Intelligent pressure sock capable of detecting pressure value

Abstract

The invention provides an intelligent pressure sock capable of detecting a pressure value, and relates to the technical field of pressure socks, the intelligent pressure sock comprises an intelligent pressure sock, the intelligent pressure sock carries a detection system, the intelligent pressure sock comprises an outer layer, a middle layer and an inner layer which are arranged in sequence, the outer layer, the middle layer and the inner layer are connected through a sewing method, the outer layer is an antibacterial nylon layer, and the middle layer is an antibacterial nylon layer. The middle layer is a medical-grade elastic fiber layer, the inner layer is a moisture-absorbing breathable fabric layer, a plurality of groups of flexible piezoresistive sensor sub-modules are arranged in the outer layer, a plurality of groups of electroactive polymer pressure sub-modules are arranged on the intelligent pressure sock, and the electroactive polymer pressure sub-modules are arranged on the outer layer. The intelligent pressure sock is further provided with a microcontroller module and a flexible battery sub-module. By combining the sensor and the microcontroller and introducing the machine learning model, the pressure change and the motion state of the user can be monitored in real time, the pressure is dynamically adjusted according to different activity requirements, the optimal pressure support is ensured, and the ulcer treatment effect is optimized.

Description

Technical Field

[0001] The present invention relates to the technical field of compression stockings, and in particular to intelligent compression stockings capable of detecting pressure values. Background Art

[0002] Venous ulcers are a common type of lower limb ulcer, typically occurring on the skin of the lower extremities, particularly the ankles and calves. They are chronic wounds caused by venous insufficiency or venous hypertension. The development of venous ulcers is closely related to long-term venous hypertension, which is often caused by venous valve failure or venous dilation, leading to poor blood return. Blood accumulates in the veins, which in turn adversely affects the skin and surrounding tissues, ultimately leading to ulcer formation.

[0003] The key to treating venous ulcers is to reduce venous hypertension in the lower limbs and promote blood return. To this end, using compression stockings and applying appropriate external pressure on the lower limbs can help venous blood flow back to the heart more smoothly, reduce venous hypertension, thereby reducing the occurrence of ulcers and improving the healing process.

[0004] Although traditional compression stockings can provide external pressure to help venous blood return, they have some shortcomings and fail to fully meet the needs of patients. For example, traditional compression stockings generally provide a fixed pressure value and are usually designed according to a standard pressure range. Although this fixed pressure design is effective in some cases, its therapeutic effect is not always ideal for every patient; secondly, traditional compression stockings usually adopt a static pressure distribution mode, that is, the stockings provide constant pressure and apply the same pressure on the entire leg or a specific area, which does not fully consider the blood flow needs of the lower limbs in different states (such as standing, walking, sitting, etc.); at the same time, traditional compression stockings cannot adjust the pressure accordingly according to the patient's activity state. Therefore, the present invention proposes a smart compression stocking that can detect pressure value to solve the problems existing in the prior art. Summary of the Invention

[0005] In response to the above problems, the purpose of the present invention is to propose a smart compression stocking that can detect pressure values. This smart compression stocking that can detect pressure values can monitor pressure distribution in real time, ensure therapeutic pressure, and has the advantage of dynamically adjusting pressure to adapt to user activities and body position changes, thereby solving the problems in the existing technology.

[0006] To achieve the purpose of the present invention, the present invention is implemented through the following technical solutions: a smart compression sock that can detect pressure values, including smart compression socks, the smart compression socks are equipped with a detection system, the smart compression socks include an outer layer, a middle layer and an inner layer arranged in sequence, the outer layer, the middle layer and the inner layer are connected by a suturing method, the outer layer is an antibacterial nylon layer, the middle layer is a medical-grade elastic fiber layer, the inner layer is a moisture-absorbing and breathable fabric layer, a flexible sensor module is provided in the outer layer, the flexible sensor module is composed of a flexible piezoresistive sensor sub-module and an acceleration sensor sub-module, the flexible piezoresistive sensor sub-modules are distributed in several groups, the smart compression socks are provided with an electroactive polymer pressure sub-module, and the electroactive polymer pressure module is provided in several groups, the smart compression socks are also provided with a microcontroller module and a flexible battery sub-module.

