Intelligent insole system for plantar pressure monitoring requirement

Abstract

The invention discloses an intelligent insole system for a plantar pressure monitoring requirement, and belongs to the technical field of sensors. The system comprises a sensing array which is formed by arranging flexible sensors and is configured to be capable of sensing the real-time pressure of the corresponding position of the foot sole; the flexible PCB is configured to play a role in supporting and integrating the sensing array; the insole body is configured to be capable of fixing the flexible PCB; the data processing unit is configured to be electrically connected with the flexible PCB, receive the pressure data collected by the sensing array in real time and analyze and process the pressure data; the flexible sensor is a silk-screen printing flexible sensor or a salt template method porous structure sensor. According to the intelligent insole, a high-performance flexible sensor array is constructed by optimizing a sensor preparation process and structural design, and high-precision, high-stability and high-comfort plantar pressure monitoring of the intelligent insole is realized.

Description

Technical Field

[0001] This invention belongs to the field of sensor technology, specifically relating to an intelligent insole system for monitoring plantar pressure. Background Technology

[0002] Plantar pressure signals contain rich physiological and pathological information and have important application value in health management, disease prevention and control, sports training and chronic disease management. Their accurate monitoring is of great significance for the early detection and rehabilitation guidance of problems such as foot arch abnormalities and diabetic foot.

[0003] Traditional plantar pressure measurement devices (such as pressure pads, optical scanning devices, and gait analyzers) can provide high-precision data, but they have drawbacks such as strong environmental dependence, poor portability, high cost, and insufficient real-time performance. They are difficult to meet the continuous monitoring needs in daily scenarios, and the test environment is quite different from the daily life environment, so the data is difficult to reflect the true plantar pressure state.

[0004] With the development of intelligent sensing technology, commercially available smart insoles attempt to solve the portability problem, but still have many technical shortcomings: First, the sensor materials lack flexibility, resulting in poor wearing comfort and affecting the accuracy of signal measurement; second, the number of sensor arrays is small, and the resolution is low, making it impossible to comprehensively and accurately capture the pressure distribution and dynamic changes in different areas of the sole; third, the sensors have poor stability, are easily affected by environmental interference, and lack reliability in long-term use; fourth, the manufacturing process of some sensors is complex, making it difficult to achieve miniaturization and array integration, which limits their application in precise gait analysis; fifth, the low-pressure response sensitivity, response / recovery speed, and wide range adaptability are insufficient, making it difficult to match the characteristics of high intensity, high frequency, and susceptibility to interference of sole pressure signals. Summary of the Invention

[0005] The present invention aims to at least partially solve one of the technical problems in the aforementioned related technologies.

[0006] Therefore, the purpose of this invention is to provide an intelligent insole system for foot pressure monitoring, which achieves high-precision, high-stability, and high-comfort foot pressure monitoring by optimizing sensor manufacturing process and structural design and constructing a high-performance flexible sensor array.

[0007] To solve the above-mentioned technical problems, the present invention is implemented as follows: This invention provides an intelligent insole system for foot pressure monitoring, the system comprising: The sensor array, composed of flexible sensors, is configured to sense real-time pressure at corresponding locations on the soles of the feet. Flexible PCB boards are configured to support and integrate the sensor array. The insole body is configured to hold a flexible PCB board. The data processing unit is configured to be electrically connected to the flexible PCB board to receive and analyze pressure data collected by the sensor array in real time.

[0008] In addition, the intelligent insole system according to the present invention, which addresses the need for plantar pressure monitoring, may also have the following additional technical features: In some embodiments, the flexible sensor is a screen-printed flexible sensor or a porous structure sensor using a salt template method.

[0009] In some embodiments, the fabrication of the screen-printed flexible sensor includes: optimizing the conductivity of the ink by adding a conductive filler of a graphene and carbon nanotube composite system, preparing a stretchable flexible substrate to amplify the deformation of the sensitive unit, and then introducing a microstructure to fabricate a flexible sensor for measuring plantar pressure signals.

[0010] In some embodiments, the mass ratio of the graphene to the carbon nanotubes is 1:1.

[0011] In some embodiments, the fabrication steps of the screen-printed flexible sensor include: S11: Conductive ink is prepared by using graphene and carbon nanotubes as conductive fillers, combined with carbon ester and silicone oil; curing agent and catalyst are added sequentially during the preparation process; S12: A sensor printing film is prepared by covering methyl vinyl silicone rubber containing a vulcanizing agent with a PTFE film and then cold-pressing and hot-pressing it. S13: A perforated silicone substrate is prepared by curing PDMS and a curing agent in a specific ratio. S14: Based on a screen printing stencil with a specific mesh size, a sensitive layer formed by the conductive ink is prepared on the sensor substrate film, and after being cut, it is encapsulated in the perforated silicone substrate to obtain the screen-printed flexible sensor.

[0012] In some of these embodiments, the porous structure sensor prepared by the salt template method is as follows: NaCl is used as a pore-forming agent, blended with PDMS and carbon fiber, and after hot pressing and curing, NaCl is dissolved to form a porous structure with a porosity that meets specific requirements. At the same time, sandpaper is used to construct micro-nano wrinkles on the surface to reduce the elastic modulus of the material. Graphene is coated onto the inner and outer surfaces of a porous structure using vacuum negative pressure impregnation technology to improve the continuity of the conductive network.

[0013] In some embodiments, the carbon fiber content is 10 wt%; The ratio of PDMS to NaCl is 1:6; The sandpaper has a mesh size of 60.

[0014] In some embodiments, the fabrication steps of the salt template porous structure sensor include: S21: A mixture of PDMS, carbon fiber, NaCl and curing agent is placed on sandpaper of a specific mesh size and rolled, and then cured and dissolved in NaCl to obtain a conductive porous microstructure sensitive layer. S22: The prepared conductive porous microstructure sensitive layer is placed in a mixture of graphene and anhydrous ethanol, and dried under negative pressure to achieve the adhesion of graphene inside and on the surface of the porous microstructure. S23: The porous microstructure with graphene attached is cut and encapsulated in a thin film to obtain the porous structure sensor obtained by the salt template method.

