Human body lower limb inertial parameter measurement method, device, medium and equipment

Abstract

The invention provides a human lower limb inertial parameter measurement method and device, a medium and equipment, and the method comprises the steps: building a lower limb dynamic model based on a measured human body and a lower limb measurement platform; wherein a measured human body sits on the lower limb measuring platform; based on the lower limb kinetic model, recognizing lower limb inertial parameters of the measured human body by adopting a recursive least square method; planning a motion track of the lower limb measurement platform based on the lower limb inertial parameters of the measured human body; a measured human body sits on a lower limb measurement platform, a lower limb dynamical model of the measured human body and the lower limb measurement platform is constructed, lower limb inertial parameters of the measured human body are identified by adopting a recursive least square method, and meanwhile, a movement track of the lower limb measurement platform is planned according to the lower limb inertial parameters; only the lower limb measurement platform with low cost is adopted to cooperate with the measured human body to construct the lower limb dynamic model, identify the lower limb inertial parameters and plan the moving trajectory, so that the measurement precision is improved.

Description

Technical Field

[0001] This application relates to the technical field of human lower limb inertial parameter measurement, and specifically relates to a method, device, medium and equipment for measuring human lower limb inertial parameters. Background Art

[0002] Human inertial parameters cover key indicators such as the weight, centroid position, moment of inertia, and radius of gyration of the human body and its various parts. These parameters are the core of studying human movement and play a crucial role in the fields of ergonomics, anthropology, and human movement science. They not only have profound academic significance but also have extensive practical application value. For example, in the progress of ergonomics, this discipline focuses on exploring the interaction among humans, machines, and the environment. Being able to accurately master human inertial parameters in fields such as product development, human-machine interaction, and biomechanical movement is extremely crucial for product optimization, improving human-machine interaction efficiency, and ensuring human safety. Another example is in the application of intelligent equipment. With the rapid development of artificial intelligence and robotics technology, the use of intelligent devices in fields such as medicine, rehabilitation, and sports is becoming increasingly popular.

[0003] Currently, common human inertial parameter measurement technologies include the water immersion method, medical imaging scanning method, and photogrammetry method, etc. The water immersion method is that the volume of water displaced by an object in water is equal to the volume of the object, and the mass of the body segment is calculated by multiplying the average density of the human body. However, since the immersion of large-volume segments may affect the measurement of subsequent segments, the water immersion method may introduce large errors when measuring the inertial parameters of segments, affecting the accuracy of the results. Medical image scanning uses X-rays and magnetic resonance imaging technology to perform a full-body scan on the subject, and finally determines the moment of inertia of each segment by integrating the volume and mass of the segments through slicing and using the parallel axis theorem. This method requires extremely high economic and time costs. Photogrammetry mainly uses photogrammetry technology to construct a 3D model of the surface topography of the subject and calculates the body segment inertial parameters using the volume integration method, and its error is also relatively large. Therefore, there is an urgent need for a method that can quickly and accurately measure human inertial parameters. Summary of the Invention

[0004] To solve the above technical problems, this application is proposed. Embodiments of this application provide a method, device, medium and equipment for measuring human lower limb inertial parameters.

[0005] According to one aspect of the present application, a method for measuring inertial parameters of a human lower limb is provided, including: constructing a lower limb dynamics model based on the measured human body and a lower limb measurement platform; wherein, the measured human body is seated on the lower limb measurement platform; identifying the inertial parameters of the lower limb of the measured human body by using the recursive least squares method based on the lower limb dynamics model; planning the motion trajectory of the lower limb measurement platform based on the inertial parameters of the lower limb of the measured human body; wherein, the motion trajectory includes position information, velocity information and acceleration information; the constructing of the lower limb dynamics model based on the measured human body and the lower limb measurement platform includes: keeping the thigh of the measured human body horizontal and controlling the lower limb measurement platform to drive the calf of the measured human body to swing; measuring the swing angle between the calf of the measured human body and the vertical direction during the swing and the output torque generated by the lower limb measurement platform; constructing the lower limb dynamics model based on the swing angle and the output torque.

