Shoulder joint resistance training device and interactive rehabilitation training method

Abstract

The invention relates to a shoulder joint resistance training device and an interactive rehabilitation training method.The shoulder joint resistance training device comprises a wearable device, a joint motion range sensor, a myoelectricity collecting circuit, a main control circuit, a communication module and an upper computer, and the joint motion range sensor, the myoelectricity collecting circuit, the main control circuit and the communication module are all arranged on the wearable device; the joint motion range sensor comprises an attitude sensor, the myoelectricity acquisition circuit comprises an electrode plate and an acquisition circuit, the output end of the electrode plate is connected with the input end of the acquisition circuit, and the output ends of the acquisition circuit and the attitude sensor are connected with the input end of the main control circuit; the main control circuit is in communication connection with the upper computer through the communication module, the upper computer is in communication connection with the shoulder joint training controller through the communication module, and the interactive rehabilitation training method is further included. According to the invention, the joint motion range and the electromyographic signals are comprehensively analyzed, and the conditions of each muscle participating in the motion under different tasks are combined, so that the refined adjustment of the resistance is realized.

Description

Technical Field

[0001] This invention relates to the field of medical rehabilitation equipment technology, specifically to a shoulder joint resistance training device and an interactive rehabilitation training method. Background Technology

[0002] Stroke patients often experience limited mobility and frequently experience varying degrees of joint and muscle atrophy and physical impairment, which severely impacts their daily lives. Clinical rehabilitation primarily employs physical therapy and exercise therapy, with exercise therapy focusing on joint movement. By activating the joints, muscle spasms are reduced, thereby stimulating the cerebral cortex to improve symptoms. Motion-sensory interactive rehabilitation training is a modern high-tech rehabilitation training technique that integrates multimedia and sports rehabilitation. It combines entertainment and intelligence, and has shown good results in the rehabilitation training of patients with movement disorders. However, most motion-sensory interactive rehabilitation training currently on the market relies on measuring joint range of motion for feedback training. This only provides a simple assessment of the patient's task completion during training and cannot perceive the muscle activity during the training process. Furthermore, some interactive rehabilitation training devices only apply a specific load during resistance training and cannot adjust the resistance in real time. In addition, while some rehabilitation robot systems use electromyography (EMG) signals as feedback to adjust resistance, they do not consider the differences in muscle strength at different ranges of motion, especially the varying degrees of involvement of different muscle groups at different ranges of motion. This results in insufficiently precise and scientific resistance adjustment, posing rehabilitation risks.

[0003] Current shoulder joint rehabilitation training equipment also has the same problem. Therefore, it is urgent to combine the characteristics of shoulder joint activity and the patient's condition to achieve the effect of adjusting resistance. Summary of the Invention

[0004] To address the problem of poor resistance adjustment accuracy in existing shoulder joint rehabilitation training equipment, this invention proposes a shoulder joint resistance training device and interactive rehabilitation training method. It comprehensively analyzes joint range of motion and electromyographic signals, and incorporates the participation of various muscles under different tasks to achieve precise resistance adjustment.

[0005] To achieve the above objectives, the first aspect of this invention provides a shoulder joint resistance training device, comprising a shoulder joint training device, the shoulder joint training device including a drive motor, a shoulder joint training mechanism, a shoulder joint training controller, a pull rope, and a handle. The handle is connected to the shoulder joint training mechanism via the pull rope. The shoulder joint training mechanism is driven by the drive motor to provide resistance for training. The shoulder joint training controller is electrically connected to the drive motor and is used to adjust the output torque of the drive motor. The device also includes a wearable device, a joint range of motion sensor, an electromyography (EMG) acquisition circuit, a main control circuit, a communication module, and a host computer. The joint range of motion sensor, EMG acquisition circuit, main control circuit, and communication module are all mounted on the wearable device. The joint range of motion sensor includes a posture sensor. The EMG acquisition circuit includes electrode pads and an acquisition circuit. The output end of the electrode pads is connected to the input end of the acquisition circuit. The output ends of the acquisition circuit and the posture sensor are connected to the input end of the main control circuit. The main control circuit is connected to the host computer via a communication module, and the host computer is connected to the shoulder joint training controller via a communication module.

