CN118230964B - Joint wear prediction method, storage medium and equipment - Google Patents
Joint wear prediction method, storage medium and equipment Download PDFInfo
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
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Abstract
The specification discloses a method, a storage medium and equipment for predicting joint abrasion, which are used for predicting joint lubrication film thickness by utilizing personalized motion data and joint parameters of a user, further predicting joint abrasion according to the joint lubrication film thickness, and after the joint abrasion at the current moment is determined, updating the joint parameters according to the joint abrasion at the current moment so as to correct the prediction method of the joint lubrication film thickness, predicting the joint abrasion by utilizing the coupling relation of lubrication and abrasion, and more conforming to the actual relative motion state between joint friction surfaces under the actual condition, thereby providing a more accurate prediction method of the joint abrasion.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a method, a storage medium, and an apparatus for joint wear prediction.
Background
As human life increases and aging increases, more than 50% of the population eventually experience joint degeneration or injury, and monitoring and predicting the wear state of the joint can provide effective guidelines for joint protection and joint replacement.
At present, when detecting joint wear, medical detection methods are often adopted, such as detection of the joint in a human body by using methods of line wear detection (X-ray), periarticular tissue fluid abrasion dust analysis, periarticular tissue extract measurement and the like, and the detection mode can only obtain the current joint wear state, but cannot accurately predict the wear state of the joint at the future moment.
Thus, the present invention provides a method, a storage medium, and an apparatus for joint wear prediction.
Disclosure of Invention
The present specification provides a method of joint wear prediction to partially solve the above-mentioned problems of the prior art.
The technical scheme adopted in the specification is as follows:
The present specification provides a method of joint wear prediction comprising:
acquiring historical data of joint movement and load of a user, and acquiring joint parameters;
Determining a designated moment of joint wear to be predicted;
According to the appointed time, determining historical data required for predicting the joint abrasion loss at the appointed time from the historical data as prediction data corresponding to the appointed time;
determining the thickness of the joint lubrication film of the user at the appointed moment according to the predicted data corresponding to the appointed moment and the joint parameters;
and determining the joint abrasion loss at the appointed time according to the predicted data, the joint lubrication film thickness and the joint parameters, updating the joint parameters according to the joint abrasion loss, re-using the updated joint parameters as the joint parameters corresponding to the next moment of the appointed time, and re-using the next moment of the appointed time as the appointed time so as to continuously determine the re-determined joint abrasion loss at the appointed time.
Optionally, the historical data of the joint movement and the load of the user specifically includes: the joint angle data of the user when exercising historically and the joint force data of the user when exercising historically.
Optionally, acquiring joint parameters specifically includes:
acquiring joint shape parameters and joint material parameters.
Optionally, determining the thickness of the joint lubrication film of the user at the designated moment according to the predicted data corresponding to the designated moment and the joint parameter specifically includes:
And determining the thickness of the joint lubrication film at the appointed moment according to a stress balance relation formed by the action force between joints, the liquid film pressure and the rough peak contact force, wherein the action force between joints is determined according to the prediction data corresponding to the appointed moment, the liquid film pressure is calculated according to the thickness of the joint lubrication film and the joint shape parameter, and the rough peak contact force is calculated according to the thickness of the joint lubrication film and the joint material parameter.
Optionally, determining the joint wear amount at the specified moment according to the prediction data, the joint lubrication film thickness and the joint parameter specifically includes:
determining a rough peak contact force according to the joint lubricating film thickness and the joint material parameters;
and determining the joint abrasion loss at the appointed moment according to the predicted data, the rough peak contact force and the joint material parameters.
Optionally, determining the rough peak contact force at the designated moment according to the joint lubrication film thickness and the joint material parameter specifically includes:
Determining a joint lubrication state corresponding to the joint lubrication film thickness, wherein the joint lubrication state comprises one of power lubrication, boundary lubrication and dry friction;
And determining the rough peak contact force at the designated moment by using a rough peak contact force determination method corresponding to the joint lubrication state according to the joint lubrication film thickness and the joint material parameters.
Optionally, updating the joint parameter according to the joint wear amount specifically includes:
and updating the joint shape parameters according to the joint abrasion amount.
Optionally, acquiring joint parameters specifically includes:
determining joint parameters according to parameters of the artificial joint to be configured;
after determining the joint wear amount at the specified time, further comprising:
If the designated time is the target time, determining whether joint parameters determined according to the artificial joint to be configured meet the abrasion standard or not according to the joint abrasion quantity at the designated time and a preset abrasion threshold;
if the joint parameters determined according to the artificial joint to be configured meet the abrasion standard, the joint parameters determined according to the artificial joint to be configured are used as target joint parameters of the user;
And configuring an artificial joint for a user according to the target joint parameters.
