Prediction method for thighbone greater trochanter reconstruction position in hip replacement

Abstract

The invention provides a method for predicting a thighbone greater trochanter reconstruction position in hip replacement, and the method comprises the steps: carrying out the three-dimensional reconstruction processing and personalized zooming processing according to an original medical image of a patient, and obtaining a personalized bone muscle model; respectively carrying out integration processing on the initial personalized three-dimensional skeleton model and each prosthesis model, and determining at least one postoperative simulation skeleton model; performing skeleton replacement processing on a corresponding skeleton region in the personalized bone muscle model by using each postoperative simulation skeleton model to obtain at least one candidate postoperative simulation bone muscle model; according to the target space coordinate data, the target plantar pressure data and the muscle activation degree data, performing muscle force calculation in combination with each candidate postoperative simulation bone muscle model and the personalized bone muscle model, and predicting a femoral greater trochanter reconstruction position according to a muscle force calculation result. In this way, through personalized simulation and calculation, the reconstruction position of the greater trochanter of the femur with the optimal gluteus medius muscle strength is accurately determined.

Description

Technical Field

[0001] The present application relates to the field of medical simulation technology, and in particular to a method for predicting the reconstruction position of the greater trochanter of the femur during hip replacement surgery. Background Art

[0002] Developmental Dysplasia of the Hip (DDH) refers to a type of disease in which the hip joint is abnormal during development, resulting in changes in the structure and function of the pelvis, hip joint, and lower limb bones. The hip joint of DDH patients is usually unstable, the acetabulum is dysplastic, and the femoral head cannot be stably embedded in the acetabulum, resulting in problems such as hip dislocation or subluxation. DDH patients are often accompanied by hip pain, limited mobility, and abnormal gait.

[0003] Total hip arthroplasty (THA) is currently the only effective way to treat DDH. With the continuous advancement of artificial joint technology, hip replacement can effectively relieve patients' pain, restore joint function, and significantly improve patients' quality of life. However, due to the skeletal malformation and severe anatomical variation of DDH patients, joint replacement surgery is more difficult than ordinary surgery and places higher demands on surgeons. However, there is no unified conclusion on the choice of reconstruction position for the greater trochanter reconstruction of DDH patients during hip replacement surgery. Among them, the positions of greater trochanter reconstruction in clinical anatomical position reconstruction and high position reconstruction have their own advantages and disadvantages. Which reconstruction method can maximize the restoration of gluteus medius muscle strength around the hip joint is a key issue for clinicians. The gluteus medius is the most important muscle to maintain the balance of normal walking in the human body. If the gluteus medius muscle strength is insufficient after joint replacement in DDH patients, pelvic imbalance will occur and lead to lower limb lameness and limping gait. Therefore, it is very important to restore the gluteus medius muscle strength as much as possible after hip replacement for the effect of surgery. Summary of the invention

[0004] In view of this, the purpose of the present application is to provide a method for predicting the reconstruction position of the greater trochanter of the femur during hip replacement surgery. Through personalized simulation and calculation, the reconstruction position of the greater trochanter of the femur when the gluteus medius muscle strength is optimal can be accurately determined, thereby effectively solving the problems of inconsistent selection of the reconstruction position of the greater trochanter in traditional methods, thereby improving the effect of hip replacement surgery and the service life of artificial joints.

[0005] The present application embodiment provides a method for predicting the reconstruction position of the greater trochanter of the femur during hip replacement surgery, the prediction method comprising: Acquire the patient's target spatial coordinate data, the patient's target plantar pressure data, and the original medical image of the patient's designated limb area; wherein the designated limb area includes a hip joint, and the target spatial data includes static coordinate data and dynamic coordinate data; Performing three-dimensional reconstruction processing according to the original medical image to determine an initial personalized three-dimensional skeletal model of the patient; Performing personalized scaling processing on the general bone and muscle model using the static coordinate data of the patient to obtain a personalized bone and muscle model of the patient; The initial personalized three-dimensional bone model is separately integrated with each prosthesis model designed for hip replacement to achieve different greater trochanter reconstruction positions, to determine at least one postoperative simulated bone model of the patient; wherein different postoperative simulated bone models have different femoral greater trochanter reconstruction positions; For each postoperative simulated bone model, using the postoperative simulated bone model to perform bone replacement processing on the corresponding bone area in the personalized bone and muscle model, to obtain at least one candidate postoperative simulated bone and muscle model of the patient; wherein the reconstruction position of the greater trochanter of the femur in different candidate postoperative simulated bone and muscle models is different; identifying whether the patient is a patient undergoing unilateral hip replacement; If yes, obtaining an electromyographic measurement signal at the gluteus medius muscle position on the opposite side of the patient, and determining muscle activation degree data according to the electromyographic measurement signal; According to the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data, the gluteus medius muscle strength on the surgical side is calculated in combination with each candidate postoperative simulated bone muscle model to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone muscle model, and the gluteus medius muscle strength on the contralateral side is calculated in combination with the personalized bone muscle model to obtain the standard gluteus medius muscle strength of the patient; Prediction of greater trochanteric reconstruction position during hip arthroplasty based on total estimated gluteus medius strength and standard gluteus medius strength.

[0006] Optionally, if the patient is not a patient undergoing unilateral hip replacement, the prediction method further comprises: According to the personal information of the patient, searching for the electromyographic measurement signal corresponding to the patient, and determining muscle activation degree data according to the electromyographic measurement signal; According to the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data, and in combination with each candidate postoperative simulated bone and muscle model, the gluteus medius muscle strength of the surgical side is calculated to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model; Prediction of greater trochanter reconstruction position during hip arthroplasty based on all estimated gluteus medius muscle strength.