[0007] A further improvement is that the detection system includes:

[0008] a microcontroller module for processing and analyzing sensor data, controlling pressure regulation, and communicating with user equipment;

[0009] The flexible sensor module is used to collect user sensing data and feed the data back to the microcontroller module in real time;

[0010] a dynamic pressure regulation module, configured to adjust the local pressure of the smart socks based on the results of the microcontroller module analyzing the sensor data;

[0011] Power management module, used to provide power support for the detection system;

[0012] User interaction module, used to realize the interaction between the detection system and the user;

[0013] Cloud service module, used for long-term data storage and remote data access.

[0014] A further improvement is that the microcontroller module includes a low-power chip sub-module for processing sensor data, a wireless transmission sub-module for wirelessly transmitting data, a data storage sub-module for providing offline data storage function, and a machine learning sub-module for analyzing sensor data with a built-in machine learning model.

[0015] A further improvement is that the method for constructing the machine learning model is:

[0016] S1: Collect historical sensor data and perform preprocessing;

[0017] S2: Label the preprocessed data and divide it into training and test sets;

[0018] S3: Build a machine learning model based on the decision tree learning model, then train it using the training set and test it using the test set;

[0019] S4: After the test passes, the trained machine learning model is pruned and deployed.

[0020] A further improvement is that the flexible sensor module also includes a signal conditioning submodule for improving sensor accuracy.

[0021] A further improvement is that the dynamic pressure regulation module includes an electroactive polymer pressure submodule for deforming by applying an electric field and a control submodule for controlling current and voltage.

[0022] A further improvement is that the power management module includes a flexible battery submodule for using a flexible battery, a charging submodule for charging by wireless charging or by a magnetic interface, and an energy-saving management submodule for saving power consumption by a built-in energy-saving strategy.

[0023] A further improvement is that the built-in energy-saving strategy is: when the user is not in motion, the system adopts intermittent sampling, and when the user is in motion, the system adopts continuous sampling.

[0024] A further improvement is that the cloud service module includes a cloud data storage submodule for storing data in the cloud and a cloud data synchronization submodule for synchronizing data using cloud storage technology.

[0025] A further improvement is that the user interaction module includes a pressure display submodule for displaying a local pressure thermogram, a data analysis submodule for analyzing historical data, and a remote access interface submodule for providing remote access functions for doctors or other authorized personnel.

[0026] The beneficial effects of the present invention are:

[0027] (1) By combining sensors and microcontrollers and introducing machine learning models, the present invention can monitor pressure changes and the user's motion status in real time, dynamically adjust pressure according to different activity requirements, ensure optimal pressure support, and thus optimize the ulcer treatment effect;

[0028] (2) The present invention provides a more accurate and personalized pressure distribution by setting an electroactive polymer pressure submodule, and then ensures that the smart compression stockings can automatically adjust the pressure in different activity states (such as sitting and walking) through dynamic pressure regulation, avoiding excessive or insufficient pressure, thereby better promoting venous return and ulcer healing. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 It is a schematic structural diagram of the intelligent compression socks of the present invention.

[0030] Figure 2 It is a schematic diagram of the three-layer composite structure of the intelligent compression socks of the present invention.

[0031] Figure 3 It is a schematic diagram of the system structure of the present invention.

[0032] Among them: 1. Outer layer; 2. Middle layer; 3. Inner layer; 4. Flexible piezoresistive sensor submodule; 5. Acceleration sensor submodule; 6. Electroactive polymer pressure submodule; 7. Microcontroller module; 8. Flexible battery submodule. DETAILED DESCRIPTION

[0033] In order to deepen the understanding of the present invention, the present invention will be further described in detail below with reference to the examples. The examples are only used to explain the present invention and do not constitute a limitation on the scope of protection of the present invention.

