] All raw data and the parsed results, including 3D force vectors, COP, knee joint angles, and other related data, are stored in the database in a time-synchronized manner. Data is exported to common formats such as CSV and MAT for subsequent offline analysis.

[0051] The overall workflow of the system is as follows: (1) The operator wears matrix sensor finger sleeves on both thumbs, and the patient's knee joint is covered with optical reflective markers.

[0052] (2) Start the system and each module completes self-test and synchronization.

[0053] (3) The operator performs the seated knee adjustment technique, and the system synchronously and continuously collects pressure distribution data and motion trajectory data.

[0054] (4) Data processing is based on the built-in algorithm to calculate and output three-dimensional mechanical characteristic parameters in real time.

[0055] (5) All data is stored synchronously and can be visualized and analyzed in the software interface.

[0056] The above description is merely a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for acquiring and analyzing three-dimensional mechanical features based on pressure gradient, characterized in that, The method includes: S1. Establish a two-dimensional rectangular coordinate system based on the center-to-center spacing of the target pressure array, define the physical coordinates of the manual pressure array, obtain the measured pressure value on the physical coordinates of each manual pressure array, and preprocess the measured pressure value. S2. Based on the preprocessed measured pressure values, construct an objective function with the goal of minimizing the sum of squared residuals; S3. Initialize the parameters of the constructed objective function, iteratively solve the objective function using a nonlinear least squares algorithm until the sum of squared residuals converges, obtain the optimal parameters, and verify the effectiveness of the optimal parameters; S4. Substitute the optimal parameters into the Gaussian plane formula to reconstruct the Gaussian pressure plane, generate a continuous pressure distribution plane, and obtain manual pressure gradient information; S5. Based on the obtained pressure gradient information of the manipulation technique, calculate the three-dimensional mechanical characteristics of the manipulation technique, which include the pressure center and tangential force, thereby realizing the acquisition and analysis of the three-dimensional mechanical characteristics of the manipulation technique based on the pressure gradient.

2. The method for acquiring and analyzing three-dimensional mechanical features based on pressure gradient according to claim 1, characterized in that, The preprocessing includes removing outliers and eliminating zero drift from the obtained measured pressure values.

3. The method for acquiring and analyzing three-dimensional mechanical features based on pressure gradient according to claim 1, characterized in that, The objective function is expressed as follows: in, For the sum of squared residuals, The amplitude is a Gaussian distribution. The coordinates of the center of the Gaussian distribution are: The standard deviation is a Gaussian distribution. For base pressure, For the first Measured pressure values ​​on the physical coordinates of each pressure element. The x-coordinate of the physical coordinates of the pressure array. The vertical axis represents the physical coordinates of the pressure array. This represents the number of pressure array elements.

4. The method for acquiring and analyzing three-dimensional mechanical features based on pressure gradient according to claim 1, characterized in that, The parameter initialization includes determining the initial value of each parameter based on the maximum pressure point of the measured pressure value.

5. The method for acquiring and analyzing three-dimensional mechanical features based on pressure gradient according to claim 4, characterized in that, The validity verification includes checking that the obtained parameters are within a preset parameter range.

6. The method for acquiring and analyzing three-dimensional mechanical features based on pressure gradient according to claim 1, characterized in that, The optimal parameters include the amplitude of the Gaussian distribution, the coordinates of the center of the Gaussian distribution, the standard deviation of the Gaussian distribution, and the base pressure.

7. The method for acquiring and analyzing three-dimensional mechanical features based on pressure gradient according to claim 1, characterized in that, The Gaussian pressure plane reconstruction obtains the pressure values ​​of each coordinate within the physical coordinate range of the manual pressure array through gridded calculation, realizing the completion from discrete points to a continuous plane and generating a continuous pressure distribution plane.

8. The method for acquiring and analyzing three-dimensional mechanical features based on pressure gradient according to claim 1, characterized in that, The coordinates of the pressure center are obtained by fitting the objective function. The torque of the pressure center is calculated based on the torque balance of the Gaussian pressure plane. The tangential force is calculated by combining the collected material elastic layer thickness.

9. A three-dimensional mechanical feature acquisition and analysis system based on pressure gradient, characterized in that, The system is used to execute the pressure gradient-based three-dimensional mechanical feature acquisition and analysis method as described in any one of claims 1-8. The system includes a mechanical sensing module, a motion capture module, and a data processing and control module. The mechanical sensing module is installed on a matrix-type flexible thin-film pressure sensor finger sleeve that can be worn on the operator's thumb. The sensing area of ​​each finger sleeve forms a pressure point matrix, which is used to collect two-dimensional pressure distribution data of the contact surface with the patient's body surface in real time during the manipulation. The motion capture module is used to capture and record the movement trajectory and posture data of the operator's thumb and / or the patient's knee joint in three-dimensional space in real time. The data processing and control module is used to solve for the optimal model parameters by minimizing the residual between the measured values ​​and the model prediction values ​​using the least squares method based on a two-dimensional Gaussian distribution model, thereby obtaining a continuous pressure distribution plane reconstructed from the Gaussian pressure plane.

10. A three-dimensional mechanical feature acquisition and analysis system based on pressure gradient according to claim 9, characterized in that, The system also includes a real-time visualization interface and a storage module. The real-time visualization interface displays the thumb movement trajectory and the real-time updated three-dimensional force vector. The storage module stores the raw data and analysis results in the database in a time-synchronized manner for subsequent offline analysis.

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