[0007] Optionally, the electromyographic measurement signal at the gluteus medius muscle position on the contralateral side of the patient is determined by the following steps: A surface electromyography signal measuring device is used to measure the electromyography signal at the gluteus medius muscle position on the opposite side when the patient walks; wherein the surface electromyography signal measuring device is arranged at the gluteus medius muscle position at the posterior and superior part of the contralateral hip joint and the posterior and inferior part of the iliac crest of the pelvis; and the placement direction of the surface electromyography signal measuring device is parallel to the direction of the muscle fibers.

[0008] Optionally, the using the static coordinate data of the patient to perform personalized scaling processing on the general bone and muscle model to obtain the personalized bone and muscle model of the patient includes: Determining the marking position of the marking point attached to the patient's limb according to the static coordinate data; Using the determined marker positions to interface with the universal musculoskeletal model to determine the patient's true anatomical parameters; Determining the scaling ratio of each bone segment in the universal bone and muscle model according to the real anatomical parameters of the patient; The universal bone and muscle model is scaled according to the scaling ratio of each bone segment to determine the personalized bone and muscle model of the patient.

[0009] Optionally, the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data are used to calculate the gluteus medius muscle strength on the surgical side in combination with each candidate postoperative simulated bone and muscle model to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model, including: For each candidate postoperative simulated bone and muscle model, a reverse analysis operation is performed on the candidate postoperative simulated bone and muscle model according to the dynamic coordinate data and the target plantar pressure data in the target spatial coordinate data to obtain the initial joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model; According to the muscle activation degree data, the initial joint reverse analysis data is corrected using an error reduction algorithm to determine the target joint reverse analysis data of the patient; Based on the target joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model, combined with the calculation of the gluteus medius muscle strength data of the patient during movement using the candidate postoperative simulated bone and muscle model, the estimated gluteus medius muscle strength under the candidate postoperative simulated bone and muscle model is determined.

[0010] Optionally, the initial joint reverse analysis data includes initial joint inverse kinematics data and initial joint inverse dynamics data. For each candidate postoperative simulated bone and muscle model, a reverse analysis operation is performed on the candidate postoperative simulated bone and muscle model according to the dynamic coordinate data in the target spatial coordinate data and the target plantar pressure data to obtain the initial joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model, including: According to the dynamic coordinate data in the target space coordinate data, inverse kinematics calculation is performed in combination with the candidate postoperative simulated bone and muscle model to obtain the initial joint inverse kinematics data of the patient under the candidate postoperative simulated bone and muscle model; According to the target plantar pressure data and the initial joint inverse kinematics data, inverse dynamics calculation is performed in combination with the candidate postoperative simulated bone and muscle model to obtain the initial joint inverse dynamics data of the patient under the candidate postoperative simulated bone and muscle model.

[0011] Optionally, the method predicts the reconstruction position of the greater trochanter in hip replacement surgery based on all estimated gluteus medius muscle strength and standard gluteus medius muscle strength, including: The muscle strength with the smallest error between the estimated gluteus medius muscle strength and the standard gluteus medius muscle strength is determined as the target gluteus medius muscle strength; The reconstruction position of the greater trochanter of the femur in hip replacement surgery is determined according to the reconstruction position of the greater trochanter of the femur in the candidate postoperative simulated bone and muscle model corresponding to the target gluteus medius muscle strength.

[0012] The present application also provides a device for predicting the reconstruction position of the greater trochanter of the femur during hip replacement surgery, the device comprising: A first acquisition module is used to acquire the patient's target spatial coordinate data, the patient's target plantar pressure data, and the original medical image of the patient's designated limb area; wherein the designated limb area includes a hip joint, and the target spatial data includes static coordinate data and dynamic coordinate data; A reconstruction module, used for performing three-dimensional reconstruction processing according to the original medical image to determine an initial personalized three-dimensional bone model of the patient; A scaling module, used for performing personalized scaling processing on the general bone and muscle model using the static coordinate data of the patient to obtain a personalized bone and muscle model of the patient; An integration module is used to perform model integration processing on the initial personalized three-dimensional bone model and each prosthesis model designed for hip replacement to achieve different greater trochanter reconstruction positions, so as to determine at least one postoperative simulated bone model of the patient; wherein different postoperative simulated bone models have different femoral greater trochanter reconstruction positions; A replacement module is used for performing bone replacement processing on the corresponding bone area in the personalized bone and muscle model using the postoperative simulated bone model for each postoperative simulated bone model, so as to obtain at least one candidate postoperative simulated bone and muscle model of the patient; wherein the reconstruction position of the greater trochanter of the femur in different candidate postoperative simulated bone and muscle models is different; An identification module, used for identifying whether the patient is a patient undergoing unilateral hip replacement surgery; a second acquisition module, for acquiring an electromyographic measurement signal at a gluteus medius muscle position on the opposite side of the patient if the patient is a patient undergoing unilateral hip replacement surgery, and determining muscle activation degree data according to the electromyographic measurement signal; a calculation module, for calculating the gluteus medius muscle strength of the surgical side according to the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data, respectively in combination with each candidate postoperative simulated bone and muscle model, to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model, and calculating the gluteus medius muscle strength of the contralateral side in combination with the personalized bone and muscle model, to obtain the standard gluteus medius muscle strength of the patient; Prediction module for predicting greater trochanter reconstruction position in hip arthroplasty based on all estimated gluteus medius muscle strength and standard gluteus medius muscle strength.

[0013] Optionally, the prediction device is further used for: If the patient is not a patient who has undergone unilateral hip replacement, searching for the electromyographic measurement signal corresponding to the patient according to the patient's personal information, and determining muscle activation degree data according to the electromyographic measurement signal; According to the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data, and in combination with each candidate postoperative simulated bone and muscle model, the gluteus medius muscle strength of the surgical side is calculated to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model; Prediction of greater trochanter reconstruction position during hip arthroplasty based on all estimated gluteus medius muscle strength.

