An intelligent sock for lower limb venous thrombosis risk monitoring

Abstract

The application discloses a lower limb venous thrombosis risk monitoring intelligent sock and relates to the technical field of medical devices.The application comprises a sock body, wherein the sock body is sequentially provided with an ankle monitoring area, a lower leg gastrocnemius muscle monitoring area and a popliteal fossa monitoring area from bottom to top;the ankle monitoring area is provided with a ring-shaped impedance electrode in a matched mode;four distributed pressure sensors and paired temperature sensors are arranged in a circumferential mode;three groups of sensor nodes are arranged in a triangular shape in the lower leg gastrocnemius muscle monitoring area, and the three groups of sensor nodes correspond to the medial head of gastrocnemius muscle, the lateral head of gastrocnemius muscle and the median intermuscular vein running area respectively.The application realizes the loop-level binding of the impedance electrode and the sock body through the yarn-increasing synchronous loop-forming process, cooperates with the self-pre-tightening suspended packaging sensor unit and the distributed redundant array design, realizes the automatic compensation of the sock body fitting degree when the sock body is slightly loose, realizes the effective data redundant backup when the sock body is moderately loose, and completely solves the core defects that the sensors of the existing wearable devices are prone to displacement, suspension and failure.

Description

Technical Field

[0001] This invention relates to the field of medical device technology, specifically to a smart sock for monitoring the risk of lower extremity venous thrombosis. Background Technology

[0002] Deep vein thrombosis (DVT) in the lower extremities is the third leading cause of cardiovascular disease death worldwide and can lead to fatal pulmonary embolism (PE). Early symptoms of DVT are often subtle (such as swelling and localized heat) and easily overlooked, but once a thrombus breaks off, it can be life-threatening.

[0003] Traditional diagnostic methods rely on ultrasound examinations or D-dimer testing, but cannot achieve continuous monitoring. The limitations of traditional solutions lie primarily in passive prevention; for example, graduated compression stockings promote venous return through physical pressure but cannot detect the risk of thrombosis. Anticoagulant drugs require regular monitoring of coagulation function and pose a risk of bleeding side effects. Manual observation, relying on patient self-reporting of symptoms or regular checks by healthcare professionals, is inefficient and prone to missed diagnoses. There is a lack of real-time and personalized monitoring; current methods cannot monitor lower limb blood flow in real time and cannot dynamically adjust prevention strategies based on individual risk. Traditional ultrasound equipment is bulky and unsuitable for wearable devices.

[0004] Existing wearable solutions have core flaws: Most publicly available DVT monitoring wearable devices use single-parameter monitoring (temperature or pressure only), resulting in poor specificity and a high false-positive rate in identifying early DVT pathological features; at the same time, the sensors are mostly mounted using a patch or weft-insertion method, without binding to the elastic substrate of the sock. After the sock is stretched, loosened, or washed, they are prone to displacement, suspension, and poor contact, leading to complete sensor failure and failing to meet the needs of long-term clinical wear; in addition, existing products are disconnected from the clinical diagnosis and treatment system, cannot connect to hospital information systems, and cannot provide medical staff with traceable clinical-grade monitoring data. Summary of the Invention

[0005] The purpose of this invention is to provide a smart sock for monitoring the risk of lower extremity venous thrombosis in order to solve the above problems.