[0006] In one embodiment, the constructing of the lower limb dynamics model based on the swing angle and the output torque includes: the lower limb dynamics model is:

[0007] Wherein, and respectively represent the moment of inertia of the calf of the measured human body and the lower limb measurement platform, and respectively represent the viscous friction coefficients of the calf of the measured human body and the lower limb measurement platform, and respectively represent the gravity moments of the calf of the measured human body and the lower limb measurement platform, M s and M h respectively represent the masses of the measured human body and the lower limb measurement platform, l and l h respectively represent the force arms of the calf of the measured human body and the lower limb measurement platform, g represents the acceleration due to gravity, and respectively represent the Coulomb friction coefficients of the calf of the measured human body and the lower limb measurement platform, θ represents the swing angle, represents the output torque generated by the lower limb measurement platform, t represents the swing time.

[0008] In one embodiment, identifying the lower limb inertial parameters of the measured human body based on the lower limb dynamics model by using the recursive least squares method includes: identifying the inertial parameters of the lower limb measurement platform; identifying the combined inertial parameters of the measured human body and the lower limb measurement platform based on the lower limb dynamics model by using the recursive least squares method; and calculating the lower limb inertial parameters of the measured human body based on the inertial parameters of the lower limb measurement platform and the combined inertial parameters.

[0009] In one embodiment, identifying the combined inertial parameters of the measured human body and the lower limb measurement platform based on the lower limb dynamics model by using the recursive least squares method includes: The calculation formula for the combined inertial parameters is: ; ; , ; , ; where, and respectively represent X the N th and the N +1 th recursive values, P N is an intermediate variable, and respectively represent the N th and the N +1 th values, represents the N +1 th value, I represents I s +I h , D represents D s + D h , Mgl represents M s gl + M h gl h , C represents C s +C h .

[0010] In one embodiment, planning the motion trajectory of the lower limb measurement platform based on the inertial parameters of the measured human body's lower limbs includes: planning the motion trajectory of the lower limb measurement platform using a polynomial motion equation; solving the polynomial motion equation based on the inertial parameters of the measured human body's lower limbs to obtain the motion trajectory of the lower limb measurement platform.

[0011] In one embodiment, planning the motion trajectory of the lower limb measurement platform using a polynomial motion equation includes: the motion trajectory of the lower limb measurement platform is: ; And the motion trajectory of the lower limb measurement platform satisfies the following boundary conditions: ; Wherein, a 0 、a 1 、a 2 、a 3 、a 4 、a 5 are respectively the polynomial coefficients of the motion trajectory, t 0 is the initial time, t is the end time, is the swing angle at the initial time, is the swing angle at the end time, is the first derivative of is the first derivative of is the second derivative of is the second derivative of

[0012] According to another aspect of the present application, there is provided a human lower limb inertial parameter measurement device, including: a dynamic model construction module for constructing a lower limb dynamics model based on the measured human body and the lower limb measurement platform; wherein, the measured human body sits on the lower limb measurement platform; an inertial parameter identification module for identifying the inertial parameters of the lower limb of the measured human body using the recursive least squares method based on the lower limb dynamics model; a motion trajectory planning module for planning the motion trajectory of the lower limb measurement platform based on the inertial parameters of the measured human body's lower limbs; wherein, the motion trajectory includes position information, velocity information, and acceleration information; the dynamic model construction module is further configured to: keep the thigh of the measured human body horizontal and control the lower limb measurement platform to drive the calf of the measured human body to swing; measure the swing angle between the calf of the measured human body and the vertical direction during the swing and the output torque generated by the lower limb measurement platform; construct the lower limb dynamics model based on the swing angle and the output torque.

[0013] According to another aspect of the present application, there is provided a computer-readable storage medium storing a computer program for executing any one of the above methods.

[0014] According to another aspect of the present application, there is provided an electronic device, including: a processor; a memory for storing executable instructions of the processor; the processor is configured to execute any one of the above methods.

