A method and device for adaptive admittance compliance control of a prosthesis

Abstract

This application applies to the field of prosthetic technology and provides a method and device for adaptive admittance compliance control of a prosthesis, including: obtaining motion data of a user while using a prosthesis; calculating the user's desired reference trajectory while using the prosthesis based on the motion data; obtaining real-time ground reaction force data while the user is using the prosthesis; constructing a preset admittance model based on the motion data and the ground reaction force data; and using the preset admittance model to correct the desired reference trajectory to obtain a target reference trajectory. This solution improves the user experience by obtaining real-time ground reaction force data while the user is using the prosthesis and adjusting the gait trajectory in real time using the preset admittance model.

Description

Technical Field

[0001] The present application relates to the technical field of prosthetic limbs, and in particular to a method and device for adaptive admittance compliance control of prosthetic limbs. Background Art

[0002] When patients with thigh amputations use prosthetic limbs to walk in the real world, they may encounter a variety of outdoor terrains, such as grass, sand, and asphalt roads, in addition to general indoor terrain. Compared with structured indoor surfaces, the softness and hardness of various outdoor terrains vary. When the prosthesis contacts different surfaces, the movement state needs to change accordingly, otherwise it will affect the user's safety.

[0003] In related solutions, the main approach is to roughly divide the user's movement states when using prostheses, and set a movement mode for each movement state. However, this method often requires the user to manually set the mode, which is difficult to adapt to changes and is not conducive to the user's normal walking. Summary of the Invention

[0004] The embodiments of the present application provide a method and device for prosthetic adaptive admittance compliance control, which can solve the technical problem of how to adjust the motion trajectory of a user's prosthetic limb in real time.

[0005] In a first aspect, an embodiment of the present application provides a method for adaptive admittance compliance control of a prosthesis, comprising:

[0006] Obtaining motion data of the user while using the prosthesis;

[0007] Calculating the user's expected reference trajectory when using the prosthesis based on the motion data;

[0008] Obtain real-time ground reaction force data when the user is using the prosthesis;

[0009] Combine motion data and ground reaction force data to build a preset admittance model;

[0010] The expected reference trajectory is corrected using the preset admittance model to obtain the target reference trajectory.

[0011] In one implementation, displacement data of a preset limb part of the user is obtained, where the preset limb part includes at least one of the following: a hip joint, a thigh joint, a knee joint, and an ankle joint;

[0012] A user prosthesis dynamics model is constructed based on the displacement data of the user's preset limb parts and the ground reaction force data. The user prosthesis dynamics model is used to calculate the user's expected reference trajectory when using the prosthesis.

[0013] In one implementation, calculating the expected reference trajectory of a user when using a prosthesis based on motion data includes:

[0014] Calculate the phase variable based on the motion data to obtain the gait phase value;

[0015] The user's expected reference trajectory when using the prosthesis is calculated based on the gait phase values.

[0016] In one implementation, a preset admittance model is constructed by combining motion data and ground reaction force data, including:

[0017] Calculate the phase variable based on the motion data to obtain the gait phase value;

[0018] Calculating a preset function using gait phase values;

[0019] Construct a preset admittance model using preset functions and ground reaction data.

[0020] In one implementation, the desired reference trajectory is corrected using a preset admittance model to obtain a target reference trajectory, including:

[0021] Calculating a preset dynamic matrix between the target reference trajectory and the desired reference trajectory using a preset admittance model;

[0022] Solve the preset dynamic matrix to obtain the target reference trajectory.

[0023] In one implementation, calculating the phase variable based on the motion data to obtain the gait phase value includes:

[0024] Obtaining thigh movement angle data of the user when using the prosthesis;

[0025] Phase variables were calculated based on thigh motion angle data;

[0026] Calculate the gait phase value based on the phase variable.