[0034] according to Figure 1-Figure 3 As shown, this embodiment proposes a smart compression sock that can detect pressure values. The smart compression sock comprises an outer layer 1, a middle layer 2, and an inner layer 3, which are arranged in sequence. The outer layer 1, the middle layer 2, and the inner layer 3 are connected by stitching. The outer layer 1 is an antibacterial nylon layer that helps resist the growth of microorganisms such as bacteria and fungi, ensuring hygiene when the user wears the smart compression socks for extended periods. The middle layer 2 is a medical-grade elastic fiber layer that provides the necessary elastic support, thereby ensuring uniform pressure distribution while ensuring comfort. In addition, the medical-grade material ensures that the socks are skin-friendly and non-irritating, making them suitable for long-term wear and effectively supporting the feet, avoiding excessive pressure or looseness. The inner layer 3 is a moisture-absorbing, breathable fabric layer that effectively absorbs foot sweat while maintaining good ventilation to avoid discomfort caused by moisture, thereby keeping the feet dry and preventing skin problems such as athlete's foot or friction and inflammation caused by excessive moisture.

[0035] The outer layer 1 houses a flexible sensor module composed of a flexible piezoresistive sensor submodule 4 and an acceleration sensor submodule 5. The flexible piezoresistive sensor submodules 4 are arranged in several groups, the number of which is determined based on actual needs. These submodules are positioned at key points along the sock (e.g., ankle, gastrocnemius, lower thigh), creating a gradient-distributed sensor network that covers the venous return pathway (e.g., the great saphenous vein). Specifically, the sensor placement should be designed based on the pressure requirements at key points and the natural direction of blood return, ensuring a gradient pressure distribution that accurately reflects venous return. Taking the ankle, gastrocnemius, and lower thigh as examples, the design of the flexible piezoresistive sensor submodule 4's layout density is illustrated. First, because the ankle is more sensitive to pressure changes, 2 to 3 groups are deployed there. Second, 4 to 5 groups are deployed on the back of the calf (gastrocnemius) to ensure coverage of the entire gastrocnemius area and reflect changes in venous return pressure. Finally, 3 to 4 groups are deployed in the lower thigh to create a pressure gradient effect, ensuring that pressure gradually decreases from the thigh root to the knee, simulating the natural return path of venous blood. Thus, by monitoring pressure changes in the ankle, gastrocnemius, and lower thigh, the detection system can determine whether there are areas of excessively high pressure and adjust the pressure through the electroactive polymer pressure submodule 6 to reduce the pressure in the high-pressure area.

[0036] The flexible piezoresistive sensor submodule 4 is made of Velostat film or EeonTex conductive fabric to monitor pressure changes. These materials have excellent flexibility and sensing capabilities, making them well-suited for embedding into socks without affecting their comfort. Velostat film is soft and can change its resistance value according to changes in pressure, making it suitable for real-time pressure monitoring. EeonTex conductive fabric has good conductivity and flexibility and can be integrated into fabric without affecting wearer comfort. The acceleration sensor submodule 5 is used to detect changes in acceleration.

[0037] The smart compression socks are provided with an electroactive polymer (EAP) pressure submodule 6, and the electroactive polymer pressure submodule 6 is provided with several groups. For the electroactive polymer pressure submodule 6, it is annular in design and is a material that can change shape or size in response to electrical signals. In smart compression socks, its application can provide users with dynamically adjusted pressure. The electroactive polymer pressure can adjust the pressure of various parts of the socks through changes in voltage or current, thereby promoting blood flow and improving comfort. The working principle is: the electroactive polymer will deform (such as expand or contract) under the action of the electrical signal, which allows the pressure to automatically adjust the pressure of the surrounding area. For example, when current flows through the electroactive polymer pressure submodule 6, it will compress or expand, thereby changing the pressure of the socks on the skin.

