Upper limb commonly used acupoint intelligent identification glove

Abstract

The application discloses an upper limb commonly-used acupoint intelligent recognition glove and belongs to the technical field of acupoint positioning auxiliary equipment. The glove comprises a glove body, a sensing unit array, an acupoint feedback unit array, a main control unit, a power supply module and a mobile terminal. The glove body is a three-layer composite structure, and from inside to outside, the three layers are a skin-friendly inner layer, a sensing circuit layer and a protective outer layer. The two types of units are integrated in the sensing circuit layer and electrically connected with the main control unit. The sensing unit array comprises a nine-axis inertial measurement unit, a flexible strain sensor, a tensile sensing belt and a piezoresistive pressure sensor. The acupoint feedback node is integrated with a miniature patch LED and a linear vibration motor, and a buffer pad is arranged on the inner side. The main control unit is internally provided with a bone degree and cun calibration module, a real-time attitude solution module and an acupoint matching driving module. The application can realize personalized acupoint selection, dynamic coordinate correction and in-situ multi-modal feedback and is suitable for home health care, traditional Chinese medicine training and rehabilitation physiotherapy scenes.

Description

Technical Field

[0001] This invention belongs to the technical field of acupoint positioning auxiliary equipment, and in particular relates to a smart glove for recognizing commonly used acupoints on the upper limbs. Background Technology

[0002] With the popularization of traditional Chinese medicine health preservation concepts, the audience for physiotherapy methods such as acupoint massage and moxibustion is becoming increasingly widespread. Acupoint location is the foundation of physiotherapy, and accurate acupoint selection is the core prerequisite for ensuring the effectiveness of physiotherapy.

[0003] Currently, acupoint assistive devices on the market mainly fall into three categories: resistive acupoint probes, which utilize the relatively low skin resistance at acupoints to scan and identify acupoint locations point by point using a metal probe. However, these devices are easily affected by factors such as skin humidity and stratum corneum thickness, resulting in a high false-judgment rate. Furthermore, they require point-by-point movement for detection, leading to low operational efficiency. AR visual acupoint systems, which use cameras to capture limb images, algorithms to identify bony landmarks, and then overlay acupoint maps for display. However, this approach relies on external display terminals, and tracking is easily lost during hand occlusion or rapid movements, significantly limiting its application scenarios. The third category is fixed acupoint gloves, which typically have massage electrodes, magnets, or vibrators set at fixed positions on a standard-sized glove, with preset acupoint locations. However, these products use a uniform, standardized layout and lack dynamic posture tracking mechanisms, resulting in a significant decrease in accuracy during dynamic use. In addition, most products rely on external devices for feedback mechanisms, failing to provide intuitive guidance at the acupoint location. Summary of the Invention

[0004] This invention provides a smart glove for recognizing common acupoints on the upper limbs, aiming to solve the problems of existing wearable acupoint devices lacking personalized calibration mechanisms, having poor positioning stability in dynamic scenarios, and failing to provide multimodal intuitive feedback for acupoint guidance and operation at the original acupoint location, thereby improving the ease of operation and comfort of use.

[0005] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A smart glove for recognizing common acupoints on the upper limbs includes a glove body, a sensor unit array, an acupoint feedback unit array, a main control unit, a power supply module, and a matching mobile terminal. The main control unit and the power supply module are integrated in an integrated box located in the arm section of the glove body. The sensor unit array and the acupoint feedback unit array are both integrated inside the glove body. The mobile terminal communicates wirelessly with the main control unit via Bluetooth.

[0006] The glove body features a full-finger extended structure, covering the area from the fingertips to below the elbow, completely covering the distribution area of ​​commonly used acupoints on the upper limbs. The gloves are available in left-hand and right-hand versions, respectively adapting to the mirror distribution of acupoints on the left and right upper limbs. The glove body adopts a three-layer composite structure, consisting of a skin-friendly inner layer, a sensing circuit layer, and a protective outer layer from the inside out.