[0006] Furthermore, the acquisition circuit includes an electrode interface, a current-limiting resistor, a preamplifier unit, and a secondary amplifier unit. The electrode interface and the electrode sheet are electrically connected. The electrode interface is connected to the input terminal of the preamplifier unit via the current-limiting resistor. The output terminal of the preamplifier unit is connected to the input terminal of the secondary amplifier unit. The output terminal of the secondary amplifier unit is connected to the main control circuit. The preamplifier unit includes the AD620AN instrumentation amplifier, and the secondary amplifier unit includes the LM324 operational amplifier.

[0007] After the electrode interface is connected to the electrode pads, the current-limiting resistor protects the circuit and prevents excessive current from damaging components. The preamplifier unit uses an AD620AN instrumentation amplifier, which features high input impedance and low noise, effectively amplifying weak electromyographic (EMG) signals. The secondary amplification unit uses an LM324 operational amplifier to further amplify the signal, bringing it to a level that the main control circuit can process. This two-stage amplification ensures the clarity and stability of the EMG signal, providing high-quality raw data for subsequent signal analysis and processing, and improving the accuracy and reliability of EMG signal acquisition.

[0008] Furthermore, the attitude sensor includes an MPU6050 gyroscope chip; The main control circuit includes MCU chip A, which is connected to the MPU6050 gyroscope chip via I2C serial communication. The ADC pin of MCU chip A is connected to the output of LM324 operational amplifier.

[0009] The posture sensor uses the MPU6050 gyroscope chip, which can accurately measure the posture and motion parameters of the shoulder joint. Its small size and low power consumption make it suitable for integration into wearable devices. The MCU chip A of the main control circuit connects to the MPU6050 via an I2C serial port, ensuring stable and fast posture data transmission. The ADC pin of MCU chip A is connected to the output of the secondary amplifier unit, allowing direct reception of processed electromyographic signals. This simplifies circuit connections, improves data processing efficiency, and enables the entire system to respond quickly to information acquired by the sensor.

[0010] Furthermore, the communication module includes one or more combinations of Bluetooth module, infrared module, WiFi module and USB module; The shoulder joint training controller includes an MCU chip B and a driver chip. The output terminal of the MCU chip B is connected to the input terminal of the driver chip. The drive motor is connected to the power supply through the driver chip. The MCU chip A is connected to the host computer through one or more combinations of Bluetooth module, infrared module and WiFi module. The MCU chip B is connected to the host computer through USB module.

[0011] A communication module is used to achieve wireless transmission of commands. Wired connections may cause motion interference during movement, while wireless transmission facilitates movement.

[0012] Furthermore, it also includes a PCB board. The wearable device includes a sleeve, and the posture sensor, acquisition circuit, main control circuit and communication module are integrated on the PCB board. The PCB board is encapsulated with a shell, and the shell is fixed to the sleeve. The number of electrode pads is two, and the two electrode pads are connected to the acquisition circuit through wires. One electrode pad is attached to the deltoid muscle of the shoulder joint, and the other electrode pad is attached to the trapezius muscle of the shoulder joint.

[0013] The posture sensor, acquisition circuitry, and other components are integrated onto a PCB board and encapsulated in a housing, then secured to a sleeve, resulting in a compact and lightweight wearable device that does not interfere with the user's normal activities. Two electrode pads are attached to the deltoid and trapezius muscles respectively, enabling targeted acquisition of electromyographic signals from key muscles of the shoulder joint. The electrodes are connected to the acquisition circuitry via wires, facilitating installation and replacement, enhancing the device's practicality and user experience, and ensuring the targeted and accurate acquisition of electromyographic signals.

