A method and device for full-contact intelligent acquisition and analysis of human foot shape

Abstract

The application discloses a human foot type full-contact intelligent acquisition and analysis method and device, which comprises the following steps: making the foot in a preset posture through a supporting and positioning component, starting a multi-air pump assembly to build a gradient negative pressure field, driving a flexible acquisition layer to deform and fit the foot contour, cooperating with the adaptive movement of a two-side bidirectional extrusion module and the elastic buffer layer design, and realizing full-range gapless contact of the foot. The heating module is started to maintain the stable temperature of the contact area, multi-dimensional data are synchronously acquired through pressure, displacement and temperature sensing units, feature extraction and contour reconstruction are performed by a data processing unit after signal conversion and fusion processing. The method and device solve the defects of insufficient contour adhesion and lack of data integrity of traditional technology through multi-technology cooperation, accurately capture key features of the foot, guarantee data comprehensiveness and accuracy, and provide high-precision foot type data support for shoe customization, medical correction and other fields.

Description

Technical Field

[0001] This invention relates to the field of human foot shape acquisition and analysis technology, and in particular to a human foot shape full-contact intelligent acquisition and analysis method and device. Background Technology

[0002] In fields such as footwear customization, medical orthotics, and sports equipment fitting, accurate human foot shape data is the core foundation for achieving product personalization and functionality. With the upgrading of consumption and the development of intelligent manufacturing technology, traditional foot shape acquisition methods such as manual measurement and two-dimensional image scanning are no longer sufficient to meet the needs of efficient, accurate, and comprehensive data acquisition. Existing foot shape acquisition technologies are gradually evolving towards automation and intelligence, but their core requirements remain focused on the comprehensive capture of the foot contour and the accurate reconstruction of data. As a complex three-dimensional curved structure, the foot has multiple key feature points such as arch height, phalanx distribution, and lateral curves. How to achieve the complete acquisition of these features has become a key prerequisite for improving the adaptability and user experience of subsequent products, and it is also driving the technological innovation of related acquisition devices and analysis methods.

[0003] Existing foot data acquisition technologies suffer from two significant drawbacks: Firstly, insufficient contour fit. Most acquisition devices rely solely on negative pressure adsorption or mechanical compression to obtain the foot contour, failing to consider the complexity of the foot's curvature and individual differences. This results in gaps in the fit in localized areas during acquisition, hindering the accurate capture of details such as the arch and toe pads, thus affecting the accuracy of the 3D model reconstruction. Secondly, incomplete data acquisition. Current technologies primarily focus on acquiring single-dimensional contour data, failing to adequately consider the impact of temperature on foot morphology and the acquisition medium. Furthermore, the lack of a collaborative acquisition mechanism for multi-dimensional data such as pressure, displacement, and temperature means that the acquired data cannot fully reflect the true state of the foot during contact with the acquisition device, making it difficult to support subsequent high-precision analysis and model reconstruction. Summary of the Invention

[0004] In order to overcome the shortcomings and deficiencies of the existing technology, the present invention provides a method and device for intelligent acquisition and analysis of human foot shape through full contact.

[0005] The technical solution adopted in this invention is a human foot shape full-contact intelligent acquisition and analysis method, comprising the following steps: S1, supporting and positioning the human foot through a device bearing structure, so that the foot is in a preset acquisition posture, and pressure sensing units that contact the foot are arranged on the surface of the bearing structure; S2, activating multiple air pump components and generating a negative pressure field according to a preset air pressure gradient, the negative pressure field acting on the surface of the foot to deform the flexible acquisition layer to conform to the foot contour, the air pump components being connected to the internal chamber of the flexible acquisition layer through independent pipelines, and each pipeline being equipped with a flow regulating component; S3, controlling the two bidirectional extrusion modules on both sides to move relative to each other in the horizontal direction, the contact end face of the extrusion module being provided with an elastic buffer layer, and through positioning... The displacement adjustment mechanism controls the extrusion stroke and extrusion rate to ensure full contact between the extrusion module and both sides of the foot; S4, the heating module is activated to maintain the flexible acquisition layer and the contact surface of the extrusion module within a preset temperature range. The heating module provides real-time feedback of the contact area temperature data through the temperature sensing unit and adjusts the heating power through closed-loop control logic; S5, the pressure sensing unit, displacement sensing unit, and temperature sensing unit simultaneously collect multi-dimensional data during the foot contact process. The multi-dimensional data is transmitted to the data processing unit via a signal conversion component; S6, the data processing unit performs feature extraction and contour reconstruction on the multi-dimensional data, and constructs a three-dimensional model of the foot based on the contact pressure distribution, deformation displacement, and temperature feedback data.

[0006] Furthermore, the pressure gradient of the negative pressure field in S2 is calculated using the following model: , in, Let be the output air pressure of the i-th air pump at the j-th data collection time. This is the initial air pressure reference value. This is the air pressure fluctuation amplitude coefficient. The angular frequency of air pressure change. This is the phase offset. The attenuation coefficient is... For the time of collection, This represents the pressure regulation order.

[0007] Furthermore, the displacement of the bidirectional extrusion module in S3 satisfies the following model: , in, This represents the actual displacement of the extrusion module at displacement stroke I. The maximum displacement threshold, This is the displacement growth factor. For the extrusion stroke, For displacement adjustment factor, For displacement fluctuation frequency, This represents the number of displacement adjustment terms.

[0008] Furthermore, the power regulation model of the heating module in S4 is as follows: , in, For heating power, The reference power value, This is the difference between the actual temperature and the preset temperature. This is the temperature deviation threshold. This is the power regulation coefficient. The temperature decay coefficient is For power regulation order, This represents the number of factors affecting temperature.

[0009] Furthermore, the fusion model for multidimensional data in S5 is as follows: , in, For the merged data, For stress data, For displacement data, For temperature data, For data weighting coefficients, , For the time derivatives of each data point, This refers to the data collection duration.

[0010] Furthermore, the contour reconstruction model in S6 is as follows: , in, For the coordinates of the 3D model, For model reconstruction coefficients, It is a spatial interpolation function. For spatial coordinates, To reconstruct the number of grid nodes.

[0011] Further, step S3 includes the following sub-steps: S31, the initial position data of the extrusion module is collected by the displacement sensing unit and transmitted to the control unit. The control unit determines the initial motion parameters of the extrusion module based on the contour estimation result after foot support positioning; S32, the control unit sends a drive signal to the displacement adjustment mechanism to make the two extrusion modules move synchronously along the guide rail. The movement is kept at a constant speed in the initial stage of movement, and the movement trajectory is corrected in real time through the position feedback signal; S33, when the elastic buffer layer of the extrusion module initially contacts the side of the foot, the pressure sensing unit triggers a contact signal. After receiving the signal, the control unit adjusts the drive parameters of the displacement adjustment mechanism to reduce the extrusion rate; S34, the displacement of the extrusion module is continuously adjusted until the contact pressure detected by the pressure sensing unit reaches the preset distribution range, and the extrusion module is controlled to maintain the current position to complete the extrusion contact process.

