Temperature-controlled intelligent insole and control method thereof

Abstract

The application provides a temperature control intelligent insole and a control method thereof, the insole comprising a structural support layer, a heat dissipation layer, a temperature adjusting layer in which semiconductor refrigerators and heat preservation patches are alternately arranged, a uniform heating layer, a buffer layer, a temperature sensor, a main control board and a power supply unit. The main control board monitors data in real time through the temperature sensor, dynamically adjusts the working state of the semiconductor refrigerator in combination with a PID algorithm and a temperature change rate control algorithm, and realizes precise temperature control. Based on a multi-modal neural network, the user's foot temperature and change rate are predicted, and in combination with biomechanical models such as deformation of fat pads under thermal stress, Achilles viscoelasticity and accumulation of soft tissue fatigue, a constraint condition is established to optimize the temperature control curve, and the comfort and soft tissue performance are maximized. Through the cooperation of multiple layers of materials and intelligent control, the application solves the problems of uneven heat dissipation, complex structure and response lag of traditional temperature control shoes.

Description

Technical Field

[0001] This invention relates to the field of smart wearable technology, and in particular to a temperature-controlled smart insole and its control method. Background Technology

[0002] Diabetic foot ulcers are a serious complication of diabetes. Due to nerve damage and impaired blood circulation, patients have reduced sensitivity to temperature and pressure changes, making their feet more susceptible to external environmental influences and leading to tissue damage. Maintaining a suitable temperature environment is crucial for reducing the risk of diabetic foot ulcers. Temperature-controlled smart shoes have been proposed as an innovative assistive tool. Their core technology combines temperature regulation and intelligent temperature management. Equipped with high-precision temperature sensors and cooling / heating modules, the shoes sense and intelligently adjust the internal temperature in real time, ensuring the feet remain within a comfortable range. Simultaneously, their embedded control system can connect to mobile devices or cloud platforms, enabling real-time synchronization of patient foot health data. Users and doctors can view and remotely monitor foot conditions via mobile applications, providing personalized care plans for patients.

[0003] However, current temperature-controlled shoe technologies have several shortcomings. Firstly, some temperature-controlled shoe designs lack efficient heat dissipation structures, leading to reduced efficiency of the cooling elements due to heat buildup during long-term operation. This affects the performance of the cooling module, causing uneven temperature distribution within the shoe and increasing patient discomfort and the risk of ulcers. Secondly, some temperature-controlled shoes have complex internal structures, employing sealed fluid channels, heat exchange systems, pump structures, and other complex components. This not only increases the weight and complexity of the shoe, placing additional burden on the patient's feet and limiting its suitability for daily use, but also results in excessively high manufacturing and maintenance costs, hindering market promotion and accessibility. Furthermore, some temperature-controlled shoes have low levels of intelligence, only capable of passive temperature regulation and unable to dynamically adjust according to the patient's real-time needs or environmental changes. This weakens the ability of medical institutions to provide remote monitoring and personalized care to patients through these devices. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a temperature-controlled smart insole and its control method to eliminate or improve one or more defects existing in the prior art, and solve the problems of poor heat dissipation performance, complex structure and weak intelligence of existing temperature-controlled shoes.

[0005] One aspect of the present invention provides a temperature-controlled smart insole, comprising:

[0006] The structural support layer is cut to a preset shape to fit the user's foot shape;

[0007] A heat dissipation layer, the heat dissipation layer comprising a phase change material, wherein a copper sheet layer is disposed on the phase change material;

[0008] A temperature regulating layer is disposed on the heat dissipation layer, the temperature regulating layer comprising a plurality of alternately arranged heat insulation patches and a plurality of semiconductor coolers;

[0009] A heat spreader layer, disposed on the temperature regulating layer, is made of graphene material;

[0010] A buffer layer is disposed on the heat dissipation layer;

[0011] At least one temperature sensor is disposed within the buffer layer;

[0012] The main control board is located within the structural support layer and connects the semiconductor cooler and the temperature sensor.

[0013] A power supply unit is disposed within the structural support layer to supply power to the main control board and the plurality of semiconductor coolers.

[0014] In some embodiments, the main control board is provided with a wireless communication module for receiving temperature control commands and feeding back operating status information. The wireless communication module adopts a Bluetooth module, a ZigBee module, a Wi-Fi module, and / or a mobile network data communication module.

[0015] In some embodiments, the phase change material is an organic phase change material or an inorganic phase change material; the organic phase change material includes long-chain alkanes, fatty acids and their lipids; the inorganic phase change material includes inorganic hydrated salt compounds;

[0016] The long-chain alkanes include hexadecane or octadecane; the fatty acids and their esters include stearic acid or butyl stearate; the inorganic hydrated salts include sodium sulfate or calcium chloride hydrate.

[0017] In some embodiments, the phase change material is in the form of phase change microcapsule dry powder or phase change material microsphere powder.

[0018] In some embodiments, the insulation patch is made of polyurethane foam or polystyrene foam;

[0019] The structural support layer and the buffer layer are made of rubber or polymer buffer materials, including styrene-butadiene rubber or cis-butadiene rubber, and the polymer buffer materials include polyurethane, polyethylene, polypropylene or polystyrene.

[0020] In some embodiments, the temperature sensor is a patch type and is distributed in the buffer layer at equal intervals according to a set interval;

[0021] The main control board adopts a flexible circuit board structure; the power supply unit adopts a battery power supply or a self-powered mechanism. The self-powered mechanism consists of two piezoelectric ceramics and an intermediate layer. The intermediate layer is made of a metal sheet or a conductive composite material. The piezoelectric ceramics are arranged and bonded together in a polarity regularity to form a bicrystalline structure.