[0015] A method, device, medium and equipment for measuring human lower limb inertial parameters provided by the present application construct a lower limb dynamics model based on the measured human body and the lower limb measurement platform; wherein, the measured human body is seated on the lower limb measurement platform; based on the lower limb dynamics model, the recursive least squares method is used to identify the lower limb inertial parameters of the measured human body; based on the lower limb inertial parameters of the measured human body, the motion trajectory of the lower limb measurement platform is planned; wherein, the motion trajectory includes position information, speed information and acceleration information; that is, by using the measured human body seated on the lower limb measurement platform, a lower limb dynamics model of the measured human body and the lower limb measurement platform is constructed, and the recursive least squares method is used to identify the lower limb inertial parameters of the measured human body, and at the same time, the motion trajectory of the lower limb measurement platform is planned according to the lower limb inertial parameters. Only a lower limb measurement platform with a lower cost is used to cooperate with the measured human body to construct a lower limb dynamics model, identify lower limb inertial parameters and plan the operation trajectory, so as to improve the measurement accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] By describing the embodiments of the present application in more detail in conjunction with the drawings, the above and other objects, features and advantages of the present application will become more obvious. The drawings are used to provide a further understanding of the embodiments of the present application, and constitute a part of the specification. Together with the embodiments of the present application, they are used to explain the present application and do not constitute a limitation to the present application. In the drawings, the same reference numerals generally represent the same components or steps.

[0017] Figure 1 is a schematic flow chart of a method for measuring human lower limb inertial parameters provided by an exemplary embodiment of the present application.

[0018] Figure 2 is a schematic diagram of the principle structure of a device for measuring human lower limb inertial parameters provided by an exemplary embodiment of the present application.

[0019] Figure 3 is a front view of a device for measuring human lower limb inertial parameters provided by an exemplary embodiment of the present application.

[0020] Figure 4 is a perspective view of a device for measuring human lower limb inertial parameters provided by an exemplary embodiment of the present application.

[0021] Figure 5 It is a schematic structural diagram of a human lower limb inertial parameter measurement device provided by an exemplary embodiment of the present application.

[0022] Figure 6 It is a structural diagram of an electronic device provided by an exemplary embodiment of the present application. Specific embodiments

[0023] Next, exemplary embodiments of the present application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. It should be understood that the present application is not limited by the exemplary embodiments described herein.

[0024] Figure 1 It is a schematic flow diagram of a human lower limb inertial parameter measurement method provided by an exemplary embodiment of the present application. As Figure 1 shown, the human lower limb inertial parameter measurement method includes the following steps: Step 110: Based on the measured human body and the lower limb measurement platform, construct a lower limb dynamics model.

[0025] Among them, the measured human body sits on the lower limb measurement platform. In the present application, by setting the lower limb measurement platform, the measured human body sits on the lower limb measurement platform (as Figure 2 shown), and the lower limb measurement platform is used to drive the calf of the measured human body to swing and measure the torque, so as to construct the dynamics model of the whole measured human body and the lower limb measurement platform, so as to know the movement law of the lower limbs of the measured human body. As Figure 3 and Figure 4 shown, the lower limb measurement platform provided by the present application includes a chair 1, a femur support plate 2, a thigh fixing plate 3, a thigh connecting plate 4, a knee joint motor 5, an inertial sensor 6, a calf connecting rod 7 and a strap 8. Among them, the chair 1 is used to carry the measured human body, the femur support plate 2 and the thigh fixing plate 3 are used to fixedly connect the chair 1 and the thigh connecting plate 4, the thigh connecting plate 4 is used to fix the thigh of the measured human body, the calf connecting rod 7 is used to fix the calf of the measured human body, the strap 8 is arranged on the thigh connecting plate 4 and the calf connecting rod 7, and the strap 8 is used to fix the thigh and calf of the measured human body on the thigh connecting plate 4 and the calf connecting rod 7 respectively. The knee joint motor 5 is used to provide the driving force for the calf connecting rod 7 to swing relative to the thigh connecting plate 4, and the inertial sensor 6 is used to collect the parameter information of the calf connecting rod 7 during the swinging process.

[0026] The specific implementation manner of the above step 110 is: keep the thigh of the measured human body horizontal and motionless, and control the lower limb measurement platform to drive the calf of the measured human body to swing; measure the swing angle between the calf of the measured human body and the vertical direction during the swinging process and the output torque generated by the lower limb measurement platform; based on the swing angle and the output torque, construct a lower limb dynamics model.

