External limb device and external limb control method

Abstract

The present invention discloses an external limb device and an external limb control method. The device includes a waist support assembly, a shoulder support assembly, a connector, at least one robotic arm, and a control module. The waist support assembly is worn on the waist of the human body, and the shoulder support assembly is worn on the shoulder of the human body. The waist support assembly and the shoulder support assembly are spaced apart. The two ends of the connector are fixedly connected to the waist support assembly and the shoulder support assembly respectively. At least one robotic arm is rotatably connected to the connector. The control module is used to collect and process the human body's motion electromyographic signals and guide the motion posture of the robotic arm through the processing results. The waist support assembly and the shoulder support assembly of the present invention are spaced apart, and the hollow design saves material and reduces the overall weight of the device. At the same time, by processing the electromyographic signals and controlling the motion posture of the robotic arm through the processed electromyographic signals, the purpose of smooth dynamic interaction between the human body and the robotic arm is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of external limb robots, and in particular to an external limb device and an external limb control method. Background Art

[0002] In recent years, thanks to the rapid development of science and technology, research on exo-robots has made significant progress. Unlike exoskeletons, exo-robots can be extended onto the human body to help humans achieve tasks beyond their capabilities, thus providing strong support for daily life and work.

[0003] Chinese patent application number 2020114971054 discloses an external limb auxiliary grasping device, which includes three parts: a grasping device, a posture extraction device, and a power input and control device. It adopts a multi-link structure for grasping, which can achieve the purpose of stable and diversified control. However, the design structure is complex, involves too many materials, and the overall mass is too heavy, which is not suitable for human wear.

[0004] Chinese patent application number 2019106119360 discloses a dual-purpose exo-limb robot for assisting human locomotion, comprising a rigid wearable exosuit, a locomotion-assisting module, and a terminal gripper. The patent states that the robot can serve as both a "third leg" to assist walking and an "arm" to assist in grasping movements. Its compact structure and integrated functionality make it suitable for patients with hemiplegia. However, the patent does not provide a clear control method, making it difficult to accurately control the device. Summary of the Invention

[0005] The purpose of the present invention is to overcome the above technical deficiencies and provide an external limb device to solve the technical problems in the prior art that the external limb device has a complex structure and the control method of the external limb cannot achieve smooth interaction between the wearer and the external limb.

[0006] In order to achieve the above technical objectives, the present invention adopts the following technical solutions:

[0007] In the first aspect, the present invention provides an external limb device, comprising: a waist support component, a shoulder support component, a connecting piece, at least one robotic arm and a control module, wherein the waist support component is worn on the waist of the human body, the shoulder support component is worn on the shoulder of the human body, the waist support component and the shoulder support component are spaced apart, the two ends of the connecting piece are fixedly connected to the waist support component and the shoulder support component respectively, the at least one robotic arm is rotatably connected to the connecting piece, the control unit is connected to the waist support component, the shoulder support component and the robotic arm, and the control module is used to collect the human body's motion electromyographic signals and generate robotic arm control instructions according to the motion electromyographic signals to control the motion posture of the robotic arm.

[0008] In some embodiments, the waist support assembly includes a waist ring and a waist locking member, the waist ring has an opening, the waist ring is worn on the human waist through the opening, one end of the connecting member is connected to the waist ring, and the waist locking member is installed at both ends of the waist ring to close the opening of the waist ring.

[0009] In some embodiments, the shoulder support assembly includes a shoulder ring, two fixing straps and a shoulder locking member, the shoulder ring has an opening, the shoulder ring is mounted on the human shoulder through the opening, the two fixing straps are spaced apart and their two ends are fixedly connected to the opposite sides of the shoulder ring, the connecting member is located between the two fixing straps and one end is connected to the shoulder ring, the shoulder locking member is installed at both ends of the shoulder ring to close the opening of the shoulder ring.

[0010] In some embodiments, the robotic arm includes a first link, a second link and a gripping portion, the first link, the second link and the gripping portion are rotatably connected in sequence, and an end of the first link away from the second link is rotatably connected to the connecting member.

