Functional electrical stimulation and pneumatic muscle exoskeleton cooperative control method based on dynamic angle distribution

Abstract

The invention discloses a functional electrical stimulation and pneumatic muscle exoskeleton cooperative control method based on dynamic angle distribution. The method comprises the steps that S1, an expected track is generated according to parameters input by a user; s2, elbow joint motion angle parameters are collected in real time to generate an actual track; s3, constructing a function for dynamically distributing angles of functional electrical stimulation and pneumatic muscle exoskeleton according to an error angle between an expected trajectory and an actual trajectory; s4, constructing two iterative learning controllers for performing iterative learning on the angles of the functional electrical stimulation and the pneumatic muscle exoskeleton respectively, and outputting functional electrical stimulation control parameters and pneumatic muscle exoskeleton control parameters; s5, the electrical stimulator outputs an electric pulse according to the pulse width signal; meanwhile, the micro pump outputs an air source to inflate the pneumatic muscle exoskeleton according to a regulating signal of the proportional valve. Error angles are dynamically distributed, output of functional electrical stimulation and pneumatic muscle exoskeleton is adjusted, the auxiliary effect of the functional electrical stimulation and the pneumatic muscle exoskeleton on the upper limb joints is adjusted, the upper limb joints complete expected movement, control precision is guaranteed, muscle fatigue possibly caused by electrical stimulation is reduced, damage to muscles is relieved, and the effect of controlling the upper limb joints is achieved. The application value of the hybrid rehabilitation system in the exercise rehabilitation field is improved.

Description

Technical Field

[0001] This invention belongs to the fields of biomedical engineering and rehabilitation engineering, specifically a method for the coordinated control of functional electrical stimulation and pneumatic muscle exoskeleton based on dynamic angle allocation. Background Art

[0002] Functional electrical stimulation (FES), as an effective rehabilitation method, applies low-frequency electrical pulses to stimulate the patient's muscles, assisting in voluntary movement and playing a crucial role in restoring motor function. However, prolonged electrical stimulation may lead to muscle fatigue, affecting rehabilitation outcomes. To address this issue, the introduction of rehabilitation robots has significantly improved the FES rehabilitation process. Through precise motion assistance, rehabilitation robots can effectively reduce the duration and intensity of electrical stimulation, thereby reducing muscle fatigue and improving patient comfort and rehabilitation efficiency.

[0003] Current collaborative control strategies largely focus on torque allocation, but torque estimation typically relies on complex Hill models, making parameter determination difficult and cumbersome. In contrast, direct angle allocation is simpler and more straightforward. Furthermore, the control allocation between the FES and the motor / orthosis needs to be more systematic and rigorous to optimize their synergy and ensure the efficiency and safety of rehabilitation training. Existing allocation strategies also fail to adequately consider the effects of fatigue. Summary of the Invention

[0004] To address the aforementioned problems, the present invention aims to provide a collaborative control method based on dynamic angle allocation. The advantage of the dynamic angle allocation strategy lies in its ability to respond in real-time to changes in the patient's movements, providing timely motion assistance, thereby improving the smoothness of training and reducing the complexity of the control system. It can flexibly adjust the auxiliary angles of functional electrical stimulation and pneumatic muscle exoskeleton based on real-time feedback, making rehabilitation training more comfortable and ensuring its safety and effectiveness.

[0005] The technical solution adopted by the present invention to achieve the above objectives is as follows:

[0006] A method for coordinated control of functional electrical stimulation and pneumatic muscle exoskeleton based on dynamic angle allocation is characterized by the following steps: electrical stimulation induces muscle contraction in the wearer, causing upper limb movement, while simultaneously controlling the pneumatic muscle exoskeleton to inflate and flexibly support the upper limb, jointly assisting the upper limb joints in completing the desired movement; the method steps include:

[0007] S1. Generate the desired trajectory based on the parameters input by the user;

[0008] S2. Real-time acquisition of elbow joint motion angle parameters to generate actual trajectory;

[0009] S3, Constructing functions, used to dynamically allocate the angles of functional electrical stimulation and pneumatic muscle exoskeleton based on the error angle between the desired trajectory and the actual trajectory;

[0010] S4. Construct two iterative learning controllers to iteratively learn the angles of functional electrical stimulation and pneumatic muscle exoskeleton, respectively, and output functional electrical stimulation control parameters and pneumatic muscle exoskeleton control parameters; the functional electrical stimulation control parameters are pulse width signals, and the pneumatic muscle exoskeleton control parameters are proportional valve adjustment signals.