[0007] The sensing unit array consists of a nine-axis inertial measurement unit, a resistive flexible strain sensor, a resistive flexible tensile sensing strip, and a piezoresistive flexible pressure sensor. All sensing elements are soldered and fixed to the flexible printed circuit board of the sensing circuit layer using SMT surface mount technology, and are electrically connected to the main control unit through copper foil lines on the board.

[0008] The nine-axis inertial measurement unit is set up in three locations: the middle of the metacarpal bone on the back of the hand, the midpoint of the transverse crease of the wrist, and the dorsal side of the middle section of the forearm. These correspond to the three rigid body segments of the hand, wrist, and forearm, and are used to collect spatial attitude data of each segment. A total of 8 resistive flexible strain sensors are provided, all of which are arranged on the back of the finger joints, with the length direction of the sensors perpendicular to the joint flexion and extension axis; 5 of them correspond to the metacarpophalangeal joints of the five fingers, and the remaining 3 correspond to the proximal interphalangeal joints of the index, middle and ring fingers, respectively, and are used to detect the bending angle of the finger joints. The resistive flexible tensile sensing strip is arranged along the limb to collect limb length and circumference data, providing a dimensional benchmark for bone measurement calibration. The piezoresistive flexible pressure sensors consist of six sensors, all with their sensing surfaces facing the skin. They are divided into two categories based on their function: three operation detection sensors, which are respectively placed on the inner side of the glove at the pads of the thumb, index finger, and middle finger, for collecting pressure data from active pressure points; and three acupoint detection sensors, which are respectively placed at the positions corresponding to the Hegu acupoint on the back of the hand, the Laogong acupoint on the palm, and the Daling acupoint on the palmar side of the wrist, for collecting acupoint contact pressure data.

[0009] The acupoint feedback unit array contains 20 acupoint feedback nodes, all soldered onto a flexible printed circuit board of the sensing circuit layer. The positions correspond to commonly used acupoints on the upper limbs in the national standard, and are arranged on the palmar and dorsal sides respectively. Each acupoint feedback node integrates a miniature LED patch and a miniature linear vibration motor. The miniature LED patch is located on the outermost side of the sensing circuit layer, and the miniature linear vibration motor is located on the side of the sensing circuit layer closer to the skin. A cushioning pad is embedded in the skin-friendly inner layer below each acupoint feedback node to improve the comfort of pressing.

[0010] The main control unit uses a low-power Bluetooth system-on-a-chip, which stores and runs three core program modules: The bone measurement calibration module is used to generate a user-specific upper limb acupoint coordinate model based on the bone measurement method, according to the bony landmark movement data collected by the sensor unit array. The real-time attitude calculation module is used to fuse real-time data from the nine-axis inertial measurement unit and the resistive flexible strain sensor to calculate the attitude of each joint of the upper limb and dynamically correct the relative coordinates of each acupoint. The acupoint matching and driving module has a built-in national standard acupoint database. It is used to locate the corresponding acupoint feedback node according to the target acupoint instruction and output the acupoint selection guidance signal. At the same time, it outputs the pressure quality feedback signal according to the data of the piezoresistive flexible pressure sensor.

[0011] Furthermore, the sensing circuit layer adopts a 0.2mm thick segmented double-layer flexible printed circuit board with polyimide as the substrate. The two layers are bonded together with insulating adhesive, and interlayer electrical connection is achieved through metallized vias.

[0012] Furthermore, the skin-friendly inner layer is made of highly elastic and breathable Lycra fabric, and the protective outer layer is made of waterproof and wear-resistant polyurethane fabric.

[0013] Compared with the prior art, the beneficial effects of the present invention are as follows: Based on the bone measurement method of traditional Chinese medicine, a personalized acupoint coordinate model is generated by combining limb size data collected by sensor array; through real-time posture calculation by multi-sensor fusion, the relative coordinates of acupoints can be dynamically corrected according to joint movement, avoiding acupoint displacement caused by fabric shift, and maintaining positioning accuracy even in normal hand activity. The acupoints are equipped with integrated light and vibration feedback, allowing users to locate and press acupoints without needing to look at external devices, completely freeing their hands. The acupoints are also equipped with cushioning pads to effectively reduce the discomfort of hard objects when pressing, improving wearing comfort. Attached Figure Description

[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments are briefly introduced below.

