Artificial intelligence ankle brace

Abstract

This invention belongs to the technical field of sports protective equipment and intelligent rehabilitation wearable devices, specifically relating to an artificial intelligence ankle brace suitable for daily sports protection, postoperative rehabilitation of ankle injuries, fall prevention for middle-aged and elderly people, and real-time monitoring of ankle status in sports enthusiasts. It includes an elastic ankle brace body and a sensor array disposed in the inner layer of the elastic ankle brace body. The sensor array includes at least one tension sensor, at least one pressure sensor, at least one balance sensor, and at least one instability sensor. This invention achieves comprehensive, real-time, and accurate monitoring of tension, pressure, balance, and instability during ankle joint movement. It integrates functions such as automated signal acquisition and processing, adaptive threshold dynamic adjustment, intelligent recognition of multiple movement modes, real-time warning of exceeding limits, fall risk assessment, emergency call functionality, and synchronous upload and analysis of movement data, combining physical elastic protection with intelligent and accurate monitoring and early warning.

Description

Technical Field

[0001] This invention belongs to the technical field of sports protective equipment and intelligent rehabilitation wearable devices, specifically relating to an artificial intelligence ankle brace suitable for daily sports protection, postoperative rehabilitation of ankle injuries, fall prevention for middle-aged and elderly people, and real-time monitoring of ankle status for athletes. Background Technology

[0002] As the core joint of the lower limbs that bears weight and generates force during movement, the ankle joint is highly susceptible to injuries such as sprains, ligament strains, and joint sprains during daily walking, running, ball sports, fitness exercises, and postoperative rehabilitation activities due to uneven stress on the ankle joint, postural imbalance, excessive range of motion, and sudden instability. For people recovering from ankle surgery, middle-aged and elderly people with mobility issues, and high-intensity sports enthusiasts, the risk of secondary ankle injuries, falls, and loss of control over rehabilitation progress is significantly increased.

[0003] Currently, conventional ankle braces on the market only offer basic physical wrapping, elastic compression, and external support protection – simple mechanical protection functions. Their simple design relies solely on physical materials to limit ankle joint movement, failing to detect real-time tension changes, pressure values, balance status, and instability during ankle movement. They lack intelligent real-time monitoring capabilities. Furthermore, traditional ankle braces lack autonomous signal acquisition, data processing, and risk warning functions. They rely solely on the user's subjective perception to judge ankle joint movement, unable to accurately identify whether ankle movement exceeds safe limits, or provide early warnings when ankle instability is imminent, overload occurs, posture is abnormal, or the risk of fall increases.

[0004] Furthermore, existing ankle braces cannot adapt to the diverse needs of different users based on weight, exercise habits, and rehabilitation stages. The warning trigger conditions are fixed and cannot be adjusted dynamically. They cannot adapt to different exercise modes such as running, walking, rehabilitation training, and prolonged sitting or standing. They also cannot record core ankle joint movement data in real time, assess fall risk, or simultaneously upload monitoring data to external terminals. Rehabilitation therapists and users cannot intuitively grasp the real-time health status of the ankle joint, the accumulation of exercise load, and the progress of rehabilitation. It is difficult to achieve the integrated intelligent management requirements of ankle joint protection, real-time monitoring, risk warning, rehabilitation control, and data traceability. The protective targeting and intelligence level are extremely low, and the actual protection and rehabilitation assistance effects are poor. Summary of the Invention

[0005] This invention addresses the industry pain points and technical deficiencies of existing traditional ankle braces, which only provide single physical protection, lack intelligent sensing and monitoring capabilities, cannot identify ankle instability and abnormal stress states in real time, lack dynamic adaptive early warning functions, cannot adapt to different sports modes and rehabilitation stages, and lack data transmission and risk assessment mechanisms. It provides an AI-powered ankle brace that achieves comprehensive, real-time, and accurate monitoring of tension, pressure, balance, and instability during ankle movement. It integrates functions such as automated signal acquisition and processing, adaptive threshold dynamic adjustment, intelligent recognition of multiple sports modes, real-time warning of exceeding limits, fall risk assessment, emergency call functionality, and synchronous upload and analysis of sports data. Balancing physical elastic protection with intelligent and precise monitoring and early warning, it is suitable for various scenarios including general sports protection, post-operative rehabilitation training, and fall prevention for the middle-aged and elderly, effectively avoiding ankle sports injuries and the risk of secondary injuries from falls.