[0006] To achieve the above objectives, the present invention specifically adopts the following technical solution: A smart sock for monitoring the risk of lower extremity deep vein thrombosis includes a sock body with an ankle monitoring area, a calf gastrocnemius muscle monitoring area, and a popliteal fossa monitoring area arranged sequentially from bottom to top. The ankle monitoring area is equipped with a ring impedance electrode and distributed pressure sensors and paired temperature sensors arranged at four points around the circumference. The calf gastrocnemius muscle monitoring area has three sets of sensor nodes arranged in a triangular pattern, corresponding to the medial head, lateral head, and median intermuscular vein course of the gastrocnemius muscle, respectively. The popliteal fossa monitoring area is equipped with a temperature sensor and a piezoelectric sensor. The impedance electrode is integrated with the main body of the sock using a single-sided double-yarn synchronous loop forming process. Each knitting needle simultaneously hooks the elastic ground yarn and the silver-plated spandex conductive yarn of the sock body to form a composite coil that is bound together. The silver-plated spandex conductive yarn is located on the skin contact surface inside the sock body. The outer side of the sock body is provided with a hardware processing module storage compartment, which contains a hardware processing module. The hardware processing module consists of a flexible microcontroller, a wireless transmission unit, a power management unit, and a micro vibration reminder unit. It also includes an intelligent early warning system, which consists of a user-end APP and a doctor-end management platform, and has a built-in multi-parameter fusion deep vein thrombosis risk assessment model and a three-level early warning mechanism.

[0007] Furthermore, the sock body has a segmented gradient pressure structure, woven from medical-grade anti-fading elastic fibers, with the pressure gradient decreasing sequentially from the ankle to the thigh. Specifically, the ankle section has a pressure of 20-30 mmHg, the calf section has a pressure of 15-25 mmHg, and the thigh section has a pressure of 8-15 mmHg. The mid-calf section and the cuff area of ​​the sock body are equipped with adjustable straps, and the cuff, popliteal fossa, and ankle areas of the sock body are equipped with medical-grade silicone anti-slip strips.

[0008] Furthermore, the sock body is provided with a thigh monitoring area, and the thigh monitoring area is provided with an impedance electrode and a ring pressure sensor, with the impedance electrode arranged in a semi-ring shape.

[0009] Furthermore, both the ring pressure sensor and the distributed pressure sensor employ flexible piezoresistive pressure sensing units. Their sensitive layer is a medical-grade silicone rubber membrane composed of graphene and carbon nanotubes, with a pyramid-shaped micro-protrusion array on the surface. The measurement range is 0-40 mmHg, the measurement accuracy is ±1 mmHg, and the resolution is 0.2 mmHg. The flexible piezoresistive pressure sensing unit is used to monitor changes in the gradient pressure of the sock and the contraction pressure of the gastrocnemius muscle, and to evaluate the muscle pump function.

[0010] Furthermore, the piezoelectric sensor employs a flexible piezoelectric blood flow sensing unit, with its sensitive layer being a biaxially stretched polarized PVDF piezoelectric film. The piezoelectric constant d33 ≥ 20 pC / N and the frequency response is 0.1-100 Hz. A conductive silicone coupling layer is composited on the skin-facing side of the PVDF film, and a silicone sound-insulating buffer layer is composited on the back side. The film is longitudinally arranged along the deep veins of the lower limbs to capture the pulsating vibration signal of the venous wall and infer changes in blood flow velocity.

[0011] Furthermore, the temperature sensor adopts a flexible NTC temperature sensing unit, whose sensitive layer is a nano-scale manganese cobalt nickel oxide thermosensitive slurry with a B value ≥3950K and a measurement accuracy of ±0.2℃. The sensing unit is fully covered with a nano-aerogel insulation layer except for the sensitive surface.

[0012] Furthermore, the sensor node includes a ring impedance electrode, a flexible piezoresistive pressure sensing unit, a flexible piezoelectric blood flow sensing unit, and a flexible NTC temperature sensing unit, with the four types of sensing units integrated into a standardized multi-parameter integrated sensor node.

[0013] Furthermore, the hardware processing module has a built-in wearable automatic start / stop unit. Through the cooperation of a Hall sensor and a permanent magnet in the storage compartment, it can realize automatic power-on when worn and automatic sleep mode when removed. The hardware processing module is IPX8 waterproof packaged, with a size of ≤3cm×2cm×0.5cm and a weight of ≤5g.