[0027] To construct an accurate lower limb dynamics model of the human body, it is necessary to conduct a detailed analysis of the swinging motion of the lower limbs. However, considering the actual application requirements and computational complexity, this application simplifies the motion of the human lower limbs into a single-degree-of-freedom model. In this model, the thigh remains stationary in the horizontal direction, while the calf swings around the knee in the sagittal plane due to the contraction and relaxation of the lower limb muscles. To construct the dynamics model of the lower limb, it is necessary to determine the torque generated by the lower limb muscles. However, it is not feasible to directly measure the torque of these muscles. Therefore, this application uses an active lower limb measurement platform to guide the swinging of the calf. Specifically, when the human subject being measured sits on the lower limb measurement platform and is completely relaxed, the thigh is fixed by the thigh fixing plate and remains stationary, and the calf swings (driven by the knee joint motor) along with the calf connecting rod. At this time, the torque generated by the muscles of the human subject being measured can be ignored, and it can be basically considered that the swinging of the calf is completely driven by the knee joint motor. During the swinging of the calf, the swinging angle between the calf of the human subject being measured and the vertical direction and the output torque generated by the lower limb measurement platform are measured, and based on the swinging angle and the output torque, a lower limb dynamics model is constructed.

[0028] Step 120: Based on the lower limb dynamics model, use the recursive least squares method to identify the lower limb inertia parameters of the human subject being measured.

[0029] Based on the lower limb dynamics model, this application uses the recursive least squares method to identify the lower limb inertia parameters of the human subject being measured. Among them, the recursive least squares method is an optimization of the traditional least squares method. Specifically, it uses historical data to predict future values and uses recursive formulas to calculate the predicted values at specific time points, while continuously adjusting the parameter estimates to reduce the sum of the squares of the current errors.

[0030] Step 130: Based on the lower limb inertia parameters of the human subject being measured, plan the motion trajectory of the lower limb measurement platform.

[0031] Among them, the motion trajectory includes position information, velocity information, and acceleration information. Motion trajectory planning refers to planning a complete motion trajectory for the lower limb measurement platform considering moving obstacles, velocity, and dynamic constraints. This motion trajectory includes not only position information but also dynamic information such as velocity and acceleration. The goal is to generate a smooth motion trajectory so that the lower limb measurement platform can move smoothly and safely along this trajectory while satisfying dynamic and kinematic constraints. Motion trajectory planning can define a safe, effective, and feasible path for the motion of the lower limb measurement platform from the initial state to the desired final state to maintain the smoothness of the lower limb measurement platform during the motion process and avoid sudden changes in torque, ensure the safety of the human subject being measured, and improve the identification accuracy.

[0032] A method for measuring human lower limb inertia parameters provided by the present application constructs a lower limb dynamics model based on the measured human body and the lower limb measurement platform; wherein, the measured human body sits on the lower limb measurement platform; based on the lower limb dynamics model, the recursive least squares method is used to identify the lower limb inertia parameters of the measured human body; based on the lower limb inertia parameters of the measured human body, the motion trajectory of the lower limb measurement platform is planned; wherein, the motion trajectory includes position information, velocity information and acceleration information; that is, by using the measured human body sitting on the lower limb measurement platform, a lower limb dynamics model of the measured human body and the lower limb measurement platform is constructed, and the recursive least squares method is used to identify the lower limb inertia parameters of the measured human body, and at the same time, the motion trajectory of the lower limb measurement platform is planned according to the lower limb inertia parameters. Only a lower limb measurement platform with a lower cost is used to cooperate with the measured human body to realize the construction of the lower limb dynamics model, the identification of the lower limb inertia parameters and the planning of the operation trajectory, so as to improve the measurement accuracy.

[0033] In one embodiment, the specific implementation manner of the above step 110 may be: The lower limb dynamics model is:

[0034] Wherein, and respectively represent the moments of inertia of the calf of the measured human body and the lower limb measurement platform, and respectively represent the viscous friction coefficients of the calf of the measured human body and the lower limb measurement platform, and respectively represent the gravitational moments of the calf of the measured human body and the lower limb measurement platform, M s and M h respectively represent the masses of the measured human body and the lower limb measurement platform, l and l h respectively represent the moment arms of the calf of the measured human body and the lower limb measurement platform, g represents the gravitational acceleration, and respectively represent the Coulomb friction coefficients of the calf of the measured human body and the lower limb measurement platform, θ represents the swing angle, represents the output torque generated by the lower limb measurement platform, t represents the swing time.

[0035] The present application constructs the above lower limb dynamics model according to the motion model of the lower limb of the measured human body and the lower limb measurement platform under a single degree of freedom.