[0012] Further, step S4 includes the following sub-steps: S41, the control unit sends a start signal to the heating module, the heating element of the heating module starts working, and the initial temperature data of the contact end face of the flexible collection layer and the extrusion module is collected by the temperature sensing unit; S42, the initial temperature data is compared with a preset temperature range. If the initial temperature is lower than the lower limit of the range, the control unit increases the heating power. If the initial temperature is higher than the upper limit of the range, the control unit decreases the heating power or stops heating; S43, during the collection process, the temperature sensing unit collects the temperature data of the contact area at fixed time intervals and transmits the data to the control unit in real time. The control unit calculates the temperature deviation through closed-loop control logic; S44, the heating power of the heating module is adjusted based on the temperature deviation so that the temperature of the contact end face of the flexible collection layer and the extrusion module is always maintained within the preset range until the collection process ends.

[0013] Further, step S5 includes the following sub-steps: S51, the pressure sensing unit converts the pressure signal generated by foot contact into an electrical signal, amplifies the electrical signal strength through a signal amplification component, and removes interference components from the signal through a filtering component to obtain standardized pressure data; S52, the displacement sensing unit collects the motion displacement of the extrusion module and the deformation of the flexible acquisition layer in real time, converts the displacement signal into a digital signal, and aligns it with the pressure data in time through a data synchronization component; S53, the temperature sensing unit collects the temperature signal of the contact area, converts it into digital temperature data through an analog-to-digital converter, and corrects the temperature data for errors through a calibration component; S54, the signal conversion component integrates the standardized pressure data, the time-aligned displacement data, and the corrected temperature data into a multi-dimensional data set, and sends it to the data processing unit according to a preset transmission protocol.

[0014] A human foot shape full-contact intelligent acquisition and analysis device is disclosed. This device is applied to a human foot shape full-contact intelligent acquisition and analysis method, comprising: a foot support and positioning support module, a multi-channel negative pressure generation and adjustment module, a bidirectional adaptive compression contact module, a constant temperature control heating module, a multi-dimensional data acquisition and conversion module, and an intelligent data processing and contour reconstruction module. The foot support and positioning support module supports the human foot and defines the acquisition posture. Pressure sensing units are arranged on its surface, and it is directly connected to the multi-channel negative pressure generation and adjustment module and the bidirectional adaptive compression contact module. The multi-channel negative pressure generation and adjustment module includes multiple independent air pump components, flow regulation pipelines, and a negative pressure chamber. It is connected to the flexible acquisition layer of the foot support and positioning support module through pipelines to generate a negative pressure field and adjust the air pressure gradient. The bidirectional adaptive compression contact module is positioned on the foot. The supporting positioning and bearing module consists of two sides, including an elastic buffer contact end face, a displacement adjustment mechanism, and a drive component. It is connected to the control unit via a control line to perform horizontal relative compression movement. The constant temperature control heating module is embedded inside the flexible acquisition layer and the compression contact end face, including a heating element, a temperature sensing unit, and a power adjustment component. It is connected to the closed-loop control unit via a signal line to perform stable temperature control. The multi-dimensional data acquisition and conversion module includes pressure, displacement, and temperature sensing components, as well as signal amplification, filtering, and analog-to-digital conversion components. It is connected to the intelligent data processing and contour reconstruction module via a data bus to perform multi-dimensional data acquisition and standardized conversion. The intelligent data processing and contour reconstruction module includes a data storage unit, a feature extraction component, and a 3D model reconstruction algorithm module. It is connected to other modules via a control line to perform data processing and foot contour reconstruction.

[0015] Beneficial Effects: This invention proposes a fully contact intelligent acquisition and analysis method and device for human foot shape. A gradient negative pressure field is constructed through a multi-pump assembly, coupled with the adaptive movement of bidirectional extrusion modules on both sides, ensuring a seamless, all-around contact between the flexible acquisition layer and the foot surface. The combined design of the elastic buffer layer and displacement adjustment mechanism adapts to different foot curvatures and individual differences, effectively eliminating localized gaps and accurately capturing detailed features such as the arch and toe pads, significantly improving the accuracy of 3D model reconstruction. Simultaneously, a constant-temperature control heating module is introduced to maintain a stable temperature environment in the contact area during acquisition, avoiding the impact of temperature changes on foot shape and the acquisition medium. Through synchronous acquisition and data fusion processing of pressure, displacement, and temperature sensors, a multi-dimensional data collaborative acquisition mechanism is constructed, comprehensively reflecting the real state of the foot during contact with the acquisition device. Each module is linked through closed-loop control logic and intelligent data processing algorithms to achieve automation and precision in the acquisition process. This ensures the comprehensiveness and accuracy of foot shape data while improving acquisition efficiency, providing high-quality data support for personalized footwear customization and promoting the development of foot shape acquisition technology towards higher precision and more comprehensive intelligent dimensions. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating the overall process of the method of the present invention. Figure 2 This is a flowchart of method step S3 of the present invention; Figure 3 This is a flowchart of method step S4 of the present invention; Figure 4 This is a flowchart of step S5 of the method of the present invention; Figure 5 This is a diagram showing the modular composition of the device of the present invention; Figure 6 This is a three-dimensional structural diagram of the device of the present invention. Detailed Implementation

[0017] It should be noted that, unless otherwise specified, the embodiments and features described in this application can be combined with each other. The application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0018] like Figure 1 As shown, a human foot shape full-contact intelligent acquisition and analysis method includes the following steps: S1, the human foot is supported and positioned by a device bearing structure, so that the foot is in a preset acquisition posture, and pressure sensing units that contact the foot are arranged on the surface of the bearing structure; S2, multiple air pump components are activated and a negative pressure field is generated according to a preset air pressure gradient. The negative pressure field acts on the surface of the foot, causing the flexible acquisition layer to deform to conform to the contour of the foot. The air pump components are connected to the internal chamber of the flexible acquisition layer through independent pipelines, and each pipeline is equipped with a flow regulating component; S3, the two bidirectional extrusion modules on both sides are controlled to move relative to each other in the horizontal direction. An elastic buffer layer is set on the contact end face of the extrusion module, and the displacement adjustment mechanism is used to adjust the relative movement of the extrusion modules. S4. Control the extrusion stroke and extrusion rate to ensure full contact between the extrusion module and both sides of the foot; S5. Activate the heating module to maintain the flexible acquisition layer and the contact surface of the extrusion module within a preset temperature range. The heating module provides real-time feedback of the contact area temperature data through the temperature sensing unit and adjusts the heating power through closed-loop control logic; S6. Simultaneously collect multi-dimensional data of the foot contact process through the pressure sensing unit, displacement sensing unit, and temperature sensing unit. The multi-dimensional data is transmitted to the data processing unit via a signal conversion component; S7. The data processing unit performs feature extraction and contour reconstruction on the multi-dimensional data, and constructs a three-dimensional model of the foot based on the contact pressure distribution, deformation displacement, and temperature feedback data.