[0038] In this embodiment, the electroactive polymer pressure submodule 6 is provided with three groups, which are respectively located at the ankle, calf and thigh, thereby promoting venous blood return and reducing edema and ulcers through gradient pressure (ankle> calf> thigh). The ankle is the starting point of venous return, and the pressure is usually higher. It is necessary to generate a larger pressure through the electroactive polymer pressure submodule 6 to promote the upward path of blood flow. The electroactive polymer pressure submodule 6 in the calf provides moderate pressure, which is slightly reduced relative to the ankle area, thereby ensuring smooth blood flow and avoiding compression. The electroactive polymer pressure submodule 6 in the thigh provides lower pressure, thereby forming a gradient pressure distribution, helping blood to flow smoothly back to the upper body, and preventing blood stagnation caused by poor venous return. Furthermore, based on the real-time data of the flexible piezoresistive sensor and the accelerometer, the smart compression socks can judge the static and dynamic state of the user and automatically adjust the current or voltage of the electroactive polymer pressure submodule 6.

[0039] The smart compression socks are also equipped with a microcontroller 7 and a flexible battery 8. The microcontroller 7 uses a low-power chip (such as ARM Cortex-M0+) and integrates a signal amplifier to filter motion noise. The flexible battery 8 uses a flexible lithium polymer battery (such as LG Chem's Curved Battery) and is embedded in the non-pressure area of the sock opening. This can not only avoid the battery's pressure on the foot, but also maintain the overall softness and comfort of the socks.

[0040] An intelligent compression sock capable of detecting pressure value, the detection system comprising:

[0041] Microcontroller module, used to process and analyze sensor data, control pressure regulation and communicate with user equipment, specifically:

[0042] The microcontroller module includes a low-power chip submodule for processing sensor data. The low-power chip is used to process sensor data in real time. This chip has a built-in signal amplifier that can enhance sensor signals and uses algorithms to filter motion noise to ensure data accuracy.

[0043] The wireless transmission submodule is used to transmit data wirelessly. It uses Bluetooth to transmit data from the microcontroller to the mobile phone app (compatible with iOS and Android) via Bluetooth, allowing users to view the data in real time.

[0044] The data storage submodule is used to provide offline data storage. When wireless communication is unavailable, the system can still store data for subsequent synchronization upload. The stored data includes pressure data and other related parameters, ensuring that the user's historical data will not be lost.

[0045] The machine learning submodule, which analyzes sensor data using built-in machine learning models, uses this model to analyze collected data and identify abnormal patterns (such as warnings of prolonged high-pressure conditions). It can also combine accelerometer data to determine the user's motion state (such as sitting still versus walking), and then adjust the corresponding strategy to ensure appropriate pressure is provided during sitting and walking.

[0046] The method for building a machine learning model is:

[0047] S1: Collect historical sensor data, namely pressure data and acceleration data, and perform preprocessing. Preprocessing involves normalizing the pressure and acceleration data to ensure that the dimensions of different sensor data are consistent, which facilitates model training.

[0048] S2: Label the preprocessed data and then divide it into training and test sets. Specifically, feature extraction is a key step in the machine learning model. Since low-power chips are used, the raw data needs to be converted into meaningful features. Then, the pressure data features are extracted, including average pressure (calculating the average pressure within a certain time window), pressure fluctuation (calculating the standard deviation of pressure changes and detecting pressure volatility), high-pressure duration (determining whether it is in a long-term high-pressure state by the duration of the pressure exceeding a certain threshold) and maximum and minimum pressure (extracting the maximum and minimum pressure values in each time window). Acceleration data feature extraction includes the mean and standard deviation of acceleration (measuring the user's exercise intensity through acceleration), gait cycle detection (detecting whether the user is walking through periodic changes in acceleration) and static period (identifying the sitting state by detecting fluctuations in acceleration values);

[0049] S3: Build a machine learning model based on a decision tree learning model. A decision tree is an efficient classification algorithm that can make decisions based on multiple features (such as the mean and standard deviation of pressure, acceleration characteristics, etc.). Because the decision tree itself has low computational complexity and strong interpretability, it can run on low-power chips. It can then be trained using a training set and tested using a test set.