[0015] In some of these implementations, the sensor array is designed based on the foot skeletal structure and gait cycle.

[0016] In some embodiments, the sensing array comprises 42 10×10mm flexible sensors mounted on a 260mm×101mm flexible PCB board; the negative electrodes of the 42 flexible sensors are connected together, while the positive electrodes are led out separately.

[0017] Compared with the prior art, the present invention has at least the following beneficial effects: In this embodiment of the invention, the provided intelligent insole system for foot pressure monitoring combines foot skeletal and gait characteristics, with an array of 42 sensors covering 8 major foot regions, densely arranged in the metatarsal / heel areas to accurately capture pressure distribution; the flexible PCB silicone substrate fits the foot for comfortable wear. In this embodiment of the invention, the provided intelligent insole system for foot pressure monitoring features a salt template sensor with excellent low-pressure performance. It has a porosity of 65.36% + 60-mesh sandpaper microstructure, a sensitivity GF=11.2 in the low-pressure zone (strain < 5%), and is compatible with static low-pressure signals from the sole of the foot. It can detect pressures from 5g to 2kg, has an 80ms response time, and exhibits only a 3% fluctuation after 3500 cycles. In this embodiment of the invention, the provided intelligent insole system for foot pressure monitoring features a simple and easily scalable screen-printed sensor process. The sensor is thin (≈200μm) and can be combined with a flexible PCB to achieve arraying, making it suitable for insole integration. It is sensitive and stable across the entire strain range: 0-60% strain GF=3.28, 60-100% strain GF=4.62, 80ms response, 120ms recovery, 5000 cycles of fluctuation < 5%, 1% strain detection limit, and is suitable for dynamic high pressure and small deformation of the foot. In this embodiment of the invention, the provided intelligent insole system for foot pressure monitoring uses a screen-printed sensor with a single-layer perforated design. PDMS is poured into a pre-formed mold, and demolded by heating and curing to form a perforated structure. The printed sensitive unit is then encapsulated with a printing film and placed in the perforated structure. The perforated portion increases the deformation and amplifies the received signal.

[0018] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0019] Figure 1 This is a flowchart of a sensor fabrication process using a salt template method disclosed in one embodiment of the present invention; Figure 2 This is a schematic diagram of the sensing mechanism of a porous structure sensor disclosed in an embodiment of the present invention; wherein, (a) is a schematic diagram of the sensor structure under different pressures, (b) is the initial state circuit, (c) is the low pressure state circuit, and (d) is the high pressure state circuit; Figure 3 This is a flowchart of the fabrication process of a screen-printed sensor disclosed in one embodiment of the present invention; Figure 4 This is a schematic diagram of the sensing principle of a screen printing sensor disclosed in an embodiment of the present invention; wherein, (a) is a schematic diagram of sensor deformation, and (b) is an equivalent circuit diagram of the sensor. Detailed Implementation

[0020] 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 are within the scope of protection of the present invention.

[0021] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and specific examples and application scenarios.

[0022] The salt template method is an economical and effective method for preparing porous structures using soluble sodium chloride (NaCl) particles as a pore-forming agent. In this invention, a certain proportion of NaCl particles are mixed with polydimethylsiloxane (PDMS) to promote the uniform dispersion of NaCl particles in the PDMS matrix. During the curing process, sandpaper is used as a substrate to cover the surface of the mixture, constructing the microstructure on the surface of the sensitive layer. By placing the cured composite material in warm water, the NaCl particles are dissolved, thereby forming a porous microstructure inside and on the surface of the PDMS matrix.

[0023] The fabrication process of porous microstructure sensors prepared by the salt template method is as follows: Figure 1 As shown, it is mainly divided into three parts: the preparation of the sensitive layer of the conductive porous microstructure, the coating of graphene inside and on the surface of the porous microstructure, and the encapsulation of the porous microstructure pressure sensor.

[0024] (1) Preparation of conductive porous microstructure sensitive layer Step 1: Weigh 0.5 g of conductive carbon fiber (CF) on a balance and put it into a 150 ml plastic container. Add 5 g of PDMS and premix it with a glass rod. Then put it into a homogenizer and set the speed to 2200 rpm for 120 s to mix the two thoroughly and evenly to obtain a CF / PDMS mixture.

[0025] Step 2: Weigh 100 g of NaCl granules and place them in a 150 ml plastic container. Use a homogenizer to stir at 2500 rpm for 120 seconds. During rapid rotation, the NaCl crystals collide with each other, causing the NaCl to break down, which can initially reduce the particle size of NaCl. Then pour it into a mortar and grind it thoroughly. Use an 80-mesh sieve to filter out the large NaCl particles. Weigh 30 g of the filtered NaCl granules and mix it with PDMS at a ratio of 6:1. Then add it to the CF / PDMS mixture and stir with a glass rod at 2200 rpm for 120 seconds in a homogenizer. Finally, add 0.5 g of PDMS curing agent to the CF / PDMS / NaCl mixture and set the stirring parameters to 2000 rpm for 120 seconds to ensure uniform mixing.

[0026] Step 3: Take two pieces of 60-grit sandpaper and cut them to 100×100 mm. The sandpaper serves as a mold for constructing the microstructure on the sensitive layer surface. The sandpaper surface needs to be cleaned with 95% ethanol first. Pour the CF / PDMS / NaCl mixture into a confinement ring with an inner diameter of 90 mm and a thickness of 2 mm. Cover the ring with sandpaper from both the top and bottom. Use a roller to repeatedly roll the sandpaper surface 5 times, imprinting the microstructure from the sandpaper onto the surface of the CF / PDMS / NaCl mixture.