[0014] Optionally, the second acquisition module is further used to determine the electromyographic measurement signal at the gluteus medius muscle position on the opposite side of the patient through the following steps: A surface electromyography signal measuring device is used to measure the electromyography signal at the gluteus medius muscle position on the opposite side when the patient walks; wherein the surface electromyography signal measuring device is arranged at the gluteus medius muscle position at the posterior and superior part of the contralateral hip joint and the posterior and inferior part of the iliac crest of the pelvis; and the placement direction of the surface electromyography signal measuring device is parallel to the direction of the muscle fibers.

[0015] Optionally, when the scaling module is used to perform personalized scaling processing on the general bone and muscle model using the static coordinate data of the patient to obtain the personalized bone and muscle model of the patient, the scaling module is used to: Determining the marking position of the marking point attached to the patient's limb according to the static coordinate data; Using the determined marker positions to interface with the universal musculoskeletal model to determine the patient's true anatomical parameters; Determining the scaling ratio of each bone segment in the universal bone and muscle model according to the real anatomical parameters of the patient; The universal bone and muscle model is scaled according to the scaling ratio of each bone segment to determine the personalized bone and muscle model of the patient.

[0016] Optionally, when the calculation module is used to calculate the gluteus medius muscle strength on the surgical side according to the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data, and respectively in combination with each candidate postoperative simulated bone and muscle model, to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model, the calculation module is used to: For each candidate postoperative simulated bone and muscle model, a reverse analysis operation is performed on the candidate postoperative simulated bone and muscle model according to the dynamic coordinate data and the target plantar pressure data in the target spatial coordinate data to obtain the initial joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model; According to the muscle activation degree data, the initial joint reverse analysis data is corrected using an error reduction algorithm to determine the target joint reverse analysis data of the patient; Based on the target joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model, combined with the calculation of the gluteus medius muscle strength data of the patient during movement using the candidate postoperative simulated bone and muscle model, the estimated gluteus medius muscle strength under the candidate postoperative simulated bone and muscle model is determined.

[0017] Optionally, the initial joint reverse analysis data includes initial joint inverse kinematics data and initial joint inverse dynamics data. When the calculation module is used to perform a reverse analysis operation on each candidate postoperative simulated bone and muscle model according to the dynamic coordinate data and the target plantar pressure data in the target spatial coordinate data to obtain the initial joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model, the calculation module is used to: According to the dynamic coordinate data in the target space coordinate data, inverse kinematics calculation is performed in combination with the candidate postoperative simulated bone and muscle model to obtain the initial joint inverse kinematics data of the patient under the candidate postoperative simulated bone and muscle model; According to the target plantar pressure data and the initial joint inverse kinematics data, inverse dynamics calculation is performed in combination with the candidate postoperative simulated bone and muscle model to obtain the initial joint inverse dynamics data of the patient under the candidate postoperative simulated bone and muscle model.

[0018] Optionally, when the prediction module is used to predict the reconstruction position of the greater trochanter of the femur in hip replacement surgery based on all estimated gluteus medius muscle strengths and standard gluteus medius muscle strengths, the prediction module is used to: The muscle strength with the smallest error between the estimated gluteus medius muscle strength and the standard gluteus medius muscle strength is determined as the target gluteus medius muscle strength; The reconstruction position of the greater trochanter of the femur in hip replacement surgery is determined according to the reconstruction position of the greater trochanter of the femur in the candidate postoperative simulated bone and muscle model corresponding to the target gluteus medius muscle strength.

[0019] An embodiment of the present application also provides an electronic device, comprising: a processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate via the bus, and when the machine-readable instructions are executed by the processor, the steps of the prediction method as described above are performed.

[0020] An embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the prediction method described above are executed.

[0021] An embodiment of the present application provides a method for predicting the reconstruction position of the greater trochanter of femur during hip replacement surgery, the prediction method comprising: obtaining target spatial coordinate data of a patient, target plantar pressure data of the patient, and original medical images of a designated limb area of ​​the patient; wherein the designated limb area includes a hip joint, and the target spatial data includes static coordinate data and dynamic coordinate data; performing three-dimensional reconstruction processing according to the original medical images to determine an initial personalized three-dimensional skeletal model of the patient; performing personalized scaling processing on a general bone and muscle model using the static coordinate data of the patient to obtain a personalized bone and muscle model of the patient; performing model integration processing on the initial personalized three-dimensional skeletal model and each prosthesis model designed for hip replacement surgery to achieve different greater trochanter reconstruction positions, respectively, to determine at least one postoperative simulated skeletal model of the patient; wherein different postoperative simulated skeletal models have different reconstruction positions of the greater trochanter of femur; for each postoperative simulated skeletal model, A model is provided, and the postoperative simulated bone model is used to perform bone replacement processing on the corresponding bone area in the personalized bone and muscle model to obtain at least one candidate postoperative simulated bone and muscle model of the patient; wherein, the reconstruction position of the greater trochanter of the femur in different candidate postoperative simulated bone and muscle models is different; it is identified whether the patient is a patient undergoing unilateral hip replacement; if so, the electromyographic measurement signal at the position of the gluteus medius muscle on the opposite side of the patient is obtained, and the muscle activation degree data is determined according to the electromyographic measurement signal; according to the target spatial coordinate data, the target plantar pressure data and the muscle activation degree data, and in combination with each candidate postoperative simulated bone and muscle model, the gluteus medius muscle strength on the surgical side is calculated, and the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model is obtained, and the contralateral gluteus medius muscle strength is calculated in combination with the personalized bone and muscle model to obtain the standard gluteus medius muscle strength of the patient; according to all the estimated gluteus medius muscle strength and the standard gluteus medius muscle strength, the reconstruction position of the greater trochanter of the femur in hip replacement is predicted. In this way, the present application establishes a personalized bone and muscle model through the patient's static and dynamic spatial coordinate data, target plantar pressure data, and electromyographic measurement signals. Combined with the three-dimensional bone model and different prosthesis designs, a candidate postoperative simulation model can be generated for each patient's specific situation to ensure the pertinence and personalization of postoperative functional recovery. And through multimodal data fusion, the estimated muscle strength of the gluteus medius on the surgical side under the candidate postoperative model is accurately calculated, combined with the standardized calculation of the gluteus medius muscle strength on the contralateral side, and the effect of the reconstruction position on postoperative muscle function is compared and analyzed. This method helps to optimize the reconstruction position of the greater trochanter of the femur, so that the patient's postoperative muscle balance and functional recovery can reach the best state. In addition, this scheme proposes to integrate the patient's initial personalized three-dimensional bone model with a variety of prosthesis models, verify the effects of different reconstruction positions through simulation, avoid the limitations of selecting prostheses and reconstruction positions based solely on intraoperative experience, and improve the predictability of postoperative recovery.