[0014] Furthermore, the microcontroller is electrically connected to all the ring impedance electrodes, flexible piezoresistive pressure sensing units, flexible piezoelectric blood flow sensing units, and flexible NTC temperature sensing units via a flexible conductive bus, and the flexible conductive bus is integrated with the sock body using a single-sided double-yarn synchronous loop forming process.

[0015] Furthermore, the three-level early warning mechanism of the intelligent early warning system is specifically as follows: Green low-risk status: All monitoring parameters are within ±10% of the user's normal baseline, and the system continuously monitors them; Yellow medium-risk warning: One or two monitoring parameters are abnormal, the risk score of deep vein thrombosis is moderate, triggering a single vibration of the sock and an APP push notification, and the data is synchronized to the doctor's terminal platform for observation; Red high-risk warning: Three or more monitoring parameters are abnormal at the same time, and the difference between parameters at the same location on both lower limbs exceeds the threshold, indicating a high risk score for deep vein thrombosis. This triggers high-frequency continuous vibration of the socks, strong reminders on the APP, and SMS notifications, which are simultaneously pushed to the attending physician.

[0016] The beneficial effects of this invention are as follows: 1. This invention is the first to realize a closed-loop integrated design of DVT prevention-monitoring-early warning-intervention, deeply integrating the clinical gold standard gradient pressure physical prevention function with multimodal thrombosis risk monitoring function, breaking the industry status quo of traditional elastic stockings and monitoring equipment being separate, solving the pain point that traditional elastic stockings cannot monitor the preventive effect, and filling the gap in long-term continuous monitoring of DVT outside the hospital.

[0017] 2. This invention achieves coil-level bonding between impedance electrodes and socks through a yarn-adding synchronous coiling process, with a deformation synchronization rate of ≥98%. Combined with a self-pre-tightening suspended encapsulated sensing unit and a distributed redundant array design, it achieves automatic compensation for fit when the socks are slightly loose and effective data redundancy backup when they are moderately loose, thus completely solving the core defects of existing wearable devices such as easy displacement, suspension, and failure of sensors.

[0018] 3. This invention constructs a four-parameter multimodal fusion monitoring system targeting the pathological mechanism of DVT. It simultaneously monitors four parameters: blood flow velocity, tissue impedance, muscle pump pressure, and local temperature difference, targeting four core pathological links of DVT: blood flow stasis, venous return obstruction, muscle pump function failure, and thrombotic inflammation. Through cross-validation of multi-dimensional data, it significantly improves the sensitivity and specificity of early warning of DVT. Preclinical validation shows a sensitivity of ≥95% and a specificity of ≥90%, which is far superior to existing single-parameter monitoring schemes. Attached Figure Description

[0019] Figure 1 This is a schematic diagram of the overall structure of the smart socks of the present invention; Figure 2 This is a schematic diagram of the sensor distribution inside the smart sock of the present invention.

[0020] Figure labels: 1. Sock body; 2. Ankle monitoring area; 3. Calf muscle monitoring area; 4. Popliteal fossa monitoring area; 5. Thigh monitoring area; 6. Hardware processing module storage compartment; 7. Impedance electrode; 8. Ring pressure sensor; 9. Temperature sensor; 10. Piezoelectric sensor; 11. Sensor node; 12. Distributed pressure sensor; 13. Paired temperature sensor. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings.