[0011] In some embodiments, the control module includes a signal acquisition unit, a signal processing unit and a signal feedback unit, and the signal acquisition unit, signal processing unit and signal feedback unit are electrically connected in sequence. The signal acquisition unit is used to collect human electromyographic signals, the signal processing unit is used to process the electromyographic signals and generate the robotic arm control instructions, and the signal feedback unit is used to control the motion posture of the robotic arm according to the robotic arm control instructions.

[0012] In a second aspect, the present invention further provides an external limb control method, which is applied to any of the external limb devices described above, and the method comprises:

[0013] Acquire human electromyographic signals;

[0014] Using a preset wavelet transform method to perform feature quantitative analysis on the human electromyographic signal to obtain a muscle synergy effect characteristic index;

[0015] According to the influence of muscle synergy on the position and force of the robot arm, the characteristic index of muscle synergy and the initial external limb adaptive impedance controller of position and force are established;

[0016] Based on a preset target posture, and according to the influence of fatigue on the maximum excitability and maximum activation time of muscle synergy, the initial external limb adaptive impedance controller is trained to obtain a target impedance controller;

[0017] Inputting the muscle synergy effect characteristic index as an input parameter into the target impedance controller to obtain the target position and target force state of the robotic arm;

[0018] Adjust the robotic arm to the target posture according to the target position and target force state.

[0019] In some embodiments, the method of using a preset wavelet transform method to perform feature quantitative analysis on the human electromyographic signal to obtain a muscle synergy effect characteristic index includes:

[0020] Performing wavelet decomposition on the human electromyographic signal to obtain multiple decomposition signals in different frequency bands;

[0021] Feature extraction is performed on the decomposed signals of the multiple different frequency bands to obtain muscle synergy feature indicators.

[0022] In some embodiments, the preset wavelet transform method can be expressed by the following formula:

[0023]

[0024] Among them, a is the scale, τ is the translation, WT represents the characteristic index of wavelet transform, and ψ is the wavelet transform parameter.

[0025] In some embodiments, the initial target impedance controller can be expressed by the following formula:

[0026]

[0027] Among them, M D ,B D are positive definite inertia matrix and damping matrix, u r is the control input of the external limbs, F is the human-machine interaction force, d ds is the external interference force, and X represents the displacement of external limb movement.

[0028] In some embodiments, after obtaining the human body electromyographic signal, the method further includes:

[0029] The preset filtering method is used to filter the human electromyographic signal to obtain a filtered electromyographic signal.

[0030] Compared with the prior art, the external limb device and external limb control method provided by the present invention include: a waist support component, a shoulder support component, a connecting piece, at least one robotic arm and a control module, wherein the waist support component is worn on the human waist, the shoulder support component is worn on the human shoulder, the waist support component and the shoulder support component are spaced apart, the two ends of the connecting piece are fixedly connected to the waist support component and the shoulder support component respectively, the at least one robotic arm is rotatably connected to the connecting piece, the control unit is connected to the waist support component, the shoulder support component and the robotic arm, and the control module is used to collect and process the human body's motion electromyographic signals, and guide the motion posture of the robotic arm through the processing results. From the perspective of the device structure, the present invention places the forces of the waist support component and the shoulder support component in contact with the human body and distributed at intervals. The hollow design not only saves materials and reduces the overall weight of the device, but also ensures the stability of the device relative to the human body. At the same time, the control module collects the human body's electromyographic signals, processes the electromyographic signals, and finally controls the movement posture of the robotic arm through the processed electromyographic signals, which can achieve the purpose of highly flexible dynamic interaction between the human body and the robotic arm. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 1 is a schematic structural diagram of an embodiment of an external limb device provided by the present invention;

[0032] Figure 2 This is a schematic structural diagram of an embodiment of the exo-limb device provided by the present invention worn on a human body;

[0033] Figure 3 1 is a schematic structural diagram of an embodiment of a waist support assembly and a shoulder support assembly in the external limb device provided by the present invention;

[0034] Figure 4 1 is a schematic structural diagram of an embodiment of a mechanical arm in the exo-limb device provided by the present invention;

[0035] Figure 5 It is a flow chart of an embodiment of the external limb control method provided by the present invention. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0037] Exo-limb robots play a very important auxiliary role in our daily lives. On the one hand, exo-limb robots can help people with disabilities complete some tasks that are difficult to complete. For example, people with difficulty moving their arms or legs can use exo-limb robots to replace the inconvenient parts of their bodies, thereby meeting the basic functions needed in daily life. On the other hand, exo-limb robots can serve as auxiliary joints, participating in activities in life or work as a third arm or a third leg, so as to improve the work efficiency of the human body.