[0019] Step S1 achieves precise foot support and positioning, laying the foundation for subsequent data collection. During implementation, the operator guides the user to place their foot on the device's support structure. This structure is made of high-strength, lightweight alloy material, with a 3mm thick flexible cushioning pad on its surface. Below the cushioning pad, 320 pressure sensing units are evenly distributed, with a detection accuracy of 0.1 N and a sampling frequency of 100 Hz. The support structure uses adjustable support legs for height and level calibration, with a height adjustment range of 15 to 20 cm and a leveling error controlled within ±0.5 mm. Once the foot is in place, the positioning baffles on both sides of the support structure automatically rise, maintaining a 2cm gap between the baffles and the sides of the foot. Simultaneously, the anti-slip texture on the bottom increases the friction between the foot and the support surface, preventing foot displacement during data collection. The pressure sensing unit detects the contact pressure distribution between the foot and the bearing surface in real time. When the contact pressure reaches 50 to 80 Newtons and the uniformity of the distribution meets the preset threshold, it determines that the foot is in the preset acquisition posture and then sends a positioning completion signal to the control unit. This signal triggers the start command of subsequent steps. This step, through the synergy of mechanical structure and sensor detection, ensures that users with different foot sizes and shapes can obtain a uniform and stable acquisition benchmark, avoiding data distortion caused by posture deviation, and providing a prerequisite guarantee for the accurate implementation of subsequent steps.

[0020] Step S2, which constructs a gradient negative pressure field using multiple air pump assemblies to drive the flexible acquisition layer to deform and conform to the foot contour, is a crucial step in achieving initial foot shape capture. Upon initiation of this step, the control unit sends a start signal to each of the 12 independent air pump assemblies. These assemblies employ miniature oil-free diaphragm air pumps with a rated operating voltage of 24 volts, a maximum output air pressure of 0.8 MPa, and a response time of less than 0.3 seconds. Each air pump is connected to a chamber inside the flexible acquisition layer via an independent 8 mm inner diameter tubing. A flow rate regulating component is connected in series within the tubing, with an adjustment accuracy of 1 ml / s, enabling precise air pressure control. The control unit controls each air pump to increase pressure in stages according to a preset program, forming a gradient negative pressure field. The initial air pressure is set at 0.1 MPa, then increases by 0.05 MPa every 0.2 seconds until the target air pressure range of 0.4 to 0.6 MPa is reached. This gradient pressure increase mode avoids discomfort to the foot caused by instantaneous high pressure. The flexible acquisition layer is made of 5 mm thick silicone material with a Shore hardness of 35. Under the action of a negative pressure field, it can deform up to 10 mm towards the foot. By closely adhering to the surface of the foot, it achieves initial contour capture. The working status of each air pump is monitored in real time by a pressure sensor. When the air pressure fluctuation exceeds ±0.02 MPa, the control unit immediately adjusts the output power of the corresponding air pump to ensure the stability of the negative pressure field. This step, through the coordination of multiple air pumps and gradient air pressure control, achieves initial accurate fit to the foot contour, laying the foundation for subsequent compression and heating processes.

[0021] Step S3 achieves full contact between both sides of the foot through the adaptive movement of the bidirectional extrusion module, further improving the contour fit accuracy. After this step is initiated, the control unit sends drive signals to the bidirectional extrusion modules on both sides. The drive component of the extrusion module uses a servo motor with a rated power of 400 watts and a speed adjustment range of 50 to 300 rpm. This is converted into horizontal linear motion via a ball screw transmission mechanism, achieving a motion accuracy of ±0.01 mm. A 4 mm thick elastic buffer layer made of polyurethane with a Shore hardness of 25 is installed on the contact surface of the extrusion module, allowing for 3 to 5 mm of elastic deformation during extrusion, preventing rigid contact from compressing the foot. Based on the foot width data collected by the pressure sensing unit in step S1, the control unit presets the extrusion stroke to 8 to 25 cm and the initial extrusion rate to 5 mm / s. When the distance between the extrusion module and the side of the foot decreases to 3 cm, the rate automatically drops to 2 mm / s. The displacement sensing unit collects the actual position data of the extrusion module in real time at a sampling frequency of 200 Hz and feeds the data back to the control unit, forming a closed-loop control. When the elastic buffer layer is in full contact with the side of the foot, and the pressure sensor detects a contact pressure of 15 to 25 Newtons, the control unit sends a stop signal, and the compression module maintains its current position. This step, through the combination of servo drive, elastic buffer and closed-loop control, achieves adaptive compression of feet of different widths, ensuring that the sides of the foot fit together without gaps, accurately capturing the side curve features, and making up for the shortcomings of single negative pressure adsorption in side contour acquisition.

[0022] Step S4 maintains a stable temperature in the contact area using a heating module to prevent temperature variations from affecting the acquisition accuracy and improve the fit between the foot and the acquisition component. Upon initiation of this step, the control unit sends a start command to the heating module. The heating module uses a flexible electrothermal film as the heating element, with a total power of 300 watts, distributed within the flexible acquisition layer and on the contact surface of the extrusion module. The heating uniformity error of the electrothermal film is less than ±1℃. The temperature sensing unit uses a thermocouple sensor with 24 detection points evenly distributed across the acquisition area. The detection accuracy is ±0.2℃, and the sampling frequency is 50 Hz. It collects temperature data from the contact area in real time and transmits it to the control unit. The control unit presets a temperature range of 32 to 36℃, which is close to the human body surface temperature. This reduces air gaps caused by temperature differences between the foot and the acquisition component and improves the deformation adaptability of the flexible material. When the detected temperature is below 32℃, the control unit increases the heating power at a rate of 0.5℃ / second; when the temperature is above 36℃, it reduces the heating power or pauses heating, maintaining temperature stability through closed-loop control logic. The heating module operates in conjunction with the negative pressure field and the extrusion module, maintaining a preset temperature range throughout the entire data collection process. This step enhances the fit between the collection medium and the foot through precise temperature control, preventing minor changes in foot shape caused by temperature fluctuations and ensuring the stability and consistency of the collected data.

[0023] Step S5 synchronously collects data through multi-dimensional sensing units, providing comprehensive and accurate raw information for subsequent processing. This is a crucial link connecting acquisition and reconstruction. After this step is initiated, the pressure sensing unit continues to maintain a sampling frequency of 100 Hz, collecting pressure distribution data generated by the contact between the foot and the supporting structure and the compression module. The data range is 0 to 100 N, with a resolution of 0.01 N, accurately capturing pressure differences in different areas such as the arch and toe pad. The displacement sensing unit simultaneously collects the deformation of the flexible acquisition layer and the final displacement data of the compression module. The deformation detection range is 0 to 15 mm, with a displacement resolution of 0.001 mm, completely recording the deformation trajectory during the acquisition process. The temperature sensing unit continuously collects temperature data of the contact area at a frequency of 50 Hz, synchronously recording temperature changes over time. All analog signals collected by the sensing units are converted into digital signals by a signal conversion component, with a conversion accuracy of 16 bits and a sampling delay of less than 0.1 seconds. The signal conversion unit synchronizes and aligns pressure, displacement, and temperature data according to timestamps, with the time synchronization error controlled within ±0.005 seconds. This data is then transmitted to the data processing unit via a high-speed data bus at a transmission rate of 1000 megabits per second. An error control mechanism is employed during data transmission to ensure no data loss or distortion. The data processing unit's cache module has a capacity of 8GB, capable of temporarily storing all multidimensional data acquired in a single session. This step, through multi-parameter synchronous acquisition and high-precision data conversion, comprehensively captures the physical information during foot contact, providing rich and reliable raw data support for subsequent feature extraction and contour reconstruction.