[0006] To address the aforementioned problems, the present invention proposes the following technical solution: an artificial intelligence ankle brace, comprising an elastic ankle brace body; and a sensor array disposed in the inner layer of the elastic ankle brace body, the sensor array including at least one tension sensor, at least one pressure sensor, at least one balance sensor, and at least one instability sensor; the sensor array is connected to a micro control unit via a flexible circuit, the micro control unit being connected to an early warning module; the micro control unit includes a signal acquisition module, a signal processing module, a threshold comparison module, and an early warning triggering module; the signal acquisition module is used to receive real-time signals from each sensor; the signal processing module is used to filter, amplify, and extract features from the acquired signals; the threshold comparison module is used to compare the processed signals with a preset threshold to determine whether they exceed a safe range; the early warning triggering module is used to trigger the early warning module to issue an early warning signal when the determination result indicates that the signal exceeds a safe range.

[0007] Furthermore, the tension sensor, pressure sensor, balance sensor, and instability sensor are evenly distributed in four directions: the front, back, medial, and lateral sides of the elastic ankle brace. Each direction has a set of sensors, and each set includes one tension sensor, one pressure sensor, one balance sensor, and one instability sensor. The tension sensor, pressure sensor, balance sensor, and instability sensor are all flexible thin-film sensors, which are made of one or more materials selected from conductive polymers, piezoelectric materials, or metal nanowires.

[0008] Furthermore, the micro control unit includes an adaptive threshold adjustment module and a motion pattern recognition module. The adaptive threshold adjustment module dynamically adjusts the preset threshold based on the user's historical motion data. The motion pattern recognition module is used to identify the user's current motion state and automatically adjust the warning triggering conditions based on the motion state. The micro control unit is also connected to a wireless communication module, which is used to transmit monitoring data to an external terminal device, including a mobile phone, tablet computer, smartwatch, or rehabilitation therapist terminal.

[0009] Furthermore, the warning module is one or more combinations of a vibrator, a buzzer, or an LED indicator, and the warning module is located in the control box on the outside of the elastic ankle brace body; the elastic ankle brace body is an integrated sleeve structure or a wrap-around buckle structure, and the wrap-around buckle structure uses one of Velcro, magnetic buckle, or snap fasteners for tightness adjustment; the bottom of the elastic ankle brace body is also provided with a plantar pressure sensor array, which is used to monitor plantar pressure distribution and gait characteristics.

[0010] Furthermore, the elastic ankle brace body is made of elastic fabric or elastic polymer material, the thickness of the elastic ankle brace body is 2mm-5mm, and the thickness of the sensor does not exceed 1mm.

[0011] Furthermore, the inner layer of the elastic ankle brace body is provided with a flexible fixation bag or adhesive layer for fixing the sensor, and the sensor and flexible circuit are detachably installed in the flexible fixation bag or adhesive layer; the outer side of the elastic ankle brace body is provided with a detachable control box, and the micro control unit and early warning module are located in the control box. The control box adopts a waterproof structure design with a waterproof rating of not less than IPX7.

[0012] Furthermore, the micro control unit also includes a rehabilitation stage identification module, which identifies the user's rehabilitation stage based on historical sensor data and adjusts the preset threshold accordingly. The micro control unit also includes a fall risk assessment module and an emergency call module. The fall risk assessment module assesses the user's fall risk level in real time, and the emergency call module automatically sends a distress signal upon detecting a fall. The micro control unit also integrates a positioning module, which acquires the user's real-time location information, and the distress signal sent by the emergency call module includes this real-time location information. The micro control unit further includes a motion performance analysis module, which analyzes and records one or more of the following motion indicators: ankle joint three-dimensional angle, angular velocity, peak ground reaction force, cumulative impact load, and muscle fatigue index.