[0011] S5, the electrical stimulator outputs electrical pulses according to the pulse width signal; at the same time, the micro pump outputs air source to inflate the pneumatic muscle exoskeleton according to the proportional valve adjustment signal.

[0012] Step S1 specifically involves:

[0013] Based on the motion characteristics during the bending process, the equation for elbow joint flexion motion is set as follows:

[0014]

[0015] Where T is the task time, set to 10 here; θ f θ0 is the maximum motion angle, determined according to the task; θ0 is the initial angle, and the polynomial coefficients k1, k2, k3 are determined according to the motion conditions.

[0016] Step S3 specifically involves:

[0017] Assigning the error angle between the expected trajectory and the actual trajectory, we have:

[0018] y d (t)=y FES (t)+y PME (t)

[0019] Where y d (t) represents the desired angle, y FES The angle of motion that needs to be adjusted for electrical stimulation of the FES is y PME The motion angles that need to be adjusted for the pneumatic muscle exoskeleton (PME);

[0020] Furthermore, the dynamically allocated electrical stimulation adjustment angle y under coordinated control FES Adjusting the angle y of the exoskeleton PME satisfy:

[0021]

[0022] The goal is to optimize the FES and PME angles to keep them within the required adjustment range while ensuring low-intensity FES output.

[0023] The solution optimizations for FES and PME are as follows:

[0024] By using fatigue as a weighting variable to consider muscle fatigue levels, a cost function J is generated:

[0025]

[0026] Where m1 and m2 are weighting coefficients. Depends on fatigue variables λ is the fatigue coefficient, and m2 is a constant; U is the angle output by FES. P =y PME The angle output by the PME;

[0027] The dynamic allocation problem is transformed into a constrained least squares optimization task; the optimization objective is to minimize the cost function:

[0028]

[0029] sty FES +y PME =y d

[0030] y FES ≤y PME

[0031] y FES >0,y PME >0

[0032] Find the appropriate y FES ,y PME To achieve the minimum value of J under constraints, the optimal dynamic angle allocation is realized. At this point, the angle allocation between FES and PME is optimal. Based on this, the pulse width and air pressure are adjusted to assist the elbow joint in completing the desired movement.

[0033] The method is implemented based on Simulink, specifically as follows:

[0034] 3-1) Construct the desired trajectory output unit using the S-Function function in Simulink;

[0035] 3-2) Calculate the error between the expected trajectory and the actual trajectory using the Add module;

[0036] 3-3) After the error is distributed through the divide_controller function, the error angles that need to be adjusted for functional electrical stimulation and pneumatic muscle exoskeleton are calculated respectively; then, combined with the control input at the previous moment, the current control input is calculated through their respective iterative learning controllers and sent to the electrical stimulation controller and the exoskeleton micropump.

[0037] Step 4) specifically involves:

[0038] 4-1) The Serial Send module based on the Simulink control system communicates with the Arduino chip and sends control input to the electrical stimulator through the Arduino UNO to adjust the electrical stimulation pulse width;

[0039] 4-2) The UDP Send module based on the Simulink control system communicates with the ESP32, and controls the solenoid valve through the ESP32 to adjust the exoskeleton air pressure value;

[0040] 4-3) The Simulink-based Serial Receive module receives joint angle data collected by the angle sensor and performs extraction, unpacking and conversion.

[0041] A functional electrical stimulation and pneumatic muscle exoskeleton-based coordinated control system based on dynamic angle allocation includes a host computer and a micropump and an electrical stimulator housed within a control package. The micropump supplies air to the pneumatic muscle exoskeleton via a trachea, causing it to inflate. The electrical stimulator outputs stimulation pulses to electrode patches attached to the arm. The host computer contains a programming unit that works in concert to stimulate the wearer, causing muscle contraction and upper limb movement, while simultaneously controlling the pneumatic muscle exoskeleton to provide flexible support to the upper limb. The programming unit in the host computer includes:

[0042] The desired trajectory unit is used to generate the desired trajectory based on the parameters input by the user.

[0043] The actual trajectory unit collects elbow joint motion angle parameters in real time and generates the actual trajectory;

[0044] The dynamic allocation unit uses a function built from the MATLAB Function module to dynamically allocate the angles of the functional electrical stimulation and the pneumatic muscle exoskeleton based on the error angle between the desired trajectory and the actual trajectory.