[0038] The present invention provides an external limb device, please refer to Figure 1 and Figure 2 , comprising: a waist support component 1, a shoulder support component 2, a connector 3, at least one robotic arm 4 and a control module 5, the waist support component 1 is worn on the human waist, the shoulder support component 2 is worn on the human shoulder, the waist support component 1 and the shoulder support component 2 are spaced apart, the two ends of the connector 3 are fixedly connected to the waist support component 1 and the shoulder support component 2, respectively, the at least one robotic arm 4 is rotatably connected to the connector 3, the control module 5 is connected to the waist support component 1, the shoulder support component 2 and the robotic arm 4, the control module 5 is used to collect and process the human body's motion electromyographic signals, and guide the motion posture of the robotic arm through the processing results.

[0039] In this embodiment, firstly, from the perspective of the device structure, the waist support component and the shoulder support component are placed in contact with the human body and are spaced apart. The hollow design not only saves materials and reduces the overall weight of the device, but also ensures the stability of the device relative to the human body. At the same time, the control module collects the human body's electromyographic signals, processes the electromyographic signals, and finally controls the movement posture of the robotic arm through the processed electromyographic signals, thereby achieving the purpose of highly flexible dynamic interaction between the human body and the robotic arm.

[0040] It should be noted that the waist support assembly 1 and the shoulder support assembly 2 mainly play the role of support and connection. It can be understood that, on the one hand, the waist support assembly and the shoulder support assembly should have sufficient comfort and softness to facilitate fitting the human body; on the other hand, a "vest-type" structure can be formed between the waist support assembly, the shoulder support assembly and the connecting parts, which not only ensures the connection strength and wearing comfort, but also saves materials and reduces the structural complexity of the device.

[0041] Furthermore, the number of robotic arms can be one, two, or more, and the number of robotic arms can be set according to actual needs. It is understood that the multiple robotic arms can work together or independently through external limb control methods. The ends of the connector 3 are located at the shoulder and waist, so the robotic arms can be installed at either the waist or the shoulder. The robotic arms can perform different functions when located in different positions, thereby increasing the scope of the collaborative and auxiliary functions of the robotic arms.

[0042] In some embodiments, see Figure 3 The waist support group 1 includes a waist ring 11 and a waist locking member 12. The waist ring 11 has an opening, and the waist ring 11 is worn on the human waist through the opening. One end of the connecting member 3 is connected to the waist ring 11, and the waist locking member 12 is installed at both ends of the waist ring 11 to close the opening of the waist ring 11.

[0043] In this embodiment, the waist ring member has a certain degree of flexibility and can be extended or bent. After the waist ring member is put on the human body, the waist ring member 11 is fixed on the human body through the waist locking member 12. Specifically, in this embodiment, the waist ring member is a Velcro.

[0044] It should be noted that the size of the waist ring 11 is adjustable to fit people of different body shapes.

[0045] In some embodiments, see Figure 3 The shoulder support assembly 2 includes a shoulder ring 21, two fixing straps 22 and a shoulder locking member 23. The shoulder ring 21 has an opening, and the shoulder ring 21 is sleeved on the human shoulder through the opening. The two fixing straps 22 are distributed at intervals and their two ends are fixedly connected to the opposite sides of the shoulder ring 21 respectively. The connecting member 3 is located between the two fixing straps 22 and one end is connected to the shoulder ring 21. The shoulder locking member 23 is installed at both ends of the shoulder ring to close the opening of the shoulder ring.

[0046] In this embodiment, the shoulder ring 21 and the two fixing straps 22 together form a shoulder-strap fixing form. As a component that fits closely with and supports the human body, the ring size of the shoulder ring 21 can be changed. At the same time, the two fixing straps are flexible and adjustable in length, which can adapt to people of different body shapes.