[0013] Furthermore, the threshold comparison module employs a multi-sensor fusion judgment algorithm to calculate the instability index I = Σ(wi × Si), where Si is the normalized value of each sensor signal and wi is the corresponding weight coefficient. When the instability index I exceeds the preset threshold, an early warning is triggered.

[0014] Furthermore, the feature extraction performed by the signal processing module on the acquired signal includes one or more of the following: signal amplitude, rate of change, and spectral features. The signal processing module uses a low-pass filter to filter the signal, with a cutoff frequency of 15Hz-25Hz.

[0015] Furthermore, the warning triggering module triggers a warning when the judgment result is outside the safe range and the duration exceeds a preset time threshold, wherein the preset time threshold is 30ms-100ms.

[0016] Due to the adoption of the above technical solution, the beneficial effects of the artificial intelligence ankle brace of the present invention are as follows: 1. This invention abandons the traditional single physical protection mode of ankle braces. By deploying a multi-dimensional sensor array in the inner layer of the ankle brace, it collects real-time data on ankle joint tension, pressure, balance and instability from all directions. Combined with the plantar pressure sensor array to simultaneously monitor gait and plantar pressure distribution, it achieves accurate perception of ankle joint movement status in all dimensions, breaking through the technical bottleneck of traditional ankle braces without intelligent monitoring.

[0017] 2. The micro control unit of this invention integrates a multi-functional processing and control module, which can realize automated signal acquisition, filtering and amplification and feature extraction. Relying on the multi-sensor fusion judgment algorithm, it accurately calculates the instability index. Combined with adaptive threshold adjustment and motion pattern recognition functions, it dynamically adapts to the protection and monitoring needs of different users, different sports scenarios and different rehabilitation stages. The early warning triggering conditions are scientific and accurate, avoiding false early warnings and missed early warnings.

[0018] 3. This invention is equipped with a multi-faceted early warning module, which provides early warnings through vibration, buzzer, and light to promptly remind users to avoid dangerous movement postures. It also has fall risk assessment, location tracking, and emergency call functions, effectively reducing the risk of fall injuries to the elderly and rehabilitation populations, and significantly improving safety.

[0019] 4. The sensor and control box of this invention adopt a detachable modular design. The ankle support body structure can be selected to adapt to different wearing habits. The overall material is thin and fits well, and there is no foreign body sensation when wearing it. The waterproof level meets the standard and is suitable for daily sports and outdoor use scenarios.

[0020] 5. This invention can synchronously transmit monitoring data to various external terminals via a wireless communication module. Rehabilitation therapists and users can view ankle joint movement performance indicators, rehabilitation progress, and load accumulation in real time, realizing integrated protection, monitoring, early warning, rehabilitation management, and data traceability. Its intelligence, practicality, and adaptability are far superior to traditional ankle support products, and its market application and promotion value is extremely high. Attached Figure Description

[0021] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings: Figure 1 This is a three-dimensional view of an artificial intelligence ankle brace according to the present invention; Figure 2 This is a schematic diagram of the receptor distribution in an artificial intelligence ankle brace according to the present invention; Figure 3 This is a cross-sectional view of the sensor hierarchy structure in an artificial intelligence ankle brace according to the present invention; Figure 4 This is a circuit connection diagram of an artificial intelligence ankle brace according to the present invention; Figure 5 This is a flowchart of signal processing in an artificial intelligence ankle brace according to the present invention; Figure 6 This is a schematic diagram of adaptive adjustment during the rehabilitation stage of an artificial intelligence ankle brace according to the present invention.