[0050] S4: After the test passes, the trained machine learning model is pruned. Finally, the machine learning model inputs the output collected by the sensor, and the result is the current user status (sitting still, walking, long-term high pressure, etc.) and then deployed after processing. Then, after judging the status, the current / voltage of the electroactive polymer submodule is adjusted according to the status judgment result, and the pressure is adjusted to maintain the appropriate pressure range.

[0051] The flexible sensor module is used to collect user sensing data and feed the data back to the microcontroller module in real time. Specifically:

[0052] The flexible sensor module includes a flexible piezoresistive sensing submodule for monitoring pressure changes by detecting changes in the resistance of the material. The sensor monitors pressure changes by detecting changes in the resistance of the material and is suitable for areas where sensors need to be locally embedded in socks, such as the ankle, gastrocnemius muscle, and lower thigh.

[0053] The accelerometer submodule is used to detect acceleration. It works based on the principle of inertia and can determine the user's motion state (such as sitting, walking, running, etc.) by detecting changes in acceleration. When the accelerometer detects a state of almost no movement, the smart compression socks can adjust the pressure to reduce pressure when sitting and avoid unnecessary burden. When periodic fluctuations in acceleration are detected, the system can determine that the user is walking and then adjust the sock pressure to provide appropriate support to ensure user comfort.

[0054] The signal conditioning submodule used to improve sensor accuracy, combined with the signal amplification and filtering functions of the low-power chip, further enhances the sensor's accuracy, reduces the impact of motion interference on data, and ensures data accuracy.

[0055] The dynamic pressure regulation module is used to adjust the local pressure of the smart socks based on the results of the microcontroller module analyzing the sensor data. Specifically:

[0056] The dynamic pressure regulation module includes an electroactive polymer submodule that is deformed by an applied electric field. When the user needs more support, such as when walking, the electroactive polymer material can expand, increasing the pressure of the sock on the foot, calf or thigh, providing stronger support. When the user is sitting or resting, the electroactive polymer material will contract, thereby reducing local pressure and providing a comfortable wearing experience. Accordingly, before use, an initial pressure value range is preset according to the specific situation, that is, a fixed pressure range is set, and then this fixed pressure range is used as a standard for subsequent monitoring. If the actual measured pressure exceeds or falls below this set range, the pressure is automatically adjusted to maintain the target pressure.

[0057] The control submodule for controlling current and voltage receives control instructions from the microcontroller and changes the magnitude of local pressure by adjusting the current and voltage of the electroactive polymer submodule. The electroactive polymer submodule deforms according to the regulated current and voltage changes, thereby changing the pressure distribution of the socks to ensure comfort and effective venous return.

[0058] The power management module is used to provide power support for the detection system. Specifically:

[0059] The power management module includes a flexible battery submodule for using flexible batteries. The flexible lithium polymer battery (such as LG Chem's Curved Battery) is embedded in the non-pressure area of the sock opening. Accordingly, the lithium polymer battery has a higher energy density than traditional batteries and can provide power support for a longer time. Due to the high energy density of the battery, it can support the long-term operation of multiple submodules.

[0060] A charging submodule used for charging via wireless charging or magnetic interface. Wireless charging technology is based on the principle of electromagnetic induction, and provides energy to the built-in flexible battery through a wireless charging pad. The advantage of wireless charging is that users do not need to disassemble the device, and only need to place the socks on the charging pad to charge. The magnetic interface charging uses a magnetic connector to connect the charging cable to the socks to achieve charging. The magnetic connector usually uses magnetic material between the socket and the charging cable connector, and automatically connects through magnetic force, avoiding wear and tear on the socket and improper use. The specific charging method is set accordingly according to actual needs, and it can also have both.