[0024] Step S6, through data processing and contour reconstruction, transforms the multidimensional raw data into a precise three-dimensional foot model, which is the core step in realizing intelligent foot shape analysis. After this step is initiated, the data processing unit first performs signal denoising on the received multidimensional data, using a digital filtering algorithm to remove environmental interference and sensor noise, improving the signal-to-noise ratio of the denoised data to over 40 dB. Subsequently, feature extraction is performed, extracting peak pressure points and pressure gradient changes from the pressure distribution data, maximum deformation and curvature of the flexible acquisition layer from the displacement data, and average temperature and fluctuation amplitude within a stable temperature range from the temperature data, extracting a total of 80 key feature parameters to form a feature vector. Based on the extracted feature parameters, the data processing unit uses a three-dimensional reconstruction algorithm to construct the foot model. During the reconstruction process, the pressure distribution data is used to determine the foot's force contour, the displacement data is used to supplement the three-dimensional spatial morphology, and the temperature data is used to correct errors that may be caused by localized fit gaps. The reconstruction algorithm achieves a mesh generation accuracy of 0.1 mm and a coordinate resolution of 0.01 mm for the 3D model, accurately reconstructing the 3D surface morphology of the foot, including key dimensional parameters such as arch height, phalanx length, and heel width. After model construction, the data processing unit performs geometric verification on the model, including metrics such as contour smoothness and dimensional consistency. Upon successful verification, the final 3D foot model data is generated, which can be stored in a standard 3D file format or directly transmitted to subsequent application systems. This step, through precise data processing and advanced reconstruction algorithms, transforms multi-dimensional physical data into a high-precision 3D model, achieving digital reconstruction of the foot shape and providing directly usable, accurate data results for downstream applications such as footwear customization and medical orthotics.

[0025] Preferably, the pressure gradient of the negative pressure field in S2 is calculated using the following model: , in, Let be the output air pressure of the i-th air pump at the j-th data collection time. This is the initial air pressure reference value. This is the air pressure fluctuation amplitude coefficient. The angular frequency of air pressure change. This is the phase offset. The attenuation coefficient is... For the time of collection, This represents the pressure regulation order.

[0026] Specifically, the air pressure gradient of the negative pressure field is based on the dynamic change law of air pressure caused by the coordinated operation of multiple air pumps. The construction of the negative pressure field needs to balance fit accuracy and foot comfort, simulating the gradient change and decay characteristics of air pressure over time. Therefore, a formula combining sinusoidal fluctuation and exponential decay is adopted. Through experiments, air pressure output data of different air pumps at different times are collected. The analysis shows that the air pressure change includes three parts: a baseline value, periodic fluctuation, and decay trend. Based on the fusion of Fourier series expansion and exponential decay model, a multi-order adjustment composite formula is formed. The initial air pressure baseline value is determined based on foot comfort experiments. The fluctuation amplitude coefficient is set to 0.03 to 0.15 in combination with the deformation requirements of the flexible acquisition layer. The air pressure change angular frequency is set to 0.5 to 3.0 according to the acquisition efficiency requirements. The phase offset is determined to be 0 to π through synchronization calibration of each air pump. The decay coefficient is set to 0.1 to 0.5 based on air pressure stability tests. The acquisition time range is controlled between 2 and 8 seconds. The adjustment order is determined to be 3 to 5 orders through error analysis. During implementation, the control unit calls the formula, initializes the parameters based on the foot positioning data in step S1, receives the air pressure data fed back by the pressure sensor in real time, substitutes it into the formula to calculate the target air pressure value, dynamically adjusts the output power of each air pump, so that the air pressure changes smoothly according to the preset gradient, avoids instantaneous pressure changes, and at the same time compensates for air path loss and environmental interference through multi-stage adjustment to ensure that the negative pressure field accurately fits the foot contour and improves the acquisition accuracy.

[0027] Preferably, the displacement of the bidirectional extrusion module in S3 satisfies the following model: , in, This represents the actual displacement of the extrusion module at displacement stroke I. The maximum displacement threshold, This is the displacement growth factor. For the extrusion stroke, For displacement adjustment factor, For displacement fluctuation frequency, This represents the number of displacement adjustment terms.

[0028] Specifically, the displacement of the bidirectional extrusion module is calculated to meet the adaptive adjustment requirements of the bidirectional extrusion module. Due to individual differences in foot width, the extrusion displacement needs to balance sufficient stroke and smooth movement. Therefore, a formula is established by combining an exponential growth model and a periodic fluctuation factor. First, the maximum displacement threshold is determined through a large amount of foot width data. Based on the growth law of displacement with stroke during extrusion, an exponential function is used to describe the basic growth trend of displacement. Then, a cosine fluctuation term is introduced to compensate for the deformation error of the elastic buffer layer. The two are then fused through a product to form an adaptively adjustable displacement calculation model. The maximum displacement threshold is set to 8 to 25 cm based on statistical data of human foot width. The displacement growth coefficient is determined to be 0.05 to 0.2 through servo motor motion characteristic testing. The displacement adjustment factor is set to 0.01 to 0.08 based on elastic buffer layer deformation experiments. The displacement fluctuation frequency is set to 0.3 to 1.2 according to the extrusion rate requirements. The number of adjustment terms is determined to be 2 to 4 after displacement accuracy verification. During implementation, the control unit first determines the extrusion stroke based on the foot width data collected in step S1, substitutes it into the formula to calculate the target displacement corresponding to different stroke positions, the servo motor drives the extrusion module to move according to the data, the displacement sensing unit collects the actual displacement data in real time and feeds it back, the control unit dynamically corrects the target displacement through the formula, compensates for mechanical transmission errors and elastic deformation effects, ensures that the extrusion module accurately fits the two sides of the foot, and achieves accurate acquisition of the side edge contour.

[0029] Preferably, the power adjustment model of the heating module in S4 is as follows: , in, For heating power, The reference power value, This is the difference between the actual temperature and the preset temperature. This is the temperature deviation threshold. This is the power regulation coefficient. The temperature decay coefficient is For power regulation order, This represents the number of factors affecting temperature.

[0030] Specifically, the power regulation model of the heating module is based on the closed-loop temperature control of the heating module. Because temperature regulation requires rapid response and stability, it must consider the reference power, temperature deviation feedback, and attenuation compensation. Therefore, a polynomial-fractional structure is used to establish the formula. Based on the reference power, the influence of temperature deviation on power is described by a power function term. A temperature attenuation term is introduced into the denominator to compensate for the heat loss of the heating element. The numerator uses a multi-order polynomial to improve the regulation accuracy. The fractional form balances the sensitivity and stability of power regulation, forming the power calculation model required for closed-loop control. The reference power value is determined to be 50 to 300 watts based on the total power of the heating module and the area of ​​the acquisition region. The temperature deviation threshold is set to ±2℃ based on the human comfort temperature range. The power regulation coefficient is determined to be 0.8 to 3.5 through temperature response experiments. The temperature attenuation coefficient is taken from 0.1 to 0.6 based on the thermal characteristics of the heating element. The power regulation order is determined to be 2 to 4 orders after temperature control accuracy verification. The number of temperature-affecting terms is set to 1 to 3. During implementation, the temperature sensing unit collects temperature data of the contact area in real time, the control unit calculates the difference between the actual temperature and the preset range, substitutes it into the formula to calculate the target heating power, and adjusts the working state of the heating element through the power adjustment component. When the temperature is close to the preset upper limit, the attenuation term in the denominator of the formula increases to suppress excessive power output. When the temperature is below the lower limit, the power is increased. Through closed-loop circulation, the temperature is ensured to be stable within the preset range to avoid temperature fluctuations affecting the acquisition accuracy.