[0015] Figure 1 This is a schematic diagram of the glove body according to Embodiment 1 of the present invention; Figure 2 This is a partial cross-sectional view of the glove body according to Embodiment 1 of the present invention; Figure 3 This is a schematic diagram of the back of the hand of the sensing circuit layer in Embodiment 1 of the present invention; Figure 4 This is a schematic diagram of the palm side of the sensing circuit layer in Embodiment 1 of the present invention; Figure 5 This is a flowchart of the bone measurement calibration process in Embodiment 1 of the present invention; Figure 6 This is a flowchart of the acupoint location and feedback process in Embodiment 1 of the present invention.

[0016] The structural names represented by the labels in the attached diagram are as follows: 1-Glove body, 101-Skin-friendly inner layer, 102-Sensing circuit layer, 103-Protective outer layer, 2-Nine-axis inertial measurement unit, 3-Resistive flexible strain sensor, 4-Resistive flexible tensile sensing band, 5-Pierre resistance flexible pressure sensor, 6-Acupoint feedback node, 601-Miniature patch LED, 602-Miniature linear vibration motor, 7-Cushioning pad, 8-Integrated box. Detailed Implementation

[0017] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Example 1

[0018] See Figures 1 to 6 As shown, the intelligent acupoint recognition glove for common upper limb acupoints provided in this embodiment mainly includes a glove body 1, a sensor unit array, an acupoint feedback unit array, a main control unit, a power supply module, and a matching mobile terminal. The sensor unit array and the acupoint feedback unit array are integrated inside the glove body 1. The main control unit and the power supply module are integrated in an integrated box 8 located on the arm section of the glove body 1. The mobile terminal communicates wirelessly with the main control unit via Bluetooth.

[0019] The glove body 1 is a full-finger extended style, covering the area from the fingertips to below the elbow, fully covering the commonly used acupoint distribution areas of the hand, wrist and forearm; the gloves are available in left-hand and right-hand versions, respectively adapted to the mirror distribution of acupoints on the left and right upper limbs.

[0020] The glove body 1 adopts a three-layer composite structure, consisting of a skin-friendly inner layer 101, a sensing circuit layer 102, and a protective outer layer 103 from the inside out. The skin-friendly inner layer 101 uses existing general-purpose high-elasticity and breathable Lycra fabric, which comes into direct contact with the skin, providing good fit and breathability without restricting joint movement; the sensing circuit layer 102 uses a 0.2mm thick segmented double-layer flexible printed circuit board (FPC) as a carrier. This FPC is an existing general-purpose flexible circuit product, using a polyimide substrate. The two layers are bonded together with insulating adhesive, and interlayer electrical connections are achieved through metallized vias. This is a mature standard process for FPC manufacturing, allowing it to bend freely with the limbs; the protective outer layer 103 uses general-purpose waterproof and wear-resistant polyurethane fabric.

[0021] The sensing unit array consists of a nine-axis inertial measurement unit 2, a resistive flexible strain sensor 3, a resistive flexible tensile sensing strip 4, and a piezoresistive flexible pressure sensor 5. The entire sensing unit array is soldered and fixed to the FPC of the sensing circuit layer 102 using the existing general SMT surface mount technology, and is electrically connected to the main control unit through copper foil lines on the board.

[0022] The nine-axis inertial measurement unit 2 is a commonly used sensing module that integrates a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer. It can output three-dimensional acceleration, angular velocity, and magnetic field strength data for calculating the spatial attitude of an object. In this embodiment, a commercially available 2mm×2mm LGA packaged general-purpose model is selected. Three units are set in this embodiment, fixed at three positions: the middle of the metacarpal bone on the back of the hand, the midpoint of the transverse crease of the wrist, and the dorsal side of the middle forearm, corresponding to the three rigid body segments of the hand, wrist, and forearm. During operation, it outputs data at a conventional 100Hz sampling frequency and transmits it to the main control unit as the basic data source for attitude calculation, thereby realizing the attitude calculation of the three segments of the upper limb.