[0045] The iterative learning unit employs two iterative learning controllers to iteratively learn the angles of functional electrical stimulation and pneumatic muscle exoskeleton, respectively, and output functional electrical stimulation control parameters and pneumatic muscle exoskeleton control parameters. The functional electrical stimulation control parameters are pulse width signals, which are used by the electrical stimulator to output electrical pulses based on the pulse width signals. The pneumatic muscle exoskeleton control parameters are proportional valve adjustment signals, which are used by the micro-pump to output air to inflate the exoskeleton based on the proportional valve adjustment signals.

[0046] The control pack is worn around the user's waist; the pneumatic muscle exoskeleton is worn on the outside of the user's elbow, and supports the elbow after being inflated; the electrode patches are attached to the surface of the upper arm biceps brachii muscle, and after receiving stimulation pulses, output electrode pulse signals to stimulate the biceps brachii muscle to contract and cause upper limb movement.

[0047] The pneumatic muscle exoskeleton includes: a fabric base and a triangular retainer and multiple driving airbags disposed thereon. The multiple driving airbags form an airbag array. The triangular retainer is located on both sides of the airbag array. Each driving airbag and two triangular retainers are sequentially connected and connected to one of the air tubes. After the multiple driving airbags and two triangular retainers are filled with air, they expand to support the human upper limb.

[0048] Furthermore, the triangular retainer takes on a triangular structure after inflation; the drive airbag expands from the center to both sides after inflation.

[0049] Furthermore, the airbag array is arranged along the length of the fabric substrate in a denser middle and sparser sides manner, and the top of the driving airbags in the sparser sides is provided with a curvature limiting layer.

[0050] Furthermore, the fabric base of the denser middle driving airbag is made of non-elastic fabric, while the fabric base of the sparser sides of the driving airbag is made of elastic fabric, and the limiting layer is made of elastic fabric.

[0051] Furthermore, the electrode patch is attached to the surface of the biceps brachii muscle in the upper arm. After receiving the stimulation pulse from the control packet, it outputs an electrode pulse signal to stimulate the biceps brachii muscle to contract and cause upper limb movement.

[0052] Furthermore, the electrode patch is a self-adhesive pin patch that connects to the wire through a 2.0 mm socket.

[0053] The advantages of the above technical solution adopted in this invention are as follows:

[0054] 1. This invention employs a dynamic angle allocation-based collaborative control method, dynamically adjusting the auxiliary force of functional electrical stimulation and pneumatic muscle exoskeleton based on feedback to ensure that patients receive appropriate support during upper limb joint movements. This method not only improves the accuracy and smoothness of movement but also reduces the risk of muscle fatigue caused by electrical stimulation.

[0055] 2. This invention fully considers the impact of muscle fatigue in its design. By minimizing muscle fatigue and motor control errors, it optimizes the synergistic effect of the FES and pneumatic muscle exoskeleton. This optimization strategy enables patients to effectively avoid over-fatigue during repetitive rehabilitation training, while maintaining the precision of movement and accelerating the rehabilitation process.

[0056] 3. This invention employs an iterative learning control method to build the control system, while introducing a forgetting factor to balance new and old information during the learning process, preventing the system from becoming overly sensitive to early errors. This ensures learning efficiency while improving control stability and long-term performance. In each iteration, the control parameters are learned and corrected, allowing the system to gradually adapt to changes in the patient and external disturbances. Attached Figure Description

[0057] Figure 1 This is a schematic diagram of the overall process of the method of the present invention;

[0058] Figure 2 This is a schematic diagram of the control system of the present invention;

[0059] Figure 3 This is a schematic diagram of the trajectory changes during the iterative process of this invention;

[0060] Figure 4 This is a schematic diagram of the angle allocation results during the iterative process of this invention;

[0061] Figure 5 This is a front view of the device of the present invention after it has been worn by a user.

[0062] Figure 6 This is a rear view of a dual-drive elbow joint system based on functional electrical stimulation and a pneumatic muscle exoskeleton according to the present invention.