[0031] Preferably, the fusion model of the multidimensional data in S5 is as follows: , in, For the merged data, For stress data, For displacement data, For temperature data, For data weighting coefficients, , For the time derivatives of each data point, This refers to the data collection duration.

[0032] Specifically, the multidimensional data fusion model addresses the need for multidimensional data fusion. Since pressure, displacement, and temperature data need to collaboratively reflect the foot contact state, single-dimensional data cannot comprehensively represent the collected information. Therefore, a formula combining linear weighting and integral fusion is adopted. First, the influence weights of the three types of data on contour acquisition are analyzed experimentally using the controlled variable method to determine the basic form of linear weighting. Then, considering the dynamic correlation of data changes over time, a time integral term is introduced to capture data change trends. The static weighting result and the dynamic integral result are fused through addition to form a fused data model that comprehensively reflects the contact state. The pressure data weighting coefficient is determined to be 0.3 to 0.5 through acquisition accuracy experiments; the displacement data weighting coefficient is 0.25 to 0.4; the temperature data weighting coefficient is set to 0.1 to 0.25; and the integral weighting coefficient is determined to be 0.05 to 0.15 based on data time correlation analysis. The acquisition duration is set to 2 to 8 seconds based on the entire acquisition process. During implementation, pressure, displacement, and temperature sensing units simultaneously collect data. The signal conversion component standardizes the data and transmits it to the data processing unit. The processing unit first performs linear weighted calculations on the three types of basic data according to the weighting coefficients in the formula, and then performs product integration on the time derivatives of the three types of data. The two results are added together to obtain the fused data. This data comprehensively integrates static contact information and dynamic change trends, solving the problem of incomplete representation by single data. It provides more complete and accurate raw data support for subsequent feature extraction, ensuring the accuracy of 3D model reconstruction.

[0033] Preferably, the contour reconstruction model in S6 is: , in, For the coordinates of the 3D model, For model reconstruction coefficients, It is a spatial interpolation function. For spatial coordinates, To reconstruct the number of grid nodes.

[0034] Specifically, the contour reconstruction model is based on the requirements of 3D foot contour reconstruction. Reconstruction needs to integrate multi-dimensional data and spatial interpolation, taking into account the spatial contribution of each data point and the interpolation accuracy. Therefore, a formula combining double summation and spatial functions is adopted. The 3D space is divided into grid nodes. The contribution values ​​of pressure, displacement, and temperature data at each node are fused through double summation terms. The coefficient corresponding to each data point is determined through calibration experiments based on its influence on spatial coordinates. Then, a spatial interpolation function is introduced to compensate for the contour gaps between nodes. The fused data and interpolation function are combined through a product to form a 3D coordinate calculation model. The model reconstruction coefficients are determined through 3D scanning calibration experiments. The pressure correlation coefficient is 0.2 to 0.45, the displacement correlation coefficient is 0.25 to 0.5, and the temperature correlation coefficient is set to 0.05 to 0.15. The spatial interpolation function uses a cubic spline type. The spatial coordinate range is set according to the human foot size: x-axis 15 to 30 cm, y-axis 5 to 15 cm, and z-axis 3 to 10 cm. The number of reconstruction grid nodes is determined to be 100 to 300 after model accuracy verification. During implementation, the data processing unit extracts feature parameters from the fused data, substitutes them into the formula to calculate the three-dimensional coordinates of each grid node, and completes the contour details between nodes through spatial interpolation functions to construct a complete three-dimensional model of the foot. After the model is constructed, the influence weight of each data is corrected by the coefficients in the formula to compensate for measurement errors and ensure that the three-dimensional model can accurately restore the curved shape and key feature points of the foot. The establishment of this formula realizes the accurate conversion of multi-dimensional data into three-dimensional spatial coordinates, and improves the integrity and accuracy of contour reconstruction.

[0035] Preferred, such as Figure 2 As shown, step S3 includes the following sub-steps: S31, the initial position data of the extrusion module is collected by the displacement sensing unit and transmitted to the control unit. The control unit determines the initial motion parameters of the extrusion module based on the contour estimation result after foot support positioning; S32, the control unit sends a drive signal to the displacement adjustment mechanism to make the two extrusion modules move synchronously along the guide rail. The movement is kept at a constant speed in the initial stage of movement, and the movement trajectory is corrected in real time through the position feedback signal; S33, when the elastic buffer layer of the extrusion module initially contacts the side of the foot, the pressure sensing unit triggers a contact signal. After receiving the signal, the control unit adjusts the drive parameters of the displacement adjustment mechanism to reduce the extrusion rate; S34, the displacement of the extrusion module is continuously adjusted until the contact pressure detected by the pressure sensing unit reaches the preset distribution range, and the extrusion module is controlled to maintain the current position to complete the extrusion contact process.

[0036] Specifically, step S3 consists of four sub-steps, which involve precise control and adaptive contact calculation of the bidirectional compression module to ensure full fit of the foot's contours through phased operation. In sub-step S31, the displacement sensing unit collects the initial position data of the compression module at a sampling frequency of 200 Hz, with a data accuracy of ±0.01 mm. After being transmitted to the control unit, the control unit combines the foot pressure distribution data collected by the 320 pressure sensing units in step S1 and determines the initial motion parameters of the compression module through a contour prediction algorithm, including the starting position, preset stroke, and initial speed, providing a precise benchmark for subsequent movement. In sub-step S32, the control unit sends a drive signal to the displacement adjustment mechanism, and the two compression modules start synchronously along the high-precision guide rail. The parallelism error of the rail is less than ±0.02 mm. In the initial stage, a uniform speed of 5 mm / s is maintained, and the position feedback signal is transmitted every 0.005 seconds. The control unit corrects the motion trajectory in real time based on the feedback data to ensure that the synchronization error of the two modules does not exceed 0.03 mm. In step S33, when the distance between the elastic buffer layer of the extrusion module and the side of the foot decreases to 3 cm, the pressure sensing unit detects a contact pressure of 5 N, immediately triggering a contact signal. Upon receiving the signal, the control unit adjusts the drive parameters of the displacement adjustment mechanism within 0.01 seconds, reducing the extrusion rate to 2 mm / s to avoid contour distortion caused by rapid extrusion. In step S34, the extrusion module continues to move slowly, and the pressure sensing unit monitors the contact pressure in real time. When the pressure distribution is between 15 and 25 N and the uniformity meets the preset requirements, the control unit sends a stop signal, and the extrusion module locks its current position. This step-by-step process achieves adaptive extrusion for different foot widths through staged rate adjustment and closed-loop control, ensuring gapless acquisition of the side contour and improving the accuracy of overall foot shape data.