[0014] A second aspect of the present invention provides an interactive rehabilitation training method for a shoulder joint resistance training device, comprising: Step 1: Perform no-load joint range of motion calibration. The user completes the maximum range of shoulder abduction and flexion movements. The joint range of motion sensor collects the shoulder joint range of motion value, and the main control circuit records the maximum shoulder joint angle value A0. Step 2: Obtain the maximum resistance load and electromyographic characteristic values ​​under a specific range of motion. Fix the joint range of motion at A0 / 2, and gradually increase the load until the user can no longer maintain this angle for training. Record the maximum resistance load F0, as well as the peak electromyographic values ​​of the main muscle group E10 and the peak electromyographic values ​​of the secondary muscle group E20. Step 3: During the training process, collect joint range of motion An, electromyography (EMG) of the primary muscle group E1n, and EMG of the secondary muscle group E2n in the training task, and calculate the comprehensive EMG value and the baseline EMG value through a weighted algorithm. Step 4: Calculate the reference threshold based on the baseline EMG value, compare the real-time comprehensive EMG value with the reference threshold to divide the training task into the initial stage and the fatigue stage, and calculate the resistance according to the initial stage and the fatigue stage respectively; Step 5: Drive the resistance controller to adjust the resistance by pressing Fn, and record the current characteristic value as the historical reference value for the next task cycle, and repeat steps 3 to 4.

[0015] Furthermore, the comprehensive electromyographic values ​​described in step 3 are as shown in formula (1): En = a × E1n + b × E2n (1); The baseline electromyographic values ​​mentioned in step 3 are shown in formula (2): E0 = a × E10 + b × E20 (2).

[0016] Furthermore, a is 0.75 and b is 0.3.

[0017] Further, step 4 includes: Step 4.1: When En < 0.62 × E0, the training task is in the initial stage; when En ≥ 0.62 × E0, the training task is in the fatigue stage. Step 4.2: The resistance in the initial stage is shown in formula (3): Fn=[1-c×(An-A0 / 2) / A0]×F0(3); Step 4.3: The resistance during the fatigue stage is shown in formula (4): Fn=[1-d×(An-A0 / 2) / A0]×F0-(1-En-1 / E0)×F0 (4).

[0018] Furthermore, c is -0.2 and d is -0.6.

[0019] The beneficial effects of the present invention through the above technical solution are as follows: (1) This invention achieves intelligent and precise training by setting up a joint range of motion sensor, electromyography (EMG) acquisition circuit, main control circuit, and communication module near the shoulder joint in a wearable device. The joint range of motion sensor can monitor the movement posture of the shoulder joint in real time, and the EMG acquisition circuit can acquire the electrophysiological signals of the muscles. These data are processed by the main control circuit and transmitted to the host computer through the communication module. The host computer then adjusts the shoulder joint training controller according to the data, so that the resistance provided by the drive motor is more in line with the actual state of the trainee, improving the scientificity and effectiveness of the training. At the same time, it realizes the real-time acquisition and feedback of training data, which facilitates timely adjustment of the training plan.

[0020] (2) This invention introduces a comprehensive adjustment of the range of motion and surface electromyography intensity, enabling resistance to change with both the angle and muscle strength. This achieves fine-tuning of resistance, helping patients achieve efficient and safe training during shoulder joint range of motion resistance training, shortening the rehabilitation process, and avoiding muscle damage. The resistance adjustment method is differentiated based on training fatigue levels, focusing on range of motion in the initial stage and muscle strength in the later stage. This further optimizes the scientific nature and safety of the training process. The method of this invention comprehensively assesses the different levels of involvement of different muscle groups during shoulder joint movement, achieving fine-tuning of resistance. Attached Figure Description

[0021] Figure 1 This is a circuit diagram of a shoulder joint resistance training device according to the present invention; Figure 2 This is one of the circuit diagrams of a shoulder joint resistance training device according to the present invention; Figure 3 This is a second circuit diagram of a shoulder joint resistance training device according to the present invention; Figure 4 This is a schematic diagram of the structure of a shoulder joint resistance training device according to the present invention; Figure 5 This is a flowchart illustrating the steps of the interactive rehabilitation training method of the present invention.