[0023] The resistive flexible strain sensor 3 is a commonly used flexible sensor with a conductive polymer composite material as its substrate. When bending or stretching deformation occurs, the density of the internal conductive pathways changes, and the resistance value changes linearly with the deformation. The bending angle can be calculated by detecting the resistance value. Its resistance-deformation characteristic is an inherent property of the component. In this embodiment, a commercially available general-purpose strip strain sensor with a width of 2mm and a thickness of 0.1mm is selected. In this embodiment, a total of 8 sensors are set, all arranged on the back of the finger joints, with the length direction of the sensor perpendicular to the joint flexion-extension axis. Five of them correspond to the metacarpophalangeal joints of the five fingers, and the remaining 3 correspond to the proximal interphalangeal joints of the index, middle, and ring fingers, respectively. During operation, the bending of the finger causes the sensor to bend synchronously, resulting in deformation and a change in resistance value. The main control unit collects the resistance value through a built-in general-purpose analog-to-digital converter (ADC) module and calculates the bending angle of the corresponding joint according to a pre-calibrated "resistance-angle" curve to assist in the calculation of hand posture. The calibration method is a conventional technique in the field: the resistance value at different bending angles is measured using a standard angle fixture, and the linear curve is fitted and written into the main control unit program.

[0024] The piezoresistive flexible pressure sensor 5 is a commonly used flexible pressure element, made of a flexible substrate and a piezoresistive sensitive material. When pressed, the resistance of the sensitive material changes with the pressure. The pressure value is obtained by detecting the resistance value. In this embodiment, a commercially available 4mm diameter, 0-20mm range general-purpose thin-film pressure sensor is selected. A total of 6 sensors are used in this embodiment, all with their sensing surfaces facing the skin. They are divided into two categories according to function: 3 for operation detection: placed on the inner side of the glove on the thumb, index finger, and middle finger pads, respectively, to collect the pressure, frequency, and duration of acupressure when the user presses acupoints; and 3 for acupoint detection: placed on the back of the hand corresponding to the Hegu acupoint, the palm corresponding to the Laogong acupoint, and the palmar side of the wrist corresponding to the Daling acupoint, respectively, to collect the contact pressure between the glove and the skin to determine whether the acupoint pressure is adequate.

[0025] During operation, the pressure is transmitted to the sensor through the fabric, causing a change in the resistance of the piezoresistive material inside the sensor. The main control unit 4 collects the resistance value in real time through the ADC module and converts it into a pressure value, which is used to determine whether the pressure is sufficient, the force is appropriate, and the duration is up to standard. The calibration of the pressure-resistance curve is a standard procedure in this field. Calibration is completed by applying a known pressure with a standard weight and recording the corresponding resistance value.

[0026] The acupoint feedback unit array contains 20 acupoint feedback nodes, all soldered onto the FPC of the sensing circuit layer 102 using SMT technology. Their positions correspond to the 20 commonly used upper limb acupoints in the national standard "Names and Locations of Acupoints," arranged on the palmar and dorsal sides. The 20 acupoints specifically include: 6 on the hand (Hegu, Laogong, Shaoshang, Shangyang, Zhongzhu, Houxi), 6 on the wrist (Neiguan, Waiguan, Yangxi, Daling, Shenmen, Yangchi), 6 on the forearm (Lieque, Pianli, Ximen, Jianshi, Zhigou, Shousanli), and 2 on the elbow (Quchi, Chize).

[0027] Each acupoint feedback node 6 is composed of a miniature patch LED 601 and a miniature linear vibration motor 602 tightly integrated at the same acupoint. The miniature patch LED 601 is a commonly used 0402 packaged patch LED with green light emission, and is arranged on the outermost side of the sensing circuit layer 102. The miniature linear vibration motor 602 is a commonly used Φ3mm ultra-thin linear vibration motor with fast response speed, and is arranged on the side of the sensing circuit layer 102 close to the skin.

[0028] A cushioning pad 7 is embedded in the skin-friendly inner layer 101 below each acupoint feedback node 6. The cushioning pad 7 is disc-shaped and made of soft silicone, which can improve the comfort of use when pressing acupoints.