[0047] In some embodiments, see Figure 4The robotic arm 4 includes a first connecting rod 41, a second connecting rod 42 and a grasping portion 43. The first connecting rod 41, the second connecting rod 42 and the grasping portion 43 are rotatably connected in sequence, and the end of the first connecting rod 41 away from the second connecting rod 42 is rotatably connected to the connecting member 3.

[0048] In this embodiment, the robotic arm 4 uses a connecting rod as the main structure, which simplifies the structure of the robotic arm and reduces the weight of the entire device. Specifically, the first connecting rod, the second connecting rod and the grasping portion are connected by a hinge, and the first connecting rod and the connecting member are also connected by a hinge.

[0049] In some embodiments, the control module 5 includes a signal acquisition unit, a signal processing unit and a signal feedback unit, and the signal acquisition unit, signal processing unit and signal feedback unit are electrically connected in sequence. The signal acquisition unit is used to collect human electromyographic signals, and the signal processing unit is used to process the electromyographic signals and transmit the processing results to the signal feedback unit. The signal unit guides the movement posture of the robotic arm according to the processing results.

[0050] In this embodiment, the human body's electromyographic signals are collected by the signal acquisition unit, and the electromyographic signals are processed. The processed results are fed back to the robotic arm through the signal feedback unit, and the robotic arm is guided to move and adjust to the desired posture.

[0051] It should be noted that the control module also includes a motor module, a control panel, and a power module, wherein the motor module includes a brushless DC motor and a flange; the control panel includes a single-chip microcomputer and an inertial navigation system; and the power module includes a battery and a voltage-dividing power supply.

[0052] Furthermore, the control panel controls the angle of rotation of the robotic arm joints, the speed of rotation of the joints, and the torque of rotation of the joints through the single-chip microcomputer; the inertial navigation module is installed on the shoulder support assembly of the external limb, which is used to collect the posture information of the external limb device relative to the human body and then adjust the position of the external limb device to ensure the successful implementation of the overall task.

[0053] Furthermore, the power module includes a battery, a voltage conversion module, and a voltage shunt module. The voltage conversion module takes 24V as input and can output 5V and 24V. The 5V voltage is used to power the microcontroller, and the 24V voltage is used to power the modules. The voltage shunt module, because there are three modules that need power, shunts the 24V voltage to achieve multi-channel output to power the three modules separately.

[0054] Furthermore, the motor module includes three brushless DC motors with a torque of 24 NM, each motor serving as a rotating joint; the flange is used to connect the motor and other modules to drive the joint to rotate.

[0055] Based on the above external limb device, the embodiment of the present invention also provides an external limb control method, please refer to Figure 5 , external limb control methods include:

[0056] S501, obtaining human electromyographic signals;

[0057] S502, using a preset wavelet transform method to perform feature quantitative analysis on the human electromyographic signal to obtain a muscle synergy effect characteristic index;

[0058] S503, establishing a muscle synergy effect characteristic index, an initial external limb adaptive impedance controller for position and force based on the degree of influence of the muscle synergy effect on the position and force of the robotic arm;

[0059] S504: Based on a preset target posture and according to the influence of fatigue on the maximum excitability and maximum activation time of muscle synergy, the initial external limb adaptive impedance controller is trained to obtain a target impedance controller;

[0060] S505: Inputting the muscle synergy effect characteristic index as an input parameter into the target impedance controller to obtain the target position and target force state of the robotic arm;

[0061] S506: Adjust the robotic arm to the target posture according to the target position and target force state.

[0062] In this embodiment, the human body's electromyographic signals are first obtained, and the characteristics of the human body's electromyographic signals are extracted by wavelet transform to obtain muscle synergy characteristic indicators. Then, according to the influence of muscle synergy on the posture of the robotic arm, and based on the preset target posture, according to the influence of fatigue on the maximum excitability and maximum activation time of muscle synergy, a target impedance controller is trained. Subsequently, the target posture and force state of the robotic arm corresponding to the current muscle synergy characteristic indicators are obtained according to the target impedance controller, and the target posture and force state are used as the target adjustment direction to adjust the movement of the robotic arm to the target posture. By extracting the human body's electromyographic signals, the embodiment of the present invention can establish dynamic interactive cooperation between the human body and the robotic arm, and at the same time has the advantage of accurate control.