[0022] Reference numerals: 1 for wearable device, 2 for joint range of motion sensor, 3 for main control circuit, 4 for communication module, 5 for host computer, 6 for electrode sheet, 7 for acquisition circuit, 701 for electrode interface, 702 for preamplifier unit, and 703 for secondary amplifier unit. Detailed Implementation

[0023] Example 1 like Figures 1-4As shown, a shoulder joint resistance training device includes a shoulder joint training device, which includes a drive motor, a shoulder joint training mechanism, a shoulder joint training controller, a pull rope, and a handle. The handle is connected to the shoulder joint training mechanism via the pull rope. The shoulder joint training mechanism is driven by the drive motor to provide resistance for training. The shoulder joint training controller is electrically connected to the drive motor and is used to adjust the output torque of the drive motor. The device also includes a wearable device 1, a joint range of motion sensor 2, an electromyography (EMG) acquisition circuit, a main control circuit 3, a communication module 4, and a host computer 5. The joint range of motion sensor 2, the EMG acquisition circuit, the main control circuit 3, and the communication module 4 are all mounted on the wearable device 1. The joint range of motion sensor 2 includes a posture sensor. The EMG acquisition circuit includes an electrode 6 and an acquisition circuit 7. The output terminal of the electrode 6 is connected to the input terminal of the acquisition circuit 7. The output terminals of the acquisition circuit 7 and the posture sensor are connected to the input terminal of the main control circuit 3. The main control circuit 3 is connected to the host computer 5 via the communication module 4, and the host computer 5 is connected to the shoulder joint training controller via the communication module 4.

[0024] The acquisition circuit 7 includes an electrode interface 701, a current-limiting resistor, a preamplifier unit 702, and a secondary amplifier unit 703. The electrode interface 701 is electrically connected to the electrode plate 6. The electrode interface 701 is connected to the input terminal of the preamplifier unit 702 via the current-limiting resistor. The output terminal of the preamplifier unit 702 is connected to the input terminal of the secondary amplifier unit 703. The output terminal of the secondary amplifier unit 703 is connected to the main control circuit 3. The preamplifier unit 702 includes an AD620AN instrumentation amplifier, and the secondary amplifier unit 703 includes an LM324 operational amplifier.

[0025] The attitude sensor includes an MPU6050 gyroscope chip; The main control circuit 3 includes an MCU chip A. The MCU chip A and the MPU6050 gyroscope chip are connected via I2C serial communication. The ADC pin of the MCU chip A is connected to the output of the LM324 operational amplifier.

[0026] The communication module 4 includes one or more combinations of Bluetooth module, infrared module, WiFi module and USB module; The shoulder joint training controller includes an MCU chip B and a driver chip. The output terminal of the MCU chip B is connected to the input terminal of the driver chip. The drive motor is connected to the power supply through the driver chip. The MCU chip A is connected to the host computer 5 through one or more combinations of Bluetooth module, infrared module and WiFi module. The MCU chip B is connected to the host computer 5 through USB module.

[0027] It also includes a PCB board. The wearable device 1 includes a sleeve. The posture sensor, acquisition circuit 7, main control circuit 3 and communication module 4 are integrated on the PCB board. The PCB board is encapsulated with a shell, and the shell is fixed to the sleeve. The number of electrode pads 6 is two. The two electrode pads 6 are connected to the electrode interface 701 by wires. One electrode pad 6 is attached to the deltoid muscle of the shoulder joint, and the other electrode pad 6 is attached to the trapezius muscle of the shoulder joint.

[0028] In this embodiment, MCU chip A and MCU chip B are STM32 microcontrollers, and communication module 4 uses an XM-15 Bluetooth module and a USB module. In this embodiment, Velcro is provided at both ends of the sleeve, and the tightness of the sleeve is adjusted via the Velcro. A push-button switch is provided on the main control circuit 3, and the output of the push-button switch is connected to the input of MCU chip A.

[0029] During the procedure, first attach the two electrode pads to the deltoid and trapezius muscles of the user's shoulder joint, respectively. Then, connect and secure the electrode interface and electrode pads using wires. The user should then put on the sleeve, ensuring it fits snugly against the shoulder and does not restrict movement.

[0030] After pressing the button switch, the main control circuit, communication module, joint range of motion sensor 2, acquisition circuit and electrode plate are powered on and work. The main control circuit establishes communication with the host computer through the communication module.