[0061] The energy-saving management submodule is used to conserve power consumption through built-in energy-saving strategies to maximize battery life. The corresponding built-in energy-saving strategies are as follows: when the user is not exercising (sitting or resting), the system uses intermittent sampling, which reduces the data collection frequency, reduces the battery load, and extends battery life. When the user is in motion, the system uses continuous sampling, increasing the data sampling frequency to monitor the user's status changes in real time and perform precise pressure adjustments. By dynamically adjusting the sampling frequency based on the user's activity status, the energy-saving management submodule can effectively reduce unnecessary energy consumption and extend the use time of the smart compression socks.

[0062] The user interaction module is used to realize the interaction between the detection system and the user, specifically:

[0063] The user interaction module includes a pressure display submodule, which displays a local pressure heat map, showing the pressure distribution of the smart compression stockings in different areas. The colors of the heat map represent different pressure levels, and gradient colors (such as from blue to red) are usually used to indicate the change from low pressure to high pressure.

[0064] The data analysis submodule is used to analyze historical data. It is responsible for collecting, storing, and analyzing historical data of smart compression socks, especially pressure changes, user activity status (such as sitting or walking), and the implementation of pressure adjustment strategies. Through in-depth analysis of historical data, users and doctors can better understand the user's health status;

[0065] The remote access interface submodule provides remote access for doctors or other authorized personnel, allowing them to view the user's real-time and historical data. Through remote access, doctors can understand the patient's health status at any time and provide personalized guidance or adjustment suggestions.

[0066] Cloud service module, used for long-term data storage and remote data access, specifically;

[0067] The cloud service module includes a cloud data storage submodule for storing data in the cloud and a cloud data synchronization submodule for synchronizing data using cloud storage technology.

[0068] The smart compression stockings were tested for pressure accuracy to verify their pressure sensing system's ability to provide high-precision pressure monitoring and ensure that pressure errors remain within a reasonable range during use. Calibration was performed using a standard pressure source (such as a pressure test bench) to ensure the sensor accurately detects varying pressures. Known pressures were then applied to different areas (ankle, calf, and thigh), and the response of each sensor was checked and its output recorded. The results confirmed that the smart compression stockings met accuracy requirements (pressure variation error within ±2 mmHg).

[0069] The sensor durability test was then carried out by fixing the sensor on a stretching test device to simulate the stretching of the compression stockings during wear, and performing at least 5000 stretching-recovery cycles. After every 1000 stretching cycles, the pressure response of the sensor was checked to see if it still met the accuracy requirements (±2 mmHg). The experiment showed that the durability of the sensor in the present invention (≥5000 stretching cycles) met the requirements.

[0070] A clinical trial was then conducted, selecting 100 patients with venous ulcers for a 15-week trial. The control group received traditional compression stockings. The evaluation method involved observing the healing process of the ulcer wounds, recording the time from the start of treatment to complete healing. The evaluation was then conducted by measuring criteria such as wound area reduction, depth reduction, and wound closure. For the control group, the traditional compression stockings healed in 8 to 15 weeks, while the present invention healed in 4 to 10 weeks, demonstrating that the present invention can accelerate healing.

[0071] Based on the above, a recurrence rate test was conducted. After the clinical trial, patients were tracked for recurrence (i.e., the frequency of ulcer recurrence). Specifically, follow-up visits were conducted three to nine months after treatment to monitor recurrence. The monitoring showed a recurrence rate of 30% to 40% for traditional compression stockings, while the recurrence rate for the present invention was 15% to 30%. This indicates that the present invention significantly reduces the recurrence rate compared to the control group.