[0022] Example 1, as Figures 1-2 As shown, a smart sock for monitoring the risk of lower extremity deep vein thrombosis includes a sock body 1. From bottom to top, the sock body 1 has an ankle monitoring area 2, a calf gastrocnemius muscle monitoring area 3, and a popliteal fossa monitoring area 4. The ankle monitoring area 2 is equipped with a ring impedance electrode 7. Distributed pressure sensors 12 and paired temperature sensors 13 are arranged at four points around the circumference. The paired temperature sensors 13 are composed of two sensing units with a spacing of ≤2cm. They are paired and calibrated before leaving the factory, and the pairing temperature difference error is ≤0.1℃. The calf gastrocnemius muscle monitoring area 3 has three sets of sensor nodes 11 arranged in a triangular pattern, corresponding to the medial head, lateral head, and median intermuscular vein course of the gastrocnemius muscle, respectively. The popliteal fossa monitoring area 4 is equipped with a temperature sensor 9 and a piezoelectric sensor 10. The impedance electrode 7 is integrally knitted with the main body of the sock 1 using a single-sided double-layered yarn synchronous loop forming process. Each knitting needle synchronously hooks the elastic ground yarn and the silver-plated spandex conductive yarn of the sock 1 to form a one-to-one bound composite coil. The silver-plated spandex conductive yarn is located on the skin contact surface of the inner side of the sock 1. Impedance detection is achieved by monitoring changes in the volume of lower limb tissue fluid through bioelectrical impedance analysis (BIA), indirectly reflecting whether venous return is abnormal (thrombosis may cause local swelling). The core functional carrier of the impedance electrode 7 of this invention is the conductive fabric electrode itself, and the core material is knittable silver-plated spandex conductive yarn, which is fully compatible with knitting technology. Its measurement accuracy is highly dependent on the continuous, stable, and large-area ohmic contact between the electrode and the skin. Only by achieving coil-level binding through the yarn layering process can it be ensured that the electrode always synchronously adheres to the skin when the sock is loose or stretched, without drastic fluctuations in contact impedance or measurement inaccuracies. Only integrated yarn layering knitting can maintain the gradient pressure distribution of the sock and achieve a wearing effect without monitoring blind spots or foreign body sensation.

[0023] The outer side of the sock body 1 is provided with a hardware processing module storage compartment 6. The hardware processing module storage compartment 6 has a built-in hardware processing module, which consists of a flexible microcontroller, a wireless transmission unit, a power management unit, and a micro vibration reminder unit. It also includes an intelligent early warning system, which consists of a user-end APP and a doctor-end management platform, and has a built-in multi-parameter fusion deep vein thrombosis risk assessment model and a three-level early warning mechanism.

[0024] The sock body 1 has a segmented gradient pressure structure, made of medical-grade anti-degradation elastic fiber. The pressure gradient decreases from the ankle to the thigh, with 20-30 mmHg pressure at the ankle, 15-25 mmHg pressure at the calf, and 8-15 mmHg pressure at the thigh. Adjustable straps are provided in the mid-calf and cuff area of ​​the sock body 1. Medical-grade silicone anti-slip strips are provided at the cuff, popliteal fossa, and ankle of the sock body 1.

[0025] Both the ring pressure sensor 8 and the distributed pressure sensor 12 adopt flexible piezoresistive pressure sensing units. Their sensitive layer is a medical-grade silicone rubber membrane composed of graphene and carbon nanotubes, and the surface is provided with a pyramid-shaped micro-protrusion array. The range is 0-40 mmHg, the measurement accuracy is ±1 mmHg, and the resolution is 0.2 mmHg. The flexible piezoresistive pressure sensing unit is used to monitor the gradient pressure of the sock body 1 and the changes in gastrocnemius muscle contraction pressure to evaluate muscle pump function.

[0026] The piezoelectric sensor 10 uses a flexible piezoelectric blood flow sensing unit. Its sensitive layer is a biaxially stretched polarized PVDF piezoelectric film with a piezoelectric constant d33≥20pC / N and a frequency response of 0.1-100Hz. A conductive silicone coupling layer is composited on the side of the PVDF film facing the skin, and a silicone sound insulation buffer layer is composited on the back. It is longitudinally arranged along the deep veins of the lower limb to capture the pulsating vibration signal of the vein wall and infer changes in blood flow velocity.

[0027] Temperature sensor 9 uses a flexible NTC temperature sensing unit. Its sensitive layer is a nano-scale manganese cobalt nickel oxide thermosensitive slurry with a B value ≥3950K and a measurement accuracy of ±0.2℃. The sensing unit is fully covered with a nano-aerogel insulation layer except for the sensitive surface.