[0022] In summary, this method innovatively combines multimodal data and personalized modeling, providing a new design, evaluation and optimization method for hip replacement, which is of great significance for improving clinical surgical outcomes.

[0023] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, preferred embodiments are specifically cited below and described in detail with reference to the attached drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying creative work.

[0025] Figure 1 A flowchart of a method for predicting the reconstruction position of the greater trochanter of the femur in hip replacement surgery provided in an embodiment of the present application; Figure 2 A schematic diagram of the location of a marking point on a human body provided in this application; Figure 3 Example 1 of the estimated results of gluteus medius muscle strength after greater trochanter reconstruction provided in this application; Figure 4 Example 2 of the estimated results of gluteus medius muscle strength after greater trochanter reconstruction provided in this application; Figure 5 Example 3 of the estimated results of gluteus medius muscle strength after greater trochanter reconstruction provided in this application; Figure 6 A schematic diagram of the structure of a device for predicting the reconstruction position of the greater trochanter of the femur in hip replacement surgery provided in an embodiment of the present application; Figure 7 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0026] To make the purpose, technical scheme and advantages of the embodiments of the present application clearer, the technical scheme in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all of the embodiments. The components of the embodiments of the present application usually described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the application claimed for protection, but merely represents the selected embodiments of the present application. Based on the embodiments of the present application, each other embodiment obtained by those skilled in the art without making creative work belongs to the scope of protection of the present application.

[0027] Developmental Dysplasia of the Hip (DDH) refers to a type of disease in which the hip joint is abnormal during development, resulting in changes in the structure and function of the pelvis, hip joint, and lower limb bones. The hip joint of DDH patients is usually unstable, the acetabulum is dysplastic, and the femoral head cannot be stably embedded in the acetabulum, resulting in problems such as hip dislocation or subluxation. DDH patients are often accompanied by hip pain, limited mobility, and abnormal gait.

[0028] Total hip arthroplasty (THA) is currently the only effective way to treat DDH. With the continuous advancement of artificial joint technology, hip replacement can effectively relieve patients' pain, restore joint function, and significantly improve patients' quality of life. However, due to the skeletal malformation and severe anatomical variation of DDH patients, joint replacement surgery is more difficult than ordinary surgery and places higher demands on surgeons. However, there is no unified conclusion on the choice of reconstruction position for the greater trochanter reconstruction of DDH patients during hip replacement surgery. Among them, the positions of greater trochanter reconstruction in clinical anatomical position reconstruction and high position reconstruction have their own advantages and disadvantages. Which reconstruction method can maximize the restoration of gluteus medius muscle strength around the hip joint is a key issue for clinicians. The gluteus medius is the most important muscle to maintain the balance of normal walking in the human body. If the gluteus medius muscle strength is insufficient after joint replacement in DDH patients, pelvic imbalance will occur and lead to lower limb lameness and limping gait. Therefore, it is very important to restore the gluteus medius muscle strength as much as possible after hip replacement for the effect of surgery.

[0029] Currently, muscle strength assessment methods are divided into invasive and non-invasive measurements. Non-invasive measurements include: calculating the force arm measured on a two-dimensional image of the hip joint, or indirectly judging through the clinical "Trendelenburg test", or indirectly assessing muscle contraction based on surface electromyographic signal examinations.

[0030] The above methods have different limitations. First, invasive measurement of muscle strength directly causes additional trauma to patients and increases the risk of local infection, which can easily lead to failure of joint replacement surgery. Secondly, the three non-invasive measurement methods all measure or evaluate the current muscle strength in real time. It is impossible to predict postoperative muscle strength through preoperative examinations. Therefore, it cannot be used as preoperative planning for hip replacement surgery, nor can it provide reference and prediction for the effect of postoperative muscle strength recovery. Third, the above three methods cannot accurately calculate the gluteus medius muscle strength of DDH patients before and after hip replacement surgery.

[0031] Among the three non-invasive measurement methods, (1) when the force arm measured on the two-dimensional image of the hip joint is substituted into the calculation formula, there are unavoidable measurement errors in manual measurement, resulting in inaccurate muscle strength assessment. At the same time, due to the limitations of the derivation of the formula, only the ratio of the muscle strength on both sides can be obtained, and the muscle strength value cannot be directly calculated. (2) The "Trendelenburg test" can only indirectly estimate the gluteus medius muscle strength, and there are too many factors that affect the test results, and it is impossible to judge the degree of correlation between the gluteus medius muscle state and the results observed in the test. (3) Surface electromyography signal examination, due to the close arrangement and overlapping of muscle structures, usually cannot obtain the muscle strength of a single muscle; and there are errors in the electromyography signal conversion process, and the electrical signal can only indirectly reflect the activity state of the muscle; more importantly, electromyography does not comprehensively consider the influence of factors such as joint angle and movement rate on muscle strength prediction during human movement, and the reference value of the results is still defective.

[0032] Therefore, these methods are difficult to determine the optimal gluteus medius muscle strength and the precise position of greater trochanter reconstruction under the optimal muscle strength, which increases the difficulty of surgical planning for preoperative prosthesis placement.