[0027] In one implementation, calculating the expected reference trajectory of a user when using a prosthesis based on the gait phase value includes:

[0028] Acquire knee joint motion data and ankle joint motion data of the user when using the prosthesis;

[0029] Constructing kinematic models of the prosthetic knee and ankle joints based on the user's knee and ankle motion data when using the prosthesis;

[0030] The expected reference trajectories of the user's knee and ankle joints when using the prosthesis are calculated based on the gait phase values ​​and the kinematic models of the prosthetic knee and ankle joints.

[0031] In a second aspect, embodiments of the present application provide a prosthetic adaptive admittance compliance control device, which has the function of implementing the method in the first aspect or any possible implementation thereof. Specifically, the device includes a unit that implements the method in the first aspect or any possible implementation thereof.

[0032] In one embodiment, the apparatus comprises:

[0033] an acquisition unit, configured to acquire motion data of a user when using a prosthesis;

[0034] a processing unit for calculating an expected reference trajectory of the user when using the prosthesis based on the motion data;

[0035] The processing unit is also used to obtain real-time ground reaction force data when the user uses the prosthesis;

[0036] The processing unit is further used to construct a preset admittance model by combining the motion data and the ground reaction force data;

[0037] The processing unit is further configured to correct the desired reference trajectory using a preset admittance model to obtain a target reference trajectory.

[0038] In a third aspect, an embodiment of the present application provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the computer device implements any one of the methods of the first aspect described above.

[0039] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a computer device, the computer device implements the method of any one of the implementation methods of the above-mentioned first aspect.

[0040] In a fifth aspect, an embodiment of the present application provides a computer program product, which, when executed on a computer device, enables the computer device to execute any one of the methods of the first aspect.

[0041] Compared with the prior art, the embodiments of the present application have the following beneficial effects: the expected reference trajectory is calculated based on the user's motion data, providing the user with an ideal gait trajectory when using a prosthesis; by obtaining the ground reaction force data of the user when using the prosthesis in real time, the user's force situation can be understood, facilitating real-time adjustment of the gait trajectory; combining the ground reaction force data to construct an admittance model helps to understand the dynamic characteristics of the user when using the prosthesis; using the preset admittance model to correct the expected reference trajectory, a target reference trajectory that is more in line with the user's actual situation is obtained, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a flow chart of a prosthetic adaptive admittance compliance control method provided in an embodiment of the present application.

[0043] Figure 2 This is a schematic diagram of a scenario in which a user uses a prosthesis, provided in an embodiment of the present application.

[0044] Figure 3 This is a schematic diagram of parameters of a preset admittance model under different terrains provided in an embodiment of the present application.

[0045] Figure 4 This is a schematic diagram of the motion trajectory of a prosthesis on different terrains provided by an embodiment of the present application.

[0046] Figure 5 This is an overall flow chart of a prosthetic adaptive admittance compliance control method provided in an embodiment of the present application.

[0047] Figure 6 Schematic diagram of the structure of a prosthetic adaptive admittance compliance control device provided in an embodiment of the present application.

[0048] Figure 7 It is a structural diagram of the computer device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0049] A prosthesis is an assistive device that replaces a missing limb part, typically used to help amputees regain some limb function. Prostheses can be categorized as upper limb prostheses or lower limb prostheses, and are custom-made based on the missing part of the body.

[0050] It is understandable that users will encounter various terrain changes when using prostheses, such as walking from a concrete road to a grassy field, or from an indoor floor to an outdoor road. Due to the different composition structures of various terrains, the forces exerted on users when using prostheses are also different.

[0051] Changes in terrain may require users to constantly adjust their posture and gait to adapt to different ground conditions. For some novice users or those with poor physical strength, it may take more energy and time to adapt to terrain changes, increasing the difficulty of using the prosthesis.

[0052] That is, in the case of terrain changes, prosthetic limb users may face instability, poor adaptability, friction and wear, weight-bearing sensation, and obstacle climbing, etc. These inconveniences may affect the user's walking experience and comfort.