[0022] Figure 7 This is a schematic diagram of a fall risk assessment model for an artificial intelligence ankle brace according to the present invention.

[0023] In the picture: 1. Elastic ankle support body; 2. Tension sensor; 3. Pressure sensor; 4. Balance sensor; 5. Instability sensor; 6. Control box. Detailed Implementation

[0024] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0025] The technical background of this application fully explains the problems of the prior art, and there are no overarching or general issues. The following description of the invention and specific embodiments will specifically describe the problems that this application needs to solve, clarify the technical problems that the technical solution needs to solve, and determine that the technical solution of this application has beneficial effects compared with the objective prior art.

[0026] This embodiment describes an artificial intelligence ankle brace, with its core load-bearing structure being an elastic ankle brace body 1, such as... Figure 1 As shown, A represents the front of the elastic ankle brace 1, B represents the inner side of the elastic ankle brace 1, C represents the outer side of the elastic ankle brace 1, and D represents the rear side of the elastic ankle brace 1. The elastic ankle brace 1 is made of elastic fabric or elastic polymer material in one piece, with an overall thickness controlled between 2mm and 5mm. It takes into account wearing comfort, elastic support and protection, and ease of wear, without restricting or interfering with normal ankle joint movement. The elastic ankle brace 1 can be selected with an integrated sleeve structure or a wrap-around buckle structure according to usage needs. The wrap-around buckle structure can adjust the tightness of the fit through Velcro, magnetic buckles, or clips to adapt to the wearing needs of people with different ankle sizes, making it highly versatile.

[0027] The inner layer of the elastic ankle brace 1 is specially designed with a flexible fixing bag or adhesive layer as a dedicated mounting and fixing structure for the sensor array. The sensor array and its matching flexible circuitry are installed inside the flexible fixing bag or adhesive layer using a detachable mounting method, making disassembly and assembly convenient. This facilitates future sensor inspection and replacement, as well as cleaning and maintenance of the ankle brace, making it easy to use and maintain. The sensor array includes at least one tension sensor 2, at least one pressure sensor 3, at least one balance sensor 4, and at least one instability sensor 5. All four types of sensors are made using flexible thin-film sensors with a thickness not exceeding 1mm. The materials used in the fabrication are one or more composites of conductive polymers, piezoelectric materials, or metal nanowires. The soft texture conforms to the skin of the ankle, providing a comfortable wearing experience without affecting normal ankle flexion, extension, rotation, and other routine movements.

[0028] To achieve comprehensive and accurate monitoring of the ankle joint, tension sensors 2, pressure sensors 3, balance sensors 4, and instability sensors 5 are evenly distributed along the four core force and movement directions: the front, back, medial, and lateral sides of the elastic ankle brace body 1. Each direction corresponds to a set of sensors, with each set consisting of one tension sensor 2, one pressure sensor 3, one balance sensor 4, and one instability sensor 5. This allows for comprehensive collection of data on tensile tension, compressive pressure, balance posture, and real-time instability fluctuations in all directions of the ankle joint, ensuring complete monitoring without blind spots and comprehensive and accurate data acquisition. Simultaneously, the bottom of the elastic ankle brace body 1 is equipped with a plantar pressure sensor array specifically designed to monitor the user's plantar pressure distribution and gait characteristics during daily walking and exercise, assisting in matching ankle joint movement status judgment and improving monitoring accuracy.

[0029] The sensor array is stably electrically connected to the microcontroller unit via flexible circuitry. The microcontroller unit is integrated into a detachable control box 6 located on the outside of the elastic ankle brace body 1. The control box 6 features a waterproof design with a waterproof rating of at least IPX7, effectively handling various scenarios such as outdoor sports, rainy days, and sweating, preventing damage to internal circuits and control components from moisture and extending the device's lifespan. A warning module is also installed inside the control box 6. This module uses one or more combinations of vibrators, buzzers, and LED indicator lights to provide multiple warning prompts, including vibration, sound, and visual alerts. These warnings are intuitive and easily noticeable, allowing users to quickly perceive abnormal ankle joint conditions and adjust their posture accordingly.