[0029] The operation of acupoint feedback node 6 is implemented through the general-purpose I / O port of the main control unit, which is a conventional circuit control technology. Acupoint guidance stage: The main control unit outputs high and low level signals to drive the miniature LED601 corresponding to the target acupoint to emit green light and flash continuously. Users can intuitively perceive the location of the acupoint through visual means without referring to a chart. During the pressing operation phase: When the pressing force reaches the preset effective threshold, the main control unit outputs a drive signal to make the miniature linear vibration motor 602 vibrate continuously, indicating that the pressing is effective; when the force is insufficient, an intermittent drive signal is output to generate short vibrations to prompt the user to increase the force; when the pressing time reaches the target, the miniature patch LED 601 turns into a solid green light to indicate that the acupoint operation is completed.

[0030] In this embodiment, the main control unit adopts the commercially available nRF52840 low-power Bluetooth system-on-chip in the prior art. The chip integrates an ARM Cortex-M4 core and a Bluetooth 5.0 communication module, and is a common mainstream main control chip in the field of wearable devices. Its development environment, compiling tools and peripheral drivers are all existing public standard resources. Three core program modules are stored and run in the chip in this embodiment: a bone proportional measurement calibration module, a real-time attitude calculation module, and an acupoint matching and driving module. Each module is implemented based on the existing mature algorithm framework and well-known theory, and the code writing can be completed without creative work.

[0031] The core theoretical basis of the bone proportional measurement calibration module is the well-known "bone proportional measurement method" in traditional Chinese medicine — this method takes human bony landmarks as the benchmark, divides the limbs into segments and specifies a fixed number of "cun" as the measurement standard for acupoint location. The improvement of this module lies in converting this traditional method into a computable digital model through sensor data. The specific operation process of this module is as follows, and those skilled in the art can directly program and implement it according to the following steps: 1. The mobile terminal sends a calibration start instruction to the main control unit via Bluetooth, and the interface of the mobile terminal guides the user to complete three groups of standard calibration actions: thumb touching the little finger, maximum flexion and extension of the wrist, and maximum flexion and extension of the elbow; 2. During the movement, the sensor unit array synchronously collects the attitude data of the nine-axis inertial measurement unit 2, the length data of the resistive flexible stretch sensing belt 4, and the angle data of the resistive flexible strain sensor 3, and identifies the corresponding positions of key bony landmarks such as wrist crease, elbow crease, and metacarpophalangeal joint through movement peak recognition; 3. The module performs coordinate conversion according to the bone proportional measurement rules: the measured distance from the wrist crease to the elbow crease is defined as 12 cun, which is taken as the longitudinal reference, and the longitudinal coordinates of each acupoint on the forearm are converted according to the standard cun proportion of each acupoint; the measured length of the second metacarpal is taken as the hand transverse reference, and the transverse coordinates of hand acupoints are converted; 4. The transverse offset of acupoints is corrected in combination with the wrist circumference data, and finally an exclusive three-dimensional coordinate model of upper limb acupoints that completely matches the user's limb size is generated and stored locally in the main control unit.

[0032] The real-time attitude calculation module is based on the existing Extended Kalman Filter (EKF) algorithm, which is a mature and widely used algorithm in the field of multi-sensor attitude calculation. The operation logic of this module is as follows: the hand, wrist, and forearm are regarded as three rigid body segments. The raw data of three nine-axis inertial measurement sensors are used as input, and the spatial tilt angle and rotation angle of each segment are calculated by the Extended Kalman Filter algorithm. At the same time, the angle data of eight strain sensors are used to supplement the bending angle of the finger joints. Based on the rigid body kinematics model, the relative displacement of each acupoint is calculated in real time according to the change of joint angle, and the acupoint coordinates are dynamically updated to ensure that the acupoint feedback node 6 always corresponds to the user's real acupoint position in dynamic scenarios such as wrist rotation and finger bending, avoiding positioning deviation caused by fabric displacement.