[0053] In response to the above problems, this application proposes a prosthetic limb control method that can solve the problem of adaptive compliant control when using a prosthetic limb on different terrains.

[0054] In order to further illustrate the technical solution of the present application, specific embodiments are provided below.

[0055] Figure 1 It is a flow chart of a prosthetic adaptive admittance compliance control method provided in an embodiment of the present application.

[0056] like Figure 1 As shown, the above method includes the following steps S101 to S105.

[0057] S101. Obtain motion data of a user when using a prosthesis.

[0058] Motion data refers to the angle data or displacement data between the user's body part and the prosthetic part when the user uses the prosthesis.

[0059] As an example and not a limitation, the motion data may include horizontal displacement data of the hip joint, vertical displacement data of the hip joint, thigh displacement data, knee joint displacement data, ankle joint displacement data, motion angle data of the user's thigh, etc. Specific motion data may be selected based on actual conditions and is not limited here.

[0060] S102: Calculate the expected reference trajectory of the user when using the prosthesis based on the motion data.

[0061] The expected reference trajectory refers to the gait trajectory calculated based on the user's personal characteristics and motion data, that is, the ideal motion state that the user should achieve when using a prosthesis.

[0062] It can be understood that the user's expected reference trajectory when using the prosthesis can be calculated more accurately based on the acquired user motion data.

[0063] S103. Acquire ground reaction force data of the user when using the prosthesis in real time.

[0064] In prosthetic limb usage, ground reaction force refers to the ground reaction force exerted on the user when they step on the ground. By acquiring real-time ground reaction force data, we can understand the force exerted on the user's leg when using the prosthesis and adjust the desired reference trajectory of the prosthesis.

[0065] S104: Construct a preset admittance model by combining the motion data and the ground reaction force data.

[0066] An admittance model is a control system model used to describe an object's response to external forces. A pre-configured admittance model is built based on the user's motion data and ground reaction force data to analyze the user's dynamic characteristics and response when using a prosthetic limb.

[0067] S105: Correct the expected reference trajectory using a preset admittance model to obtain a target reference trajectory.

[0068] The target reference trajectory refers to the real-time gait trajectory generated by combining the user's motion data and the ground reaction force during the user's movement.

[0069] The expected reference trajectory is calculated based on the user's motion data to provide the user with an ideal gait trajectory when using a prosthesis; by obtaining the user's ground reaction force data in real time when using the prosthesis, the user's force situation can be understood, facilitating real-time adjustment of the gait trajectory; combining the ground reaction force data to construct an admittance model helps to understand the dynamic characteristics of the user when using the prosthesis; using the admittance model to correct the expected reference trajectory, a target reference trajectory that better suits the user's actual situation is obtained, thereby improving the user experience.

[0070] In one implementation, the prosthesis is a three-link model comprising a prosthetic socket link, a shank link, and a foot link.

[0071] The following combination Figure 2 Let me introduce it in detail.

[0072] Figure 2 This is a schematic diagram of a scenario in which a user uses a prosthesis, provided in an embodiment of the present application.

[0073] like Figure 2 As shown, the prosthetic model is a three-link model with five degrees of freedom in a two-dimensional space, including a prosthetic socket link, a shank link, and a foot link.

[0074] The prosthetic socket connecting rod is the contact part between the prosthesis and the user's residual limb, and can also be understood as the connecting part of the prosthesis. It is responsible for transmitting the user's movement input to the other parts of the prosthesis.

[0075] The shank link is the part that connects the prosthetic socket and the foot, representing the lower half of the prosthesis. The shank link plays the role of connecting the various parts of the prosthesis in the three-link model.

[0076] The foot link represents the foot portion of the prosthesis, which is the part that the user steps on. In the three-link model, the foot link is responsible for contacting the ground and supporting the body's weight.

[0077] The three-link model is relatively simple and includes the main parts of the prosthesis, making it easy to model, simulate, and analyze.