[0036] In one embodiment, the specific implementation of step 120 may be: identifying the inertial parameters of the lower limb measurement platform; based on the lower limb dynamics model, using the recursive least squares method to identify the combined inertial parameters of the measured human body and the lower limb measurement platform; calculating the lower limb inertial parameters of the measured human body based on the inertial parameters of the lower limb measurement platform and the combined inertial parameters.

[0037] To identify the lower limb inertial parameters of the measured human body, the present application first identifies the inertial parameters of the lower limb measurement platform (which can be determined by the mechanical structure of the lower limb measurement platform), and then uses the recursive least squares method to identify the combined inertial parameters of the measured human body and the lower limb measurement platform. After determining the combined inertial parameters of the measured human body and the lower limb measurement platform and the inertial parameters of the lower limb measurement platform, the lower limb inertial parameters of the measured human body can be obtained by subtracting the two.

[0038] In one embodiment, the specific implementation of step 120 may be: The calculation formula for the combined inertial parameters is: ; ; , ; , ; where and respectively represent X the N th and N +1 th recursive values of P N is an intermediate variable (set to simplify the writing form of the formula), and respectively represent the N th and N +1 th values of represents the N +1 th value of I represents I s +I h , D represents D s +D h , Mgl represents M s gl + M h glh , C represents C s +C h .

[0039] This application rewrites the above lower limb dynamics model into a matrix form: ; wherein, , ; Substituting it into the recurrence formula, the calculation formula of the above combined inertia parameters can be obtained.

[0040] In one embodiment, the specific implementation manner of the above step 130 may be: using a polynomial motion equation to plan the motion trajectory of the lower limb measurement platform; solving the polynomial motion equation based on the lower limb inertia parameters of the measured human body to obtain the motion trajectory of the lower limb measurement platform.

[0041] This article uses a polynomial motion equation to control the movement of the knee joint motor to maintain the smoothness of the lower limb measurement platform during movement, avoid sudden changes in torque, ensure the safety of the measured human body, and improve the identification accuracy.

[0042] In one embodiment, the specific implementation manner of the above step 130 may be: The motion trajectory of the lower limb measurement platform is: ; And the motion trajectory of the lower limb measurement platform satisfies the following boundary conditions: ; wherein, a 0 、a 1 、a 2 、a 3 、a 4 、a 5 are respectively the polynomial coefficients of the motion trajectory, t 0 is the initial time, t is the end time, is the swing angle at the initial time, is the swing angle at the end time, is the first derivative of is the first derivative of is the second derivative of is the second derivative of

[0043] In this application, a microcontroller can be used to sample parameters and issue control instructions at a period of 30 ms. The swing angle from 0° to 90° is divided into multiple points (for example, 20 points), and the movement time is 0.6 s. Based on this, the above boundary conditions are set, so as to solve the polynomial coefficients of the movement trajectory of the lower limb measurement platform, and then obtain the movement trajectory equation of the lower limb measurement platform. Similarly, the movement trajectory from 90° to 0° of the swing angle can be obtained.

[0044] Figure 5 FIG. 4 is a schematic structural diagram of a human lower limb inertial parameter measurement device provided by an exemplary embodiment of this application. As Figure 5 shown, the human lower limb inertial parameter measurement device 50 includes: a dynamic model construction module 51, configured to construct a lower limb dynamics model based on the measured human body and the lower limb measurement platform; wherein, the measured human body rides on the lower limb measurement platform; an inertial parameter identification module 52, configured to identify the lower limb inertial parameters of the measured human body by using the recursive least squares method based on the lower limb dynamics model; a movement trajectory planning module 53, configured to plan the movement trajectory of the lower limb measurement platform based on the lower limb inertial parameters of the measured human body; wherein, the movement trajectory includes position information, speed information and acceleration information; wherein, the above dynamic model construction module 51 is further configured to: keep the thigh of the measured human body horizontal and stationary, and control the lower limb measurement platform to drive the calf of the measured human body to swing; measure the swing angle between the calf of the measured human body and the vertical direction during the swing process, and the output torque generated by the lower limb measurement platform; construct a lower limb dynamics model based on the swing angle and the output torque.