[0063] In other embodiments of step S502, methods such as root mean square envelope detection, TKE operator, and wavelet transform can also be used to quantify the electromyographic signal. Specifically, by quantitatively analyzing the amplitude and average frequency of the electromyographic signal, and analyzing the muscle synergy activation matrix M during the human-machine collaboration process, iterative non-negative matrix decomposition is performed on it and expressed as M=C m×g W g×k , where W g×k is the muscle synergy modal matrix, C m×gis the corresponding time coefficient matrix.

[0064] In step S503, an external limb adaptive impedance controller is designed. Affected by the nonlinearity of the external limb and system interference, the dynamic model of the external limb can be expressed as Among them, M D ,B D are positive definite inertia matrix and damping matrix, u r is the control input of the external limbs, F is the human-machine interaction force, and f ds It is the external interference force and is related to the operation object.

[0065] Furthermore, in order to effectively eliminate the influence of external interactive environment interference and nonlinear factors of the external limb system, the external limb adaptive controller in this embodiment is a structure of impedance control and feedforward control, wherein the feedforward control part is mainly used to compensate for the influence of nonlinear factors of the external limb system itself and improve the dynamic control response performance of the system, and the impedance control part is used to ensure that the external interactive environment interference f ds The stability of the system can be improved under the condition of , and the influence of irregular human body movement on the system stability and accuracy can be compensated.

[0066] In step S504, the impedance characteristics of the human upper limbs and the rigidity and flexibility of the operating environment determine that the parameters of the impedance controller are variable. The impedance controller is mainly expressed as the relationship between stiffness, damping and human-computer interaction state. The difficulty of its design lies in finding the changing rules of stiffness and damping. The relative contribution change of muscle synergy before and after fatigue and the change of maximum activation time are used as one of the reference variables to measure the change of human motor function in human-computer collaboration. The relative contribution change refers to the different excitement of the muscle before and after fatigue, which leads to the change of electromyographic signal, and the maximum activation time refers to the time required for the muscle to reach maximum excitement. Combined with the influence of factors such as external limb nonlinearity and external interaction environment interference, the dynamic model of the external limb system is expressed as in and are the resistance stiffness and damping parameters under the influence of the above factors respectively.

[0067] In order to achieve the optimal control of impedance control, the human motion function impact evaluation index based on muscle synergy, position and speed matching is constructed, and the influence of motion error, interaction force and human motion function is established. and The relevant cost function is substituted into the closed-loop model of the impedance controller. Therefore, the design problem of the impedance controller parameters is simplified to solving the problem based on the minimum value of the cost function. Through reinforcement learning and other methods, the parameter variation pattern of the impedance controller can be found.

[0068] In some embodiments, the method of using a preset wavelet transform method to perform feature quantitative analysis on the human electromyographic signal to obtain a muscle synergy effect characteristic index includes:

[0069] Performing wavelet decomposition on the human electromyographic signal to obtain multiple decomposition signals in different frequency bands;

[0070] Feature extraction is performed on the decomposed signals of the multiple different frequency bands to obtain muscle synergy feature indicators.

[0071] In this embodiment, the wavelet transform method can be expressed by the following formula:

[0072]

[0073] Among them, a is the scale and τ is the translation.

[0074] In some embodiments, after obtaining the human body electromyographic signal, the method further includes:

[0075] The preset filtering method is used to filter the human electromyographic signal to obtain a filtered electromyographic signal.

[0076] In this embodiment, the electromyographic signal acquisition channel is used to collect the electromyographic signal of the human body during human-machine collaboration, and the collected electromyographic signal is filtered using a second-order Butterworth filter with a bandwidth of 40-55Hz to remove interference signals in the signal and obtain a filtered electromyographic signal.

[0077] The specific embodiments of the present invention described above do not limit the scope of protection of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the scope of protection of the claims of the present invention.