[0078] In one implementation, displacement data of a preset limb part of the user is obtained, where the preset limb part includes at least one of the following: a hip joint, a thigh, a knee joint, and an ankle joint; and a user prosthetic limb dynamics model is constructed based on the displacement data of the preset limb part of the user and the ground reaction force data.

[0079] Combine Figure 2The user's body part includes mass points representing the hip joint and residual thigh. The prosthetic part includes the prosthetic socket, the lower leg, and three links of the foot.

[0080] The movement angle of the user's thigh is measured by an inertial measurement unit installed on the socket. The movement angles of the prosthetic knee and ankle joints are measured by encoders at the joints. A six-dimensional force sensor is installed below the prosthetic ankle joint to measure the ground reaction force on the prosthetic side when the amputee walks. The direction of the ground reaction force is as follows: Figure 2 As shown in .

[0081] The configuration space ρ of the user's prosthetic dynamics model is defined by the configuration coordinate q = (q x ,q z ,q h ,q k ,q a )∈R 5 definition.

[0082] The user's prosthesis dynamics model can be expressed as the following formula (1):

[0083]

[0084] Among them, q x and q z represents the horizontal and vertical displacement of the hip joint, q h ,q k and q a Represent the displacements of the thigh, knee and ankle joints respectively. M(q)∈R 5×5 represents the inertia matrix, Denotes the Coriolis and centrifugal matrices, G(q)∈R 5×1 J∈R represents the gravity vector, and u represents the control input vector consisting of the forces applied to the hip, knee, and ankle joints. 5×2 represents the Jacobian matrix, F f ∈R 2×1 represents the ground reaction forces in the horizontal and vertical directions, and d represents the bounded additional disturbance to the system.

[0085] In practical applications, the inertia matrix M(q) satisfies the following properties: m1≤‖M(q)‖≤m2,m3≤‖M -1 (q)‖≤m4, where m1-m4 are all positive coefficients and It is obliquely symmetrical.

[0086] It is understood that this modeling can help researchers better understand the dynamic behavior of prostheses during movement and provide a basis for subsequent control design. The control of the prosthetic system is achieved by controlling the input vectors, including the forces applied to the hip, knee, and ankle joints, to better adapt it to different activity requirements.

[0087] In one implementation, calculating the expected reference trajectory of the user when using the prosthesis based on motion data includes: calculating a phase variable based on the motion data to obtain a gait phase value; and calculating the expected reference trajectory of the user when using the prosthesis based on the gait phase.

[0088] In one implementation, a preset admittance model is constructed by combining motion data and ground reaction force data, including: calculating a phase variable based on the motion data to obtain a gait phase value; calculating a preset function using the gait phase value; and constructing a preset admittance model using the preset function and ground reaction force data.

[0089] In one implementation, the expected reference trajectory of a user when using a prosthesis is calculated based on the gait phase value, including: obtaining knee joint motion data and ankle joint motion data of the user when using the prosthesis; constructing a kinematic model of the prosthetic knee and ankle joints based on the knee joint motion data and ankle joint motion data of the user when using the prosthesis; and calculating the expected reference trajectory of the knee and ankle joints of the user when using the prosthesis based on the gait phase value and the kinematic model of the prosthetic knee and ankle joints.

[0090] It can also be understood that the expected reference trajectory of the prosthesis is first established without considering the influence of the ground reaction force, and then the expected reference trajectory is corrected using a preset admittance model according to the ground reaction force.

[0091] Gait phases refer to the timing of one event relative to other events within a complete gait cycle. Common gait phases in human gait include the stance phase and the swing phase. The stance phase is when the foot is supporting weight on the ground, while the swing phase is when the other foot swings forward in the air. Analysis of gait phases can help understand the coordination and timing of key events during gait.

[0092] First, the inertial measurement unit installed on the prosthetic socket is used to measure the motion angle q of the amputee's residual thigh h .