[0033] The acupoint matching and driving module has a built-in upper limb acupoint database that conforms to national standards. It stores the relative coordinates and numbers of standard acupoints. Its operation process is as follows, which consists of routine data processing and I / O control operations: 1. Receive the target acupoint instruction sent by the mobile terminal 6, and retrieve the standard relative coordinates of the acupoint from the database; 2. Map the standard coordinates to the user-specific acupoint coordinate model through affine transformation, and match them to the corresponding acupoint feedback node number 6 on the glove; 3. Output drive signals through general-purpose I / O ports to control the blinking of the miniature patch LED601 of the corresponding node to complete the acupoint guidance; 4. During the pressing process, the pressure data of the piezoresistive flexible pressure sensor 5 is received in real time, compared with the preset effective pressure threshold and duration threshold, and the corresponding vibration and light feedback signals are output to realize the pressing quality monitoring.

[0034] In this embodiment, the power supply module uses a readily available 3.7V 150mAh ultra-thin flexible lithium battery, which is charged via existing universal magnetic contacts. A single full charge allows for continuous operation for no less than 8 hours, meeting daily usage needs. The mobile terminal is a readily available smartphone or tablet computer, which communicates with the main control unit by installing a supporting application. This enables conventional interactive functions such as acupoint query, therapy plan push, voice guidance, and therapy data recording and storage.

[0035] The complete usage process of this invention is as follows: Initial calibration: The user wears gloves corresponding to their hand shape, connects to the main control unit via a mobile terminal, and follows the guidance to complete three sets of calibration actions; the sensing unit collects bony landmark data, and the bone measurement calibration module generates a personalized acupoint model, thus completing the calibration.

[0036] Routine acupoint selection: The user puts on gloves and turns on the device, which automatically connects to the mobile terminal; the user selects the target acupoint or physiotherapy plan on the mobile terminal, and the instruction is sent to the main control unit; the acupoint matching and driving module drives the corresponding acupoint feedback node 6 to flash for guidance.

[0037] Pressing operation: The user presses the acupoint, and the pressure sensor collects the pressure data in real time; the system provides feedback on the pressing quality through vibration and light, and prompts completion when the target is reached; the mobile terminal automatically records the data of this physiotherapy.

[0038] For those skilled in the art, various modifications and variations can be made to the above embodiments without departing from the principles of the present invention, and all such modifications and variations should fall within the protection scope of the present invention.

Claims

1. A smart glove for recognizing common acupoints on the upper limb, comprising a glove body (1) wearable on one side of a user's upper limb, and a main control unit and a power supply module, characterized in that: It includes an integrated box (8), a sensor unit array and an acupoint feedback unit array; the integrated box (8) is disposed on the arm section of the glove body (1), and the main control unit and the power supply module are both integrated in the integrated box (8); the glove body (1) is a three-layer composite structure consisting of a skin-friendly inner layer (101), a sensor circuit layer (102) and a protective outer layer (103) arranged sequentially from the inside to the outside, and the sensor circuit layer (102) is provided with a flexible printed circuit board; The sensor unit array and the acupoint feedback unit array are both set on the flexible printed circuit board and are electrically connected to the main control unit through the flexible printed circuit board; the sensor unit array includes a nine-axis inertial measurement unit (2), a resistive flexible strain sensor (3), a resistive flexible tensile sensing strip (4) and a piezoresistive flexible pressure sensor (5), which are used to collect limb size, joint posture and pressure data. The acupoint feedback unit array includes several acupoint feedback nodes (6) corresponding to standard acupoints on the upper limb. Each acupoint feedback node (6) integrates a miniature patch LED (601) and a miniature linear vibration motor. A buffer pad (7) is provided on the inner side of each acupoint feedback node (6). The main control unit has a built-in bone measurement calibration module, a real-time posture calculation module and an acupoint matching driving module. The bone measurement calibration module is used to generate a user-specific acupoint coordinate model based on sensor data and bone measurement method. The real-time posture calculation module is used to fuse multi-sensor data to calculate joint posture and dynamically correct acupoint coordinates. The acupoint matching driving module is used to drive the acupoint feedback node (6) to output acupoint selection guidance and pressure quality feedback signal.