[0022] On the other hand, the present invention also includes a control method for the above-mentioned temperature-controlled smart insole, the method being executed based on a main control board, the method comprising the following steps:

[0023] Receive external commands to set the rated temperature of the insole;

[0024] Receive the real-time temperature of the insole from each temperature sensor at a fixed sampling rate;

[0025] Based on the real-time temperature of the insole and the rated temperature, control signals for each thermoelectric cooler are generated using a proportional-integral-derivative algorithm and a temperature change rate control algorithm, and then sent to the corresponding thermoelectric cooler for temperature control via a communication interface.

[0026] In some embodiments, the expression for temperature control using the proportional-integral-derivative algorithm is:

[0027] ;

[0028] in, The output signal of the controller represents the output power of the TEC drive circuit. Temperature error is the difference between the set value and the actual temperature. This is the proportionality coefficient. The integral coefficient is... These are the differential coefficients;

[0029] The expression for temperature control performed by the temperature change rate control algorithm is as follows:

[0030] ;

[0031] This indicates the rate of change of the output power of the temperature control element. The proportional coefficient representing the temperature rate control. The integral coefficient representing the temperature rate control. Indicates the maximum permissible rate of change. This indicates the current rate of temperature change.

[0032] In some embodiments, the method further includes:

[0033] Based on a preset temperature adjustment strategy, the system predicts the user's foot temperature and temperature change rate using a pre-trained multimodal neural network under specified user physiological characteristics and usage scenario characteristics.

[0034] Biomechanical performance indicators are calculated based on a soft tissue performance physical model, including the degree of deformation of the user's foot fat pad, the viscoelasticity of the Achilles tendon, and the degree of soft tissue fatigue.

[0035] Based on the biomechanical performance indicators and comfort boundaries, constraints are established. Under these constraints, the soft tissue performance index and comfort index are maximized, and the optimal temperature control curve is output.

[0036] The optimal temperature control curve is used to replace the rated temperature of the insole. Based on the real-time temperature of the insole and the optimal temperature control curve, control signals for each semiconductor cooler are generated using the integral-differential algorithm and the temperature change rate control algorithm.

[0037] In some embodiments, the multimodal neural network is based on bidirectional LSTM to capture dynamic temporal features.

[0038] The beneficial effects of the present invention are at least as follows:

[0039] The temperature-controlled smart insole and its control method described in this invention include a structural support layer, a heat dissipation layer, a temperature regulation layer, a heat equalization layer, a cushioning layer, a temperature sensor, a main control board, and a power supply unit. The phase change material in the heat dissipation layer works in conjunction with the copper sheet layer to effectively store and dissipate heat; the semiconductor cooler in the temperature regulation layer is alternately arranged with insulation patches to achieve precise temperature regulation; the heat equalization layer uses graphene material to ensure uniform heat distribution; the cushioning layer provides additional comfort and protection; the temperature sensor monitors the temperature in real time to ensure precise control; the main control board integrates a wireless communication module for easy remote monitoring and data transmission; the power supply unit can use a battery or a self-powered mechanism to improve energy efficiency. The control method receives external commands to set the rated temperature, combines real-time temperature feedback, and uses a PID algorithm and a temperature change rate control algorithm to generate control signals, precisely adjusting the working state of the semiconductor cooler to achieve dynamic temperature control of the insole. Furthermore, based on a preset temperature adjustment strategy, a multimodal neural network is used to predict the user's foot temperature and rate of change, combined with biomechanical performance model calculation indicators, to establish constraints, optimize the temperature control curve, and improve user comfort and soft tissue performance. This technical solution effectively addresses the shortcomings of existing temperature-controlled shoes in terms of heat dissipation, structural complexity, and level of intelligence, providing diabetic foot patients with an efficient, comfortable, and intelligent foot temperature management solution that significantly reduces the risk of foot ulcers and improves their quality of life.

[0040] Additional advantages, objects, and features of the invention will be set forth in part in the description which follows, and will also become apparent in part to those skilled in the art upon studying the description, or may be learned by practice of the invention. The objects and other advantages of the invention can be realized and obtained by means of the structures specifically pointed out in the specification and drawings.

[0041] Those skilled in the art will understand that the objectives and advantages achievable with this invention are not limited to those specifically described above, and that the above and other objectives achievable with this invention will become clearer from the following detailed description. Attached Figure Description

[0042] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, are not intended to limit the scope of the invention. The components in the drawings are not drawn to scale but are merely illustrative of the principles of the invention. For ease of illustration and description of certain parts of the invention, corresponding portions in the drawings may be enlarged, i.e., may appear larger relative to other components in an exemplary device actually manufactured according to the invention. In the drawings:

[0043] Figure 1 This is a schematic diagram of the structure of a temperature-controlled smart insole according to an embodiment of the present invention.

[0044] Figure 2 This is a schematic diagram of the working process of the intelligent temperature-controlled insole according to another embodiment of the present invention.

[0045] Figure 3 This is another embodiment of the intelligent temperature-controlled insole of the present invention.

[0046] Figure label:

[0047] 100: Structural support layer; 200: Heat dissipation layer; 300: Temperature regulation layer;

[0048] 301: Semiconductor cooler; 302: Thermal insulation patch; 400: Heat spreader layer;

[0049] 500: Buffer layer; 600: Temperature sensor; 700: Main control board;

[0050] 800: Power supply unit. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments and accompanying drawings. Here, the illustrative embodiments and descriptions of this invention are used to explain the invention, but are not intended to limit the invention.

[0052] It should also be noted that, in order to avoid obscuring the invention with unnecessary details, only the structures and / or processing steps closely related to the solution according to the invention are shown in the accompanying drawings, while other details that are not closely related to the invention are omitted.

[0053] It should be emphasized that the term "including / comprises" as used herein refers to the presence of a feature, element, step, or component, but does not exclude the presence or addition of one or more other features, elements, steps, or components.

[0054] It should also be noted that, unless otherwise specified, the term "connection" in this article can refer not only to a direct connection, but also to an indirect connection involving an intermediary.