[0031] Example 2 Based on the shoulder joint resistance training device in Example 1, this example describes the interactive rehabilitation training method, such as... Figure 5 The following are included: Step 1: Perform no-load joint range of motion calibration. The user completes the maximum range of shoulder abduction and flexion movements. The joint range of motion sensor 2 collects the shoulder joint range of motion value, and the main control circuit 3 records the maximum shoulder joint angle value A0. Step 2: Obtain the maximum resistance load and electromyographic characteristic values ​​under a specific range of motion. Fix the joint range of motion at A0 / 2, and gradually increase the load until the user can no longer maintain this angle for training. Record the maximum resistance load F0, as well as the peak electromyographic values ​​of the main muscle group E10 and the peak electromyographic values ​​of the secondary muscle group E20. Step 3: During the training process, collect joint range of motion An, electromyography (EMG) of the primary muscle group E1n, and EMG of the secondary muscle group E2n in the training task, and calculate the comprehensive EMG value and the baseline EMG value through a weighted algorithm. Step 4: Calculate the reference threshold based on the baseline EMG value, compare the real-time comprehensive EMG value with the reference threshold to divide the training task into the initial stage and the fatigue stage, and calculate the resistance according to the initial stage and the fatigue stage respectively; Step 5: Drive the resistance controller to adjust the resistance by pressing Fn, and record the current characteristic value as the historical reference value for the next task cycle, and repeat steps 3 to 4.

[0032] The comprehensive electromyographic values ​​described in step 3 are shown in formula (1): En = a × E1n + b × E2n (1); The baseline electromyographic values ​​mentioned in step 3 are shown in formula (2): E0 = a × E10 + b × E20 (2).

[0033] a is 0.75 and b is 0.3.

[0034] Step 4 includes: Step 4.1: When En < 0.62 × E0, the training task is in the initial stage; when En ≥ 0.62 × E0, the training task is in the fatigue stage. Step 4.2: The resistance in the initial stage is shown in formula (3): Fn=[1-c×(An-A0 / 2) / A0]×F0(3); Step 4.3: The resistance during the fatigue stage is shown in formula (4): Fn=[1-d×(An-A0 / 2) / A0]×F0-(1-En-1 / E0)×F0 (4).

[0035] The value of c is -0.2 and the value of d is -0.6.

[0036] Among them, a = 0.75, b = 0.3, c = -0.2 and d = -0.6 are achieved by fitting data through actual experimental data.

[0037] Specifically, 50 sets of experiments were conducted, with data collected from patients with shoulder joint inflammation, muscle injury, and limited range of motion. Measurements included surface electromyography (EMG) values ​​and corresponding range of motion of the deltoid and trapezius muscles under different resistances. By analyzing the relationship between EMG, range of motion, and resistance, the patent's scheme and data formulas (1-4) were derived. Then, data fitting was performed to obtain the optimal fit coefficient ad.

[0038] The user performs a maximum range of shoulder abduction and flexion movements without load. The MPU6050 gyroscope chip (i.e., joint range of motion sensor 2) on wearable device 1 collects the shoulder joint range of motion values ​​in real time and transmits the data to the MCU chip A of the main control circuit 3.

[0039] MCU chip A records the maximum shoulder joint angle value A0 as one of the benchmark parameters for subsequent training, and sends A0 to the host computer 5 for storage through communication module 4.

[0040] The shoulder joint training controller controls the drive motor to fix the user's joint range of motion at position A0 / 2 (i.e., half of the maximum range of motion).

[0041] Gradually increase the load on the shoulder joint training mechanism (achieved by adjusting the output torque of the drive motor through the shoulder joint training controller) until the user can no longer maintain that angle for training.

[0042] Two electrode pads 6 collect electromyographic signals from the deltoid muscle (primary muscle group) and trapezius muscle (secondary muscle group) in real time. The signals are transmitted to the preamplifier unit 702 (AD620AN instrumentation amplifier) ​​for initial amplification via the electrode interface 701 and the current limiting resistor. After further amplification by the secondary amplifier unit 703 (LM324 operational amplifier), the signals are transmitted to the ADC pin of the MCU chip A in the main control circuit 3.

[0043] MCU chip A processes the electromyographic signals, records the maximum impedance load F0, and the peak electromyographic values ​​of the main muscle group E10 and the secondary muscle group E20 at this time, and sends these data to the host computer 5 through the communication module 4.

[0044] MCU chip A calculates the baseline electromyography value E0 (E0=a×E10+b×E20) according to formula (2) En=a×E1n+b×E2n (where a=0.75, b=0.3), which serves as the baseline for subsequent electromyography analysis.