[0063] Figure 7 This is a schematic diagram of the pneumatic muscle exoskeleton in this invention;

[0064] In the diagram: 1-Control pack, 2-Pneumatic muscle exoskeleton, 3-Electrode patch, 4-Trachea, 5-Wire, 6-Fixture, 7-Curvature limiting layer, 8-Triangle retainer, 9-Drive airbag, 10-Elastic fabric base, 11-Non-elastic fabric base. Detailed Implementation

[0065] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of the present invention. However, the present invention can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of the invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0066] Figure 1 This is the overall flowchart of the present invention. Figure 2 This is a schematic diagram of the control system of the present invention. First, based on the motion characteristics of the bending process, the elbow joint bending motion equation is set:

[0067]

[0068] Where F(t) is the desired trajectory, T is the task time, which is set to 10 here; θ f The maximum motion angle is determined based on the task; the polynomial coefficients k1, k2, and k3 are determined based on the motion conditions.

[0069] Then, the error angle y between the expected trajectory F(t) and the actual trajectory F'(t) is calculated. d Distributing F(t) = F(t) - F'(t), we have:

[0070] y d (t)=y FES (t)+y PME (t)

[0071] Where y d (t) represents the desired angle, and the motion angle that the pneumatic muscle exoskeleton FES needs to adjust is y. FES The required motion angle for functional electrical stimulation of the PME is y. PME , The maximum angle of motion for electrical stimulation. Let be the maximum angle of motion of the exoskeleton. Let the minimum angle be denoted as . To ensure safety and effective output, the dynamically allocated electrical stimulation adjustment angle y under coordinated control is... FES Adjusting the angle y of the exoskeleton PME satisfy:

[0072]

[0073] The main goal is to control the optimized FES and PME angles within the required adjustment range, while ensuring low-intensity FES output to stimulate muscle activity, reduce fatigue, and extend training time.

[0074] According to relevant research, muscle fatigue is related to the setting of FES parameters. As the frequency, amplitude, and pulse width of FES increase, muscle activation increases, but fatigue is also more likely to occur. Correspondingly, reducing the stimulation intensity of FES can reduce muscle activation and fatigue. To effectively control fatigue levels, this study suggests reducing the pulse width of electrical stimulation to allow the PME to bear more exercise load, thereby maintaining moderate muscle activation while minimizing fatigue. The fatigue variable should be included as a weighted variable in the cost function to account for muscle fatigue levels.

[0075] Design cost function J:

[0076]

[0077] Where m1 and m2 are weighting coefficients, and m1 depends on the fatigue variable. set up m2 is a constant. Let the outputs of FES and PME be U, respectively. F U P Fatigue variable is λ is the fatigue coefficient, and we have:

[0078]

[0079] U P =y PME

[0080]

[0081] The dynamic allocation problem can be transformed into a constrained least squares optimization task. The optimization objective is to minimize the cost function:

[0082]

[0083] sty FES +y PME =y d

[0084] y FES >0,y PME >0

[0085] There exists a suitable y FES ,y PME This allows J to reach its minimum value under constraints, achieving optimal dynamic angle allocation. At this point, the angle allocation between FES and PME is optimal.

[0086] Based on this, the pulse width and air pressure are adjusted to assist the elbow joint in completing the desired movement. When the distribution error decreases, the control parameters of FES and PME are closer to the desired control input, thereby making the actual movement trajectory of the elbow joint closer to the desired trajectory and reducing the elbow joint movement error.

[0087] Based on this, a desired trajectory output module is constructed using the S-Function function in Simulink; the error between the desired trajectory and the actual trajectory is calculated through the Add module; after the error is distributed through the divide_controller, the required adjustment angles for functional electrical stimulation and pneumatic muscle exoskeleton are calculated separately, and then combined with the control input at the previous moment, the current control input is calculated through their respective iterative learning controllers and sent to the electrical stimulation controller and the exoskeleton controller; the electrical stimulation pulse width and exoskeleton air pressure are adjusted to adjust the motion assistance angle of the elbow joint by the electrical stimulation and exoskeleton, which is applied to the elbow joint; the actual elbow joint forearm motion angle relative to the upper arm is fed back in real time through the angle sensor.

[0088] Then, the communication module of the electrical stimulator was debugged. The Simulink control system communicates with the Arduino based on the Serial Send module, and sends control input to the electrical stimulator through the Arduino UNO to adjust the electrical stimulation pulse width. The communication module of the pneumatic muscle exoskeleton was also debugged. The Simulink control system communicates with the ESP32 based on the UDP Send module, and controls the solenoid valve through the ESP32 to adjust the exoskeleton air pressure value. Simulink receives the included angle data collected by the angle sensor based on the Serial Receive module, and performs extraction, unpacking and conversion.