[0055] In the following description, embodiments of the invention will be illustrated with reference to the accompanying drawings. In the drawings, the same reference numerals represent the same or similar parts, or the same or similar steps.

[0056] Current temperature-controlled shoe technologies still have several design shortcomings. First, heat dissipation of the cooling module is a major technological weakness. Some temperature-controlled shoe designs lack efficient heat dissipation structures, causing the cooling elements to significantly reduce efficiency due to heat accumulation during long-term operation. This insufficient heat dissipation not only affects the performance of the cooling module but may also lead to uneven temperature distribution within the shoe, thereby increasing foot discomfort and the risk of ulcers for patients. Secondly, the complexity of the internal structure of temperature-controlled shoes is a significant issue. Some designs employ complex components such as sealed fluid channels, heat exchange systems (e.g., TEC and fans), and pump structures. While this improves functionality, it also significantly increases the weight and complexity of the shoe. For diabetic foot patients, this complex design places additional burden on the feet, exacerbating pressure on ulcers or lesions, and also limiting the product's suitability for daily use. Furthermore, the high manufacturing and maintenance costs of complex structures directly impact the product's marketability and accessibility. Finally, some temperature-controlled shoes have a low level of intelligence, only achieving passive temperature regulation and failing to dynamically adjust according to the patient's real-time needs or environmental changes. This lack of intelligence and personalization not only reduces the product's appeal but also weakens healthcare institutions' ability to provide remote monitoring and personalized care to patients through the device.

[0057] In view of this, the present invention provides a temperature-controlled smart insole, comprising: a structural support layer 100, a heat dissipation layer 200, a temperature regulating layer 300, a heat equalization layer 400, a buffer layer 500, a temperature sensor 600, a main control board 700, and a power supply unit 800.

[0058] The structural support layer 100 serves as the basic structure of the insole and is made of rubber or polymer cushioning materials. Rubber cushioning materials include styrene-butadiene rubber or cis-butadiene rubber, while polymer cushioning materials include polyurethane, polyethylene, polypropylene, or polystyrene.

[0059] The heat dissipation layer 200 is composed of a phase change material and copper sheets. The layer can be a single piece or a distributed multi-piece structure, with the phase change material encapsulating the copper sheets. The phase change material absorbs heat through a phase change, storing the heat generated by the device. The copper sheets evenly distribute the heat from the upper layer, improving heat dissipation efficiency.

[0060] In some embodiments, the phase change material is an organic phase change material or an inorganic phase change material; the organic phase change material includes long-chain alkanes, fatty acids and their esters; the inorganic phase change material includes inorganic hydrated salt compounds. Long-chain alkanes include hexadecane or octadecane; fatty acids and their esters include stearic acid or butyl stearate; the inorganic hydrated salt compounds include sodium sulfate or calcium chloride hydrate.

[0061] In some embodiments, the phase change material is in the form of phase change microcapsule dry powder or phase change material microsphere powder. Using phase change material in the form of phase change microcapsule dry powder or phase change material microsphere powder can significantly improve the performance and user experience of temperature-controlled smart insoles. This form of phase change material has a large specific surface area, allowing for rapid absorption and release of heat, thereby improving the temperature regulation response speed of the insole. Simultaneously, they can be evenly distributed in the cushioning layer, enabling more uniform absorption, storage, and release of heat, avoiding localized temperature unevenness, and improving the temperature uniformity of the insole. Furthermore, the phase change microcapsules or microsphere powder have good mechanical strength, are not easily broken, effectively preventing phase change material leakage and maintaining the structural integrity and durability of the insole. This form of phase change material also possesses a certain degree of flexibility and elasticity, allowing for better conforming to the shape of the foot, providing a comfortable wearing experience, simplifying the production process, and reducing manufacturing costs.

[0062] A temperature-regulating layer 300 is disposed on the heat dissipation layer 200. The temperature-regulating layer 300 includes a plurality of alternately arranged thermal insulation patches 302 and a plurality of thermoelectric coolers 301. The alternating arrangement of the thermal insulation patches 302 and the thermoelectric coolers 301 can prevent temperature loss during heating and cooling processes. In some embodiments, the thermal insulation patches 302 are made of polyurethane foam or polystyrene foam.

[0063] The thermoelectric cooler 301, also known as a thermoelectric cooler (TEC), operates on the principle of the inverse Seebeck and Peltier effects. When a direct current passes through a thermocouple composed of two different semiconductor materials (typically P-type and N-type semiconductors), one end absorbs heat (cooling end) while the other releases heat (heating end). This is because the movement of charge carriers (electrons and holes) as current flows through the semiconductor material leads to heat transfer. In P-type semiconductors, holes are the dominant charge carriers, moving from the high-temperature end to the low-temperature end as current flows, carrying away heat; while in N-type semiconductors, electrons are the dominant charge carriers, moving from the low-temperature end to the high-temperature end, absorbing heat. This heat transfer causes one end of the thermoelectric cooler 301 to cool and the other end to heat, thus achieving a cooling effect.

[0064] In temperature-controlled smart insoles, a thermoelectric cooler 301 is used as the core temperature control element. By controlling the magnitude and direction of the current, the cooling or heating power of the thermoelectric cooler 301 can be adjusted, and its operating mode (cooling or heating) can be changed. When it is necessary to lower the insole temperature, the current flows through the thermoelectric cooler 301, causing its cooling end to absorb heat from the insole, thereby lowering the temperature; when it is necessary to raise the temperature, the direction of the current is changed, causing the heating end to release heat, thereby raising the insole temperature. The thermoelectric cooler 301 has advantages such as being noiseless, vibration-free, small in size, lightweight, highly reliable, and capable of precise temperature control, making it very suitable for application in wearable devices such as smart insoles where space and weight are limited.