The present specification provides an apparatus for joint wear prediction, comprising:
the acquisition module is used for acquiring historical data of joint movement and load of a user and acquiring joint parameters;
the moment determining module is used for determining the appointed moment of the joint wear quantity to be predicted;
the data determining module is used for determining historical data required for predicting the joint abrasion loss at the appointed moment in the historical data according to the appointed moment, and the historical data are used as prediction data corresponding to the appointed moment;
The thickness prediction module is used for determining the thickness of the joint lubrication film of the user at the appointed moment according to the prediction data corresponding to the appointed moment and the joint parameters;
The wear amount prediction module is used for determining the joint wear amount at the appointed time according to the prediction data, the joint lubrication film thickness and the joint parameter, updating the joint parameter according to the joint wear amount, re-using the updated joint parameter as the joint parameter, re-using the next time at the appointed time as the appointed time, and continuously determining the re-determined joint wear amount at the appointed time.
The present specification provides a computer readable storage medium storing a computer program which when executed by a processor implements the method of joint wear prediction described above.
The present specification provides an apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing a method of joint wear prediction as described above when executing the program.
The above-mentioned at least one technical scheme that this specification adopted can reach following beneficial effect:
In the method for predicting the joint wear provided by the specification, historical data of joint movement and load of a user are obtained, joint parameters are obtained, a designated moment of joint wear to be predicted is determined, historical data required for predicting the joint wear of the designated moment is determined in the historical data according to the designated moment, the historical data is used as prediction data corresponding to the designated moment, the joint lubrication film thickness of the user at the designated moment is determined according to the prediction data corresponding to the designated moment and the joint parameters, the joint wear of the designated moment is determined according to the joint lubrication film thickness and the joint parameters, the joint parameters are updated according to the joint wear, the updated joint parameters are re-used as joint parameters corresponding to the next moment of the designated moment, the next moment of the designated moment is re-used as the designated moment, and the re-determined joint wear of the designated moment is continuously determined.
According to the method, the motion data and the joint parameters of a user are utilized to predict the thickness of the joint lubricating film, the joint abrasion amount is further predicted according to the thickness of the joint lubricating film, after the joint abrasion amount at the current moment is determined, the joint parameters can be updated according to the joint abrasion amount at the current moment, so that the prediction method of the thickness of the joint lubricating film is corrected, the joint abrasion amount is predicted by utilizing the coupling relation of lubrication and friction, the real relative motion state between joint friction surfaces is more consistent with the actual situation, and a more accurate prediction method of the joint abrasion amount can be provided.
Drawings
The accompanying drawings, which are included to provide a further understanding of the specification, illustrate and explain the exemplary embodiments of the present specification and their description, are not intended to limit the specification unduly. In the drawings:
FIG. 1 is a flow chart of a method of joint wear prediction according to the present disclosure;
FIG. 2 is a schematic illustration of a joint configuration of the present disclosure;
FIG. 3 is a schematic diagram of coordinates of any node of the joint under test in the present specification;
FIG. 4 is a schematic illustration of an apparatus for joint wear prediction as provided herein;
fig. 5 is a schematic view of the electronic device corresponding to fig. 1 provided in the present specification.
Detailed Description
For the purposes of making the objects, technical solutions and advantages of the present specification more apparent, the technical solutions of the present specification will be clearly and completely described below with reference to specific embodiments of the present specification and corresponding drawings. It will be apparent that the described embodiments are only some, but not all, of the embodiments of the present specification. All other embodiments, which can be made by one of ordinary skill in the art without undue burden from the present disclosure, are intended to be within the scope of the present application based on the embodiments herein.
The following describes in detail the technical solutions provided by the embodiments of the present specification with reference to the accompanying drawings.
Fig. 1 is a schematic flow chart of a method for predicting joint wear in the present specification, where the method for predicting joint wear specifically includes the following steps:
S100: historical data of joint movement and load of a user is obtained, and joint parameters are obtained.
First, joint data of a user during exercise is acquired as history data of joint movement of the user, and joint parameters indicating physical characteristics of a joint to be measured of the user are acquired.
Wherein the user is the user of the joint to be tested; the method for acquiring the historical data of the joint movement and the load can directly call the prestored historical data of the user, or acquire the time sequence data of the joint movement and the load after measuring the movement state of the user, and acquire the historical data according to the time sequence data of the joint movement and the load; the joint to be measured can be a whole body joint part such as a hip joint, a knee joint, a shoulder joint, an elbow joint, an ankle joint, an interphalangeal joint and the like.
Specifically, the method for measuring the motion state of the user to obtain the historical data may be to use CT or nuclear magnetic resonance technology to obtain individualized skeleton anatomical parameters, such as skeleton geometric parameters of the trunk, pelvis, thigh and calf, then perform motion capture test, attach mark points at skeleton anatomical positions of the body surface, measure the motion of coordinates of the mark points with time during various motion processes of the human body through the motion capture device and the force measuring plate, and the motion processes include walking, jogging, up-down steps, and the like, further, use opensim and other simulation software to establish an individualized skeleton motion model according to the measured human body anatomical parameters and the time sequence data of the coordinate change of the mark points measured by the motion capture, and obtain the time sequence data of the state change of the joint to be measured during the motion process of the human body as the historical data.