[0028] The sensor node 11 includes a ring impedance electrode 7, a flexible piezoresistive pressure sensing unit, a flexible piezoelectric blood flow sensing unit, and a flexible NTC temperature sensing unit. These four types of sensing units are integrated into the standardized multi-parameter integrated sensor node 11.

[0029] The hardware processing module has a built-in wearable automatic start / stop unit. Through the cooperation of Hall sensor and permanent magnet in the storage compartment, it realizes automatic power-on and automatic sleep mode when the wearer is taken off. The hardware processing module is IPX8 waterproof packaged, with a size of ≤3cm×2cm×0.5cm and a weight of ≤5g.

[0030] The microcontroller is electrically connected to all the ring impedance electrodes 7, flexible piezoresistive pressure sensing units, flexible piezoelectric blood flow sensing units, and flexible NTC temperature sensing units via a flexible conductive bus. The flexible conductive bus is integrated with the main body of the sock 1 using a single-sided double-yarn synchronous loop forming process.

[0031] The three-level early warning mechanism of the intelligent early warning system is as follows: Green low-risk status: All monitoring parameters are within ±10% of the user's normal baseline, and the system continuously monitors them; Yellow medium-risk warning: One or two monitoring parameters are abnormal, the deep vein thrombosis risk score is medium, triggering a single vibration of the sock and an APP push notification, and the data is synchronized to the doctor's terminal platform for observation; Red high-risk warning: Three or more monitoring parameters are abnormal at the same time, and the difference between parameters at the same position on both lower limbs exceeds the threshold, indicating a high risk score for deep vein thrombosis. This triggers high-frequency continuous vibration of the sock, strong reminder on the APP, and SMS notification, which are simultaneously pushed to the attending physician.

[0032] Usage steps: (1) Wearing self-test and baseline calibration: After the user wears the device, the system automatically starts a full sensor fit self-test. The flexible piezoresistive pressure sensing unit detects a pre-tightening force ≥2mmHg, the impedance electrode 7 detects a contact impedance ≤5kΩ, and the flexible piezoelectric blood flow sensing unit detects a signal-to-noise ratio ≥40dB. The self-test is then deemed to have passed. Subsequently, stable data of the user in a resting and lying position for 30 seconds is collected to establish a personal normal baseline. At the same time, the baseline control calibration of both lower limbs is completed.

[0033] (2) Multi-parameter synchronous data acquisition: The system continuously acquires data at a preset frequency, and the impedance electrode 7, flexible piezoresistive pressure sensing unit, flexible piezoelectric blood flow sensing unit, and flexible NTC temperature sensing unit are detected in real time.

[0034] (3) The microcontroller receives data. The microcontroller uses a flexible substrate, and the edges of the module are rounded to avoid friction. It processes the raw data in real time, packages it into a format suitable for transmission, and sends the data to the Bluetooth module via serial port. It connects to a mobile APP via Bluetooth to send data to the mobile phone / cloud. It can also support remote medical monitoring, display monitoring data in real time, and issue alarms when blood flow is abnormal or the risk of thrombosis increases. (4) Multi-parameter fusion risk assessment: Input the effective data into the multi-parameter fusion DVT risk assessment model, and assign the following weights: abnormal blood flow velocity 40%, abnormal muscle pump function 25%, abnormal tissue impedance 20%, and abnormal local temperature difference 15%. Calculate the comprehensive risk score through a weighted algorithm, and at the same time compare the data of both lower limbs to identify unilateral abnormalities. (5) Tiered early warning and clinical intervention: A comprehensive risk score of <30 points indicates a low risk level. The system will continuously monitor the risk and generate a monitoring report every two hours. A comprehensive risk score of 30-70 points indicates a yellow medium risk, triggering a single vibration of the sock and an APP push notification to guide the user to move their lower limbs and check the fit of the sock. The data is synchronized to the doctor's end for marking and observation, and the nursing staff completes the follow-up within two hours. If the comprehensive risk score is ≥70, it is considered a red high-risk condition, which triggers high-frequency vibration of the sock 1, strong APP reminder and patient / family SMS notification, and pushes to the attending physician and nurse station. It is recommended to complete the lower extremity venous ultrasound examination within two hours. The monitoring data is automatically synchronized to the patient's electronic medical record in the hospital HIS system. (6) Long-term trend management: The system continuously records users' long-term monitoring data, predicts the trend of thrombosis risk changes through machine learning models, provides users with personalized prevention suggestions, and provides clinical medical staff with a basis for DVT risk classification management.