[0065] The heat spreader layer 400, disposed on the temperature regulating layer 300, is made of graphene. Graphene has extremely high thermal conductivity, enabling it to quickly and evenly conduct and distribute the heat generated by the semiconductor cooler 301 across the entire insole surface, effectively preventing localized overheating or overcooling and ensuring uniform foot temperature and comfort. The graphene layer can be placed on top of the temperature regulating layer 300, in direct contact with it to maximize heat reception and conduction. The thickness of the graphene layer can be adjusted according to actual needs, generally between 0.1 and 2 mm, ensuring good heat spread without increasing the thickness and weight of the insole. Furthermore, the graphene layer can be combined with other materials or structures in the heat spreader layer 400, such as working in conjunction with copper sheets or phase change materials, to further improve heat conduction and storage efficiency.

[0066] A cushioning layer 500 is disposed on top of the heat-dampening layer 400. The cushioning layer 500 is made of rubber-based or polymer-based cushioning materials. Rubber-based cushioning materials include styrene-butadiene rubber (SBR) or butadiene rubber (BR), while polymer-based cushioning materials include polyurethane, polyethylene, polypropylene, or polystyrene. Rubber-based cushioning materials, such as SBR or BR, possess good elasticity, abrasion resistance, and shock absorption properties, effectively absorbing foot impact and providing a comfortable wearing experience. Polymer-based cushioning materials, including polyurethane, polyethylene, polypropylene, or polystyrene, not only have excellent cushioning performance but also allow for adjustments in density and thickness to meet the comfort requirements of different users. By rationally selecting and designing the materials and structure of the cushioning layer 500, the comfort and protection of the insole can be further enhanced above the heat-dampening layer 400, while maintaining the lightweight and durability of the entire insole system.

[0067] At least one temperature sensor 600 is disposed within the buffer layer 500. In some embodiments, the temperature sensor 600 is a patch type, and is distributed at equal intervals within the buffer layer 500 according to a set interval; the main control board 700 adopts a flexible circuit board structure; the power supply unit 800 adopts a battery-powered or self-powered mechanism, the self-powered mechanism consists of two piezoelectric ceramics and an intermediate layer, the intermediate layer is made of a metal sheet or a conductive composite material, and the piezoelectric ceramics are arranged and bonded together according to a regular polarity to form a bicrystalline structure.

[0068] The main control board 700 is disposed within the structural support layer 100 and connects the semiconductor cooler 301 and the temperature sensor 600. In some embodiments, the main control board 700 is provided with a wireless communication module for receiving temperature control commands and feeding back operating status information. The wireless communication module adopts a Bluetooth module, a ZigBee module, a Wi-Fi module, and / or a mobile network data communication module.

[0069] The power supply unit 800 is located inside the structural support layer 100 and provides power to the main control board 700 and multiple semiconductor coolers 301.

[0070] On the other hand, the present invention also includes a control method for temperature-controlled smart insoles, the method being executed based on a main control board 700, the method comprising the following steps S101~S103:

[0071] Step S101: Receive external instructions to set the rated temperature of the insole.

[0072] Step S102: Receive the real-time temperature of the insole from each temperature sensor 600 according to a fixed sampling rate.

[0073] Step S103: Based on the real-time temperature and rated temperature of the insole, control signals for each semiconductor cooler 301 are generated through proportional-integral-derivative algorithm and temperature change rate control algorithm, and sent to the corresponding semiconductor cooler 301 through the communication interface for temperature control.

[0074] The main control board 700 receives instructions from the user device via a wireless communication module to set the target temperature of the insole. Users can send instructions via mobile applications or other devices to set their desired foot temperature range. Multiple temperature sensors 600 distributed within the insole monitor the surface temperature of the insole in real time at a fixed sampling rate and send the data to the main control board 700 via GPIO ports. The main control board 700 receives this data and obtains the current temperature distribution of the insole. The main control board 700 compares the received real-time temperature with the rated temperature and calculates the error. Then, it uses a PID algorithm and a temperature change rate control algorithm to process the error and generate control signals. These signals are sent to the corresponding semiconductor cooler 301 via a communication interface to adjust its cooling or heating power, so that the insole temperature quickly and accurately reaches and maintains near the set value.

[0075] In some embodiments, the expression for temperature control using the proportional-integral-derivative algorithm is:

[0076] ;

[0077] in, The output signal of the controller represents the output power of the TEC drive circuit. Temperature error is the difference between the set value and the actual temperature. This is the proportionality coefficient. The integral coefficient is... These are the differential coefficients;

[0078] The expression for temperature control using the temperature change rate control algorithm is:

[0079] ;

[0080] This indicates the rate of change of the output power of the temperature control element. The proportional coefficient representing the temperature rate control. The integral coefficient representing the temperature rate control. Indicates the maximum permissible rate of change. This indicates the current rate of temperature change.

[0081] In some embodiments, the method further includes steps S201 to S204:

[0082] Step S201: Based on a preset temperature adjustment strategy, predict the user's foot temperature and temperature change rate using a pre-trained multimodal neural network under specified user physiological characteristics and usage scenario characteristics.

[0083] Step S202: Calculate biomechanical performance indicators based on the soft tissue performance physical model. The biomechanical performance indicators include the degree of deformation of the user's foot fat pad, the viscoelasticity of the Achilles tendon, and the soft tissue fatigue.

[0084] Step S203: Establish constraints based on biomechanical performance indicators and comfort boundaries, maximize the soft tissue performance index and comfort index under the constraints, and output the optimal temperature control curve.

[0085] Step S204: Replace the rated temperature of the insole with the optimal temperature control curve, and generate control signals for each semiconductor cooler 301 based on the real-time temperature of the insole and the optimal temperature control curve, using the integral-differential algorithm and the temperature change rate control algorithm.