The method for acquiring the joint parameters may be to acquire the joint parameters of the human body's own joint by CT or nuclear magnetic resonance technology, or to determine the joint parameters according to the joint parameters applicable to the artificial joint of the user, or may be other possible acquisition methods, which are not limited in this specification.
In one or more embodiments of the present description, the historical data of the user's joint movement specifically includes: the joint angle data of the user when exercising historically and the joint force data of the user when exercising historically.
Specifically, a personalized skeleton kinematics model of the user can be built according to the measured human anatomy parameters and time sequence data of the time-varying coordinates of the dynamically captured marking points.
When time sequence data of the coordinate of the marking point which is dynamically captured and measured and changes along with time is collected, the time interval-collecting interval between adjacent time points can be adjusted according to actual requirements; marking point coordinate data acquired for any time point in the motion process，The translational degree of freedom and the rotational degree of freedom along three coordinate directions for each marking point are generalized coordinates. The time sequence data of the change of the joint angle of the joint to be measured along with time can be determined according to the generalized coordinate q to be used as the joint angle data when a user moves in history, the inverse dynamics solution of the skeletal muscle of the human body is carried out by combining the generalized coordinate q and the ground counter force measured by the force measuring plate, the acting force between joints at the moment of each mark point when the user moves in history is obtained, and the process for any mark point is as follows:
Wherein q is the generalized coordinate as described above, For a broad range of speeds,For generalized acceleration, M is a distribution matrix of human body mass and inertia, D and K are corresponding damping matrix and stiffness matrix, f is the overall stress condition of the marked point, and Fa is the external load such as foot contact force and moment measured by the force measuring plate. According to the motion equation, the force F between joints, which is the generalized force of the interaction between joints, can be solved reversely, and the generalized force comprises liquid film pressure, friction force, normal contact of rough peaks, tangential friction force, stress moment and the like.
In one or more embodiments of the present disclosure, the joint parameters specifically include a joint shape parameter and a joint material parameter, and acquiring the joint parameter may be acquiring the joint shape parameter and the joint material parameter, where the joint shape parameter represents a size and a shape of a joint to be measured, and the joint material parameter represents a material of the joint to be measured, including a wear coefficient, a friction coefficient, a hardness, a density, an elastic modulus, a poisson ratio, and the like of the joint to be measured.
S102: and determining the appointed moment of the joint wear quantity to be predicted.
After the historical data of the joint movement of the user is obtained and the joint parameters are obtained, the joint state represented by the joint parameters in step S100 can be the initial state of the joint to be measured, and the joint abrasion amount of the joint to be measured at each moment in the prediction period after the initial state is predicted by the historical data obtained in step S100.
Specifically, each time in the prediction period is sequentially taken as a designated time, the joint wear amount of each designated time is determined, when the first prediction is performed on the joint to be detected, the designated time is the first time in the prediction period, for example, when the time interval between the times in the preset prediction period is 0.1s, when the first prediction is performed on the joint to be detected, the designated time is 0.1s after the initial state, and similarly, after the wear amount of the first time is predicted, the joint wear amounts of the second time (0.2 s after the initial state) and the subsequent times are predicted until the joint wear amount of the joint to be detected after the prediction period is determined. It should be noted that 0.1S does not limit the prediction interval, which is the time interval between adjacent time points in the prediction period, and in practical application, the prediction interval may be determined according to the acquisition interval of the joint motion in the history data acquired in S100, and in one or more embodiments of the present specification, the prediction interval may be equal to the acquisition interval.
In one or more embodiments of the present description, a prediction period may be preset, for example: when the prediction period is 1 year, the method can be used for predicting the joint wear amount of each appointed time by taking each time within 1 year after the initial state of the joint to be detected as the appointed time one by one until the joint wear amount of the joint to be detected at the final time of the prediction period is determined.
S104: and according to the appointed time, determining historical data required for predicting the joint abrasion loss at the appointed time from the historical data as prediction data corresponding to the appointed time.
After the specified time is determined, the history data required for predicting the joint wear amount at the specified time can be determined from the history data. From the foregoing, the history data is time series data of acquiring the joint movement after measuring the movement state of the user, and the time series data describes the change of the movement state of the joint in the movement state of the user, so the method provided in the present specification uses the change rule of the movement state of the joint described by the time series data as the change rule of the movement state of the joint in the prediction process, and predicts the joint wear amount of the joint to be measured based on the change rule.
Wherein, the historical data required by predicting the joint wear amount at the specified time can be determined according to the ordering of each time point in the historical data and the ordering of the specified time in the prediction period. For example, when the historical data is s1-s2-s3-s4- … -sn (s 1 is the historical data corresponding to the first time point in the historical data, sn is the historical data corresponding to the last time point in the historical data), the historical data required for predicting the joint wear amount at the first time in the prediction period is s1, and the historical data required for predicting the joint wear amount at the second time in the prediction period is s2.