[0072] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above-described embodiments. The above-described embodiments and descriptions are merely illustrative of the principles of the present invention. Various changes and improvements may be made to the present invention without departing from the framework and scope of application of the present invention. Such changes and improvements are intended to fall within the scope of the present invention. The scope of protection claimed in the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart compression sock capable of detecting pressure values, comprising smart compression socks equipped with a detection system, characterized in that: The smart compression socks include an outer layer, a middle layer and an inner layer arranged in sequence, and the outer layer, the middle layer and the inner layer are connected by a suturing method. The outer layer is an antibacterial nylon layer, the middle layer is a medical-grade elastic fiber layer, and the inner layer is a moisture-absorbing and breathable fabric layer. A flexible sensor module is provided in the outer layer, and the flexible sensor module consists of a flexible piezoresistive sensor sub-module and an acceleration sensor sub-module. The flexible piezoresistive sensor sub-modules are distributed in several groups. The smart compression socks are provided with an electroactive polymer pressure sub-module, and the electroactive polymer pressure modules are provided in several groups. The smart compression socks are also provided with a microcontroller module and a flexible battery sub-module.

2. The intelligent compression socks capable of detecting pressure values according to claim 1, characterized in that: The detection system comprises: a microcontroller module for processing and analyzing sensor data, controlling pressure regulation, and communicating with user equipment; The flexible sensor module is used to collect user sensing data and feed the data back to the microcontroller module in real time; a dynamic pressure regulation module, configured to adjust the local pressure of the smart socks based on the results of the microcontroller module analyzing the sensor data; Power management module, used to provide power support for the detection system; User interaction module, used to realize the interaction between the detection system and the user; Cloud service module, used for long-term data storage and remote data access.

3. The intelligent compression socks capable of detecting pressure values according to claim 1, characterized in that: The microcontroller module includes a low-power chip submodule for processing sensor data, a wireless transmission submodule for wirelessly transmitting data, a data storage submodule for providing offline data storage function, and a machine learning submodule for analyzing sensor data with a built-in machine learning model.

4. The intelligent compression stockings capable of detecting pressure values according to claim 3, characterized in that: The method for constructing the machine learning model is: S1: Collect historical sensor data and perform preprocessing; S2: Label the preprocessed data and divide it into training and test sets; S3: Build a machine learning model based on the decision tree learning model, then train it using the training set and test it using the test set; S4: After the test passes, the trained machine learning model is pruned and deployed.

5. The intelligent compression socks capable of detecting pressure values according to claim 1, characterized in that: The flexible sensor module also includes a signal conditioning submodule for improving sensor accuracy.

6. The intelligent compression stockings capable of detecting pressure values according to claim 2, characterized in that: The dynamic pressure regulation module includes an electroactive polymer pressure submodule for deforming when an electric field is applied and a control submodule for controlling current and voltage.

7. The intelligent compression socks capable of detecting pressure values according to claim 2, characterized in that: The power management module includes a flexible battery submodule for using a flexible battery, a charging submodule for charging by wireless charging or by a magnetic interface, and an energy-saving management submodule for saving power consumption by a built-in energy-saving strategy.

8. The intelligent compression stockings capable of detecting pressure values according to claim 7, characterized in that: The built-in energy-saving strategy is: when the user is not in motion, the system adopts intermittent sampling; when the user is in motion, the system adopts continuous sampling.

9. The intelligent compression stockings capable of detecting pressure values according to claim 2, characterized in that: The cloud service module includes a cloud data storage submodule for storing data in the cloud and a cloud data synchronization submodule for synchronizing data using cloud storage technology.

10. The intelligent compression socks capable of detecting pressure values according to claim 2, characterized in that: The user interaction module includes a pressure display submodule for displaying a local pressure thermogram, a data analysis submodule for analyzing historical data, and a remote access interface submodule for providing a remote access function for doctors or other authorized personnel.

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