[0086] In step S201, the user's physiological characteristics include gender, age, and shoe size, while the usage scenario characteristics include the type of shoes worn, the state of movement, and the ambient temperature. In some embodiments, the multimodal neural network captures dynamic temporal features based on a bidirectional LSTM and is pre-trained based on historical data, enabling it to predict the user's foot temperature and the rate of temperature change based on the user's physiological characteristics and usage scenario characteristics.

[0087] In step S202, the physical model of soft tissue performance includes a model of the degree of deformation of fat pad under thermal stress, a model of temperature-viscoelastic relationship curve of Achilles tendon fibers, and a soft tissue fatigue cumulative algorithm model.

[0088] A model for the degree of deformation of fat pads under thermal stress is used to quantify the effect of temperature changes on the deformation of foot fat pads. It can be implemented based on thermoelastic coupled finite element analysis (FEA). For example, a temperature-dependent hyperelastic material (such as the Mooney-Rivlin model) can be defined in COMSOL or Abaqus. Combined with the thermal expansion equation, the parameters of elastic modulus changing with temperature can be calibrated through experimental data to simulate soft tissue deformation at different temperatures.

[0089] The Achilles tendon fiber temperature-viscoelastic relationship curve model aims to describe the dynamic response of Achilles tendon viscoelasticity with temperature. It can be achieved by using the generalized Maxwell model combined with the time-temperature equivalence principle (WLF equation), obtaining Prony series parameters through dynamic mechanical analysis (DMA) experiments, constructing temperature-sensitive viscoelastic constitutive equations using MATLAB or FEBio, calculating stress relaxation and creep behavior at different temperatures, and verifying the temperature dependence of Achilles tendon fiber viscoelasticity through temperature-controlled tensile tests.

[0090] The soft tissue fatigue accumulation algorithm model is used to predict the fatigue damage accumulation of soft tissue under cyclic loading. It can be based on Miner's linear damage law or continuous damage mechanics (CDM), combined with rainflow counting method to extract the load spectrum, use SN curve (strain-life relationship) to calibrate fatigue parameters, and implement the damage accumulation algorithm through Python's pyFatigue library or nCode DesignLife. Specifically, the fatigue life equation can be calibrated through cyclic tensile testing of isolated soft tissue.

[0091] In step S203, the user's foot fat pad deformation degree, Achilles tendon viscoelasticity, and soft tissue fatigue are constrained by establishing thresholds to ensure user comfort.

[0092] Specifically, biomechanical constraints include ensuring that fat pad deformation does not exceed a safe threshold (e.g., Δ). d (max ≤ 10%), Achilles tendon viscoelastic modulus within the physiological range (e.g., E min≤ E ( T )≤ E (max) and fatigue accumulation value is below the critical value (e.g. D fatigue ≤1, based on Miner's law). Comfort constraints include temperature range limits (e.g., 25℃≤T(t)≤40℃) and temperature change rate limits (e.g., ... ).

[0093] The soft tissue performance index can be calculated using the following formula:

[0094] ;

[0095] in, w 1+ w 2+ w 3 = 1.

[0096] The comfort index can be calculated using the following formula:

[0097] ;

[0098] in, T ideal For ideal comfort temperature (e.g., 32°C) C α and β are empirical parameters that control temperature deviation and fluctuation penalties.

[0099] Transform it into a multi-objective optimization problem, expressed as:

[0100] ;

[0101] Here, γ is a trade-off factor between performance and comfort (e.g., γ increases during movement and decreases when at rest).

[0102] The optimal temperature control curve can be obtained by using a genetic algorithm or a particle swarm optimization algorithm.

[0103] In step S204, the adjustment is performed in accordance with the adjustment methods of steps S101 to S103.

[0104] The present invention will now be described with reference to a specific embodiment:

[0105] This embodiment develops a smart insole device with temperature control effect, and a closed-loop control system to control its temperature. The device can automatically cool and heat the feet of the user wearing the smart insole. The system is mainly suitable for diabetic foot patients, ensuring that the temperature of their soles is within the user's preset temperature or the appropriate temperature range predicted by the algorithm, so as to meet the patient's needs for preventing foot ulcers.

[0106] The temperature-controlled insole device consists of a TEC semiconductor chip that utilizes the Peltier effect to achieve heating and cooling functions, an intelligent adjustment circuit, a power supply, a temperature sensor, a phase change thermal storage material with a suitable phase change temperature, and a copper tube, forming a heat dissipation structure and an external shape structure.

[0107] Its specific working principle is as follows:

[0108] (1) Cooling and heating functions: These are achieved by a temperature control element, a heat spreader, a main control circuit, and a heat dissipation structure. The temperature control element is a thermoelectric cooler (TEC). This device is made using the Peltier effect of semiconductor materials. The principle of the Peltier effect is that when a direct current passes through a thermocouple composed of two semiconductors, one end heats up and the other end releases heat. Therefore, the TEC can achieve both cooling and heating, and its working efficiency and operating state are determined by the magnitude and direction of the current. Using a TEC device to achieve cooling and heating functions has the advantages of continuous operation and no noise or vibration during operation. The heat spreader can be made of materials such as graphene, which can quickly and evenly distribute heat to the entire surface to prevent the local temperature of the insole surface from being too high or too low. The main control circuit includes a microcontroller chip and peripheral peripherals and circuits to ensure the realization of the above-mentioned cooling and heating functions as well as the subsequent closed-loop control algorithm. The heat dissipation structure is composed of phase change heat storage material and a copper plate. Its purpose is to maintain the temperature of the non-working end of the cooling element, which is closely related to the working principle and efficiency of the cooling element.

[0109] (2) When the TEC wants to maintain a stable cooling and heating power, the temperature of its working end decreases or increases, while the non-working end changes in the opposite way. The principle is to keep the temperature difference between the two ends of the TEC semiconductor chip within a certain range. Therefore, if it is necessary to maintain the cooling or heating effect, it is necessary to ensure that the smart insole has good heat dissipation performance. In this invention, phase change materials and copper plates are used to ensure a stable heat dissipation rate. The phase change material has good energy storage efficiency and can store the heat generated by the non-working end when the TEC is cooling. This can ensure that the non-working end maintains a suitable temperature when the TEC is in the cooling and heating state. The main function of the plate is to transfer excess heat to the outside and achieve heat dissipation together with the phase change material.