S106: and determining the thickness of the joint lubrication film of the user at the appointed moment according to the predicted data corresponding to the appointed moment and the joint parameters.
After the prediction data corresponding to the specified time is determined, the thickness of the joint lubricating film of the joint to be detected at the specified time can be determined according to the prediction data and the joint parameters of the joint to be detected, as shown in fig. 2, wherein A represents a joint skeleton, B represents a joint capsule, C represents joint synovial fluid, the thickness of the joint lubricating film is the thickness of the joint lubricating fluid between friction surfaces of two joint skeletons inside the joint capsule, and when the joint moves, the two friction surfaces can be separated by forming liquid film pressure inside the joint lubricating fluid, so that the abrasion condition of the joint is reduced.
In the related studies, it is often considered that the two friction surfaces are completely separated by the joint synovial fluid, the generation of wear is prevented by a dynamic lubrication state (that is, when the joint synovial fluid separates the two friction surfaces, such studies assume that wear does not occur), or that wear is generated between the friction surfaces by dry friction interaction (such studies assume that the effect of the joint synovial fluid is ignored), both of which cannot reflect the actual relative motion state between the joint friction surfaces in the actual situation, whereby the method provided in the present specification simulates the coupling relationship of lubrication and wear between the joint friction surfaces in the actual situation, predicts the joint wear amount of the joint to be measured, and in this step, the joint lubrication film thickness is first determined.
Specifically, the joint form at the designated time can be determined by the prediction data, the joint clearance at the designated time can be determined according to the joint form and the joint parameters at the designated time, and the joint lubrication film thickness can be determined according to the joint clearance at the designated time.
In one or more embodiments of the present disclosure, the thickness of the joint lubrication film at the specified time is determined according to a stress balance relationship formed by an inter-joint acting force, a liquid film pressure and a rough peak contact force, wherein the inter-joint acting force is determined according to prediction data corresponding to the specified time, the liquid film pressure is calculated according to the thickness of the joint lubrication film and the joint shape parameter, and the rough peak contact force is calculated according to the thickness of the joint lubrication film and the joint material parameter.
Specifically, a generalized spherical Reynolds equation can be adopted to establish a lubrication model of joint synovial fluid, the thickness of the joint lubrication film is determined, the thickness of each node of the joint to be measured reaches the stress balance through the lubrication model, and then the distribution of the thickness of each node of the joint to be measured is determined according to the thickness of each node, and the thickness of the joint lubrication film at the designated moment is used as the thickness of the joint lubrication film of a user, and the specific generalized spherical Reynolds equation is expressed as:
As shown in fig. 3, for any node of the joint to be measured, the origin O of coordinates is guaranteed to be uniform, and θ and Φ are spherical coordinates of the node and respectively represent longitude and latitude; 、、 Euler angular velocities in three directions (x-axis, y-axis, z-axis) of the node, respectively; h is the thickness of the joint lubricating film of the node; r is the radius of the joint fossa, p is the liquid film pressure, and eta is the dynamic viscosity of the joint synovial fluid.
Wherein, for the node,、、The generalized coordinate q corresponding to the appointed time can be obtained after coordinate conversion, and the generalized coordinate q can be determined through prediction data; r can be determined according to joint parameters; the initial film thickness h at a given time can be determined by the following formula:
Wherein c is the nominal joint clearance, which belongs to the joint shape parameter; εx, εy, εz are AndThe eccentricity ratios of the represented nodes in three directions (x axis, y axis and z axis) can be obtained after q coordinate conversion of generalized coordinate data corresponding to the designated moment; σs is the joint surface roughness, which belongs to the joint material parameters.
Η may be determined by the following formula:
Wherein, The shear rate of joint synovial fluid can be obtained by the coordinate data q of the mark point corresponding to the appointed moment; p is the liquid film pressure; eta infinity is a high shear rate lower limiting viscosity; η0 is the base viscosity at low shear rate; C. m is,And (3) the joint motion is obtained by calibrating the joint motion and load according to historical data of the joint motion and the load as constants.
Then substituting the initial film thickness, obtaining a liquid film pressure p by solving a generalized spherical Reynolds equation, calculating a rough peak contact force pa according to the current film thickness and joint material parameters through a Greenwood/Tripp model, and establishing a stress balance expression between a joint acting force F and the liquid film pressure p and between the rough peak contact force pa according to the instantaneous quasi-static balance state of joint stress:
When the stress balance expression cannot be established according to the current liquid film pressure p and the current rough peak contact force pa, the film thickness of the node is updated again according to the current liquid film pressure p, and the updated liquid film pressure p and the updated rough peak contact force pa are obtained according to the updated film thickness of the node until the updated liquid film pressure p and the current rough peak contact force pa can establish the stress balance expression, so that the film thickness when the stress balance expression is established is determined as the film thickness of the node.