[0030] The micro-control unit serves as the intelligent core control center of this AI-powered ankle brace, with all functional modules working in tandem to complete the entire process of data processing and intelligent management. During normal wear and operation, the signal acquisition module continuously receives various raw analog signals from tension sensors 2, pressure sensors 3, balance sensors 4, instability sensors 5, and the plantar pressure sensor array, ensuring continuous and real-time data acquisition without data delay or disconnection. Subsequently, the signal processing module performs standardized preprocessing on the acquired raw signals, sequentially performing signal amplification, clutter filtering, and core feature extraction. The filtering operation uses a low-pass filter with a strictly limited cutoff frequency of 15Hz-25Hz to effectively filter out high-frequency interference clutter generated during movement. Signal feature extraction simultaneously acquires multiple core parameters, including signal amplitude, signal rate of change, and spectral characteristics, refining the effective monitoring signal and providing an accurate and reliable data foundation for subsequent data comparison and judgment.

[0031] The micro control unit serves as the intelligent core control hub of the device, integrating a signal acquisition module, signal processing module, threshold comparison module, early warning triggering module, adaptive threshold adjustment module, motion pattern recognition module, rehabilitation stage recognition module, fall risk assessment module, emergency call module, positioning module, and motion performance analysis module. These modules work collaboratively to achieve intelligent control throughout the entire process. The signal acquisition module continuously receives real-time raw signals from various tension sensors 2, pressure sensors 3, balance sensors 4, instability sensors 5, and the plantar pressure sensor array. The signal processing module performs unified filtering, amplification, and feature extraction on the received raw signals. The filtering stage uses a low-pass filter with a strictly controlled cutoff frequency between 15Hz and 25Hz. Signal feature extraction covers one or more of the following: signal amplitude, rate of change, and spectral characteristics, eliminating signal noise interference and ensuring the accuracy of subsequent data analysis.

[0032] The threshold comparison module employs a multi-sensor fusion judgment algorithm to perform data comparison and judgment. Specifically, the instability index is calculated using the formula I = Σ(wi × Si), where Si is the normalized value of the signal after processing by each sensor, and wi is the weighting coefficient set for the corresponding sensor. The threshold comparison module compares the calculated instability index I with the system's preset safety threshold in real time to accurately determine whether the ankle joint's movement exceeds the safe activity and force range. The adaptive threshold adjustment module can dynamically and intelligently adjust the system's preset threshold based on the user's long-term historical exercise data, combined with basic information such as the user's weight, exercise habits, and ankle tolerance, avoiding the problem of poor adaptability of fixed thresholds. The exercise mode recognition module can automatically identify the user's current walking, running, rehabilitation training, standing rest, and other different exercise states, and automatically match and adjust the warning trigger conditions accordingly to meet the protection needs of different exercise scenarios.

[0033] The rehabilitation stage identification module can automatically identify the different rehabilitation stages of ankle injury users, such as early postoperative rehabilitation, mid-term training rehabilitation, and late-term recovery exercise rehabilitation, based on long-term historical sensor monitoring data. It also simultaneously adjusts safety preset thresholds and warning standards to meet the full-cycle protection and monitoring needs of rehabilitation. The fall risk assessment module dynamically assesses the user's fall risk level in real time based on sensor data, accurately predicting potential fall hazards. The positioning module collects the user's precise location information in real time. When a sudden fall event is detected, the emergency call module automatically triggers and sends a distress signal carrying real-time location information, promptly pushing it to family members and rehabilitation therapists' terminals to ensure the user's personal safety. The motion performance analysis module analyzes and records in real time core motion indicators such as ankle joint three-dimensional angles, angular velocity, peak ground reaction force, cumulative impact load, and muscle fatigue index, comprehensively recording ankle joint motion health data.