[0033] Based on this, an embodiment of the present application provides a method for predicting the reconstruction position of the greater trochanter of the femur during hip replacement surgery. Through personalized simulation and calculation, the reconstruction position of the greater trochanter of the femur when the gluteus medius muscle strength is optimal is accurately determined, thereby effectively solving the problems of inconsistent selection of the reconstruction position of the greater trochanter in traditional methods, thereby improving the effect of hip replacement surgery and the service life of artificial joints.

[0034] See also Figure 1 , Figure 1 This is a flow chart of a method for predicting the reconstruction position of the greater trochanter of the femur during hip replacement surgery provided in an embodiment of the present application. Figure 1 As shown in , the prediction method provided in the embodiment of the present application includes: S101, obtaining target spatial coordinate data of a patient, target plantar pressure data of the patient, and original medical images of a designated limb region of the patient.

[0035] S102: Perform three-dimensional reconstruction processing according to the original medical image to determine an initial personalized three-dimensional skeletal model of the patient.

[0036] S103: Perform personalized scaling processing on the general bone and muscle model using the static coordinate data of the patient to obtain a personalized bone and muscle model of the patient.

[0037] S104, integrating the initial personalized three-dimensional bone model with each prosthesis model designed for hip replacement to achieve different greater trochanter reconstruction positions, and determining at least one postoperative simulated bone model of the patient.

[0038] S105. For each postoperative simulated bone model, use the postoperative simulated bone model to perform bone replacement processing on the corresponding bone area in the personalized bone and muscle model to obtain at least one candidate postoperative simulated bone and muscle model of the patient.

[0039] S106. Identify whether the patient is a patient undergoing unilateral hip replacement.

[0040] S107: If yes, obtain an electromyographic measurement signal at the gluteus medius muscle on the opposite side of the patient, and determine muscle activation degree data according to the electromyographic measurement signal.

[0041] S108. Calculate the gluteus medius muscle strength on the surgical side according to the target spatial coordinate data, target plantar pressure data, and muscle activation degree data, respectively, in combination with each candidate postoperative simulated bone and muscle model, to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model, and calculate the gluteus medius muscle strength on the contralateral side in combination with the personalized bone and muscle model, to obtain the standard gluteus medius muscle strength of the patient. S109. Predict the position of the greater trochanter reconstruction during hip arthroplasty based on all estimated gluteus medius muscle strength and standard gluteus medius muscle strength.

[0042] Regarding step S101, in this step, the target space data includes static coordinate data and dynamic coordinate data.

[0043] The designated limb area includes at least the hip joint; for example, the designated limb area may be the lower limb area, the area below the waist, the area below the chest, or the whole body area. The specific limb range can be adaptively selected according to actual conditions and is not limited here. Among them, this solution is aimed at hip replacement surgery, so the designated limb area of ​​this solution can be the area including the lower limbs and pelvis.

[0044] The target space coordinate data can be obtained through a motion capture system, that is, static coordinate data and dynamic coordinate data are obtained through a motion capture system. In addition, static coordinate data and dynamic coordinate data can also be obtained in other ways. For example, an optical or infrared motion capture system is used to record the position of the patient's bones and joints in a static state to obtain static coordinate data. The motion trajectory of the patient during walking or specified actions is captured by a multi-camera system and marker points to obtain dynamic coordinate data.

[0045] The target plantar pressure data may be collected by a pressure sensor, and the original medical image may be a CT image.

[0046] Before executing step S101, a motion capture system (VICON system software) may be pre-built, a three-dimensional force plate (pressure sensor) may be laid, and multiple maker points (marker points) may be pasted at designated limb areas (such as the pelvis and lower limbs) of the DDH patient.

[0047] For examples, see Figure 2 , Figure 2 A schematic diagram of the location of a marking point on a human body provided in this application, such as Figure 2 As shown, during the model simulation of hip replacement, the marker points are pasted in the lower limbs and pelvic area.

[0048] Continuing with step S101, before obtaining the target spatial coordinate data and target plantar pressure data of the patient, the prediction method further includes: S1011, obtaining initial spatial coordinate data of the patient, and obtaining initial plantar pressure data of the patient.

[0049] S1012: Integrate and store the initial spatial coordinate data and the initial plantar pressure data in a predetermined format to obtain target measurement data.

[0050] S1013: Visualize and analyze the target measurement data to obtain spatial coordinate verification data and plantar pressure verification data.

[0051] S1014: Use the spatial coordinate verification data to perform consistency verification with the initial spatial coordinate data, and use the plantar pressure verification data to perform consistency verification with the initial plantar pressure data.

[0052] S1015: If the verification results of the two are consistent, the initial spatial coordinate data is determined as the target spatial coordinate data, and the initial plantar pressure data is determined as the target plantar pressure data.

[0053] It should be noted that, in steps S1011-S1015, the storage format of each data can be determined adaptably and is not limited here.

[0054] The storage format of the target space coordinate data may be .trc, and the storage format of the target plantar pressure data may be .mot.

[0055] Regarding step S102, this step may include: denoising and segmenting the original medical image (such as CT) to extract the region of interest (ROI) of the bone structure. Then, an image segmentation algorithm (such as U-Net) is used to extract the bone boundary, and the two-dimensional image data is reconstructed into a three-dimensional model through the Marching Cubes algorithm. And ensure that the model is consistent with the patient's anatomical features (adjust the geometric proportion and resolution) to obtain the initial personalized three-dimensional bone model of the patient.

[0056] With respect to step S103, this step includes: introducing a standard bone and muscle model (such as an OpenSim model) as a basic framework; calculating a personalized scaling ratio based on the patient's static coordinate data; and then adjusting the geometric shape and anatomical position of the bones and muscles according to the calculated personalized scaling ratio to ensure that the muscle start and end positions are consistent with the patient's actual structure. After the adjustment is completed, a personalized bone and muscle model of the patient is obtained.