[0093] Then establish the phase variable h(q h ) The gait phase s is estimated based on the thigh motion angle, as shown in the following formula (2):

[0094]

[0095] Among them, h, k, b, s0 are the hyperparameters of the function, which are solved by minimizing the error between the predicted thigh angle value and the average thigh angle value of humans in the public dataset.

[0096] Finally, the kinematic models of the prosthetic knee and ankle joints are established, and the expected reference trajectories of the prosthetic knee and ankle joints are generated based on each gait phase, as shown in the following formula (3):

[0097] q j (s) = g(s) = β0 + β1s + β2s 2 +…+β n s n ,j=k,a. (3)

[0098] Where k and a represent the desired knee and ankle joint motion trajectories, respectively. g(s) is a set of n-order polynomial basis functions. n = 14 ensures that the established model meets the average human kinematic requirements. β0-β n are the coefficients of the polynomial function, which are determined by cubic spline interpolation.

[0099] Cubic spline interpolation is an interpolation technique used to estimate the value of unknown data points using an interpolating polynomial between known data points. In this method, the known data points are segmented and connected into small cubic polynomial segments, ensuring that the function value, derivative, and second-order derivative at the connection points are continuous. This produces a smooth curve that allows the interpolated function to approximate the original data well between the data points while maintaining overall smoothness and continuity.

[0100] Personalized gait control can be achieved by using the user's thigh motion angle and establishing a gait phase estimation model. This personalized customization can help improve the user's adaptability and comfort with the prosthesis. Using the average human thigh angle values ​​from a public dataset as a reference, the model's precision and accuracy can be improved by minimizing the error between the predicted and actual values. This helps ensure that the prosthetic control system provides a more precise response to the user's movement needs. By establishing a kinematic model of the prosthetic knee and ankle joints to generate the desired reference trajectory, the prosthetic movement can be made more natural and coordinated, helping to improve the user's walking efficiency and comfort when using the prosthesis. By establishing a kinematic model of the prosthetic knee and ankle joints based on the average human thigh angle values ​​from a public dataset and the polynomial basis functions of the polynomial function, it can be ensured that the established model meets the average human kinematic requirements, helping to make the prosthetic system more consistent with the human physiological structure and movement characteristics, and improving the user's comfort and naturalness.

[0101] By using cubic spline interpolation to determine the coefficients of the polynomial function, the polynomial function can be flexibly controlled and adjusted. This flexibility can help adapt to the individual differences and exercise needs of different users.

[0102] In one implementation, building a preset admittance model in combination with ground reaction force data includes: calculating a preset function using gait phase; and building the preset admittance model using the preset function and ground reaction force data.

[0103] In one implementation, a preset admittance model is used to correct a desired reference trajectory to obtain a target reference trajectory, including: calculating a preset dynamic matrix between the target reference trajectory and the desired reference trajectory using the preset admittance model; and solving the preset dynamic matrix to obtain the target reference trajectory.

[0104] In one implementation, the preset dynamic matrix includes at least one of the following: an inertia matrix, a damping matrix, and a stiffness matrix.

[0105] The preset function may be a sigmoid function.

[0106] The inertia matrix describes the inertial properties of each point or mass element in a system and reflects the system's inertial response to acceleration. The inertia matrix plays a key role in multibody system dynamics, used to describe the system's inertial properties and acceleration response.

[0107] The damping matrix describes the damping characteristics between various components in a system, that is, the damping response of the system when subjected to external motion disturbances. The damping matrix can affect the vibration attenuation and stability of the system and is an important parameter for controlling the damping characteristics of the control system.

[0108] The stiffness matrix describes the stiffness characteristics between the various components in a system, that is, the system's resistance to deformation due to external forces. The stiffness matrix reflects the system's stiffness properties and deformation response, and is important for analyzing the system's elastic properties and deformation behavior.

[0109] It can be understood that the admittance model can dynamically adjust the relationship between force and position when the robot interacts with the outside world. That is, when the external force changes, the admittance model can correct the robot's motion trajectory to achieve smooth interaction between the robot and the outside world.