[0110] (3) The closed-loop control function relies on the coordinated work of the temperature sensor, control circuit, TEC and the PID control algorithm in the main control unit to realize the function. In actual operation, the user sets the temperature range in advance, the temperature sensor monitors the temperature of the insole surface in real time, the main function of the main controller is to read the sensor data, run the PID algorithm, output PWM signal to control the output power of TEC, and TEC and its drive circuit adjust the output power and current direction input to TEC chip through H-bridge circuit.

[0111] (4) This smart insole can be paired with an intelligent algorithm on a host computer software to effectively improve the user's foot temperature environment and provide professional suggestions on the control temperature threshold range and rate of change. Improving the foot skin temperature and ambient temperature for young people and the elderly is of great significance for preventing foot diseases, improving the mechanical properties of foot soft tissues, and enhancing foot comfort. Foot comfort and the appropriate foot environment temperature for each user are closely related to the user's age, gender, shoe type, current exercise state, and foot temperature. Therefore, by predicting the thermal status of footwear under different variables and determining the appropriate foot temperature for users under different exercise states, the user's foot comfort and health when wearing shoes can be guaranteed. To achieve the above goals, this patent designs a multimodal intelligent optimization system that integrates biomechanical modeling and deep learning technology to achieve dynamic regulation of foot temperature and optimization of exercise comfort. The algorithm first collects basic user information, exercise state, and foot temperature time series data, combines environmental parameters to construct a standardized feature matrix, and uses interactive features such as age and exercise state to mine the foot temperature change pattern. While predicting temperature thresholds using a bidirectional LSTM neural network, a coupled physical model is used to analyze biomechanical properties such as fat pad deformation and Achilles tendon viscoelasticity changes under thermal stress. A multi-objective optimization algorithm is employed to balance maximizing soft tissue performance and minimizing discomfort index under multiple constraints such as biomechanical performance thresholds, skin tolerance, and shoe thermal conductivity. Ultimately, a personalized temperature control strategy is output to ensure the user's foot health and comfort.

[0112] Temperature control function implementation process

[0113] The main functional modules of temperature-controlled shoes can be divided into TEC cooling chips, intelligent adjustment circuits, power supply, temperature sensors, heat dissipation structures made of phase change materials and copper plates, and external shape structures. The modules that play the main temperature control function include temperature sensors for temperature monitoring, phase change materials and copper plates as heat dissipation structures, semiconductor cooling chips as cooling and heating modules, and the main control unit.

[0114] In actual operation, the user sets the surface temperature of the insole via Bluetooth or other communication methods. The temperature sensor receives the current surface temperature in real time and sends it to the main control unit through the GPIO port at a fixed sampling rate. After receiving the current temperature information, the main control unit uses a PID algorithm to take the difference between the input temperature signal and the rated temperature as the error, and uses the PID algorithm to generate a control signal for the TEC. The control signal is then sent to the TEC's drive circuit through the communication interface to achieve temperature control.

[0115] Phase change materials and heat dissipation structures such as copper plates passively fulfill their functions, ensuring the stable operation of the TEC and its drive circuit.

[0116] Implementation of temperature-based PID algorithm

[0117] The core of closed-loop temperature control is feedback control. To achieve this function, a set value, a sensor, a controller, an actuator, and a controlled object are required.

[0118] In this embodiment, the setpoint is the target temperature, the sensor is a temperature sensor (such as a thermistor, DS18B20, etc.) used to measure the current temperature in real time, the controller is the main control unit and its circuit, whose main function is to compare the setpoint and the actual value, calculate the error and generate a control signal, the actuator is a TEC cooling chip and its drive circuit, whose main function is to adjust heating or cooling according to the control signal; the controlled object is the surface temperature of the smart insole.

[0119] The PID (Proportional-Integral-Derivative) controller is the most common algorithm in temperature control, and its output formula is:

[0120] ;

[0121] in, The output signal of the controller represents the output power of the TEC drive circuit. Temperature error is the difference between the set value and the actual temperature. This is the proportionality coefficient. The integral coefficient is... These are the differential coefficients;

[0122] The closed-loop control process is as follows:

[0123] 1. Set the target temperature, i.e., the user inputs the target temperature.

[0124] 2. Temperature acquisition by the sensor: The sensor measures the current temperature in real time and converts it into a digital signal or an electrical signal.

[0125] 3. Calculation error: The controller calculates the error e(t).

[0126] 4. PID Calculation: The controller performs PID calculation based on the error to generate the control quantity u(t).

[0127] 5. Actuator adjustment: The control signal u(t) drives the actuator (such as a PWM-modulated heater or cooler) to adjust the system energy input.

[0128] 6. Feedback loop: The updated temperature is detected by the sensor again, and steps 2-5 are executed repeatedly until the actual temperature stabilizes near the set value.

[0129] Temperature-rate control based:

[0130] The main purpose of temperature change rate control is to limit the rate of temperature change, which can both suppress abrupt changes and adjust parameters to achieve control of different change rates, so as to realize the function of real-time regulation of the foot temperature change rate of temperature-controlled insoles. The controller implemented is similar to the temperature control mentioned above, using the difference between the expected temperature change rate parameter and the current temperature change rate as an error to control the output power of the TEC unit, so as to achieve the effect of regulating the temperature change rate.

[0131] The expression for temperature control using the temperature change rate control algorithm is:

[0132] ;

[0133] represents the rate of change of the output power of the temperature control element, represents the proportional coefficient in the temperature rate control algorithm, represents the integral coefficient in the temperature rate control algorithm, represents the maximum allowable rate of change, and represents the current rate of temperature change.