[0027] Step 4: Place the CF / PDMS / NaCl mixture, covered with sandpaper on both sides, into a flat vulcanizing machine. Apply a 2 kg iron plate to the top surface and set the temperature and time to 95 ℃ for 2 hours. This pressure curing ensures that the microstructure of the sandpaper is well presented on the surface of the CF / PDMS / NaCl mixture. After curing, dissolve the NaCl in deionized water for 24 hours. To accelerate the dissolution rate and prevent NaCl saturation in the deionized water, change the deionized water every 12 hours. After the NaCl dissolves, rinse the sample with flowing deionized water for 1 minute, squeezing the sample during rinsing to better remove NaCl solution adhering to the sample's interior and surface. Finally, dry the cleaned sample in a 100 ℃ oven for 2 hours to obtain a preliminary porous microstructured sensitive layer.

[0028] (2) Graphene coated inside and on the surface of porous microstructure Step 1: Dissolve 0.5 g of graphene in 50 ml of anhydrous ethanol. Since graphene has poor solubility in water and does not easily form a stable dispersion, ultrasonic dispersion was used to improve the dispersion by ultrasonic vibration for 5 min. Then, the mixture was stirred at 2000 rpm for 3 min using a magnetic stirrer to ensure uniform dispersion of the graphene in the ethanol solution, resulting in a graphene / anhydrous ethanol mixture.

[0029] Step 2: The porous microstructure sensitive layer sample is immersed in a uniformly dispersed graphene / anhydrous ethanol mixture, and then placed in a vacuum oven at -99 kPa for 1 hour to allow the graphene to fully penetrate the porous structure under pressure. After immersion, the oven temperature is set to 80 ℃ and dried for 0.5 hours to allow the anhydrous ethanol solution to evaporate, and the remaining graphene adheres to the surface of the porous microstructure, resulting in a final porous microstructure sensitive layer with graphene coated both internally and externally.

[0030] (3) Packaging of porous microstructure pressure sensor The prepared sensitive layer was cut into 10×10 mm pieces, and two identical samples were stacked together to form the sensor's sensitive layer. Conductive copper foil was placed on the top and bottom surfaces, and conductive silver wires were attached to the copper foil surfaces, serving as the sensor's electrodes. The outermost layer was encapsulated with a 55 μm PI film, which not only ensured a tight fit between the electrodes and the sensitive layer but also acted as an encapsulation layer to prevent external interference with the sensor.

[0031] PDMS, as the most common matrix material in the preparation of composite materials, has the following significant characteristics: (1) excellent chemical stability, which can maintain the stability of structure and performance in complex chemical environments and is not prone to chemical reactions; (2) optical transparency >90%, which has potential value in the preparation of optical sensors and other devices; (3) excellent mechanical properties, good flexibility and elasticity, with an elastic modulus range of 0.4~3.5 MPa after curing, which can withstand deformation without damage. Compared with other common polymer materials, PDMS exhibits more superior flexibility; (4) good biocompatibility, which will not produce an immune response when applied to flexible sensors and in contact with human skin; (5) good flowability, which can be processed into various complex shapes through different molds to meet the structural requirements of different application scenarios. In this invention, PDMS is used as the matrix material of the sensitive layer, carbon fiber (CF) is used as the conductive filler, and NaCl particles are used as templates. Through the "blending-hot pressing" method, CF and NaCl are uniformly dispersed in the PDMS matrix. CF can build a conductive network in the PDMS matrix, reduce the overall resistance, and improve the conductivity of the sensitive layer. By dissolving NaCl particles to create a porous structure within the sensitive layer, the elastic modulus of the sensor can be effectively reduced. Furthermore, by coating the sensitive layer with graphene both internally and externally using vacuum negative pressure, the sensor's sensitivity is further enhanced.

[0032] The working mechanism of porous microstructure sensors is as follows Figure 2 As shown, this mechanism reveals the structural evolution and electrical response characteristics of the sensor under different pressure conditions. Figure 2 (a) shows a schematic diagram of the sensor structure under different pressures. Its resistance can be divided into two parts: the first part is the contact resistance (Rs) generated at the interface between the electrode and the sensitive layer, and the second part is the volume resistance (Rb) of the sensitive layer itself. This resistance division is based on the physical structure of the sensor. The contact resistance originates from the electron transport characteristics of the microscopic interface between the electrode and the sensitive layer, while the volume resistance reflects the electron conduction characteristics inside the sensitive layer material.

[0033] like Figure 2 As shown in (b), in the initial state, the internal conductive paths of the sensor are relatively few, and its equivalent circuit can be considered as a series structure of Rs and Rb. This series circuit reflects that in the initial state, electron transport must pass through the contact interface and the interior of the sensitive layer in sequence, and the limitation of the conductive paths leads to a high overall resistance. Under low voltage, the microstructure on the sensor surface undergoes compressive deformation, and the contact interface between the electrode and the microstructure on the sensor surface significantly expands. This change causes a sharp increase in the number of internal conductive paths. Figure 2As shown in (c), the equivalent circuit can be considered as the initial series structure (Rs and Rb) with the addition of multiple parallel branches. According to circuit theory, the increase of parallel branches reduces the overall resistance, thus the overall resistance of the sensor decreases in this state. The compression deformation of the microstructure optimizes the electron transport path and enhances the conductivity of the sensor. Under high voltage, the internal pores of the sensor undergo a complex deformation process; some pores are compressed and deformed, while others are compressed and closed. This reduces the overall thickness of the sensor and further increases the internal conductive path, leading to a rapid decrease in the volume resistivity (Rb) of the sensitive layer. Its simplified equivalent circuit is shown below. Figure 2 As shown in (d). However, as the pressure continues to increase, the number of closed pores increases, the elastic modulus of the sensitive layer increases significantly, and the material modulus increases, resulting in a decrease in the resistance change. According to the definition of sensor sensitivity (sensitivity is the ratio of the resistance change rate to the pressure change), a decrease in resistance change under the same pressure directly leads to a decrease in sensor sensitivity.

[0034] The performance of the porous structure sensor will be tested below.