[0045] In the formal training phase, the user holds the handles to perform shoulder joint resistance training. During the training process: The joint range of motion sensor 2 continuously collects real-time joint range of motion An and transmits the data to the MCU chip A of the main control circuit 3 via the I2C serial port; The electromyography (EMG) acquisition circuit 7 continuously acquires the EMG signals of the primary muscle group (E1n) and the secondary muscle group (E2n), amplifies them, and then transmits them to the MCU chip A.

[0046] MCU chip A calculates the real-time comprehensive electromyography value En according to formula (1) En=a×E1n+b×E2n; at the same time, it calls E0 stored in step 2 as the reference electromyography value to provide data support for subsequent stage division.

[0047] MCU chip A compares the real-time integrated electromyography (EMG) value En with the baseline EMG value E0: When En < 0.62 × E0, the training task is considered to be in the initial stage. When En≥0.62×E0, it is determined to be in the fatigue stage.

[0048] If it is in the initial stage, the real-time resistance Fn is calculated according to the formula (3) Fn=[1-c×(An-A0 / 2) / A0]×F0 (where c=-0.2). For example, when An is greater than A0 / 2, (An-A0 / 2) / A0 is a positive value. After multiplying by c (-0.2), the overall term is negative. Subtracting the negative value is equivalent to increasing the resistance to match the muscle load requirements under greater activity.

[0049] If the muscle is in a fatigue stage, the real-time resistance Fn is calculated according to formula (4): Fn=[1-d×(An-A0 / 2) / A0]×F0-(1-En-1 / E0)×F0 (where d=-0.6). This formula, based on the influence of activity level, introduces the ratio of the previous electromyographic value En-1 to the baseline value E0. When the muscle is fatigued (En increases), the resistance will be appropriately reduced to avoid overload.

[0050] MCU chip A sends the calculated resistance value Fn to MCU chip B of the shoulder joint training controller. MCU chip B controls the output torque of the drive motor through the driver chip, so that the resistance of the shoulder joint training mechanism is adjusted in real time according to Fn.

[0051] After each training cycle, MCU chip A records the current feature values ​​(such as the final En, An, Fn, etc.) as historical reference values ​​for the next task cycle, and then repeats steps 3 to 4 until training is complete.

[0052] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Therefore, all equivalent changes or modifications made to the structure, features and principles described in the claims of the present invention should be included within the scope of the present invention.

Claims

1. A shoulder joint resistance training device, comprising a shoulder joint training apparatus, the shoulder joint training apparatus including a drive motor, a shoulder joint training mechanism, a shoulder joint training controller, a pull rope, and a handle, the handle being connected to the shoulder joint training mechanism via the pull rope, the shoulder joint training mechanism being driven by the drive motor to provide resistance for training, the shoulder joint training controller being electrically connected to the drive motor, and the shoulder joint training controller being used to adjust the output torque of the drive motor, characterized in that... It also includes a wearable device (1), a joint range of motion sensor (2), an electromyography (EMG) acquisition circuit, a main control circuit (3), a communication module (4), and a host computer (5). The joint range of motion sensor (2), the EMG acquisition circuit, the main control circuit (3), and the communication module (4) are all mounted on the wearable device (1). The joint range of motion sensor (2) includes a posture sensor. The EMG acquisition circuit includes an electrode pad (6) and an acquisition circuit (7). The output end of the electrode pad (6) is connected to the input end of the acquisition circuit (7). The output ends of the acquisition circuit (7) and the posture sensor are connected to the input end of the main control circuit (3). The main control circuit (3) is connected to the host computer (5) via the communication module (4), and the host computer (5) is connected to the shoulder joint training controller via the communication module (4).

2. The shoulder joint resistance training device according to claim 1, characterized in that, The acquisition circuit (7) includes an electrode interface (701), a current-limiting resistor, a preamplifier unit (702), and a secondary amplifier unit (703). The electrode interface (701) and the electrode plate (6) are electrically connected. The electrode interface (701) is connected to the input terminal of the preamplifier unit (702) via the current-limiting resistor. The output terminal of the preamplifier unit (702) is connected to the input terminal of the secondary amplifier unit (703). The output terminal of the secondary amplifier unit (703) is connected to the main control circuit (3). The preamplifier unit (702) includes an AD620AN instrumentation amplifier, and the secondary amplifier unit (703) includes an LM324 operational amplifier.