[0057] In one embodiment provided in the present application, the method of performing personalized scaling processing on the general bone and muscle model using the static coordinate data of the patient to obtain the personalized bone and muscle model of the patient includes: S1031. Determine the marking position of the marking point pasted on the patient's limb according to the static coordinate data.

[0058] S1032: Use the determined marker positions to connect with the universal bone and muscle model to determine the patient's true anatomical parameters.

[0059] S1033. Determine the scaling ratio of each bone segment in the universal bone-muscle model according to the actual anatomical parameters of the patient.

[0060] S1034, scaling the general bone and muscle model according to the scaling ratio of each bone segment to determine the personalized bone and muscle model of the patient.

[0061] With respect to step S1031, the static coordinate data is analyzed to determine the coordinate point (marking position) of each marking point in the same coordinate system.

[0062] For step S1032, the joint positions corresponding to the patient are marked in the universal musculoskeletal model, the coordinates of the patient's marked points are aligned with the marked points of the universal model, and the offset between each pair of marked points is calculated. Then, the patient's bone length, joint spacing and other anatomical parameters are determined based on the distance and angle changes between the marked points.

[0063] Regarding step S1033, in this step, the scaling factor (scaling ratio) of each bone segment in the bone-muscle model is calculated according to the real anatomical parameters of the patient (such as joint spacing and bone length).

[0064] For step S1034, each bone segment is linearly transformed according to the calculated scaling ratio, and the starting and ending points and path points of the muscle are recalculated based on the adjusted bones, and the mechanical parameters of the muscle (such as the maximum contraction length) are adjusted to obtain a personalized bone-muscle model of the patient.

[0065] With respect to step S104, different post-operative simulated bone models have different reconstruction positions of the greater trochanter of the femur.

[0066] In this step, multiple prosthesis models are imported to simulate different greater trochanter reconstruction positions. Then, for each prosthesis model, the prosthesis model is virtually implanted with the personalized three-dimensional bone model to ensure geometric alignment and precise docking of the contact area; after the implantation is completed, the postoperative simulation bone model of different greater trochanter reconstruction positions is obtained.

[0067] The number of the postoperative simulated bone models is the same as the number of the prosthesis models.

[0068] For example, the construction of the postoperative simulated bone model can be achieved through the cooperation of multiple software. For example: the personalized bone and muscle model of the patient is determined by Mimics three-dimensional reconstruction software, and multiple prosthesis models are constructed by SolidWorks; then the personalized bone and muscle model is imported into SolidWorks, and integrated with each prosthesis model respectively, and the model origin coordinates and the position of the model center of mass are adjusted during integration to make it consistent with the normal biomechanical structure position of the human body, and finally the postoperative simulated bone model after each prosthesis model is integrated is obtained.

[0069] With respect to step S105 , the reconstruction positions of the greater trochanter of the femur in different candidate postoperative simulated bone and muscle models are different.

[0070] In this step, for each postoperative simulated bone model, the target bone region including the reconstructed greater trochanter of the femur in the postoperative simulated bone model is used to replace the corresponding bone region in the personalized bone-muscle model. Then, following the continuity of the bone-muscle connection region, the muscle attachment point is adjusted to adapt to the new bone structure, thereby obtaining a postoperative simulated bone-muscle model.

[0071] For example, the determination of the postoperative simulated bone and muscle model can be completed by the cooperation of SolidWorks software and OpenSim software.

[0072] For example, the postoperative simulation bone model in SolidWorks software is imported into OpenSim software, and bone replacement processing is performed with the personalized bone and muscle model in OpenSim software.

[0073] For step S106, determine whether the patient is a patient undergoing unilateral hip replacement (performing left-side surgery or right-side surgery) based on the patient's basic information (such as case information or surgical plan information, etc.). If yes, execute step S107, otherwise execute step S201.

[0074] Regarding step S107, in this step, if it is determined that the patient is a patient undergoing unilateral hip replacement, an electromyographic measurement signal at the gluteus medius muscle position on the opposite side of the patient is acquired by a surface electromyographic signal measuring device, and then the electromyographic measurement signal is processed to obtain the patient's muscle activation degree data.

[0075] Here, the contralateral side is the other side than the surgical side. For example, if the surgical side is the left side, the contralateral side is the right side, and if the surgical side is the right side, the contralateral side is the left side.

[0076] Among them, in an embodiment provided in the present application, the electromyographic measurement signal at the position of the gluteus medius muscle on the opposite side of the patient is determined by the following steps: using a surface electromyographic signal measuring device to measure the electromyographic measurement signal at the position of the gluteus medius muscle on the opposite side when the patient walks; wherein the surface electromyographic signal measuring device is arranged at the gluteus medius muscle position at the posterior and superior part of the contralateral hip joint and the posterior and inferior part of the iliac crest of the pelvis; the placement direction of the surface electromyographic signal measuring device is parallel to the direction of the muscle fibers.

[0077] In this way, the surface electromyography device is placed in the gluteus medius to ensure accurate capture of the electromyographic signal of the gluteus medius and avoid interference from other muscles; the placement direction is parallel to the muscle fibers to reduce signal distortion and improve signal accuracy and reliability; and the electromyographic signal of the contralateral gluteus medius is measured in real time while the patient is walking, providing data support for preoperative evaluation and postoperative recovery monitoring. This solution avoids invasive operations and reduces patient discomfort through surface electromyography signal collection.

[0078] Regarding step S108, in this step, for each postoperative simulated bone and muscle model, the target spatial coordinate data, target plantar pressure data and muscle activation degree data are combined with the postoperative simulated bone and muscle model to perform an estimated calculation of the gluteus medius muscle strength, and the estimated gluteus medius muscle strength of the surgical side of the patient under the postoperative simulated bone and muscle model is estimated. In this way, the gluteus medius muscle strength corresponding to different greater trochanter reconstruction positions can be estimated.