[0110] The preset admittance model is shown in the following formula (4):

[0111]

[0112] Among them, M r 、B r and K r Represent the inertia matrix, damping matrix and stiffness matrix of the system respectively. d represents the expected reference trajectory of the prosthesis generated in step 2. r Indicates that the external force τ ext The modified trajectory under the influence of .f(s) is the sigmoid function that represents the parameters of the admittance model that change with the gait phase.

[0113]

[0114] Among them, o, p, a, and w are the hyperparameters of the sigmoid function.

[0115] It is understandable that the stiffness of the human leg and joints increases with the softness of the terrain. Therefore, when an amputee walks on different terrains, the hyperparameters of the f(s) function will also change accordingly based on the softness of the terrain.

[0116] The following combination Figure 3 and Figure 4 To introduce the test results of the above method.

[0117] Figure 3 This is a schematic diagram of parameters of a preset admittance model under different terrains provided in an embodiment of the present application.

[0118] Figure 4 This is a schematic diagram of the motion trajectory of a prosthesis on different terrains provided by an embodiment of the present application.

[0119] Assuming that the test terrain includes indoor treadmills and outdoor asphalt roads, grass, and gravel roads, the information of the test users is shown in Table 1.

[0120] Table 1

[0121] serial number gender height weight age 1 male 170 61 43

[0122] For four different terrains, namely treadmill, asphalt, grass and gravel road, the preset admittance model proposed in this application also generates corresponding parameters, such as Figure 3 shown.

[0123] By collecting the motion trajectory of the prosthesis on four types of terrain, such as Figure 4 As shown in Figure 2, compared to the original reference trajectory, the prosthetic limb's trajectory is corrected under the influence of the ground reaction force. Furthermore, the tracking error between the prosthetic limb's true trajectory and the corrected trajectory is significantly smaller than that of the original reference trajectory. This demonstrates that the corrected trajectory is more suitable for prosthetic movement on different terrains.

[0124] The following combination Figure 5 To comprehensively introduce the prosthetic control methods mentioned above.

[0125] Figure 5 This is an overall flow chart of a prosthetic adaptive admittance compliance control method provided in an embodiment of the present application.

[0126] like Figure 5 As shown, Figure 5 The process includes the following steps S501 to S505.

[0127] S501. Pre-establish a user's prosthetic limb dynamics model.

[0128] S502. Design an original reference trajectory of the prosthesis based on the gait phase.

[0129] S503. Establish an admittance controller suitable for the prosthetic system.

[0130] S504: Adjust the parameters of the admittance controller according to different terrains.

[0131] S505 , using an admittance model to correct the original reference trajectory of the prosthesis based on the sensed external force.

[0132] The prosthetic control method described above uses the user's thigh to control the movement of the prosthesis, improving the user's ability to manipulate the prosthesis and ensuring user safety. By utilizing a variable-parameter admittance model, it can help users achieve stable walking on different outdoor surfaces and realize smooth interaction between the human-prosthesis system and the external environment.

[0133] The above mainly introduces the method of the embodiment of the present application in conjunction with the accompanying drawings. It should be understood that although the various steps in the flowcharts involved in the various embodiments described above are shown in sequence, these steps are not necessarily performed in sequence in the order shown in the figures. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be performed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above may include multiple steps or multiple stages, and these steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily to be performed in sequence, but can be performed in turn or alternately with other steps or at least a portion of the steps or stages in other steps. A device of an embodiment of the present application is introduced below in conjunction with the accompanying drawings. For the sake of brevity, appropriate omissions will be made when introducing the device below, and the relevant content can refer to the relevant description in the method above and will not be repeated.

[0134] Figure 6 Schematic diagram of the structure of a prosthetic adaptive admittance compliance control device provided in an embodiment of the present application.

[0135] like Figure 6 As shown, the apparatus 1000 includes the following units.