[0037] Preferred, such as Figure 3 As shown, step S4 includes the following sub-steps: S41, the control unit sends a start signal to the heating module, the heating element of the heating module starts working, and the initial temperature data of the contact end face of the flexible collection layer and the extrusion module is collected by the temperature sensing unit; S42, the initial temperature data is compared with the preset temperature range. If the initial temperature is lower than the lower limit of the range, the control unit increases the heating power. If the initial temperature is higher than the upper limit of the range, the control unit decreases the heating power or stops heating; S43, during the collection process, the temperature sensing unit collects the temperature data of the contact area at fixed time intervals and transmits the data to the control unit in real time. The control unit calculates the temperature deviation through closed-loop control logic; S44, the heating power of the heating module is adjusted based on the temperature deviation so that the temperature of the contact end face of the flexible collection layer and the extrusion module is always maintained within the preset range until the collection process ends.

[0038] Specifically, step S4 consists of four sub-steps for precise temperature control of the heating module. Through staged temperature adjustment and closed-loop control, a stable temperature environment is maintained in the contact area. In sub-step S41, the control unit sends a start signal to the heating module, and the 300-watt flexible electric heating film heating element immediately starts. 24 thermocouple temperature sensing units are evenly distributed in the acquisition area, collecting initial temperature data of the flexible acquisition layer and the contact end face of the extrusion module at a sampling frequency of 50 Hz, with a detection accuracy of ±0.2℃. The initial data is transmitted to the control unit within 0.02 seconds, completing the establishment of the temperature reference. In sub-step S42, the control unit compares the initial temperature data with the preset temperature range of 32 to 36℃. If the initial temperature is lower than 32℃, the control unit increases the heating power to 80% of the rated power; if it is higher than 36℃, it reduces it to 30% or stops heating, quickly achieving initial temperature adjustment. In step S43, the temperature sensing unit continuously collects temperature data at fixed time intervals of 0.02 seconds during the data acquisition process and transmits it to the control unit in real time. The control unit calculates the difference between the actual temperature and the preset range using a temperature deviation algorithm, with a deviation calculation accuracy of ±0.1℃, providing an accurate basis for power adjustment. In step S44, the control unit adjusts the heating power of the heating module based on the temperature deviation value. For every 1℃ increase in deviation, the power is adjusted by 50 watts. Through closed-loop control logic, the temperature fluctuation range of the contact area is controlled within ±0.3℃ until the entire data acquisition process is completed. This step-by-step process, through the continuous operation of rapid start-up, preliminary adjustment, real-time monitoring, and precise correction, avoids the impact of temperature changes on foot shape and the acquisition medium, while improving the fit between the foot and the acquisition component, ensuring the stability and consistency of the acquired data.

[0039] Preferred, such as Figure 4 As shown, step S5 includes the following sub-steps: S51, the pressure sensing unit converts the pressure signal generated by foot contact into an electrical signal, amplifies the electrical signal strength through a signal amplification component, and removes interference components from the signal through a filtering component to obtain standardized pressure data; S52, the displacement sensing unit collects the motion displacement of the extrusion module and the deformation of the flexible acquisition layer in real time, converts the displacement signal into a digital signal, and aligns it with the pressure data in time through a data synchronization component; S53, the temperature sensing unit collects the temperature signal of the contact area, converts it into digital temperature data through an analog-to-digital converter, and corrects the temperature data for errors through a calibration component; S54, the signal conversion component integrates the standardized pressure data, the time-aligned displacement data, and the corrected temperature data into a multi-dimensional data set, and sends it to the data processing unit according to a preset transmission protocol.

[0040] Specifically, step S5 involves four sub-steps for the acquisition, conversion, and integration of multi-dimensional data. Staged signal processing ensures the comprehensiveness, accuracy, and synchronization of the data. In sub-step S51, the pressure sensing unit converts the pressure signal generated by foot contact into an electrical signal with a range of 0 to 100 Newtons. The signal amplification component amplifies the signal amplitude by 1000 times, and the filtering component uses digital low-pass filtering technology to remove interference components above 50 Hz, obtaining standardized pressure data with a resolution of 0.01 Newtons, ensuring the purity of the pressure signal. In sub-step S52, the displacement sensing unit acquires the motion displacement of the extrusion module and the deformation of the flexible acquisition layer at a sampling frequency of 200 Hz. The displacement data ranges from 0 to 15 mm with a resolution of 0.001 mm. After analog-to-digital conversion, it is converted into a digital signal. The data synchronization component aligns the displacement data with the pressure data according to the timestamp, controlling the time synchronization error within ±0.005 seconds to ensure the spatiotemporal consistency of the two types of data. In step S53, the temperature signal collected by the temperature sensing unit is converted into digital temperature data by the analog-to-digital converter with a conversion accuracy of 16 bits. The calibration unit corrects the data using a preset temperature error compensation algorithm, ensuring that the error of the corrected data is less than ±0.1℃, thus guaranteeing the accuracy of the temperature data. In step S54, the signal conversion unit integrates the standardized pressure data, time-aligned displacement data, and corrected temperature data into a multi-dimensional data set. The data set is encapsulated according to a preset frame format and transmitted to the data processing unit via a high-speed data bus at a transmission rate of 1000 Mbps. During transmission, a cyclic redundancy check mechanism is used to ensure that there is no data loss or distortion. This step-by-step process, through the coherent processing of signal amplification, filtering, synchronization, calibration, and integration, comprehensively captures the multi-dimensional physical information of the foot contact process, providing high-quality raw data support for subsequent feature extraction and contour reconstruction.

[0041] like Figure 5As shown, a human foot shape full-contact intelligent acquisition and analysis device is applied to a human foot shape full-contact intelligent acquisition and analysis method. The device includes: a foot support and positioning support module, a multi-channel negative pressure generation and adjustment module, a bidirectional adaptive compression contact module, a constant temperature control heating module, a multi-dimensional data acquisition and conversion module, and an intelligent data processing and contour reconstruction module. The foot support and positioning support module supports the human foot and defines the acquisition posture. Pressure sensing units are arranged on its surface and directly connected to the multi-channel negative pressure generation and adjustment module and the bidirectional adaptive compression contact module. The multi-channel negative pressure generation and adjustment module includes multiple independent air pump components, flow regulation pipelines, and a negative pressure chamber. It is connected to the flexible acquisition layer of the foot support and positioning support module through pipelines to generate a negative pressure field and adjust the air pressure gradient. The bidirectional adaptive compression contact module is set in... The foot support and positioning load-bearing module has elastic buffer contact surfaces, displacement adjustment mechanisms, and drive components on both sides. It is connected to the control unit via control lines to perform horizontal relative compression movement. The constant temperature control heating module is embedded in the flexible acquisition layer and the compression contact surface. It includes heating elements, temperature sensing units, and power adjustment components. It is connected to the closed-loop control unit via signal lines to perform stable temperature control. The multi-dimensional data acquisition and conversion module includes pressure, displacement, and temperature sensing components, as well as signal amplification, filtering, and analog-to-digital conversion components. It is connected to the intelligent data processing and contour reconstruction module via a data bus to perform multi-dimensional data acquisition and standardized conversion. The intelligent data processing and contour reconstruction module includes a data storage unit, feature extraction components, and a 3D model reconstruction algorithm module. It is connected to other modules via control lines to perform data processing and foot contour reconstruction.