[0035] Example 2, based on the above examples, further includes a thigh monitoring area 5 provided on the sock body 1, an impedance electrode 7 and an annular pressure sensor 8 provided on the thigh monitoring area 5, the impedance electrode 7 being arranged in a semi-circular shape.

[0036] This embodiment is a long tube-shaped product above the knee, suitable for high-risk patients with DVT such as those undergoing hip replacement, pelvic surgery, or severe trauma. Based on embodiment 1, a monitoring area is added to the lower thigh. Two sets of multi-parameter sensing nodes are arranged in the femoral vein area on the inner thigh, 12cm above the patella, and equipped with a ring pressure sensor 8 and a semi-ring impedance electrode 7. The thigh pressure is 8-15mmHg. The rest of the structure is the same as that of embodiment 1.

[0037] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A smart sock for monitoring the risk of lower extremity venous thrombosis, comprising a sock body (1), characterized in that, The sock body (1) is provided with an ankle monitoring area (2), a calf gastrocnemius muscle monitoring area (3) and a popliteal fossa monitoring area (4) from bottom to top. The ankle monitoring area (2) is equipped with a ring impedance electrode (7) and a distributed pressure sensor (12) and a pair of temperature sensors (13) are arranged at four points around the circumference. The calf gastrocnemius muscle monitoring area (3) is arranged with three sets of sensor nodes (11) in a triangular pattern, which correspond to the medial head, lateral head and median intermuscular vein course of the gastrocnemius muscle, respectively. The popliteal fossa monitoring area (4) is equipped with a temperature sensor (9) and a piezoelectric sensor (10). The impedance electrode (7) is knitted into a single-sided double-yarn synchronous looping process with the main body of the sock body (1). Each knitting needle simultaneously hooks the elastic ground yarn and the silver-plated spandex conductive yarn of the sock body (1) to form a composite coil that is bound one by one. The silver-plated spandex conductive yarn is located on the skin contact surface inside the sock body (1). The outer side of the sock body (1) is provided with a hardware processing module storage compartment (6). The hardware processing module storage compartment (6) is located between the calf gastrocnemius muscle monitoring area (3) and the popliteal fossa monitoring area (4). The hardware processing module storage compartment (6) contains a hardware processing module, which consists of a flexible microcontroller, a wireless transmission unit, a power management unit, and a micro vibration reminder unit. It also includes an intelligent early warning system, which consists of a user-end APP and a doctor-end management platform, and has a built-in multi-parameter fusion deep vein thrombosis risk assessment model and a three-level early warning mechanism.

2. The smart sock for monitoring the risk of lower extremity venous thrombosis according to claim 1, characterized in that, The sock body (1) has a segmented gradient pressure structure and is made of medical-grade anti-attenuation elastic fiber. The pressure gradient decreases from the ankle to the thigh. The ankle pressure is 20-30 mmHg, the calf pressure is 15-25 mmHg, and the thigh pressure is 8-15 mmHg. The mid-calf section and the cuff area of ​​the sock body (1) are provided with adjustable straps. The cuff, popliteal fossa, and ankle of the sock body (1) are provided with medical silicone anti-slip strips.

3. The smart sock for monitoring the risk of lower extremity venous thrombosis according to claim 1, characterized in that, The sock body (1) is provided with a thigh monitoring area (5), and the thigh monitoring area (5) is provided with an impedance electrode (7) and a ring pressure sensor (8). The impedance electrode (7) is arranged in a semi-ring shape.