[0034] The early warning trigger module employs a delayed trigger mechanism. It only issues a warning signal when the threshold comparison module determines that the ankle joint condition exceeds a safe range, and the abnormal state lasts for more than a preset time threshold of 30ms-100ms. This effectively avoids false warnings caused by instantaneous signal fluctuations or brief postural changes, ensuring accurate and reliable warning triggering. The micro-control unit is connected to a wireless communication module, which synchronously transmits all real-time monitoring data, motion indicators, rehabilitation data, and early warning records to external terminal devices such as mobile phones, tablets, smartwatches, or rehabilitation therapist terminals. This allows users to check their ankle condition in real time, and rehabilitation therapists to remotely monitor rehabilitation progress, combining intelligent protection with scientific rehabilitation management.

[0035] After preprocessing, the standardized signal is transmitted to the threshold comparison module. This module uses a multi-sensor fusion algorithm to perform a comprehensive analysis, calculating the instability index using the formula I = Σ(wi × Si). Here, Si is the normalized value of the processed signal from each sensor, and wi is the pre-matched weighting coefficient for each sensor. The weights are configured differently based on the varying forces and instability impacts on different ankle joint positions, precisely matching the actual force patterns of ankle movement. The threshold comparison module then compares the real-time calculated instability index I with the system's currently active preset safety threshold to accurately determine whether the ankle joint's real-time movement is within a safe force and range of motion.

[0036] Addressing the specific needs of post-operative rehabilitation patients, the rehabilitation stage identification module, relying on long-term accumulated historical sensor monitoring data, automatically and intelligently determines the user's different rehabilitation stages, such as early post-operative rest and rehabilitation, mid-term functional training rehabilitation, and late-term high-intensity recovery training. It simultaneously adjusts or raises the preset safety thresholds and warning standards accordingly, aligning with the gradual progression of rehabilitation training and avoiding secondary injuries caused by excessive weight-bearing during rehabilitation. The fall risk assessment module combines ankle joint posture data, plantar pressure distribution data, and body balance data in real time to dynamically classify and assess the user's real-time fall risk level, predicting potential falls in advance. When the device detects a sudden fall, the emergency call module immediately activates automatically, simultaneously retrieving the user's precise geographical location information collected in real time by the positioning module. A distress signal carrying location coordinates, basic user information, and fall alarm prompts is quickly pushed to family members' and rehabilitation therapists' terminals via wireless communication, enabling rapid emergency response in fall situations and comprehensively protecting the personal safety of elderly users and those undergoing rehabilitation.

[0037] The present invention and its embodiments have been described above. This description is not restrictive, and the accompanying drawings are only one embodiment of the present invention; the actual structure is not limited thereto. In conclusion, if those skilled in the art are inspired by this description and design similar structures and embodiments without departing from the spirit of the invention, such designs should fall within the protection scope of the present invention.

Claims

1. An artificial intelligence ankle brace, characterized in that, The device includes an elastic ankle brace body (1); and a sensor array disposed on the inner layer of the elastic ankle brace body (1), the sensor array including at least one tension sensor (2), at least one pressure sensor (3), at least one balance sensor (4), and at least one instability sensor (5); the sensor array is connected to a micro control unit via a flexible circuit, the micro control unit being connected to an early warning module; the micro control unit includes a signal acquisition module, a signal processing module, a threshold comparison module, and an early warning trigger module; the signal acquisition module is used to receive real-time signals from each sensor; the signal processing module is used to filter, amplify, and extract features from the acquired signals; the threshold comparison module is used to compare the processed signals with a preset threshold to determine whether they exceed the safe range; The warning triggering module is used to trigger the warning module to issue a warning signal when the judgment result is outside the safe range.