[0045] A human lower limb inertial parameter measurement device provided by this application constructs a lower limb dynamics model through the dynamic model construction module 51 based on the measured human body and the lower limb measurement platform; wherein, the measured human body rides on the lower limb measurement platform; the inertial parameter identification module 52 identifies the lower limb inertial parameters of the measured human body by using the recursive least squares method based on the lower limb dynamics model; the movement trajectory planning module 53 plans the movement trajectory of the lower limb measurement platform based on the lower limb inertial parameters of the measured human body; wherein, the movement trajectory includes position information, speed information and acceleration information; that is, by using the measured human body riding on the lower limb measurement platform, a lower limb dynamics model of the measured human body and the lower limb measurement platform is constructed, and the recursive least squares method is used to identify the lower limb inertial parameters of the measured human body. At the same time, according to the lower limb inertial parameters, the movement trajectory of the lower limb measurement platform is planned. Only a lower limb measurement platform with a relatively low cost is used to cooperate with the measured human body to realize the construction of the lower limb dynamics model, identify the lower limb inertial parameters and plan the operation trajectory, so as to improve the measurement accuracy.

[0046] In one embodiment, the above dynamic model construction module 51 can be further configured to: The lower limb dynamics model is:

[0047] Among them, and respectively represent the moments of inertia of the calf of the measured human body and the lower limb measurement platform, and respectively represent the viscous friction coefficients of the calf of the measured human body and the lower limb measurement platform, and respectively represent the gravitational moments of the calf of the measured human body and the lower limb measurement platform, M s and M h respectively represent the masses of the measured human body and the lower limb measurement platform, l and l h respectively represent the lever arms of the calf of the measured human body and the lower limb measurement platform, g represents the acceleration due to gravity, and respectively represent the Coulomb friction coefficients of the calf of the measured human body and the lower limb measurement platform, θ represents the swing angle, represents the output torque generated by the lower limb measurement platform, t represents the swing time.

[0048] In one embodiment, the above-mentioned inertia parameter identification module 52 can be further configured to: identify the inertia parameters of the lower limb measurement platform; based on the lower limb dynamics model, use the recursive least squares method to identify the combined inertia parameters of the measured human body and the lower limb measurement platform; based on the inertia parameters of the lower limb measurement platform and the combined inertia parameters, calculate the lower limb inertia parameters of the measured human body.

[0049] In one embodiment, the above-mentioned inertia parameter identification module 52 can be further configured to: The calculation formula for the combined inertia parameters is: ; ; , ; , ; Among them, and respectively represent X the N th and the N +1th recursive values of P N is an intermediate variable, and respectively represent The N th and N th + 1 values, represent the N th + 1 value, I represent I s +I h , D represent D s + D h , Mgl represent M s gl + M h gl h , C represent C s +C h .

[0050] In one embodiment, the above-mentioned motion trajectory planning module 53 can be further configured to: plan the motion trajectory of the lower limb measurement platform by using a polynomial motion equation; solve the polynomial motion equation based on the lower limb inertia parameters of the measured human body to obtain the motion trajectory of the lower limb measurement platform.

[0051] In one embodiment, the above-mentioned motion trajectory planning module 53 can be further configured to: The motion trajectory of the lower limb measurement platform is: ; And the motion trajectory of the lower limb measurement platform satisfies the following boundary conditions: ; Wherein, a 0 、a 1 、a 2 、a 3 、a 4 、a 5 are respectively the polynomial coefficients of the motion trajectory, t 0 is the initial time, t is the end time, is the swing angle at the initial time, is the swing angle at the end time, is the first derivative of is the first derivative of is the second derivative of is the second derivative of.

[0052] Next, with reference to Figure 6 the electronic device according to an embodiment of the present application will be described. The electronic device may be any one or both of the first device and the second device, or a stand-alone device independent of them, and the stand-alone device may communicate with the first device and the second device to receive the input signals collected therefrom.

[0053] Figure 6 The block diagram of the electronic device according to an embodiment of the present application is illustrated.

[0054] As Figure 6 shown, the electronic device 10 includes one or more processors 11 and a memory 12.

[0055] The processor 11 may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device 10 to perform desired functions.