[0136] The acquisition unit 1001 is used to acquire motion data of a user when using a prosthesis.

[0137] The processing unit 1002 is configured to calculate an expected reference trajectory of the user when using the prosthesis based on the motion data.

[0138] The processing unit 1002 is further configured to obtain, in real time, ground reaction force data of the user when using the prosthesis.

[0139] The processing unit 1002 is further configured to construct a preset admittance model by combining the motion data and the ground reaction force data.

[0140] The processing unit 1002 is further configured to correct the desired reference trajectory using a preset admittance model to obtain a target reference trajectory.

[0141] In one implementation, the apparatus 1000 further includes a storage unit 1003 , which can be used to store instructions and / or data, thereby implementing the method in the above embodiment.

[0142] It should be noted that the information interaction, execution process, etc. between the above-mentioned units are based on the same concept as the method embodiment of this application. Their specific functions and technical effects can be found in the method embodiment part and will not be repeated here.

[0143] Figure 7 This is a schematic diagram of the structure of the computer device provided in the embodiment of the present application. Figure 7 As shown, the computer device 3000 of this embodiment includes: at least one processor 3100 ( Figure 7 Only one processor, memory 3200, and a computer program 3210 stored in the memory 3200 and executable on at least one processor 3100 are shown. When the processor 3100 executes the computer program 3210, the computer device implements the steps in the above-described embodiments.

[0144] The processor 3100 may be a central processing unit (CPU), or may be another general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), an off-the-shelf programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. A general-purpose processor may be a microprocessor or any conventional processor.

[0145] In some embodiments, the memory 3200 may be an internal storage unit of the computer device 3000, such as a hard disk or memory of the computer device 3000. In other embodiments, the memory 3200 may also be an external storage device of the computer device 3000, such as a plug-in hard disk equipped on the computer device 3000, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Furthermore, the memory 3200 may also include both an internal storage unit of the computer device 3000 and an external storage device. The memory 3200 is used to store an operating system, application programs, boot loader data, and other programs, such as program code of a computer program. The memory 3200 may also be used to temporarily store data that has been output or is about to be output.

[0146] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above-mentioned functional units is used as an example for illustration. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units in the embodiment can be integrated into one processing unit, or each unit can exist physically alone, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application. The specific working process of the units in the above-mentioned system can refer to the corresponding process in the aforementioned method embodiment, which will not be repeated here.

[0147] An embodiment of the present application further provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a computer device, the computer device can implement the steps in the above-mentioned method embodiments.

[0148] The embodiments of the present application provide a computer program product. When the computer program product is executed on a computer device, the computer device can implement the above-mentioned methods.

[0149] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present application implements all or part of the process of the above-mentioned method embodiment by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the computer device can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file, or some intermediate form. The computer-readable medium can at least include: any entity or device capable of carrying computer program code to the camera / terminal device, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal, and software distribution medium. For example, a USB flash drive, mobile hard drive, magnetic disk, or optical disk. In some jurisdictions, based on legislation and patent practice, computer-readable media cannot be electric carrier signals or telecommunication signals.

[0150] It should be understood that the size of the sequence number of each step in the above embodiment does not mean the order of execution, and the execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present application. In the description, for the purpose of illustration rather than limitation, specific details such as specific system structure and technology are proposed to provide a thorough understanding of the embodiment of the present application. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits and methods are omitted to avoid unnecessary details that hinder the description of the present application.

[0151] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, integers, steps, operations, elements and / or components, but does not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and / or collections thereof.

[0152] It will also be understood that the term "and / or" used in this specification and the appended claims refers to and includes any and all possible combinations of one or more of the associated listed items.

[0153] Additionally, in the specification of this application and the appended claims, the terms "include", "comprise", "have" and their variations all mean "including but not limited to", unless specifically emphasized otherwise.

[0154] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described or recorded in detail in a certain embodiment, reference can be made to the relevant description of other embodiments.