2. The artificial intelligence ankle brace according to claim 1, characterized in that: The tension sensor (2), pressure sensor (3), balance sensor (4), and instability sensor (5) are evenly distributed in the front, back, inner, and outer directions of the elastic ankle brace body (1). Each direction is provided with a set of sensors, and each set includes a tension sensor, a pressure sensor, a balance sensor, and an instability sensor. The tension sensor (2), pressure sensor (3), balance sensor (4), and instability sensor (5) are all flexible thin film sensors, which are made of one or more materials selected from conductive polymers, piezoelectric materials, or metal nanowires.

3. The artificial intelligence ankle brace according to claim 1, characterized in that: The micro control unit includes an adaptive threshold adjustment module and a motion pattern recognition module. The adaptive threshold adjustment module dynamically adjusts the preset threshold based on the user's historical motion data. The motion pattern recognition module is used to identify the user's current motion state and automatically adjust the warning triggering conditions based on the motion state. The micro control unit is also connected to a wireless communication module, which is used to transmit monitoring data to an external terminal device, including a mobile phone, tablet computer, smartwatch, or rehabilitation therapist terminal.

4. The artificial intelligence ankle brace according to claim 1, characterized in that: The warning module is one or more of a vibrator, a buzzer, or an LED indicator, and the warning module is located in the control box (6) on the outside of the elastic ankle brace body (1); the elastic ankle brace body (1) is an integrated sleeve structure or a wrap-around buckle structure, and the wrap-around buckle structure uses one of Velcro, magnetic buckle, or snap fastener for tightness adjustment; the bottom of the elastic ankle brace body (1) is also provided with a plantar pressure sensor array, which is used to monitor plantar pressure distribution and gait characteristics.

5. The artificial intelligence ankle brace according to claim 1, characterized in that: The elastic ankle support body (1) is made of elastic fabric or elastic polymer material, the thickness of the elastic ankle support body (1) is 2mm-5mm, and the thickness of the sensor does not exceed 1mm.

6. The artificial intelligence ankle brace according to claim 1, characterized in that: The inner layer of the elastic ankle brace body (1) is provided with a flexible fixing bag or adhesive layer for fixing the sensor, and the sensor and flexible circuit are detachably installed in the flexible fixing bag or adhesive layer; the outer side of the elastic ankle brace body (1) is provided with a detachable control box (6), and the micro control unit and the early warning module are located in the control box (6). The control box (6) adopts a waterproof structure design and the waterproof rating is not lower than IPX7.

7. The artificial intelligence ankle brace according to claim 1, characterized in that: The micro control unit also includes a rehabilitation stage identification module, which identifies the user's rehabilitation stage based on historical sensor data and adjusts the preset threshold accordingly. The micro control unit further includes a fall risk assessment module and an emergency call module. The fall risk assessment module assesses the user's fall risk level in real time, and the emergency call module automatically sends a distress signal upon detecting a fall. The micro control unit also integrates a positioning module, which acquires the user's real-time location information, and the distress signal sent by the emergency call module includes this real-time location information. Finally, the micro control unit includes a motion performance analysis module, which analyzes and records one or more of the following motion indicators: ankle joint three-dimensional angle, angular velocity, peak ground reaction force, cumulative impact load, and muscle fatigue index.

8. The artificial intelligence ankle brace according to claim 1, characterized in that: The threshold comparison module uses a multi-sensor fusion judgment algorithm to calculate the instability index I = Σ(wi × Si), where Si is the normalized value of each sensor signal and wi is the corresponding weight coefficient. When the instability index I exceeds the preset threshold, an early warning is triggered.

9. The artificial intelligence ankle brace according to claim 1, characterized in that: The signal processing module performs feature extraction on the acquired signal, including one or more of the following: signal amplitude, rate of change, and spectral features. The signal processing module uses a low-pass filter to filter the signal, with a cutoff frequency of 15Hz-25Hz.

10. An artificial intelligence ankle brace according to claim 1, characterized in that: The warning triggering module triggers a warning when the judgment result is outside the safe range and the duration exceeds a preset time threshold, which is 30ms-100ms.

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