Thus, the thickness of each node in the joint to be measured at the specified time, that is, the joint lubrication film thickness distribution of the joint to be measured at the specified time, can be obtained as the joint lubrication film thickness at the specified time.
S108: and determining the joint abrasion loss at the appointed time according to the predicted data, the joint lubrication film thickness and the joint parameters, updating the joint parameters according to the joint abrasion loss, re-using the updated joint parameters as the joint parameters corresponding to the next moment of the appointed time, and re-using the next moment of the appointed time as the appointed time so as to continuously determine the re-determined joint abrasion loss at the appointed time.
In view of the above, the method provided in the present specification predicts the joint wear amount of the joint to be measured by using the coupling relation between lubrication and friction, instead of directly calculating the joint wear amounts generated by the two friction surfaces under the dry friction condition, after determining the thickness of the joint lubrication film at the specified time, the influence of the thickness of the joint lubrication film on the relative motion state (the relative motion state includes dynamic lubrication, boundary lubrication and dry friction) of the two friction surfaces may be determined, and further, based on the current inter-joint acting force under the thickness of the joint lubrication film, the joint wear amounts caused by friction between the two friction surfaces may be determined according to the relative motion state.
Specifically, the rough peak contact force may be determined based on the film thickness of each node of the joint to be measured according to the generalized spherical Reynolds equation, the relative sliding amount of the friction surface of each node at the designated time may be determined according to the predicted data, the node wear amount at the designated time may be determined according to the relative sliding amount, the rough peak contact force and the joint material parameter, the joint wear amount of the joint to be measured at the designated time may be determined according to the wear amount of each node, the joint parameter may be updated according to the joint wear amount due to irreversible deformation of the joint to be measured, and the updated joint parameter may be re-used as the joint parameter, so that after the next time at the designated time is re-used as the designated time, the determination of the joint wear amount at the designated time may be performed again from step S102 according to the updated designated time and the updated joint parameter.
In one or more embodiments of the present description, the joint shape parameters are updated according to the amount of joint wear.
Specifically, after the influence of the joint wear on the joint parameters is introduced, when the specified time is not the first time in the prediction period, the determination formula of the film thickness h may be corrected for each node of the joint to be measured as:
Wherein δelastic is the joint elastic displacement caused by the liquid film pressure at the designated moment, the liquid film pressure p is determined according to the film thickness h of the node by using the generalized spherical Reynolds equation, then the joint elastic displacement can be solved according to the elastic mechanical displacement equation and the minimum potential energy principle, the displacement component Δi (three directions are represented by u, v and w) of the node can be determined by using the generalized coordinate q of the node at the designated moment and the liquid film pressure p, and the stress component σi and the strain component εi are respectively:
further, determining an overall stiffness matrix K of the joint to be measured according to each node delta i, sigma i and epsilon i of the joint to be measured (ne is a finite element unit of the joint to be measured, namely the total number of nodes, and is determined according to joint shape parameters):
after the integral rigidity matrix is obtained, the joint elastic displacement can be obtained as follows:
The elastic displacement of any node can be expressed as:
wherein F is a node load vector, and can be determined according to the liquid film pressure p of each mark point.
Hi, new represents the amount of wear of the node at a given moment, determined by updated joint shape parameters, specifically:
hi, new is obtained by adding the node cumulative wear amount hi, old at the start of the i-th time and the node wear amount hi at the i-th time (assuming that the specified time is the i-th time in the prediction period here).
The joint parameters and hi, new are thereby updated continuously until the prediction of the amount of joint wear at the final moment in the prediction period is completed.
When the joint to be measured is the joint of the user, the subsequent maintenance proposal or medical proposal can be predicted and determined according to the abrasion loss of the joint.
In one or more embodiments of the present disclosure, when the history data corresponding to the i-th time in the prediction period is the history data of the last time point, the history data of the first time point may be used as the history data corresponding to the i+1th time in the prediction period.
The method for predicting the joint abrasion loss shown in fig. 1 predicts the joint lubrication film thickness by using the motion data and the joint parameters of a user, further predicts the joint abrasion loss according to the joint lubrication film thickness, and after determining the joint abrasion loss at the current moment, can update the joint parameters according to the joint abrasion loss at the current moment so as to correct the prediction method of the joint lubrication film thickness, predicts the joint abrasion loss by using the coupling relation of lubrication and friction, is more in line with the actual relative motion state between the joint friction surfaces in the actual situation, and can provide a more accurate prediction method of the joint abrasion loss.
In step S108 shown in fig. 1, a rough peak contact force is determined according to the joint lubrication film thickness and the joint material parameter, and a joint wear amount at the specified time is determined according to the prediction data, the rough peak contact force, and the joint material parameter.