[0035] 1. Microstructural characterization of porous sensor: Testing method: Surface and cross-sectional morphology observation: The surface and cross-section of the sensitive layer were observed using a scanning electron microscope (model JSM-IT800) to analyze the pore structure and distribution of conductive fillers (carbon fiber, graphene); Elemental content and distribution analysis: The elemental distribution and quantitative analysis of the sensitive layer cross section were performed using a Horiba 8091-H energy dispersive spectrometer, with a focus on detecting residual Na and Cl elements (to evaluate the NaCl dissolution effect). Porosity and pore size distribution testing: Porosity and pore size distribution were calculated using a Micron Autopore 9520 high-pressure mercury intrusion analyzer based on the Washburn equation (mercury surface tension 0.4842 N / m, contact angle 140°). Surface roughness test: The surface roughness (Ra) of samples prepared with 60-mesh, 100-mesh, 150-mesh, and 280-mesh sandpaper and PTFE substrates was measured using a laser confocal microscope (OLS5000) and a white light interferometer (ContourX-500).

[0036] Test results show that the sensitive layer forms a sponge-like porous structure, with pores originating from NaCl dissolution. The pore size is concentrated in the range of 50-100 μm (with the highest proportion of 62.83 μm pores), and the porosity reaches 65.36%. Carbon fibers are uniformly dispersed in the PDMS matrix to form a conductive network, and graphene is impregnated and attached to the inner and outer surfaces of the pores through vacuum negative pressure, significantly improving conductivity. Energy dispersive spectroscopy analysis shows that Na element residue is 0.65 wt% and Cl element residue is 1.84 wt%, proving that NaCl is fully dissolved with only trace amounts remaining, thus avoiding any impact on sensing performance. The smaller the sandpaper mesh number, the greater the sample surface roughness: the Ra of the 60-mesh sandpaper sample is 117.06 μm (7.6 times that of the 280-mesh sample), while the Ra of the PTFE substrate sample is only 0.32 μm. Lower mesh sandpaper can construct more significant surface micro-wrinkles.

[0037] 2. Effect of different filler contents on resistivity Effect of different carbon fiber (CF) contents on resistivity: The resistivity change of the sensitive layer in the range of 4-12 wt% was measured using a four-probe resistivity meter. When the CF content increased from 5 wt% to 10 wt%, the resistivity decreased from 75 kΩ to 3 kΩ, showing a significant decreasing trend. After exceeding 10 wt%, the decrease in resistivity slowed down and tended to stabilize, indicating that at 10 wt%, CF had formed a complete conductive network in the PDMS matrix. Excessive CF can lead to agglomeration and reduce the flexibility of the material; therefore, 10 wt% is the optimal CF content.

[0038] The effect of different PDMS / NaCl ratios on sensor performance: Five groups of samples (surface covered with 60-mesh sandpaper, unimpregnated with graphene) were set with PDMS / NaCl ratios of 1:3, 1:4, 1:5, 1:6, and no NaCl added. Pressure was applied using a stretching machine, and the resistance change rate of each group was measured. The resistance change rate of the sample without NaCl was only 6%, while the resistance change rate increased significantly after adding NaCl. The performance was optimal at PDMS / NaCl = 1:6: the resistance change rate reached 75% under 200 kPa pressure, 1.5 times higher than the 1:3 sample (50%). This is because the high proportion of NaCl creates more pores, reduces the material's elastic modulus, and leads to a rapid increase in the conductive path under pressure, resulting in a greater decrease in resistance.

[0039] The effect of different sandpaper mesh sizes on sensor performance: Using PI film, 60-mesh, 100-mesh, 150-mesh, and 280-mesh sandpaper as substrates (PDMS / NaCl=1:6), the resistance change rate of samples under pressures of 0-200 kPa was measured. The results show that in the low-pressure region (0-25 kPa): the smaller the sandpaper mesh size, the higher the resistance change rate. The 60-mesh sandpaper sample showed a resistance change rate of 51% at 15 kPa (compared to only 20% for the PI film sample). This is because the micro-wrinkles on the surface of the lower-mesh sandpaper are more pronounced, resulting in a larger increase in the contact area between the electrode and the sensitive layer under pressure, leading to a rapid increase in the conductive path. In the high-pressure region (100-200 kPa): the curves of each group of samples basically overlapped. Due to the compaction of pores and surface microstructures, the resistance change mainly stemmed from the compression of the material itself, and the sensitivity tended to be similar.

[0040] 3. Effects of different NaCl contents on sensor performance Compression tests were conducted on sensitive layers with PDMS / NaCl ratios of 1:3, 1:4, 1:5, and 1:6 using a universal tensile testing machine (WDW-30E), and stress-strain curves were obtained. The results showed that all samples exhibited a concave nonlinear stress-strain curve exhibiting a "rapid deformation → slow deformation" pattern: under low pressure, the surface microstructure and pores were compressed, resulting in low modulus and large deformation; under high pressure, the structure was compacted, increasing the modulus and decreasing the deformation. The maximum strain was 81% for PDMS / NaCl = 1:6 (compared to only 64% for the 1:3 sample), and the curves for the 1:5 and 1:6 samples overlapped within the 40% strain range, indicating that the pores were close to saturation at 1:6. Further increasing NaCl would not significantly improve porosity and would likely lead to viscous mixtures and filler agglomeration.

[0041] 4. The effect of different sandpaper grit on sensor performance Sensitivity Testing: Using a tensile testing machine (CMT5504), the resistance change rate of graphene-impregnated and unimpregnated sensors was tested under pressures ranging from 0 to 200 kPa. Simultaneously, the sensitivity (GF) and linearity (R) of the graphene-impregnated sensor were measured in different strain ranges (<5%, 5%-50%, >50%). 2 The results showed that the sensor performance was significantly improved after impregnation with graphene: the resistance change rate reached 90% at 200 kPa (compared to 75% for the unimpregnated sample), due to the optimized continuity of the conductive network by graphene; the sensitivity decreased with increasing strain: GF=11.2 (R²=0.995) for strain <5%, GF=0.61 (R²=0.981) for strain 5%-50%, and GF=0.19 (R²=0.995) for strain >50%. 2 =0.975), the high sensitivity in the low-pressure region stems from the synergistic compression effect of surface microstructure and pores.