[0056] The memory 12 may include one or more computer program products, and the computer program products may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may include, for example, random access memory (RAM) and / or cache memory, etc. The non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc. One or more computer program instructions may be stored on the computer-readable storage media, and the processor 11 may run the program instructions to implement the methods of the various embodiments of the present application described above and / or other desired functions. Various contents such as input signals, signal components, noise components, etc. may also be stored in the computer-readable storage media.

[0057] In one example, the electronic device 10 may further include: an input device 13 and an output device 14, and these components are interconnected through a bus system and / or other forms of connection mechanisms (not shown).

[0058] When the electronic device is a stand-alone device, the input device 13 may be a communication network connector for receiving the input signals collected from the first device and the second device.

[0059] In addition, the input device 13 may further include, for example, a keyboard, a mouse, etc.

[0060] The output device 14 can output various information to the outside, including the determined distance information, direction information, etc. The output device 14 can include, for example, a display, a speaker, a printer, a communication network, and remote output devices connected thereto, etc.

[0061] Of course, for the sake of simplicity, Figure 6 only some of the components related to this application in the electronic device 10 are shown, and components such as a bus, an input / output interface, etc. are omitted. In addition, according to specific application scenarios, the electronic device 10 may further include any other appropriate components.

[0062] In addition to the above methods and devices, an embodiment of the present application may also be a computer program product, which includes computer program instructions that, when run by a processor, cause the processor to execute the steps in the methods according to various embodiments of the present application described in the above "Exemplary Method" section of this specification.

[0063] The computer program product can be written in any combination of one or more programming languages for programming code to perform the operations of the embodiments of the present application. The programming languages include object-oriented programming languages such as Java, C++, etc., and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computing device, partially on the user's device, executed as an independent software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0064] Furthermore, an embodiment of the present application may also be a computer-readable storage medium, on which computer program instructions are stored, and when the computer program instructions are run by a processor, the processor is caused to execute the steps in the methods according to various embodiments of the present application described in the above "Exemplary Method" section of this specification.

[0065] The computer-readable storage medium can adopt any combination of one or more readable media. The readable media can be a readable signal medium or a readable storage medium. The readable storage medium can, for example, include but is not limited to an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0066] The basic principles of the present application have been described in conjunction with specific embodiments. However, it should be noted that the advantages, benefits, effects, etc. mentioned in the present application are only examples and not limitations. It cannot be considered that these advantages, benefits, effects, etc. are essential for each embodiment of the present application. Additionally, the specific details disclosed above are only for illustrative and easy-to-understand purposes and not limitations. These details do not limit the present application to necessarily implementing with the above specific details.

[0067] The block diagrams of the devices, apparatuses, equipment, and systems involved in the present application are only illustrative examples and do not intend to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open-ended terms, meaning "including but not limited to", and can be used interchangeably with each other. The word "or" and "and" used herein refer to the phrase "and / or" and can be used interchangeably with it, unless the context clearly indicates otherwise. The word "such as" used herein refers to the phrase "such as but not limited to" and can be used interchangeably with it.

[0068] It should also be noted that in the devices, equipment, and methods of the present application, each component or each step can be decomposed and / or recombined. These decompositions and / or recombinations should be regarded as equivalent solutions of the present application.

[0069] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the broadest scope consistent with the principles and novel features disclosed herein.

[0070] The above description has been given for purposes of illustration and description. In addition, this description does not intend to limit the embodiments of the present application to the forms disclosed herein. Although multiple example aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, changes, additions, and sub-combinations thereof.

Claims

1. A method for measuring inertial parameters of the human lower limbs, characterized in that, Including: Based on the measured human body and the lower limb measurement platform, a lower limb dynamics model is constructed; wherein, the measured human body sits on the lower limb measurement platform; Based on the lower limb dynamics model, the lower limb inertia parameters of the measured human body are identified by using the recursive least squares method; Based on the lower limb inertia parameters of the measured human body, the motion trajectory of the lower limb measurement platform is planned; wherein, the motion trajectory includes position information, velocity information and acceleration information; The constructing of the lower limb dynamics model based on the measured human body and the lower limb measurement platform includes: Keeping the thigh of the measured human body horizontal and controlling the lower limb measurement platform to drive the calf of the measured human body to swing; Measuring the swing angle between the calf of the measured human body and the vertical direction during the swing and the output torque generated by the lower limb measurement platform; Based on the swing angle and the output torque, the lower limb dynamics model is constructed.