[0042] like Figure 6The diagram shows a 3D structural schematic of the human foot shape full-contact intelligent acquisition and analysis device. The device features an integrated layout, tightly integrating the six core functional modules described in the invention. Its compact structure and clear functional divisions perfectly embody the design concept of full-contact, high-precision, and intelligent foot shape acquisition. The core of the device is the foot support and positioning carrier module, which forms the basic carrier for foot placement. A flexible acquisition layer is laid on its surface, beneath which pressure sensing units are evenly distributed to detect the foot's contact pressure distribution in real time. Combined with the anti-slip texture and positioning baffle on the bottom, it accurately fixes the foot's acquisition posture, laying a stable benchmark for subsequent acquisition. Symmetrically arranged on both sides of the carrier module are bidirectional adaptive compression contact modules. The contact surfaces of these modules are equipped with elastic buffer layers. Through a built-in displacement adjustment mechanism and driving components, they can move synchronously in opposite directions along the horizontal direction, adaptively conforming to the side contours of feet of different widths, eliminating side edge acquisition gaps, and accurately capturing the side edge curve features of the foot. The device integrates a multi-channel negative pressure generation and regulation module, comprising multiple independent air pump components. Each air pump is connected to the internal chamber of the flexible acquisition layer via an independent flow regulation pipeline. It can construct a negative pressure field according to a preset pressure gradient, driving the flexible acquisition layer to deform and closely conform to the complex curves of the sole and dorsum of the foot, capturing crucial details such as the arch and toe pads without omission. A constant temperature control heating module is embedded within the contact surface between the flexible acquisition layer and the extrusion module, working in conjunction with a temperature sensing unit to maintain a stable contact temperature of 32-36℃ using closed-loop control logic, preventing temperature fluctuations from affecting foot shape and the fit of the acquisition medium. The device is equipped with multi-dimensional data acquisition components throughout its entire range, integrating pressure, displacement, and temperature sensors to simultaneously collect multi-dimensional data during the contact process. After signal conversion and processing, this data is transmitted to the intelligent data processing and contour reconstruction module. The device achieves all-round, gapless contact data collection of the foot through the coordinated operation of negative pressure adsorption, bidirectional extrusion, constant temperature control, and multi-dimensional sensing. The structural design takes into account both mechanical stability and collection accuracy, perfectly matching the invention's technical goal of solving the problems of insufficient fit and lack of data integrity in traditional collection methods. It provides high-precision foot data support for scenarios such as footwear customization and medical correction.

[0043] The formula in this invention integrates the calculation of different scalar and vector parameters. Through standardization, weight allocation, and physical correlation modeling, it eliminates differences in parameter dimensions and establishes logical connections. First, different types of parameters undergo unified standardization transformation. For example, the numerical range of scalar parameters like pressure is mapped to a range consistent with parameters such as displacement and temperature, ensuring a unified calculation scale. In this invention, the pressure data range is converted to a range compatible with displacement and temperature data, making the components of scalar pressure values ​​and vector displacements additive and comparable. Second, weight coefficients are assigned based on the degree of influence of each parameter on the target acquisition. The contribution ratio of different parameters is determined through experimental calibration. For example, the weight of the pressure parameter is set according to its influence on contour fit, and the weight of the displacement vector is adjusted based on its importance in spatial morphology representation, ensuring that scalar and vector parameters participate in the calculation in a reasonable proportion in the formula. Furthermore, by utilizing the inherent correlation of physical processes to construct a coupled model, this invention directly relates pressure, displacement, and temperature parameters to foot contour acquisition. Pressure changes reflect the degree of contact tightness, displacement vectors characterize spatial morphology, and temperature data affects the fit. The formula quantifies this correlation mathematically, such as by integrating the components of the displacement vector with pressure and temperature scalars according to the physical laws of the contact process, achieving coordinated calculation of different types of parameters. Simultaneously, adjustment factors and compensation terms are introduced into the formula to correct the differences between scalars and vectors in dimensionality and physical meaning, ensuring that the calculation results accurately reflect the true state of the acquisition process. Ultimately, this achieves effective integration of multi-dimensional and different types of parameters, providing data support for accurate acquisition and model reconstruction.

[0044] A method and device for intelligent full-contact acquisition and analysis of human foot shape is disclosed. This method utilizes a multi-pump assembly to construct a gradient negative pressure field, combined with the deformation characteristics of a flexible acquisition layer. This allows the acquisition medium to actively conform to the complex curvature of the foot. Simultaneously, bidirectional extrusion modules on both sides achieve adaptive movement through a displacement adjustment mechanism. An elastic buffer layer can adapt to the lateral morphology of different individuals' feet, avoiding localized gap problems caused by single adsorption or extrusion. Through the dual effects of negative pressure adsorption and bidirectional extrusion, all areas of the foot can form full contact with the acquisition components during the acquisition process, accurately capturing key feature points such as arch height, toe contours, and lateral curves. This completely solves the problem that traditional techniques struggle to simultaneously address the complexity of the foot and individual differences, significantly improving the accuracy of 3D model reconstruction.

[0045] This method and device maintain a stable environment in the contact area during data acquisition by introducing a constant-temperature heating module, avoiding interference from temperature changes on foot morphology and the acquisition medium, thus ensuring the stability of the acquired data. Simultaneously, a multi-dimensional data acquisition mechanism for pressure, displacement, and temperature is constructed. Various sensing units synchronously capture multi-dimensional information during the contact process, and after signal conversion and data fusion processing, comprehensively reflect the true state of contact between the foot and the acquisition device. Each module is linked through closed-loop control logic to achieve dynamic adjustment of acquisition parameters and real-time data processing. This ensures both the comprehensiveness and accuracy of the data and improves acquisition efficiency, providing sufficient data support for subsequent high-precision analysis and model reconstruction, and completely solving the problem that traditional single-dimensional acquisition cannot meet the needs of high-precision applications.

[0046] In the description of this invention, it should be noted that, unless otherwise specified and limited, the terms "set," "install," "connect," "link," and "fix" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0047] Although embodiments of the invention have been shown and described, it will be understood by those skilled in the art that various equivalent changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the appended claims and their equivalents.

Claims

1. A method for intelligent acquisition and analysis of human foot shape through full contact, characterized in that, Includes the following steps: S1. The device supports and positions the human foot through a supporting structure, placing the foot in a preset collection posture. Pressure sensing units that contact the foot are arranged on the surface of the supporting structure. S2. Multiple air pump assemblies are activated to generate a negative pressure field according to a preset pressure gradient. This negative pressure field acts on the foot surface, causing the flexible collection layer to deform and conform to the foot's contour. The air pump assemblies are connected to the internal chamber of the flexible collection layer via independent pipelines, each pipeline equipped with a flow regulating component. S3. The two bidirectional extrusion modules on both sides are controlled to move relative to each other in the horizontal direction. An elastic buffer layer is provided on the contact end face of the extrusion modules. The extrusion stroke and extrusion rate are controlled by a displacement adjustment mechanism to ensure the extrusion... S4. The pressure module makes full contact with both sides of the foot; S5. The heating module is activated to maintain the contact surface of the flexible collection layer and the pressure module within a preset temperature range. The heating module provides real-time feedback of the temperature data of the contact area through the temperature sensing unit and adjusts the heating power through closed-loop control logic; S6. Multi-dimensional data of the foot contact process is collected synchronously through the pressure sensing unit, displacement sensing unit and temperature sensing unit. The multi-dimensional data is transmitted to the data processing unit through the signal conversion component; S7. The data processing unit performs feature extraction and contour reconstruction on the multi-dimensional data and constructs a three-dimensional model of the foot based on the contact pressure distribution, deformation displacement and temperature feedback data.