[0079] For the personalized bone muscle model, the target spatial coordinate data, the target plantar pressure data and the muscle activation degree data are combined with the personalized bone muscle model to perform an estimated calculation of the gluteus medius muscle strength to obtain the patient's standard gluteus medius muscle strength. Here, the standard gluteus medius muscle strength is the muscle strength of the normal side (contralateral side) of the patient.

[0080] For step S109, for patients undergoing unilateral hip replacement surgery, in one embodiment provided in the present application, predicting the reconstruction position of the greater trochanter of the femur in hip replacement surgery based on all estimated gluteus medius muscle strengths and standard gluteus medius muscle strengths includes: determining the muscle strength with the smallest error between all estimated gluteus medius muscle strengths and the standard gluteus medius muscle strength as the target gluteus medius muscle strength; determining the reconstruction position of the greater trochanter of the femur in hip replacement surgery based on the reconstruction position of the greater trochanter of the femur in a candidate postoperative simulated bone and muscle model corresponding to the target gluteus medius muscle strength.

[0081] Here, the greater trochanter reconstruction position in the candidate postoperative simulated bone and muscle model corresponding to the target gluteus medius muscle strength is the optimal position for greater trochanter reconstruction.

[0082] In addition, when the patient is not a patient who undergoes unilateral hip replacement surgery (i.e., a patient who undergoes bilateral hip replacement surgery), in one embodiment provided in the present application, the prediction method further includes: S201. Searching for an electromyographic measurement signal corresponding to the patient according to the patient's personal information, and determining muscle activation degree data according to the electromyographic measurement signal.

[0083] S202, calculating the gluteus medius muscle strength on the surgical side according to the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data, and combining each candidate postoperative simulated bone and muscle model, to obtain an estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model.

[0084] S203. Predict the position of greater trochanter reconstruction during hip arthroplasty based on all estimated gluteus medius muscle strength.

[0085] For step S201, the example of this step may include: searching for matching electromyographic measurement signal records in a hospital database or electromyographic signal storage system according to the patient's personal information (such as age, gender, weight, medical history, etc.). If there is no direct corresponding data, the electromyographic data of people with similar characteristics to the patient can be used for speculation. Signal processing is performed based on the electromyographic measurement signal found to determine the muscle activation degree data.

[0086] Regarding step S202, the description of S202 can refer to the description of S108, and can achieve the same technical effect, so it is not repeated here.

[0087] It should be noted that the difference between S202 and S108 is that each candidate postoperative simulated bone and muscle model in S202 can correspond to two estimated gluteus medius muscle strengths (left and right sides), while each candidate postoperative simulated bone and muscle model in S108 can correspond to only one estimated gluteus medius muscle strength.

[0088] With respect to step S203, for patients who undergo bilateral replacement surgery, when predicting the reconstruction position of the greater trochanter during hip replacement surgery based on all estimated gluteus medius muscle strengths, the optimal reconstruction position of the greater trochanter is determined based on the principles of bilateral consistency and maximum muscle strength.

[0089] With respect to steps S202 and S108, in one embodiment provided in the present application, the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data are used to calculate the gluteus medius muscle strength of the surgical side in combination with each candidate postoperative simulated bone and muscle model to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model, including: S301. For each candidate postoperative simulated bone and muscle model, a reverse analysis operation is performed on the candidate postoperative simulated bone and muscle model according to the dynamic coordinate data and the target plantar pressure data in the target spatial coordinate data to obtain the initial joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model.

[0090] S302. According to the muscle activation degree data, an error reduction algorithm is used to correct the initial joint reverse analysis data to determine the target joint reverse analysis data of the patient.

[0091] S303, based on the reverse analysis data of the target joint of the patient under the candidate postoperative simulated bone and muscle model, combined with the calculation of the muscle strength data of the gluteus medius of the patient during the movement of the candidate postoperative simulated bone and muscle model, determine the estimated gluteus medius muscle strength under the candidate postoperative simulated bone and muscle model.

[0092] For step S301, in one embodiment provided in the present application, the initial joint reverse analysis data includes initial joint inverse kinematics data and initial joint inverse dynamics data, and for each candidate postoperative simulated bone and muscle model, a reverse analysis operation is performed on the candidate postoperative simulated bone and muscle model according to the dynamic coordinate data and the target plantar pressure data in the target spatial coordinate data to obtain the initial joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model, including: S3011. Perform inverse kinematics calculations based on the dynamic coordinate data in the target space coordinate data and in combination with the candidate postoperative simulated bone and muscle model to obtain initial joint inverse kinematics data of the patient under the candidate postoperative simulated bone and muscle model.

[0093] S3012. Perform inverse dynamics calculations based on the target plantar pressure data and the initial joint inverse kinematics data, and in combination with the candidate postoperative simulated bone and muscle model, to obtain the initial joint inverse kinematics data of the patient under the candidate postoperative simulated bone and muscle model.

[0094] For steps S3011 and S3012, by way of example, inverse kinematics calculations and inverse dynamics calculations may be performed using OpenSim software.

[0095] Joint inverse kinematics data mainly includes information such as the position and angle of the joint, while joint inverse dynamics data mainly focuses on the forces and moments exerted on the joints and their surrounding tissues (such as muscles, ligaments, etc.) during movement.

[0096] Regarding step S302, in this step, the initial joint reverse analysis data is optimized and corrected using an error reduction algorithm (such as least squares method, Kalman filter, etc.) according to the muscle activation degree data. The algorithm minimizes the difference between the estimated data and the actual data through iterative adjustment, and the corrected data is the target joint reverse analysis data.

[0097] For step S303, the target joint reverse analysis data, the patient's muscle activation degree and the candidate postoperative simulated bone and muscle model are combined, and a comprehensive calculation is performed through the kinematic and dynamic models to obtain the estimated muscle strength of the gluteus medius under different models.