3. The shoulder joint resistance training device according to claim 2, characterized in that, The attitude sensor includes an MPU6050 gyroscope chip; The main control circuit (3) includes MCU chip A. MCU chip A and MPU6050 gyroscope chip are connected via I2C serial communication. The ADC pin of MCU chip A is connected to the output of LM324 operational amplifier.

4. The shoulder joint resistance training device according to claim 3, characterized in that, The communication module (4) includes one or more combinations of Bluetooth module, infrared module, WiFi module and USB module; The shoulder joint training controller includes an MCU chip B and a driver chip. The output terminal of the MCU chip B is connected to the input terminal of the driver chip. The drive motor is connected to the power supply through the driver chip. The MCU chip A is connected to the host computer (5) through one or more combinations of Bluetooth module, infrared module and WiFi module. The MCU chip B is connected to the host computer (5) through USB module.

5. The shoulder joint resistance training device according to claim 1, characterized in that, It also includes a PCB board. The wearable device (1) includes a sleeve. The posture sensor, acquisition circuit (7), main control circuit (3) and communication module (4) are integrated on the PCB board. The PCB board is encapsulated with a shell, and the shell is fixed to the sleeve. The number of electrode pads (6) is two. The two electrode pads (6) are connected to the electrode interface (701) by wires. One electrode pad (6) is attached to the deltoid muscle of the shoulder joint, and the other electrode pad (6) is attached to the trapezius muscle of the shoulder joint.

6. An interactive rehabilitation training method based on the shoulder joint resistance training device according to any one of claims 1 to 5, characterized in that, include: Step 1: Perform no-load joint range of motion calibration. The user completes the maximum range of shoulder abduction and flexion movements. The joint range of motion sensor (2) collects the shoulder joint range of motion value, and the main control circuit (3) records the maximum shoulder joint range of motion value A0. Step 2: Obtain the maximum resistance load and electromyographic characteristic values ​​under a specific range of motion. Fix the joint range of motion at A0 / 2, and gradually increase the load until the user can no longer maintain this angle for training. Record the maximum resistance load F0, as well as the peak electromyographic values ​​of the main muscle group E10 and the peak electromyographic values ​​of the secondary muscle group E20. Step 3: During the training process, collect joint range of motion An, electromyography (EMG) of the primary muscle group E1n, and EMG of the secondary muscle group E2n in the training task, and calculate the comprehensive EMG value and the baseline EMG value through a weighted algorithm. Step 4: Calculate the reference threshold based on the baseline EMG value, compare the real-time comprehensive EMG value with the reference threshold to divide the training task into the initial stage and the fatigue stage, and calculate the resistance according to the initial stage and the fatigue stage respectively; Step 5: Drive the resistance controller to adjust the resistance by pressing Fn, and record the current characteristic value as the historical reference value for the next task cycle, and repeat steps 3 to 4.

7. The interactive rehabilitation training method of the shoulder joint resistance training device according to claim 6, characterized in that, The comprehensive electromyographic values ​​described in step 3 are shown in formula (1): En = a × E1n + b × E2n (1); The baseline electromyographic values ​​mentioned in step 3 are shown in formula (2): E0 = a × E10 + b × E20 (2).

8. The interactive rehabilitation training method of the shoulder joint resistance training device according to claim 7, characterized in that, a is 0.75 and b is 0.

3.

9. The interactive rehabilitation training method of the shoulder joint resistance training device according to claim 7, characterized in that, Step 4 includes: Step 4.1: When En < 0.62 × E0, the training task is in the initial stage; when En ≥ 0.62 × E0, the training task is in the fatigue stage. Step 4.2: The resistance in the initial stage is shown in formula (3): Fn=[1-c×(An-A0 / 2) / A0]×F0(3); Step 4.3: The resistance during the fatigue stage is shown in formula (4): Fn=[1-d×(An-A0 / 2) / A0]×F0-(1-En-1 / E0)×F0 (4).

10. The interactive rehabilitation training method of the shoulder joint resistance training device according to claim 9, characterized in that, The value of c is -0.2 and the value of d is -0.6.

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