2. The human foot shape full-contact intelligent acquisition and analysis method according to claim 1, characterized in that, The pressure gradient of the negative pressure field in S2 is calculated using the following model: ， in, Let be the output air pressure of the i-th air pump at the j-th data collection time. This is the initial air pressure reference value. This is the air pressure fluctuation amplitude coefficient. The angular frequency of air pressure change. This is the phase offset. The attenuation coefficient is... For the time of collection, This represents the pressure regulation order.

3. The human foot shape full-contact intelligent acquisition and analysis method according to claim 1, characterized in that, The displacement of the bidirectional extrusion module in S3 satisfies the following model: ， in, This represents the actual displacement of the extrusion module at displacement stroke I. The maximum displacement threshold, This is the displacement growth factor. For the extrusion stroke, For displacement adjustment factor, For displacement fluctuation frequency, This represents the number of displacement adjustment terms.

4. The human foot shape full-contact intelligent acquisition and analysis method according to claim 1, characterized in that, The power regulation model of the heating module in S4 is as follows: ， in, For heating power, The reference power value, This is the difference between the actual temperature and the preset temperature. This is the temperature deviation threshold. This is the power regulation coefficient. The temperature decay coefficient is For power regulation order, This represents the number of factors affecting temperature.

5. The human foot shape full-contact intelligent acquisition and analysis method according to claim 1, characterized in that, The fusion model for multidimensional data in S5 is as follows: ， in, For the merged data, For stress data, For displacement data, For temperature data, For data weighting coefficients, , For the time derivatives of each data point, This refers to the data collection duration.

6. The human foot shape full-contact intelligent acquisition and analysis method according to claim 1, characterized in that, The contour reconstruction model in S6 is as follows: ， in, For the coordinates of the 3D model, For model reconstruction coefficients, It is a spatial interpolation function. For spatial coordinates, To reconstruct the number of grid nodes.

7. The human foot shape full-contact intelligent acquisition and analysis method according to claim 1, characterized in that, S3 includes the following steps: S31, the initial position data of the extrusion module is collected by the displacement sensing unit and transmitted to the control unit. The control unit determines the initial motion parameters of the extrusion module based on the contour estimation result after foot support positioning; S32, the control unit sends a drive signal to the displacement adjustment mechanism to make the extrusion modules on both sides start moving synchronously along the guide rail. The movement is kept at a constant speed in the initial stage of movement, and the movement trajectory is corrected in real time through the position feedback signal; S33, when the elastic buffer layer of the extrusion module initially contacts the side of the foot, the pressure sensing unit triggers a contact signal. After receiving the signal, the control unit adjusts the drive parameters of the displacement adjustment mechanism to reduce the extrusion rate; S34, the displacement of the extrusion module is continuously adjusted until the contact pressure detected by the pressure sensing unit reaches the preset distribution range, and the extrusion module is controlled to maintain the current position to complete the extrusion contact process.

8. The human foot shape full-contact intelligent acquisition and analysis method according to claim 1, characterized in that, S4 includes the following steps: S41, the control unit sends a start signal to the heating module, the heating element of the heating module starts working, and the initial temperature data of the contact end face of the flexible collection layer and the extrusion module is collected by the temperature sensing unit; S42, the initial temperature data is compared with the preset temperature range. If the initial temperature is lower than the lower limit of the range, the control unit increases the heating power. If the initial temperature is higher than the upper limit of the range, the control unit decreases the heating power or stops heating; S43, during the collection process, the temperature sensing unit collects the temperature data of the contact area at fixed time intervals and transmits the data to the control unit in real time. The control unit calculates the temperature deviation through closed-loop control logic; S44, the heating power of the heating module is adjusted based on the temperature deviation so that the temperature of the contact end face of the flexible collection layer and the extrusion module is always maintained within the preset range until the collection process ends.

9. The human foot shape full-contact intelligent acquisition and analysis method according to claim 1, characterized in that, S5 includes the following sub-steps: S51, the pressure sensing unit converts the pressure signal generated by foot contact into an electrical signal, amplifies the electrical signal strength through a signal amplification component, and removes interference components from the signal through a filtering component to obtain standardized pressure data; S52, the displacement sensing unit collects the motion displacement of the extrusion module and the deformation of the flexible acquisition layer in real time, converts the displacement signal into a digital signal, and aligns it with the pressure data in time through a data synchronization component; S53, the temperature sensing unit collects the temperature signal of the contact area, converts it into digital temperature data through an analog-to-digital converter, and corrects the temperature data for errors through a calibration component; S54, the signal conversion component integrates the standardized pressure data, the time-aligned displacement data, and the corrected temperature data into a multi-dimensional data set, and sends it to the data processing unit according to a preset transmission protocol.

10. A human foot shape full-contact intelligent acquisition and analysis device, characterized in that, The device is applied to the human foot shape full contact intelligent acquisition and analysis method described in claim 1, including: foot support positioning and bearing module, multi-channel negative pressure generation and adjustment module, bidirectional adaptive extrusion contact module, constant temperature control heating module, multi-dimensional data acquisition and conversion module, and intelligent data processing and contour reconstruction module; The foot support and positioning module supports the human foot and defines the acquisition posture. Its surface is equipped with pressure sensing units, which are directly connected to a multi-channel negative pressure generation and adjustment module and a bidirectional adaptive compression contact module. The multi-channel negative pressure generation and adjustment module includes multiple independent air pump components, flow regulation pipelines, and negative pressure chambers. It is connected to the flexible acquisition layer of the foot support and positioning module via pipelines to generate a negative pressure field and adjust the air pressure gradient. The bidirectional adaptive compression contact module is located on both sides of the foot support and positioning module and includes elastic buffer contact end faces, displacement adjustment mechanisms, and drive components. It is connected to the control unit via control lines to perform horizontal relative compression. The system comprises a dynamic, constant-temperature control heating module embedded within the flexible acquisition layer and the extrusion contact surface. This module includes a heating element, a temperature sensing unit, and a power adjustment component. It is connected to a closed-loop control unit via signal lines for stable temperature control. The multi-dimensional data acquisition and conversion module includes pressure, displacement, and temperature sensing components, as well as signal amplification, filtering, and analog-to-digital conversion components. It is connected to the intelligent data processing and contour reconstruction module via a data bus for multi-dimensional data acquisition and standardized conversion. The intelligent data processing and contour reconstruction module includes a data storage unit, a feature extraction component, and a 3D model reconstruction algorithm module. It is connected to other modules via control lines for data processing and foot contour reconstruction.

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