Claims

1. A method for controlling an external limb, applied to an external limb device, characterized in that: The exo-limb device includes: a waist support assembly, a shoulder support assembly, a connector, at least one robotic arm, and a control module; The waist support assembly is worn on the waist of a human body, and the shoulder support assembly is worn on the shoulder of a human body. The waist support assembly and the shoulder support assembly are spaced apart. The two ends of the connecting member are fixedly connected to the waist support assembly and the shoulder support assembly respectively. The at least one mechanical arm is rotatably connected to the connecting member. The control module is connected to the waist support assembly, the shoulder support assembly and the mechanical arm. The control module is used to collect the human body's motion electromyographic signals and generate mechanical arm control instructions according to the motion electromyographic signals to control the motion posture of the mechanical arm. The method comprises: Acquire human electromyographic signals; Using a preset wavelet transform method to perform feature quantitative analysis on the human electromyographic signal to obtain a muscle synergy effect characteristic index; According to the influence of muscle synergy on the position and force of the robot arm, the characteristic index of muscle synergy and the initial external limb adaptive impedance controller of position and force are established; Based on a preset target posture, and according to the influence of fatigue on the maximum excitability and maximum activation time of muscle synergy, the initial external limb adaptive impedance controller is trained to obtain a target impedance controller; Inputting the muscle synergy effect characteristic index as an input parameter into the target impedance controller to obtain the target position and target force state of the robotic arm; Adjust the robotic arm to the target posture according to the target position and target force state.

2. The external limb control method according to claim 1, characterized in that: The waist support assembly includes a waist ring member and a waist locking member; The waist ring has an opening, and the waist ring is worn on the human waist through the opening. One end of the connecting piece is connected to the waist ring, and the waist locking piece is installed at both ends of the waist ring to close the opening of the waist ring.

3. The external limb control method according to claim 1, characterized in that: The shoulder support assembly includes a shoulder ring, two fixing straps and a shoulder locking member; The shoulder ring has an opening, and the shoulder ring is mounted on the human shoulder through the opening. The two fixing belts are distributed at intervals and their two ends are fixedly connected to the opposite sides of the shoulder ring respectively. The connecting member is located between the two fixing belts and one end is connected to the shoulder ring. The shoulder locking member is installed at both ends of the shoulder ring to close the opening of the shoulder ring.

4. The external limb control method according to claim 1, characterized in that: The robotic arm includes a first connecting rod, a second connecting rod and a grasping portion; The first connecting rod, the second connecting rod and the grabbing portion are rotatably connected in sequence, and one end of the first connecting rod away from the second connecting rod is rotatably connected to the connecting member.

5. The external limb control method according to claim 1, characterized in that: The control module includes a signal acquisition unit, a signal processing unit and a signal feedback unit, and the signal acquisition unit, signal processing unit and signal feedback unit are electrically connected in sequence; The signal acquisition unit is used to collect human electromyographic signals, the signal processing unit is used to process the electromyographic signals and generate the robotic arm control instructions, and the signal feedback unit is used to control the motion posture of the robotic arm according to the robotic arm control instructions.

6. The external limb control method according to claim 1, characterized in that: The method of using a preset wavelet transform method to perform a quantitative analysis on the human electromyographic signal to obtain a muscle synergy effect characteristic index includes: Performing wavelet decomposition on the human electromyographic signal to obtain multiple decomposition signals in different frequency bands; Feature extraction is performed on the decomposed signals of the multiple different frequency bands to obtain muscle synergy feature indicators.

7. The external limb control method according to claim 6, characterized in that: The preset wavelet transform method can be reflected by the following formula: Among them, a is the scale, τ is the translation, and WT represents the characteristic index of wavelet transform. is the wavelet transform parameter.

8. The external limb control method according to claim 1, characterized in that: The initial external limb adaptive impedance controller can be expressed by the following formula: in, are positive definite inertia matrix and damping matrix respectively, For external limb control input, For human-computer interaction, is the external interference force, and X represents the displacement of external limb movement.

9. The external limb control method according to claim 1, characterized in that: After obtaining the human body electromyographic signal, the method further includes: The preset filtering method is used to filter the human electromyographic signal to obtain a filtered electromyographic signal.

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