[0089] Finally, the Simulink control system is run, and the controller outputs control input through iterative learning to adjust the auxiliary motion angles of functional electrical stimulation and pneumatic muscle exoskeleton. After multiple iterations, the two work together to assist the upper limb joints in completing the desired movement.

[0090] Figure 3 This diagram illustrates the trajectory changes during the iterative process of this invention. As the number of iterations increases, the actual trajectory gradually approaches the desired trajectory, indicating that this method can achieve effective tracking.

[0091] Figure 4 This diagram illustrates the angle allocation results during the iterative process of this invention. As the number of iterations increases, the allocated angles for functional electrical stimulation and the pneumatic muscle exoskeleton gradually decrease, indicating the effectiveness of the iterative learning control method. The error decreases with increasing iterations, and the required auxiliary angle gradually decreases. Simultaneously, the weight coefficient of functional electrical stimulation is smaller than that of the pneumatic muscle exoskeleton, indicating the effectiveness of the allocation strategy. The pneumatic muscle exoskeleton plays a major auxiliary role, ensuring control accuracy, reducing muscle fatigue, and demonstrating good real-time application value. The dynamic changes indicate that the system is continuously undergoing dynamic adjustments.

[0092] like Figure 5 and Figure 6 As shown, the user wears this device. A dual-drive assistive movement device for the elbow joint based on electrical stimulation and a pneumatic muscle exoskeleton consists of a control pack 1, a pneumatic muscle exoskeleton 2, electrode patches 3, an air tube 4, wires 5, and a fixing element 6. The pneumatic muscle exoskeleton 2 is connected to the control pack 1 via the air tube 4, and the electrode patches 3 are connected to the control pack 1 via the wires 5. The control pack 1 provides an air source to the pneumatic muscle exoskeleton 2 and provides stimulation pulses to the electrode patches 3. The pneumatic muscle exoskeleton 2 is fixed to the outside of the elbow joint by the fixing element 6. The control pack 1 is worn around the user's waist and contains a micro-pump and an electrical stimulator. The micro-pump is connected to the air tube 4 to output the air source, and the electrical stimulator is connected to the wires 5 to output stimulation pulses. The electrode patches 3 are attached to the biceps brachii muscle of the upper arm, stimulating the biceps brachii muscle to contract upon receiving stimulation pulses. Upon the introduction of air, the patches expand, flexibly supporting the upper limb.

[0093] like Figure 7As shown, the pneumatic muscle exoskeleton 2 includes a fabric base, multiple driving airbags 9 arrayed on the fabric base, and triangular retainers 8 located on both sides of the multiple driving airbags 9. Each driving airbag 9 and the two triangular retainers 8 are sequentially connected and connected to an air tube 4. After being inflated by an air source, the multiple driving airbags 9 and the two triangular retainers 8 expand, thereby flexibly supporting the human upper limb. The multiple driving airbags 9 are arranged along the length of the fabric base in a denser middle and sparser side manner, and the top of the driving airbags 9 in the sparser side parts is provided with a curvature limiting layer 7. The triangular retainers form a triangular structure after inflation; the driving airbags expand from the middle to both sides after inflation. The fabric base below the denser driving airbags 9 in the middle is made of a non-elastic fabric base 11, and the fabric base below the sparser driving airbags 9 on both sides is made of an elastic fabric base 10.

[0094] The elastic fabric base 10 and the limiting layer 7 are made of spandex material through elastic weaving. The non-elastic fabric base 11 is made of nylon Oxford cloth.

[0095] Both the drive airbag and the triangle retainer are primarily made of fabric and TPU film to ensure flexible support and sealing performance.

[0096] The electrode patches are self-adhesive pin patches that connect to wire 5 via 2.0 mm sockets. This limits the output of the electrical stimulator to ensure safe use.

[0097] The fastener 6 uses a ring-shaped strap or Velcro.

[0098] The miniature pump in control package 1 is a Kamer KZP12, and the electrical stimulator is a Sichary dual-channel electrical stimulation module.