2. The method for measuring human lower limb inertial parameters according to claim 1, characterized in that The constructing of the lower limb dynamics model based on the swing angle and the output torque includes: The lower limb dynamics model is: Wherein, and respectively represent the moments of inertia of the calf of the measured human body and the lower limb measurement platform, and respectively represent the viscous friction coefficients of the calf of the measured human body and the lower limb measurement platform, and respectively represent the gravitational moments of the calf of the measured human body and the lower limb measurement platform, M s and M h respectively represent the masses of the measured human body and the lower limb measurement platform, l and l h respectively represent the lever arms of the calf of the measured human body and the lower limb measurement platform, g represents the acceleration due to gravity, and respectively represent the Coulomb friction coefficients of the calf of the measured human body and the lower limb measurement platform, θ represents the swing angle, represents the output torque generated by the lower limb measurement platform, t represents the swing time.

3. The method for measuring inertial parameters of the human lower limbs according to claim 2, characterized in that, The identifying of the lower limb inertia parameters of the measured human body by using the recursive least squares method based on the lower limb dynamics model includes: Identifying the inertia parameters of the lower limb measurement platform; Based on the lower limb dynamics model, the combined inertia parameters of the measured human body and the lower limb measurement platform are identified by using the recursive least squares method; Based on the inertia parameters of the lower limb measurement platform and the combined inertia parameters, the lower limb inertia parameters of the measured human body are calculated.

4. The method for measuring human lower limb inertial parameters according to claim 3, wherein The identifying of the combined inertia parameters of the measured human body and the lower limb measurement platform by using the recursive least squares method based on the lower limb dynamics model includes: The calculation formula of the combined inertia parameters is: ； ； ， ； ， ； Among them, and respectively represent X the N th and N th + 1 recurrence values, P N is an intermediate variable, and respectively represent the N th and N th + 1 values, represents the N th + 1 value, I represents I s +I h , D represents D s +D h , Mgl represents M s gl + M h gl h , C represents C s +C h .

5. The method for measuring human lower limb inertial parameters according to claim 1, characterized in that The planning of the motion trajectory of the lower limb measurement platform based on the lower limb inertia parameters of the measured human body includes: Planning the motion trajectory of the lower limb measurement platform by using a polynomial motion equation; Based on the lower limb inertia parameters of the measured human body, the polynomial motion equation is solved to obtain the motion trajectory of the lower limb measurement platform.

6. The method for measuring human lower limb inertial parameters according to claim 5, wherein The planning of the motion trajectory of the lower limb measurement platform by using a polynomial motion equation includes: The motion trajectory of the lower limb measurement platform is: ； And the motion trajectory of the lower limb measurement platform satisfies the following boundary conditions: ； Among them, a 0 、a 1 、a 2 、a 3 、a 4 、a 5 are the polynomial coefficients of the motion trajectory respectively, t 0 is the initial time, t is the end time, is the swing angle at the initial time, is the swing angle at the end time, is the first derivative of is the first derivative of is the second derivative of is the second derivative of.

7. A human lower limb inertial parameter measurement device, characterized in that, Including: A dynamic model construction module, configured to construct a lower limb dynamics model based on the measured human body and the lower limb measurement platform; wherein, the measured human body sits on the lower limb measurement platform; An inertia parameter identification module, configured to identify the lower limb inertia parameters of the measured human body by using the recursive least squares method based on the lower limb dynamics model; A motion trajectory planning module, configured to plan the motion trajectory of the lower limb measurement platform based on the lower limb inertia parameters of the measured human body; wherein, the motion trajectory includes position information, velocity information and acceleration information; The dynamic model construction module is further configured to: Keep the thigh of the measured human body horizontal and control the lower limb measurement platform to drive the calf of the measured human body to swing; Measure the swing angle between the calf of the measured human body and the vertical direction during the swinging process, and the output torque generated by the lower limb measurement platform; Based on the swing angle and the output torque, construct the lower limb dynamics model.

8. A computer-readable storage medium, characterized in that, The storage medium stores a computer program, and the computer program is used to execute the method according to any one of claims 1-6 above.

9. An electronic device, characterized in that, Comprising: A processor; A memory for storing instructions executable by the processor; The processor is used to execute the method according to any one of claims 1-6 above.

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