[0134] This embodiment also provides a software algorithm. The operation flow of the intelligent temperature-controlled insole system based on user data is shown in the figure below. It mainly consists of four modules.

[0135] A. User data input terminal

[0136] Users first provide personalized parameters such as gender, age, activity status, shoe type, and current foot temperature. The temperature sensor in the smart temperature-controlled shoe automatically detects the user's initial foot temperature, and this data will serve as the basis for predictions by the multimodal intelligent optimization system. The activity status may include variables such as activity intensity and type, while the shoe type involves characteristic parameters such as material breathability.

[0137] B. Multimodal intelligent optimization system algorithm analysis of the user's appropriate temperature control strategy

[0138] The collected user data is input into the host computer's software system. The software system uses a multimodal intelligent optimization model based on biomechanics and deep learning technology to perform dynamic foot temperature regulation strategies and sports comfort optimization analysis. It then outputs a personalized temperature control strategy suitable for the user's feet, which is stored in the host computer for the user to understand and sent to the smart temperature-controlled insole to guide the adjustment of the temperature regulation rate and expected threshold.

[0139] C. Intelligent temperature control system

[0140] Temperature-controlled insoles dynamically regulate temperature based on model-predicted parameters through semiconductor thermoelectric elements (TEC) or fluid circulation systems to achieve precise control of heating / cooling rates and steady-state maintenance after reaching the appropriate temperature.

[0141] D. Environmental optimization closed loop

[0142] The system continuously monitors the foot temperature environment, ultimately maintaining the foot under the recommended temperature control strategy provided by the multimodal intelligent optimization system, ensuring foot health and a suitable foot environment.

[0143] The method for predicting foot temperature changes and steady-state temperature is shown in the figure below. The model is established based on the relevant characteristic information of the subjects recruited in the experiment, and after coupling analysis of the changes in the viscoelasticity and energy absorption efficiency of the foot soft tissue under different states and foot temperatures. Its ultimate goal is to output a personalized temperature control curve for the temperature-controlled insole to the user. This curve can ensure that the user can dynamically regulate the foot temperature environment while maximizing the performance of the foot soft tissue and minimizing the discomfort index.

[0144] The intelligent temperature-controlled shoe of this invention can adjust the temperature of the insole surface in real time according to the user's settings, in order to help diabetic foot patients reduce the risk of foot ulcers and ensure the foot health of diabetic foot patients. Compared with the existing patent design, this invention not only uses TEC temperature control elements to simultaneously cool and heat, but also simplifies the overall structure by using phase change materials and copper plate passive heat dissipation, while ensuring the efficiency and effect of cooling.

[0145] Simultaneously, this invention designs a closed-loop control system paired with an intelligent temperature-controlled insole, and a multimodal intelligent optimization system based on biomechanics and neural network technology. This algorithm performs coupled analysis based on the user's current age, gender, shoe type, and exercise status, as well as changes in biomechanical properties such as the energy absorption efficiency of the fat pad and the viscoelasticity of the Achilles tendon under thermal stress. It outputs a personalized temperature control strategy for the insole while maximizing soft tissue performance and minimizing discomfort. Furthermore, the closed-loop control algorithm for temperature and temperature change rate within the insole ensures efficient execution of the temperature strategy provided by the intelligent optimization system, maintaining a suitable foot environment for the user under different exercise states and health levels, thus ensuring foot comfort and health.

[0146] In summary, the temperature-controlled smart insole and its control method of the present invention include a structural support layer, a heat dissipation layer, a temperature regulation layer, a heat equalization layer, a buffer layer, a temperature sensor, a main control board, and a power supply unit. The phase change material in the heat dissipation layer works synergistically with the copper sheet layer to effectively store and dissipate heat; the semiconductor cooler and insulation patches in the temperature regulation layer are alternately arranged to achieve precise temperature regulation; the heat equalization layer uses graphene material to ensure uniform heat distribution; the buffer layer provides additional comfort and protection; the temperature sensor monitors the temperature in real time to ensure precise control; the main control board integrates a wireless communication module for easy remote monitoring and data transmission; the power supply unit can use a battery or a self-powered mechanism to improve energy efficiency. The control method sets the rated temperature by receiving external commands, combines real-time temperature feedback, and uses PID algorithms and temperature change rate control algorithms to generate control signals, precisely adjusting the working state of the semiconductor cooler to achieve dynamic temperature control of the insole. Furthermore, based on a preset temperature adjustment strategy, a multimodal neural network is used to predict the user's foot temperature and rate of change, and combined with biomechanical performance models to calculate indicators, establish constraints, optimize the temperature control curve, and improve user comfort and soft tissue performance. This technical solution effectively addresses the shortcomings of existing temperature-controlled shoes in terms of heat dissipation, structural complexity, and level of intelligence, providing diabetic foot patients with an efficient, comfortable, and intelligent foot temperature management solution that significantly reduces the risk of foot ulcers and improves their quality of life.

[0147] Those skilled in the art will understand that the exemplary components, systems, and methods described in conjunction with the embodiments disclosed herein can be implemented in hardware, software, or a combination of both. Whether implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this invention. When implemented in hardware, it can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this invention are programs or code segments used to perform the desired tasks. The programs or code segments can be stored in a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried in a carrier wave.

[0148] It should be clarified that the present invention is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of the present invention is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of the present invention.

[0149] In this invention, features described and / or illustrated for one embodiment may be used in the same or similar manner in one or more other embodiments, and / or combined with or in place of features of other embodiments.

[0150] The above description is merely a preferred embodiment of the present invention and is not intended to limit the invention. For those skilled in the art, various modifications and variations can be made to the embodiments of the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the scope of protection of the present invention.