[0099] When the user wears the device, firstly, the control pack 1 is worn around the user's waist. The pneumatic muscle exoskeleton 2 is fixed to the outside of the elbow joint via the fastener 6, and the electrode patch 3 is attached to the biceps brachii muscle of the upper arm. Then, the switch of the micro-pump and electrical stimulator inside the control pack 1 is pressed. The micro-pump outputs air through the air tube 4, and the electrical stimulator outputs stimulation pulses. At this time, the electrode patch 3 attached to the biceps brachii muscle receives the stimulation pulses and stimulates the biceps brachii muscle to contract, generating arm movement. Simultaneously, the triangular retainer inflates into a triangular structure, and the drive airbag expands to both sides after inflation, providing support to the user's arm. The fabric base of the densely packed drive airbag 9 in the middle is made of non-elastic fabric 11, and the drive airbag 9 in this part provides stress support against the elbow after inflation. Since the fabric base of the sparsely packed drive airbags 9 on both sides is made of elastic fabric 10, the drive airbag 9 in this part can bend and extend to both sides after inflation to adapt to the radius of curvature of the elbow movement, forming flexible support on both sides of the elbow.

[0100] This scheme adjusts the output pulse width of the electrical stimulator switch and changes the inflation volume of the micro motor by adjusting the proportional valve air pressure, so that the pneumatic muscle exoskeleton 2 can complete bending movements of different speeds and ranges with the elbow joint.

[0101] The above description is merely a few embodiments of this application and is not intended to limit this application in any way. Although this application discloses preferred embodiments as described above, it is not intended to limit this application. Any changes or modifications made by those skilled in the art without departing from the scope of the technical solution of this application using the disclosed technical content are equivalent to equivalent implementation cases and fall within the scope of the technical solution.

Claims

1. A method for coordinated control of functional electrical stimulation and pneumatic muscle exoskeleton based on dynamic angle allocation, characterized in that, The following steps are performed: electrical stimulation induces muscle contraction in the wearer, causing upper limb movement; simultaneously, a pneumatic muscle exoskeleton is inflated to provide flexible support for the upper limb, jointly assisting the upper limb joints in completing the desired movement; the method includes: S1. Generate the desired trajectory based on the parameters input by the user; S2. Real-time acquisition of elbow joint motion angle parameters to generate actual trajectory; S3, Constructing functions, used to dynamically allocate the angles of functional electrical stimulation and pneumatic muscle exoskeleton based on the error angle between the desired trajectory and the actual trajectory; S4. Construct two iterative learning controllers to iteratively learn the angles of functional electrical stimulation and pneumatic muscle exoskeleton, respectively, and output functional electrical stimulation control parameters and pneumatic muscle exoskeleton control parameters; the functional electrical stimulation control parameters are pulse width signals, and the pneumatic muscle exoskeleton control parameters are proportional valve adjustment signals. S5, the electrical stimulator outputs electrical pulses according to the pulse width signal; at the same time, the micro pump outputs air source to inflate the pneumatic muscle exoskeleton according to the proportional valve adjustment signal.

2. The method for coordinated control of functional electrical stimulation and pneumatic muscle exoskeleton based on dynamic angle allocation according to claim 1, characterized in that, Step S1 specifically involves: Based on the motion characteristics during the bending process, the equation for elbow joint flexion motion is set as follows: Where T is the task time, set to 10 here; θ f θ0 is the maximum motion angle, determined according to the task; θ0 is the initial angle, and the polynomial coefficients k1, k2, k3 are determined according to the motion conditions.

3. The method for coordinated control of functional electrical stimulation and pneumatic muscle exoskeleton based on dynamic angle allocation according to claim 1, characterized in that, Step S3 specifically involves: Assigning the error angle between the expected trajectory and the actual trajectory, we have: y d (t)=y FES (t)+y PME (t) Where y d (t) represents the desired angle, y FES The angle of motion that needs to be adjusted for electrical stimulation of the FES is y PME The motion angles that need to be adjusted for the pneumatic muscle exoskeleton (PME); Furthermore, the dynamically allocated electrical stimulation adjustment angle y under coordinated control FES Adjusting the angle y of the exoskeleton PME satisfy: The goal is to optimize the FES and PME angles to keep them within the required adjustment range while ensuring low-intensity FES output.