[0042] Frequency response test: Under 50% strain, dynamic pressure at frequencies of 1 Hz, 1.5 Hz, and 2 Hz was applied to the sensor, with 10 cycles for each frequency, and the voltage response curve was recorded. The results show that the sensor voltage is stable at 1.5-4 V within the 1-2 Hz frequency range, with no significant fluctuations or attenuation. It can accurately capture dynamic pressure changes, meeting the monitoring requirements of human gait (walking, jogging, and other activities with frequencies mostly between 1-2 Hz).

[0043] Response and recovery speed tests: Under 50% strain, the sensor's response time from pressure application to signal stabilization, and the recovery time from pressure removal to signal recovery were recorded. Results showed that the sensor's response speed was 80 ms and its recovery speed was 160 ms. The sum of these two times is much shorter than the time required for daily human activities (walking 0.5-0.7 s, climbing stairs 0.9-1.1 s, jogging 0.3-0.5 s), allowing for real-time capture of rapid changes in plantar pressure.

[0044] Stability Test: Under 30% strain, the sensor underwent 3500 cycles of pressure-relief testing, and the voltage response fluctuations were recorded. The response curves of the first 10 cycles and the last 10 cycles were compared. The results show that the sensor voltage fluctuation during the test was only 3%, and the curves of the first 10 cycles and the last 10 cycles highly overlapped, with no significant performance degradation. This demonstrates its excellent long-term stability and its ability to meet the requirements for long-term plantar pressure monitoring.

[0045] 5. Application Testing Testing method: Pressure response of weights: Apply 5 g, 10 g, 30 g (low pressure) and 1 kg, 1.5 kg, 2 kg (high pressure) weights respectively, and record the voltage response; Human activity recognition: The sensor is attached to the finger (press test) and finger joint (30°-90° bending test) to record the voltage signal; Airflow response: Blow air onto the sensor surface and observe the changes in resistance and voltage.

[0046] The results show that: The sensor has a clear voltage response to weights of different masses. The signal differentiation is high at low pressure (5-30 g), and although the sensitivity decreases at high pressure (1-2 kg), it can still identify weights stably. When the finger is pressed, the voltage fluctuates regularly. The greater the joint flexion angle (30°→90°), the smaller the voltage response amplitude, which can accurately identify limb movements. Airflow can induce deformation of the microstructure on the sensor surface, leading to changes in resistance and voltage response, demonstrating its potential for application in pressure detection in multiple scenarios.

[0047] Previously, a flexible pressure sensor with a sponge-like structure was fabricated using NaCl as a template. Besides the salt template method, it can also be fabricated using screen printing technology. By adding conductive fillers (graphene / carbon nanotube composite system) to optimize the conductivity of the ink, a stretchable flexible substrate can be prepared. By introducing microstructures, a flexible sensor suitable for measuring plantar pressure signals can be fabricated. This sensor exhibits good adhesion, is easy to array on flexible PCBs, and can be used to measure motion signals from different parts of the human body, showing great application potential in fields such as electronic skin and smart sensing.

[0048] The fabrication process of flexible sensors using screen printing is as follows: Figure 3 As shown, the process mainly consists of four parts: preparation of conductive ink, preparation of sensor substrate film, preparation of perforated silicone substrate, preparation of sensitive layer by screen printing, and sensor encapsulation. The specific preparation steps are as follows: (1) Preparation of conductive ink Step 1: Weigh 5 g of carbon ester, 0.4 g of graphene, and 0.4 g of carbon nanotubes into a 150 ml plastic container using a balance, then add 10 g of silicone oil. Place the plastic container in a homogenizer and first evacuate it until the vacuum level reaches -99 kPa. Then start stirring at a speed of 2200 r for 180 s. Vacuuming during stirring eliminates air bubbles generated during the process, ensuring the conductive materials are thoroughly and evenly mixed within the matrix.

[0049] Step 2: Remove the well-stirred conductive ink from the homogenizer. Due to the friction between the filler and the matrix during high-speed rotation and stirring, a certain amount of heat will be generated. Let it cool at room temperature for 3 minutes. Then, add 2 g of curing agent using a dropper and continue to put it into the homogenizer for vacuuming. Set the parameters to 2200 r and the time to 60 s.

[0050] Step 3: Although adding a curing agent can transform the conductive ink from a liquid to a solid state after printing, the reaction rate is slow, affecting the preparation efficiency. Therefore, after the curing agent is stirred evenly, it is also cooled at room temperature for 3 minutes. Then, 20 μL of catalyst is added using a pipette, and the stirring parameters are set to 2000 r / 30 s to ensure that the catalyst is mixed evenly and to shorten the curing time after printing.

[0051] (2) Preparation of sensor printing film Step 1: Weigh 40 g of methyl vinyl silicone rubber containing vulcanizing agent and place it in a 30×30 mm confinement ring. First, cover its upper and lower surfaces with a layer of polytetrafluoroethylene (PTFE) film to prevent the silicone rubber from sticking to the stainless steel plate and making demolding difficult. Then, clamp the customized stainless steel mold on the surface of the PTFE film.

[0052] Step 2: In order to better control the thickness of the printing film, the silicone rubber is first placed in the cold pressing area of ​​the flat vulcanizing machine and pressed at 10 MPa for 5 minutes. The thickness of the printing film is 0.3 mm.

[0053] Step 3: The curing temperature for methyl vinyl silicone rubber containing a vulcanizing agent is between 150℃ and 200℃. Within this range, the vulcanizing agent can decompose to generate free radicals, initiating the cross-linking reaction of the methyl vinyl silicone rubber. Below 150℃, the vulcanizing agent decomposes slowly, resulting in a long curing time; above 200℃, the rubber molecular chains may break, leading to a decrease in performance. Therefore, the cold-pressed substrate film is placed in the hot-pressing zone of a flatbed vulcanizing machine for pressure curing and shaping. The pressure is set at 13 MPa, the temperature at 160℃, and the curing time at 10 min. The cured substrate film is 0.1 mm thick.