Claims

1. A temperature-controlled intelligent insole, characterized in that, include: The structural support layer is cut to a preset shape to fit the user's foot shape; A heat dissipation layer is disposed on the structural support layer and is formed by combining a phase change material and a copper sheet; the phase change material is an organic phase change material or an inorganic phase change material; the phase change material is in the form of phase change microcapsule dry powder or phase change material microsphere powder. A temperature regulating layer is disposed on the heat dissipation layer, the temperature regulating layer comprising a plurality of alternately arranged heat insulation patches and a plurality of semiconductor coolers; A heat spreader layer, disposed on the temperature regulating layer, is made of graphene material; A buffer layer is disposed on the heat dissipation layer; At least one temperature sensor is disposed within the buffer layer; The main control board is located within the structural support layer and connects the semiconductor cooler and the temperature sensor. The main control board adopts a flexible circuit board structure; A power supply unit is disposed within the structural support layer to supply power to the main control board and the plurality of semiconductor coolers; The main control board is used to perform the following operations: Receive external commands to set the rated temperature of the insole; Receive the real-time temperature of the insole from each temperature sensor at a fixed sampling rate; Based on the real-time temperature of the insole and the rated temperature, a control signal for each thermoelectric cooler is generated by a proportional-integral-derivative algorithm and a temperature change rate control algorithm, and then sent to the corresponding thermoelectric cooler for temperature control through a communication interface. The main control board is also used to perform the following operations: Based on a preset temperature adjustment strategy, a pre-trained multimodal neural network predicts the user's foot temperature and temperature change rate under specified user physiological characteristics and usage scenario characteristics; the multimodal neural network is based on bidirectional LSTM to capture dynamic temporal features; Biomechanical performance indicators are calculated based on a soft tissue performance physical model, including the degree of deformation of the user's foot fat pad, the viscoelasticity of the Achilles tendon, and the degree of soft tissue fatigue. Based on the biomechanical performance indicators and comfort boundaries, constraints are established. Under these constraints, the soft tissue performance index and comfort index are maximized, and the optimal temperature control curve is output. The optimal temperature control curve is used to replace the rated temperature of the insole. Based on the real-time temperature of the insole and the optimal temperature control curve, the temperature change rate control algorithm based on the integral-differential algorithm is used to generate control signals for each semiconductor cooler.

2. The temperature-controlled intelligent insole according to claim 1, characterized in that, The main control board is equipped with a wireless communication module for receiving temperature control commands and feeding back operating status information. The wireless communication module adopts a Bluetooth module, a ZigBee module, a Wi-Fi module and / or a mobile network data communication module.

3. The temperature-controlled intelligent insole according to claim 1, characterized in that, The organic phase change material includes long-chain alkanes, fatty acids and their lipids; the inorganic phase change material includes inorganic hydrated salt compounds. The long-chain alkanes include hexadecane or octadecane; the fatty acids and their esters include stearic acid or butyl stearate; the inorganic hydrated salts include sodium sulfate or calcium chloride hydrate.

4. The temperature-controlled intelligent insole according to claim 1, characterized in that, The insulation patch is made of polyurethane foam or polystyrene foam; The structural support layer and the buffer layer are made of rubber or polymer buffer materials, including styrene-butadiene rubber or cis-butadiene rubber, and the polymer buffer materials include polyurethane, polyethylene, polypropylene or polystyrene.

5. The temperature-controlled intelligent insole according to claim 1, characterized in that, The temperature sensor is a patch type and is distributed in the buffer layer at equal intervals according to a set interval. The power supply unit is powered by a battery or a self-powered mechanism. The self-powered mechanism consists of two piezoelectric ceramics and an intermediate layer. The intermediate layer is made of a metal sheet or a conductive composite material. The piezoelectric ceramics are arranged and bonded together in a regular polarity pattern to form a bicrystalline structure.

6. A control method for the temperature-controlled intelligent insole according to any one of claims 1 to 5, characterized in that, The method is executed based on the main control board and includes the following steps: Receive external commands to set the rated temperature of the insole; Receive the real-time temperature of the insole from each temperature sensor at a fixed sampling rate; Based on the real-time temperature of the insole and the rated temperature, a control signal for each thermoelectric cooler is generated by a proportional-integral-derivative algorithm and a temperature change rate control algorithm, and then sent to the corresponding thermoelectric cooler for temperature control via a communication interface. The method further includes: Based on a preset temperature adjustment strategy, the system predicts the user's foot temperature and temperature change rate using a pre-trained multimodal neural network under specified user physiological characteristics and usage scenario characteristics. Biomechanical performance indicators are calculated based on a soft tissue performance physical model, including the degree of deformation of the user's foot fat pad, the viscoelasticity of the Achilles tendon, and the degree of soft tissue fatigue. Based on the biomechanical performance indicators and comfort boundaries, constraints are established. Under these constraints, the soft tissue performance index and comfort index are maximized, and the optimal temperature control curve is output. The optimal temperature control curve is used to replace the rated temperature of the insole. Based on the real-time temperature of the insole and the optimal temperature control curve, control signals for each semiconductor cooler are generated using the integral-differential algorithm and the temperature change rate control algorithm.

7. The control method for temperature-controlled intelligent insoles according to claim 6, characterized in that, The expression for temperature control using the proportional-integral-differential algorithm is as follows: ； in, The output signal of the controller represents the output power of the TEC drive circuit. Temperature error is the difference between the set value and the actual temperature. This is the proportionality coefficient. The integral coefficient is... These are the differential coefficients; The expression for temperature control performed by the temperature change rate control algorithm is as follows: ； This indicates the rate of change of the output power of the temperature control element. This represents the proportional coefficient in the temperature rate control algorithm. This represents the integral coefficient in the temperature rate control algorithm. Indicates the maximum permissible rate of change. This indicates the current rate of temperature change.

8. The control method for temperature-controlled intelligent insoles according to claim 6, characterized in that, The multimodal neural network is based on bidirectional LSTM to capture dynamic temporal features.

Images