2. The intelligent acupoint recognition glove for commonly used upper limb acupoints according to claim 1, characterized in that: The nine-axis inertial measurement unit (2) consists of three units, which are respectively located at the middle of the metacarpal bone on the back of the hand, the midpoint of the transverse crease of the wrist, and the dorsal position of the middle section of the forearm. Each nine-axis inertial measurement unit (2) integrates a three-axis accelerometer, a three-axis gyroscope, and a three-axis magnetometer.

3. The intelligent acupoint recognition glove for commonly used upper limb acupoints according to claim 1, characterized in that: The resistive flexible strain sensor (3) has a total of 8 sensors, of which 5 are arranged on the dorsal side of the metacarpophalangeal joints of the five fingers, and 3 are arranged on the dorsal side of the proximal interphalangeal joints of the index, middle and ring fingers. The length direction of the sensor is perpendicular to the flexion and extension direction of the joint, and is used to detect the bending angle of the corresponding joint. The resistive flexible tensile sensor strip (4) has a total of 3 strips, of which 2 strips are arranged symmetrically along the longitudinal direction of the dorsal side of the forearm, with the ends corresponding to the wrist crease and elbow crease respectively, and 1 strip is arranged circumferentially along the wrist, and is used to collect limb length and circumference data.

4. The intelligent acupoint recognition glove for commonly used upper limb acupoints according to claim 1, characterized in that: The piezoresistive flexible pressure sensor (5) has a total of 6 sensors, of which 3 are arranged on the pads of the thumb, index finger, and middle finger respectively, for collecting active pressure intensity; the remaining 3 are arranged on the back of the hand corresponding to the Hegu acupoint, the palm corresponding to the Laogong acupoint, and the palmar side of the wrist corresponding to the Daling acupoint, with the sensing surface facing the skin side, for collecting acupoint contact pressure and duration.

5. The intelligent acupoint recognition glove for commonly used upper limb acupoints according to claim 1, characterized in that: The acupoint feedback nodes (6) are set up in total, including Hegu, Laogong, Shaoshang, Shangyang, Zhongzhu, Houxi, Neiguan, Waiguan, Yangxi, Daling, Shenmen, Yangchi, Lieque, Pianli, Ximen, Jianshi, Zhigou, Shousanli, Quchi, and Chize.

6. The intelligent acupoint recognition glove for commonly used upper limb acupoints according to claim 1, characterized in that: The buffer pad (7) is a disc-shaped silicone pad that is embedded in the skin-friendly inner layer (101) below the acupoint feedback node (6).

7. The intelligent acupoint recognition glove for commonly used upper limb acupoints according to claim 1, characterized in that: The glove body (1) is a full-finger extended structure, covering the area from the fingertip to the area below the elbow; the glove body (1) adopts a three-layer composite structure, from the inside to the outside, it consists of a skin-friendly inner layer (101), a sensing circuit layer (102), and a protective outer layer (103), wherein the sensing circuit layer (102) integrates a sensing unit and a feedback unit on a segmented double-layer flexible printed circuit board as a carrier; the gloves are divided into left-hand and right-hand versions, which correspond to the mirror distribution of acupoints on the left and right upper limbs, respectively.

8. The intelligent acupoint recognition glove for commonly used upper limb acupoints according to claim 1, characterized in that: The real-time posture calculation module uses an extended Kalman filter algorithm to fuse multi-sensor data, calculate the angles and spatial postures of each joint in real time, and dynamically update the relative coordinates of acupoints. The bone measurement calibration module is specifically used to: collect the bony landmarks of the user's wrist crease, elbow crease, and metacarpophalangeal joints, establish longitudinal coordinates with the wrist crease to elbow crease as a 12-inch reference, establish transverse coordinates with metacarpal length as a reference, and generate a personalized acupoint coordinate model after combining limb circumference correction.

9. The intelligent acupoint recognition glove for commonly used upper limb acupoints according to claim 1, characterized in that: It also includes a mobile terminal, which communicates with the main control unit via Bluetooth and is used to provide functions such as acupoint query, physiotherapy plan push, operation guidance and data recording.

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