The thickness of the joint lubrication film determined in step S106 is a film thickness that enables each node of the joint to be measured to reach stress balance. The rough peak contact force was determined from the joint lubricating film thickness, and then the joint wear amount hi at the specified time was:
wherein k is the comprehensive wear coefficient of the joint to be measured, H is the surface hardness, both belong to joint material parameters, pa is the rough peak contact force of each node, x is the elastic displacement of the node, and the average wear load in time T is calculated according to the wear load calculation formula The method comprises the following steps:
Wherein, Is the relative sliding speed between the two surfaces, and can be determined according to the predicted data.
The wear depth hi of a single node within one prediction interval Tacc can be calculated from the above two formulas as:
therefore, after the abrasion depth of each finite element unit is determined, the joint abrasion amount of the joint to be detected at the appointed moment can be determined.
In step S108 shown in fig. 1, a joint lubrication state corresponding to the joint lubrication film thickness is determined, wherein the joint lubrication state includes one of dynamic lubrication, boundary lubrication and dry friction, and the rough peak contact force at the specified time is determined by using a rough peak contact force determination method corresponding to the joint lubrication state according to the joint lubrication film thickness and the joint material parameter.
In view of the above, the method provided in the present specification predicts the joint wear amount by using the coupling relation between lubrication and wear, specifically, for each node of the joint to be measured, determines the ratio h/σs of the film thickness to the joint surface roughness according to the film thickness of the node, and determines the joint state corresponding to the node according to h/σs—when (h/σs)4 Is power lubrication, when 1(H/σs) < 4 is boundary lubrication, when (h/σs) < 1 is dry friction, for different joint states, calculated by Greenwood/Tripp model:
Wherein E is the elastic modulus; e1 and E2 respectively represent the elastic modulus of two friction surfaces of the joint to be tested; v1 and V2 respectively represent Poisson ratios of two friction surfaces of the joint to be tested; eta is the number of rough peaks in the normal contact area of the node; Is the density of microprotrusion peaks; The curvature radius of the top of the microprotrusion body, sigma s is the joint surface roughness of the joint to be measured, and the roughness of two friction surfaces of the joint to be measured can be calculated:
in addition, in step S100 shown in fig. 1, joint parameters may be determined according to parameters of the artificial joint to be configured.
The joint to be tested may be an artificial joint instead of a user' S own joint, so that after step S108 shown in fig. 1, if the specified time is the target time, it is determined whether the joint parameter determined according to the artificial joint to be configured meets the wear standard according to the joint wear amount at the specified time and the preset wear threshold, if the joint parameter determined according to the artificial joint to be configured meets the wear standard, the joint parameter determined according to the artificial joint to be configured is used as the target joint parameter of the user, and the artificial joint is configured for the user according to the target joint parameter.
The target moment is the final moment of the prediction period, and the joint abrasion loss of the artificial joint to be configured at the target moment is determined, so that whether the joint parameters of the artificial joint to be configured meet the abrasion standard for a user or not can be predicted, wherein the abrasion loss in the service period does not exceed the abrasion threshold. And then, taking the joint parameters of the artificial joint to be configured, which meet the abrasion standard, as target joint parameters of a user, and configuring the personalized artificial joint for the user according to the target joint parameters.
Therefore, the personalized artificial joint can be customized for each user, and the service life of the artificial joint is prolonged.
In one or more embodiments of the present disclosure, when the joint parameters of the artificial joint to be configured do not meet the wear standard, the joint parameters and the joint material parameters may be reconfigured, and according to the reconfigured parameters, the method shown in fig. 1 is applied to obtain the joint wear amount at the target moment, and then the redetermined joint wear amount is compared with a preset wear threshold until the reconfigured parameters meet the wear standard.
The method for predicting the joint wear provided above for one or more embodiments of the present specification, based on the same thought, further provides a corresponding device for predicting the joint wear, as shown in fig. 4.
Fig. 4 is a schematic diagram of an apparatus for joint wear prediction provided in the present specification, specifically including:
the acquisition module 400 acquires historical data of joint movement and load of a user and acquires joint parameters;
A time determination module 402 that determines a specified time of the joint wear amount to be predicted;
A data determining module 404, configured to determine, from the history data, history data required for predicting the joint wear amount at the specified time, as prediction data corresponding to the specified time, according to the specified time;
A thickness prediction module 406, configured to determine a thickness of a joint lubrication film of the user at the specified time according to the predicted data corresponding to the specified time and the joint parameter;
The wear amount prediction module 408 determines the joint wear amount at the specified time based on the prediction data, the joint lubrication film thickness, and the joint parameter, updates the joint parameter based on the joint wear amount, re-uses the updated joint parameter as the joint parameter, and re-uses the next time at the specified time as the specified time to continue determining the re-determined joint wear amount at the specified time.
Optionally, the historical data of the joint movement and the load of the user specifically includes: the joint angle data of the user when exercising historically and the joint force data of the user when exercising historically.
Optionally, the obtaining module 400 is specifically configured to: acquiring joint shape parameters and joint material parameters.