4. The method for coordinated control of functional electrical stimulation and pneumatic muscle exoskeleton based on dynamic angle allocation according to claim 3, characterized in that, The solution optimizations for FES and PME are as follows: By using fatigue as a weighting variable to consider muscle fatigue levels, a cost function J is generated: Where m1 and m2 are weighting coefficients. Depends on fatigue variables λ is the fatigue coefficient, and m2 is a constant; U is the angle output by FES. P =y PME The angle output by the PME; The dynamic allocation problem is transformed into a constrained least squares optimization task; the optimization objective is to minimize the cost function: sty FES +y PME / and d and FES ≤y PME and FES >0,y PME >0 Find the appropriate y FES ,y PME To achieve the minimum value of J under constraints, the optimal dynamic angle allocation is realized. At this point, the angle allocation between FES and PME is optimal. Based on this, the pulse width and air pressure are adjusted to assist the elbow joint in completing the desired movement.

5. The method for coordinated control of functional electrical stimulation and pneumatic muscle exoskeleton based on dynamic angle allocation according to claim 1, characterized in that, The method is implemented based on Simulink, specifically as follows: 3-1) Construct the desired trajectory output unit using the S-Function function in Simulink; 3-2) Calculate the error between the expected trajectory and the actual trajectory using the Add module; 3-3) After the error is distributed through the divide_controller function, the error angles that need to be adjusted for functional electrical stimulation and pneumatic muscle exoskeleton are calculated respectively; then, combined with the control input at the previous moment, the current control input is calculated through their respective iterative learning controllers and sent to the electrical stimulation controller and the exoskeleton micropump.

6. The method for coordinated control of functional electrical stimulation and pneumatic muscle exoskeleton based on dynamic angle allocation according to claim 1, characterized in that, Step 4) specifically involves: 4-1) The Serial Send module based on the Simulink control system communicates with the Arduino chip and sends control input to the electrical stimulator through the Arduino UNO to adjust the electrical stimulation pulse width; 4-2) The UDP Send module based on the Simulink control system communicates with the ESP32, and controls the solenoid valve through the ESP32 to adjust the exoskeleton air pressure value; 4-3) The Simulink-based Serial Receive module receives joint angle data collected by the angle sensor and performs extraction, unpacking and conversion.

7. A functional electrical stimulation and pneumatic muscle exoskeleton coordinated control system based on dynamic angle allocation, characterized in that, The device includes a host computer and a micro-pump and an electrical stimulator housed within a control package. The micro-pump delivers air through a trachea to the pneumatic muscle exoskeleton, causing it to inflate. The electrical stimulator outputs stimulation pulses to electrode patches attached to the arm. The host computer contains a programming unit that works in conjunction with these components to stimulate the wearer, causing muscle contraction and upper limb movement, while simultaneously controlling the pneumatic muscle exoskeleton to provide flexible support for the upper limb. The programming unit in the host computer includes: The desired trajectory unit is used to generate the desired trajectory based on the parameters input by the user. The actual trajectory unit collects elbow joint motion angle parameters in real time and generates the actual trajectory; The dynamic allocation unit uses a function built from the MATLAB Function module to dynamically allocate the angles of the functional electrical stimulation and the pneumatic muscle exoskeleton based on the error angle between the desired trajectory and the actual trajectory. The iterative learning unit employs two iterative learning controllers to iteratively learn the angles of functional electrical stimulation and pneumatic muscle exoskeleton, respectively, and output functional electrical stimulation control parameters and pneumatic muscle exoskeleton control parameters. The functional electrical stimulation control parameters are pulse width signals, which are used by the electrical stimulator to output electrical pulses based on the pulse width signals. The pneumatic muscle exoskeleton control parameters are proportional valve adjustment signals, which are used by the micro-pump to output air to inflate the exoskeleton based on the proportional valve adjustment signals.

8. The functional electrical stimulation and pneumatic muscle exoskeleton coordinated control system based on dynamic angle allocation according to claim 1, characterized in that, The control pack is worn around the user's waist; the pneumatic muscle exoskeleton is worn on the outside of the user's elbow, and supports the elbow after being inflated; the electrode patches are attached to the surface of the upper arm biceps brachii muscle, and after receiving stimulation pulses, output electrode pulse signals to stimulate the biceps brachii muscle to contract and cause upper limb movement.

9. The functional electrical stimulation and pneumatic muscle exoskeleton coordinated control system based on dynamic angle allocation according to claim 1, characterized in that, The pneumatic muscle exoskeleton includes: a fabric base and a triangular retainer and multiple driving airbags disposed thereon. The multiple driving airbags form an airbag array. The triangular retainer is located on both sides of the airbag array. Each driving airbag and two triangular retainers are sequentially connected and connected to one of the air tubes. After the multiple driving airbags and two triangular retainers are filled with air, they expand to support the human upper limb.

Images