[0054] (3) Preparation of the hole structure Step 1: Add curing agent to PDMS at a ratio of 10:1. During stirring, air bubbles will inevitably be introduced, and their presence will severely affect the uniformity and mechanical properties of the cured PDMS. To eliminate air bubbles in the PDMS during stirring, the vacuum degree of the homogenizer is set to -99 kPa, and the mixture is stirred at 1500 r for 60 s to obtain a homogeneous PDMS.

[0055] Step 2: Pour PDMS directly into a custom mold. Place the mold containing PDMS in an oven at 100°C for 1 hour to cure. After the PDMS is completely cured, remove it from the mold to obtain a perforated silicone rubber substrate. 100°C allows the curing agent in the PDMS to fully initiate the cross-linking reaction, completing the curing process within 1 hour, transforming the PDMS from a liquid state into a solid state with certain mechanical strength.

[0056] (4) Screen printing for the preparation of the sensitive layer and the encapsulation of the sensor Step 1: Clean the 100-mesh screen printing stencil and substrate with alcohol to remove surface dust and ensure good adhesion between the ink and the stencil and substrate during screen printing. Place the screen printing stencil on the substrate, then pour the prepared conductive ink onto the stencil at a distance of 6 mm from the pattern. This distance is to allow sufficient ink volume during squeegee application and to prevent ink from prematurely seeping into the pattern area, resulting in unclear pattern edges. Then, use a squeegee to spread the ink evenly on the screen surface.

[0057] Step 2: Tilt the polyurethane rubber scraper This method allows for the creation of a suitable pressure angle during the squeegee coating process, enabling the ink to pass smoothly through the screen under the push of the squeegee. During printing, a certain pressure is applied, and the ink is repeatedly squeegeed at a uniform speed of 10 mm / s five times. Uniform squeegee coating ensures the even distribution of ink on the substrate, preventing ink buildup or uneven thickness. Repeated squeegee coating five times further increases the ink adhesion and uniformity, resulting in a sensitive layer with stable electrical properties.

[0058] Step 3: Slowly peel the printed substrate from the screen printing plate and allow it to cure at room temperature for 24 hours. Cut out a sensing unit, attach copper foil to both ends of it (the copper foil serves as the electrodes of the electrode sensor), then attach a protective film. Place the sensing unit in the center of the prepared perforated structure to complete the sensor fabrication.

[0059] like Figure 4 As shown in the figure, this diagram illustrates the schematic of a screen-printed sensor. Figure 4 (a) shows a schematic diagram of the sensor's deformation. Screen printing technology, as a high-precision material preparation process, can accurately construct stretchable strain sensors with specific microstructures. In practical applications, the sensor is attached to a silicone surface with a perforated structure. Silicone, due to its unique elasticity and flexibility, provides excellent mechanical cushioning and a suitable environment for the sensor. When external pressure is applied to the sensor surface, the mechanical conduction mechanism causes the sensor to deform. Specifically, when the sensor receives pressure, the mesh structure of the sensor's conductive layer is stretched. Geometrically, the sensor is elongated in the length direction and thinned in the thickness direction. According to the law of resistance, during this deformation process, the electron conduction path in the conductive layer becomes longer, while the cross-sectional area decreases. These two factors work together to cause a rapid increase in the sensor's resistance.

[0060] Figure 4(b) shows the equivalent circuit diagram of the sensor. From the perspective of the equivalent circuit, the conductive layer of the sensor is equivalent to an adjustable large resistor composed of multiple resistors R0 connected in series. The R0 resistor is composed of multiple small resistance units R1 and large resistance units R2. When the sensor is not under pressure, each resistance unit is in its initial state, and they are interconnected to form a specific resistance network. At this time, the equivalent resistance of the entire sensor is at a relatively stable reference value. When the sensor is subjected to pressure and deforms, the grid structure of the conductive layer changes, causing the resistance values ​​of each small resistance unit R1 and large resistance unit R2 to change. Due to the increased length and smaller cross-sectional area, the electron conduction resistance increases, and the resistance values ​​of these resistance units all increase. Furthermore, the connection relationship between the resistance units does not change during the deformation process, but due to the change in resistance value, the total resistance of the entire equivalent circuit also increases. This is consistent with the principle that physical geometric changes lead to an increase in resistance. Thus, the change in resistance in the circuit realizes the conversion and sensing of the electrical signal of the physical quantity of external pressure.

[0061] This invention focuses on multi-dimensional testing of the microstructure, ink compatibility, and core sensing performance of screen printing sensors, clarifying the correlation between process parameters and performance. The test content, methods, and conclusions are as follows.

[0062] 1. Microstructure testing Test content: sensor surface grid morphology, conductive filler distribution, and thickness of the printed film and conductive layer.

[0063] Test method: The mesh structure of different mesh counts (40-100 mesh) was observed using an optical microscope (Nikon Eclipse E200), and the surface / cross-sectional filler distribution and thickness were characterized using a scanning electron microscope (JSM-IT800).

[0064] Conclusion: The mesh diameter corresponding to 40-100 mesh screens is 510.10-206.74μm, and the higher the mesh number, the denser the mesh. Graphene and carbon nanotubes are uniformly dispersed in the substrate to form a conductive network. The substrate film thickness is 0.1mm, the conductive layer thickness is 34.1μm, and the overall thickness is thin (≈200μm). Low mesh screens are easy to form obvious meshes but few in number, while high mesh (>100 mesh) are prone to clogging due to high ink viscosity. 100 mesh screens balance the density of the conductive network and the uniformity of printing.

[0065] 2. Conductive ink printing performance test Test content: ink viscosity, storage modulus (G') and loss modulus (G"), to evaluate printability.

[0066] Test method: The shear rate-viscosity curve of 7-10wt% filler ink was measured using a rheometer (Anton Paar MCR 702), and the modulus change was analyzed by dynamic shear mode.