[0155] Those skilled in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0156] In the embodiments provided in this application, it should be understood that the disclosed devices, computer equipment and methods can be implemented in other ways. For example, the device and computer equipment embodiments described above are merely schematic. For example, the division of units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0157] The above-described embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. A method for adaptive admittance compliance control of a prosthesis, characterized in that: include: Acquiring motion data of a user when using the prosthesis, wherein the motion data refers to angle data or displacement data between a part of the user's body and a part of the prosthesis when the user uses the prosthesis; calculating an expected reference trajectory of the user when using the prosthesis based on the motion data; Obtain real-time ground reaction force data when the user is using the prosthesis; Building a preset admittance model by combining the motion data and the ground reaction force data; Correcting the desired reference trajectory using the preset admittance model to obtain a target reference trajectory; Calculating the expected reference trajectory of the user when using the prosthesis according to the motion data includes: Calculating a phase variable according to the motion data to obtain a gait phase value; An expected reference trajectory of the user when using the prosthesis is calculated according to the gait phase value.

2. The method according to claim 1, characterized in that The method further comprises: Acquiring displacement data of a preset limb part of the user, wherein the preset limb part includes at least one of the following: a hip joint, a thigh joint, a knee joint, and an ankle joint; A user prosthesis dynamics model is constructed according to the displacement data of the preset limb part of the user and the ground reaction force data. The user prosthesis dynamics model is used to calculate the expected reference trajectory of the user when using the prosthesis.

3. The method according to claim 1, characterized in that The step of constructing a preset admittance model by combining the motion data and the ground reaction force data includes: Calculating a phase variable according to the motion data to obtain a gait phase value; Calculating a preset function using the gait phase value; A preset admittance model is constructed using a preset function and the ground reaction force data.

4. The method according to any one of claims 1 to 3, characterized in that The method of correcting the desired reference trajectory by using the preset admittance model to obtain a target reference trajectory includes: Calculating a preset dynamic matrix between the target reference trajectory and the desired reference trajectory using the preset admittance model; The preset dynamics matrix is ​​solved to obtain the target reference trajectory.

5. The method according to claim 1, wherein The calculating the phase variable according to the motion data to obtain the gait phase value includes: Obtaining thigh movement angle data of the user when using the prosthesis; Calculating the phase variable according to the thigh movement angle data; The gait phase value is calculated according to the phase variable.

6. The method according to claim 1, characterized in that The calculating, according to the gait phase value, an expected reference trajectory of the user when using the prosthesis, comprises: Acquire knee joint motion data and ankle joint motion data of the user when using the prosthesis; constructing kinematic models of the prosthetic knee and ankle joints according to the knee and ankle motion data of the user when using the prosthesis; Calculate the expected reference trajectories of the knee joint and ankle joint of the user when using the prosthesis according to the gait phase value and the kinematic models of the prosthetic knee joint and ankle joint.

7. A prosthetic limb adaptive admittance compliance control device, characterized in that: include: an acquiring unit, configured to acquire motion data of a user when using the prosthesis, wherein the motion data refers to angle data or displacement data between a part of the user's body and a part of the prosthesis when the user uses the prosthesis; a processing unit, configured to calculate an expected reference trajectory of the user when using the prosthesis based on the motion data; The processing unit is also used to obtain real-time ground reaction force data when the user uses the prosthesis; The processing unit is further configured to construct a preset admittance model by combining the motion data and the ground reaction force data; The processing unit is further configured to correct the desired reference trajectory using the preset admittance model to obtain a target reference trajectory; Calculating the expected reference trajectory of the user when using the prosthesis according to the motion data includes: Calculating a phase variable according to the motion data to obtain a gait phase value; An expected reference trajectory of the user when using the prosthesis is calculated according to the gait phase value.

8. A computer device, characterized in that: The computer device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the computer device implements the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a computer device, the method according to any one of claims 1 to 6 is implemented.

Images