Optionally, the thickness prediction module 406 is specifically configured to: and determining the thickness of the joint lubrication film at the appointed moment according to a stress balance relation formed by the action force between joints, the liquid film pressure and the rough peak contact force, wherein the action force between joints is determined according to the prediction data corresponding to the appointed moment, the liquid film pressure is calculated according to the thickness of the joint lubrication film and the joint shape parameter, and the rough peak contact force is calculated according to the thickness of the joint lubrication film and the joint material parameter.
Optionally, the wear amount prediction module 408 is specifically configured to: and determining a rough peak contact force according to the joint lubricating film thickness and the joint material parameters, and determining the joint abrasion loss at the appointed moment according to the predicted data, the rough peak contact force and the joint material parameters.
Optionally, the wear amount prediction module 408 is specifically configured to: and determining a joint lubrication state corresponding to the joint lubrication film thickness, wherein the joint lubrication state comprises one of dynamic lubrication, boundary lubrication and dry friction, and determining the rough peak contact force by using a rough peak contact force determination method corresponding to the joint lubrication state according to the joint lubrication film thickness and the joint material parameters.
Optionally, the wear amount prediction module 408 is specifically configured to: and updating the joint shape parameters according to the joint abrasion amount.
Optionally, the obtaining module 400 is specifically configured to: determining joint parameters according to parameters of the artificial joint to be configured;
The wear amount prediction module 408 is further configured to: if the designated time is the target time, determining whether the joint parameters determined according to the artificial joint to be configured meet the abrasion standard or not according to the joint abrasion amount at the designated time and a preset abrasion threshold, and if the joint parameters determined according to the artificial joint to be configured meet the abrasion standard, taking the joint parameters determined according to the artificial joint to be configured as the target joint parameters of the user, and configuring the artificial joint for the user according to the target joint parameters.
The present specification also provides a computer readable storage medium having stored thereon a computer program operable to perform the method of joint wear prediction provided in fig. 1 above.
The present specification also provides a schematic structural diagram of the electronic device shown in fig. 5. At the hardware level, as illustrated in fig. 5, the joint wear prediction device includes a processor, an internal bus, a network interface, a memory, and a nonvolatile memory, and may of course include hardware required by other services. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs to implement the method of joint wear prediction described above with respect to fig. 1. Of course, other implementations, such as logic devices or combinations of hardware and software, are not excluded from the present description, that is, the execution subject of the following processing flows is not limited to each logic unit, but may be hardware or logic devices.
In the 90 s of the 20 th century, improvements to one technology could clearly be distinguished as improvements in hardware (e.g., improvements to circuit structures such as diodes, transistors, switches, etc.) or software (improvements to the process flow). However, with the development of technology, many improvements of the current method flows can be regarded as direct improvements of hardware circuit structures. Designers almost always obtain corresponding hardware circuit structures by programming improved method flows into hardware circuits. Therefore, an improvement of a method flow cannot be said to be realized by a hardware entity module. For example, a programmable logic device (Programmable Logic Device, PLD) (e.g., field programmable gate array (Field Programmable GATE ARRAY, FPGA)) is an integrated circuit whose logic functions are determined by user programming of the device. A designer programs to "integrate" a digital system onto a PLD without requiring the chip manufacturer to design and fabricate application-specific integrated circuit chips. Moreover, nowadays, instead of manually manufacturing integrated circuit chips, such programming is mostly implemented with "logic compiler (logic compiler)" software, which is similar to the software compiler used in program development and writing, and the original code before being compiled is also written in a specific programming language, which is called hardware description language (Hardware Description Language, HDL), but HDL is not just one, but a plurality of kinds, such as ABEL（Advanced Boolean Expression Language）、AHDL（Altera Hardware Description Language）、Confluence、CUPL（Cornell University Programming Language）、HDCal、JHDL（Java Hardware Description Language）、Lava、Lola、MyHDL、PALASM、RHDL（Ruby Hardware Description Language）, and VHDL (Very-High-SPEED INTEGRATED Circuit Hardware Description Language) and Verilog are currently most commonly used. It will also be apparent to those skilled in the art that a hardware circuit implementing the logic method flow can be readily obtained by merely slightly programming the method flow into an integrated circuit using several of the hardware description languages described above.
The controller may be implemented in any suitable manner, for example, the controller may take the form of, for example, a microprocessor or processor and a computer readable medium storing computer readable program code (e.g., software or firmware) executable by the (micro) processor, logic gates, switches, application SPECIFIC INTEGRATED Circuits (ASICs), programmable logic controllers, and embedded microcontrollers, examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, atmel AT91SAM, microchip PIC18F26K20, and Silicone Labs C8051F320, the memory controller may also be implemented as part of the control logic of the memory. Those skilled in the art will also appreciate that, in addition to implementing the controller in a pure computer readable program code, it is well possible to implement the same functionality by logically programming the method steps such that the controller is in the form of logic gates, switches, application specific integrated circuits, programmable logic controllers, embedded microcontrollers, etc. Such a controller may thus be regarded as a kind of hardware component, and means for performing various functions included therein may also be regarded as structures within the hardware component. Or even means for achieving the various functions may be regarded as either software modules implementing the methods or structures within hardware components.