[0067] Conclusion: The higher the filler content, the greater the ink viscosity, and all inks exhibit "shear thinning" characteristics (viscosity decreases under high shear rates); under low shear stress, G'>G (the ink is elastic and has good shape retention), while under high shear stress, G”>G' (the ink is viscous and easily penetrates the screen); inks with 8wt% filler can balance elasticity and flowability, avoid blurring of printed patterns or clogging of holes, and are suitable for screen printing processes.

[0068] The results of the key performance tests are shown in Table 1.

[0069] Table 1

[0070] 3. Screen Printing Sensor Application Testing Test content: Verify the sensor's ability to recognize signals from different human activities (pressing, joint bending, foot / heel pressure) and evaluate its adaptability in foot monitoring scenarios.

[0071] Test method: The sensor was attached to the finger (press test), index finger joint (30°-90° bending), elbow joint (repeated bending), back of hand (clenching / releasing fist), and forefoot / heel respectively, and the voltage response curve was recorded.

[0072] Results: Different pressure levels corresponded to significantly different voltage peaks when the finger pressed, distinguishing pressure differences. As the index finger joint bending angle increased from 30° to 90°, the voltage increased in a stepwise manner (increased deformation led to increased resistance). Even with small deformation, the sensor still output a stable voltage signal when the elbow joint was bent and the hand was clenched into a fist. Significant differences in voltage peaks were observed between the forefoot and heel when pressure was applied (reflecting different force levels). Conclusion: The sensor exhibits good conformal adhesion, accurately identifying activity signals from multiple parts of the body, meeting the needs of pressure monitoring in different areas of the foot, and providing core component support for future intelligent insole arrays.

[0073] Two types of sensors were previously fabricated using the salt template method and screen printing method. Due to differences in structure, materials, and strain patterns, the sensors prepared by these two methods exhibit different performance characteristics. The performance characteristics of the two sensors are compared below to select a more suitable sensor for plantar pressure signal detection. By analyzing the skeletal structure and gait cycle of the human foot, the sensor array was designed, and the smart insole was integrated by combining a flexible PCB board with a silicone substrate. Through the acquisition and analysis of static and dynamic plantar signals from eight characteristic regions of the soles of different individuals, the characteristics of plantar pressure distribution in different people can be effectively detected, demonstrating the significant application value of this smart insole in meeting the needs of plantar pressure monitoring.

[0074] 1. Comparison and Selection of Sensors The characteristics of gait plantar pressure signals are strong signal strength, regionalized signal distribution, and significant individual differences. Therefore, sensors used to collect plantar gait signals need to have high sensitivity, fast response speed, and miniaturization. A comparison of the performance of porous microstructure sensors and screen-printed sensors is shown in Table 2; their key performance characteristics are as follows.

[0075] Table 2 Performance parameters of porous microstructure sensors and screen-printed sensors

[0076] Firstly, comparing the performance of the two sensors reveals that the porous microstructure sensor has higher sensitivity than the screen-printed sensor in the low-pressure range. However, as strain increases, the sensitivity of the porous microstructure sensor decreases compared to the screen-printed sensor. During the measurement of plantar pressure signals, the porous microstructure sensor cannot effectively distinguish plantar signals under high strain. Both sensors have the same response speed, but the recovery speed of the screen-printed sensor is superior to that of the porous microstructure sensor.

[0077] A comparison is made between the fabrication processes and arraying capabilities of the two sensor methods. The screen printing method is simpler than the salt template method, allowing for precise design of the sensor shape using a customized screen, facilitating mass production. The resulting sensors are thinner (approximately 200 μm), offering better fit and flexibility. Combined with a customized flexible PCB, they can be better arrayed for use on insoles. However, the porous microstructure sensors fabricated using the salt template method require leads from the top and bottom surfaces and are thicker than screen-printed sensors, making miniaturization and arraying difficult.

[0078] In summary, screen-printed sensors were selected for acquiring plantar pressure signals and were designed into an array.

[0079] Foot skeletal structure and gait analysis: The human foot is composed of 26 bones (7 tarsal bones, 5 metatarsal bones, and 14 phalanges). The tarsal bones (hindfoot) bear the core weight, the metatarsal bones (midfoot) support the arch and cushion impact, and the phalanges (forefoot) adjust the contact angle to maintain balance. These three bones work together to achieve functions such as walking and standing. This structural feature provides an anatomical basis for subsequent plantar zonation. The complete gait cycle includes the support phase (60%-65%, from heel strike to toe lift) and the swing phase (35%-40%, from toe lift to heel strike again), which is further subdivided into the initial stage of double-leg support (12%), single-leg support (38%), the final stage of double-leg support (12%), and the initial / mid / final stages of swing (10% / 14% / 14% each). This clarifies the dynamic changes in plantar pressure at different stages, providing a reference for sensor array layout and signal acquisition timing.

[0080] Foot measurement area division: Based on the foot bones and functions, the sole of the foot is divided into 8 areas (toe area, medial / middle / lateral metatarsal area, medial / lateral arch area, medial / lateral heel area), which can accurately locate pressure abnormalities (such as high pressure on the medial metatarsal area corresponding to hallux valgus), and assist in disease diagnosis and gait analysis.

[0081] Sensor Array Design: Based on the division of plantar pressure zones, sensors were systematically arranged for different areas of the sole. A 260mm × 101mm insole was designed using AutoCAD, integrating 42 10×10mm screen-printed sensors. 43 leads were designed using Altium Designer software. To simplify the PCB layout, the positive terminal of each sensor was led out separately, while the negative terminals were shared. Given that the metatarsal and heel areas account for 98% of plantar pressure, the sensors in these two areas were arranged more densely, with a 5mm spacing between adjacent sensors on the left and right sides, and a 10mm spacing between adjacent sensors on the top and bottom. In the arch area, the spacing between adjacent sensors on the top and bottom was 10mm, and the spacing between adjacent sensors on the left and right sides was 20mm. This array design integrates screen-printed sensing units onto a flexible printed circuit board (PCB) shaped like a custom insole. First, conductive silver paste is applied to the electrodes of each individual sensor. The screen-printed sensors are then attached to their corresponding positions on the PCB. Next, 502 glue is applied around the sensors to prevent slippage during testing and maintain stability. These steps are repeated to complete the sensor array arrangement. Finally, the flexible PCB is bonded to a 5 mm silicone substrate, completing the encapsulation of the smart insole.