4. The smart sock for monitoring the risk of lower extremity venous thrombosis according to claim 3, characterized in that, Both the ring pressure sensor (8) and the distributed pressure sensor (12) adopt flexible piezoresistive pressure sensing units. Their sensitive layer is a medical silicone rubber membrane composed of graphene and carbon nanotubes, and the surface is provided with a pyramid-shaped micro-protrusion array. The range is 0-40 mmHg, the measurement accuracy is ±1 mmHg, and the resolution is 0.2 mmHg. The flexible piezoresistive pressure sensing unit is used to monitor the gradient pressure of the sock body (1) and the changes in the gastrocnemius muscle contraction pressure to evaluate the muscle pump function.

5. The smart sock for monitoring the risk of lower extremity venous thrombosis according to claim 4, characterized in that, The piezoelectric sensor (10) adopts a flexible piezoelectric blood flow sensing unit. Its sensitive layer is a biaxially stretched polarized PVDF piezoelectric film with a piezoelectric constant d33≥20pC / N and a frequency response of 0.1-100Hz. The PVDF film is composited with a conductive silicone coupling layer on the side facing the skin and a silicone sound insulation buffer layer on the back. It is longitudinally arranged along the deep veins of the lower limbs to capture the pulsating vibration signal of the vein wall and infer the change in blood flow velocity.

6. The smart sock for monitoring the risk of lower extremity venous thrombosis according to claim 5, characterized in that, The temperature sensor (9) adopts a flexible NTC temperature sensing unit. Its sensitive layer is a nano-level manganese cobalt nickel oxide thermosensitive slurry with a B value ≥3950K and a measurement accuracy of ±0.2℃. The sensing unit is fully covered with a nano-aerogel insulation layer except for the sensitive surface.

7. The smart sock for monitoring the risk of lower extremity venous thrombosis according to claim 6, characterized in that, The sensor node (11) includes a ring impedance electrode (7), a flexible piezoresistive pressure sensing unit, a flexible piezoelectric blood flow sensing unit, and a flexible NTC temperature sensing unit. The four types of sensing units are integrated into a standardized multi-parameter integrated sensor node (11).

8. The smart sock for monitoring the risk of lower extremity venous thrombosis according to claim 1, characterized in that, The hardware processing module has a built-in wearable automatic start / stop unit. Through the cooperation of a Hall sensor and a permanent magnet in the storage compartment, it can realize automatic power-on and automatic sleep mode when the wearer is taken off. The hardware processing module is IPX8 waterproof packaged, with a size of ≤3cm×2cm×0.5cm and a weight of ≤5g.

9. The smart sock for monitoring the risk of lower extremity venous thrombosis according to claim 8, characterized in that, The microcontroller is electrically connected to all the ring impedance electrodes (7), flexible piezoresistive pressure sensing units, flexible piezoelectric blood flow sensing units, and flexible NTC temperature sensing units via a flexible conductive bus. The flexible conductive bus is integrated with the main body of the sock (1) using a single-sided double-yarn synchronous loop forming process.

10. The smart sock for monitoring the risk of lower extremity venous thrombosis according to claim 1, characterized in that, The three-level early warning mechanism of the intelligent early warning system is as follows: Green low-risk status: All monitoring parameters are within ±10% of the user's normal baseline, and the system continuously monitors them; Yellow medium-risk warning: One or two monitoring parameters are abnormal, the deep vein thrombosis risk score is medium, triggering the sock body (1) single vibration and APP push reminder, and the data is synchronized to the doctor's end platform for marking and observation; Red high-risk warning: Three or more monitoring parameters are abnormal at the same time, and the difference between parameters at the same position on both lower limbs exceeds the threshold. The risk score of deep vein thrombosis is high, triggering the sock body (1) high-frequency continuous vibration, strong APP reminder and SMS notification, which are simultaneously pushed to the attending physician.

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