The system, apparatus, module or unit set forth in the above embodiments may be implemented in particular by a computer chip or entity, or by a product having a certain function. One typical implementation is a computer. In particular, the computer may be, for example, a personal computer, a laptop computer, a cellular telephone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.
For convenience of description, the above devices are described as being functionally divided into various units, respectively. Of course, the functions of each element may be implemented in one or more software and/or hardware elements when implemented in the present specification.
It will be appreciated by those skilled in the art that embodiments of the present invention may be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
It will be appreciated by those skilled in the art that embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, the present specification may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present description can take the form of a computer program product on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.
The description may be described in the general context of computer-executable instructions, such as program modules, being executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform particular tasks or implement particular abstract data types. The specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices that are linked through a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media including memory storage devices.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments. In particular, for system embodiments, since they are substantially similar to method embodiments, the description is relatively simple, as relevant to see a section of the description of method embodiments.
The foregoing is merely exemplary of the present disclosure and is not intended to limit the disclosure. Various modifications and alterations to this specification will become apparent to those skilled in the art. Any modifications, equivalent substitutions, improvements, or the like, which are within the spirit and principles of the present description, are intended to be included within the scope of the claims of the present application.
Claims (8)
1. A method of joint wear prediction, the method comprising:
acquiring historical data of joint movement and load of a user, and acquiring joint parameters;
Determining a designated moment of joint wear to be predicted;
According to the appointed time, determining historical data required for predicting the joint abrasion loss at the appointed time from the historical data as prediction data corresponding to the appointed time;
determining the thickness of the joint lubrication film of the user at the appointed moment according to the predicted data corresponding to the appointed moment and the joint parameters;
determining the joint abrasion loss at the appointed time according to the predicted data, the joint lubrication film thickness and the joint parameters, updating the joint parameters according to the joint abrasion loss, re-using the updated joint parameters as the joint parameters corresponding to the next moment of the appointed time, and re-using the next moment of the appointed time as the appointed time so as to continuously determine the re-determined joint abrasion loss at the appointed time;
the method for acquiring the joint parameters specifically comprises the following steps:
Acquiring joint shape parameters and joint material parameters;
Determining the thickness of the joint lubrication film of the user at the appointed time according to the predicted data corresponding to the appointed time and the joint parameters, specifically comprising:
And determining the thickness of the joint lubrication film at the appointed moment according to a stress balance relation formed by the action force between joints, the liquid film pressure and the rough peak contact force, wherein the action force between joints is determined according to the prediction data corresponding to the appointed moment, the liquid film pressure is calculated according to the thickness of the joint lubrication film and the joint shape parameter, and the rough peak contact force is calculated according to the thickness of the joint lubrication film and the joint material parameter.
2. The method of claim 1, wherein the user's historical data of joint movement and load, in particular, comprises: the joint angle data of the user when exercising historically and the joint force data of the user when exercising historically.
3. The method of claim 1, wherein determining the amount of joint wear at the specified time based on the predicted data, the joint lubrication film thickness, and the joint parameters, comprises:
determining a rough peak contact force according to the joint lubricating film thickness and the joint material parameters;
and determining the joint abrasion loss at the appointed moment according to the predicted data, the rough peak contact force and the joint material parameters.
4. A method according to claim 3, wherein determining a asperity peak contact force based on the joint lubrication film thickness and the joint material parameters, comprises:
Determining a joint lubrication state corresponding to the joint lubrication film thickness, wherein the joint lubrication state comprises one of power lubrication, boundary lubrication and dry friction;
And determining the rough peak contact force by using a rough peak contact force determination method corresponding to the joint lubrication state according to the joint lubrication film thickness and the joint material parameters.
5. The method of claim 1, wherein updating the joint parameters based on the amount of joint wear, comprises:
and updating the joint shape parameters according to the joint abrasion amount.
6. The method of claim 1, wherein acquiring joint parameters comprises:
determining joint parameters according to parameters of the artificial joint to be configured;
after determining the joint wear amount at the specified time, further comprising:
If the designated time is the target time, determining whether joint parameters determined according to the artificial joint to be configured meet the abrasion standard or not according to the joint abrasion quantity at the designated time and a preset abrasion threshold;
if the joint parameters determined according to the artificial joint to be configured meet the abrasion standard, the joint parameters determined according to the artificial joint to be configured are used as target joint parameters of the user;
And configuring an artificial joint for a user according to the target joint parameters.
7. A computer readable storage medium, characterized in that the storage medium stores a computer program which, when executed by a processor, implements the method of any of the preceding claims 1-6.
8. An apparatus comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the method of any of claims 1-6 when the program is executed by the processor.
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