[0082] Using a flexible PCB board as the electrode lead-out part of the sensor, the flexible PCB board has good flexibility. The screen-printed sensor is integrated on the flexible PCB board, and multiple sensors are integrated and arrayed. This reduces the complexity of multi-channel leads and effectively reduces the impact of the leads on the sensor signal acquisition.

[0083] Acquisition and analysis of plantar signals: Visual interface construction: The system is developed using PyQt, including login (to protect privacy), information entry (entering height / weight and associating with pressure analysis), data acquisition (Bluetooth connection, serial port configuration, data storage), and data display (8-area voltage curve) interfaces, realizing a closed loop of "acquisition-storage-analysis".

[0084] Static / Dynamic Pressure Measurement and Analysis: Ten volunteers were tested. In the static state (standing for 15 seconds), the plantar pressure was positively correlated with body weight (pressure of 20.6 kPa for a 92 kg tester). High arch (voltage in the arch area < 0.05 V) and flat feet (voltage in the arch area > 0.6 V) could be identified. In the dynamic state (walking), the voltage amplitude was 1.18-2.36 times that in the static state, and the higher the body weight, the higher the peak value. The voltage contour plot was plotted using Matlab to visually present the differences in pressure distribution.

[0085] Any part of this invention not described in detail can be referred to in the prior art or in the art known to those skilled in the art. This embodiment does not limit such part and will not describe it in detail here.

[0086] The embodiments of the present invention have been described above with reference to the accompanying drawings. However, the present invention is not limited to the specific embodiments described above. The specific embodiments described above are merely illustrative and not restrictive. Those skilled in the art can make many other forms under the guidance of the present invention without departing from the spirit and scope of the claims, and all of these forms are within the protection scope of the present invention.

Claims

1. A smart insole system for foot pressure monitoring, characterized in that, The system includes: The sensor array, composed of flexible sensors, is configured to sense real-time pressure at corresponding locations on the soles of the feet. Flexible PCB boards are configured to support and integrate the sensor array. The insole body is configured to hold a flexible PCB board. The data processing unit is configured to be electrically connected to the flexible PCB board to receive and analyze pressure data collected by the sensor array in real time.

2. The intelligent insole system for foot pressure monitoring according to claim 1, characterized in that, The flexible sensor is a screen-printed flexible sensor or a porous structure sensor using the salt template method.

3. The intelligent insole system for foot pressure monitoring according to claim 2, characterized in that, The fabrication process of the screen-printed flexible sensor includes: optimizing the conductivity of the ink by adding a conductive filler of a graphene and carbon nanotube composite system, preparing a stretchable flexible substrate to amplify the deformation of the sensitive unit, and then introducing a microstructure to fabricate a flexible sensor for measuring plantar pressure signals.

4. The intelligent insole system for foot pressure monitoring according to claim 3, characterized in that, The mass ratio of the graphene to the carbon nanotubes is 1:

1.

5. The intelligent insole system for foot pressure monitoring according to claim 2, characterized in that, The fabrication steps of the screen-printed flexible sensor include: S11: Conductive ink is prepared by using graphene and carbon nanotubes as conductive fillers, combined with carbon ester and silicone oil; curing agent and catalyst are added sequentially during the preparation process; S12: A sensor printing film is prepared by covering methyl vinyl silicone rubber containing a vulcanizing agent with a PTFE film and then cold-pressing and hot-pressing it. S13: A perforated silicone substrate is prepared by curing PDMS and a curing agent in a specific ratio. S14: Based on a screen printing stencil with a specific mesh size, a sensitive layer formed by the conductive ink is prepared on the sensor substrate film, and after being cut, it is encapsulated in the perforated silicone substrate to obtain the screen-printed flexible sensor.

6. The intelligent insole system for foot pressure monitoring according to claim 2, characterized in that, The preparation method of the porous structure sensor by the salt template method is as follows: NaCl is used as a pore-forming agent, which is blended with PDMS and carbon fiber. After hot pressing and curing, NaCl is dissolved to form a porous structure with a porosity that meets specific requirements. At the same time, sandpaper is used to construct micro-nano wrinkles on the surface to reduce the elastic modulus of the material. Graphene is coated onto the inner and outer surfaces of a porous structure using vacuum negative pressure impregnation technology to improve the continuity of the conductive network.

7. The intelligent insole system for foot pressure monitoring according to claim 6, characterized in that, The carbon fiber content is 10 wt%; The ratio of PDMS to NaCl is 1:6; The sandpaper has a mesh size of 60.

8. The intelligent insole system for foot pressure monitoring according to claim 2, characterized in that, The fabrication steps of the porous structure sensor using the salt template method include: S21: A mixture of PDMS, carbon fiber, NaCl and curing agent is placed on sandpaper of a specific mesh size and rolled, and then cured and dissolved in NaCl to obtain a conductive porous microstructure sensitive layer. S22: The prepared conductive porous microstructure sensitive layer is placed in a mixture of graphene and anhydrous ethanol, and dried under negative pressure to achieve the adhesion of graphene inside and on the surface of the porous microstructure. S23: The porous microstructure with graphene attached is cut and encapsulated in a thin film to obtain the porous structure sensor obtained by the salt template method.

9. The intelligent insole system for foot pressure monitoring according to claim 1, characterized in that, The sensor array is designed based on the foot skeletal structure and gait cycle.

10. The intelligent insole system for foot pressure monitoring according to claim 1, characterized in that, The sensor array comprises 42 10×10mm flexible sensors, mounted on a 260mm×101mm flexible PCB board; the negative electrodes of the 42 flexible sensors are connected together, while the positive electrodes are led out separately.

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