[0098] In addition, see the examples Figure 3 , Figure 4 , Figure 5 , Figure 3 Example 1 of the estimated results of gluteus medius muscle strength after greater trochanter reconstruction provided in this application; Figure 4 Example 2 of the estimated results of gluteus medius muscle strength after greater trochanter reconstruction provided in this application; Figure 5 This application provides an example 3 of the estimated results of gluteus medius muscle strength after greater trochanter reconstruction. Figure 3 As shown, Figure 3 It is actually the result of the change in gluteus medius muscle strength when the greater trochanter does not move. Figure 4 It is actually the result of the change in gluteus medius muscle strength when the greater trochanter moves up 10 mm. Figure 5 It is actually the result of the change in gluteus medius muscle strength when the greater trochanter is moved up by 20 mm. Thus, the above-mentioned results can be used to determine the optimal reconstruction position of the greater trochanter according to the preset determination rules.

[0099] In this way, the present application establishes a personalized bone and muscle model through the patient's static and dynamic spatial coordinate data, target plantar pressure data, and electromyographic measurement signals. Combined with the three-dimensional bone model and different prosthesis designs, a candidate postoperative simulation model can be generated for each patient's specific situation to ensure the pertinence and personalization of postoperative functional recovery. And through multimodal data fusion, the estimated muscle strength of the gluteus medius on the surgical side under the candidate postoperative model is accurately calculated, combined with the standardized calculation of the gluteus medius muscle strength on the contralateral side, and the effect of the reconstruction position on postoperative muscle function is compared and analyzed. This method helps to optimize the reconstruction position of the greater trochanter of the femur, so that the patient's postoperative muscle balance and functional recovery can reach the best state. In addition, this scheme proposes to integrate the patient's initial personalized three-dimensional bone model with a variety of prosthesis models, verify the effects of different reconstruction positions through simulation, avoid the limitations of selecting prostheses and reconstruction positions based solely on intraoperative experience, and improve the predictability of postoperative recovery.

[0100] In summary, this method innovatively combines multimodal data and personalized modeling, providing a new design, evaluation and optimization method for hip replacement, which is of great significance for improving clinical surgical outcomes.

[0101] Based on the same inventive concept, a prediction device corresponding to the prediction method is also provided in the embodiment of the present application. Since the principle of solving the problem by the device in the embodiment of the present application is similar to the above-mentioned prediction method in the embodiment of the present application, the implementation of the device can refer to the implementation of the method, and the repeated parts will not be repeated.

[0102] See also Figure 6 , Figure 6 This is a schematic diagram of the structure of a device for predicting the reconstruction position of the greater trochanter of the femur during hip replacement surgery provided in an embodiment of the present application. Figure 6 As shown in , the prediction device 600 includes: A first acquisition module 610 is used to acquire the patient's target spatial coordinate data, the patient's target plantar pressure data, and the original medical image of the patient's designated limb area; wherein the designated limb area includes a hip joint, and the target spatial data includes static coordinate data and dynamic coordinate data; A reconstruction module 620 is used to perform a three-dimensional reconstruction process based on the original medical image to determine an initial personalized three-dimensional skeletal model of the patient; A scaling module 630 is used to perform personalized scaling processing on the general bone and muscle model using the static coordinate data of the patient to obtain a personalized bone and muscle model of the patient; The integration module 640 is used to perform model integration processing on the initial personalized three-dimensional bone model and each prosthesis model designed for hip replacement to achieve different greater trochanter reconstruction positions, so as to determine at least one postoperative simulated bone model of the patient; wherein different postoperative simulated bone models have different femoral greater trochanter reconstruction positions; A replacement module 650 is used for performing bone replacement processing on the corresponding bone area in the personalized bone and muscle model using the postoperative simulated bone model for each postoperative simulated bone model, so as to obtain at least one candidate postoperative simulated bone and muscle model of the patient; wherein the reconstruction position of the greater trochanter of the femur in different candidate postoperative simulated bone and muscle models is different; An identification module 660 is used to identify whether the patient is a patient undergoing unilateral hip replacement surgery; The second acquisition module 670 is used for acquiring the electromyographic measurement signal at the gluteus medius muscle of the contralateral side of the patient if the patient is a patient undergoing unilateral hip replacement, and determining the muscle activation degree data according to the electromyographic measurement signal; The calculation module 680 is used to calculate the gluteus medius muscle strength of the surgical side according to the target spatial coordinate data, the target plantar pressure data and the muscle activation degree data, and respectively in combination with each candidate postoperative simulated bone muscle model, to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone muscle model, and to calculate the gluteus medius muscle strength of the contralateral side in combination with the personalized bone muscle model, to obtain the standard gluteus medius muscle strength of the patient; The prediction module 690 is used to predict the reconstruction position of the greater trochanter in hip replacement surgery based on all estimated gluteus medius muscle strengths and standard gluteus medius muscle strengths.

[0103] Optionally, the prediction device 600 is further used for: If the patient is not a patient who has undergone unilateral hip replacement, searching for the electromyographic measurement signal corresponding to the patient according to the patient's personal information, and determining muscle activation degree data according to the electromyographic measurement signal; According to the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data, and in combination with each candidate postoperative simulated bone and muscle model, the gluteus medius muscle strength of the surgical side is calculated to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model; Prediction of greater trochanter reconstruction position during hip arthroplasty based on all estimated gluteus medius muscle strength.

[0104] Optionally, the second acquisition module 670 is further configured to determine an electromyographic measurement signal at the gluteus medius muscle position on the opposite side of the patient through the following steps: A surface electromyography signal measuring device is used to measure the electromyography signal at the gluteus medius muscle position on the opposite side when the patient walks; wherein the surface electromyography signal measuring device is arranged at the gluteus medius muscle position at the posterior and superior part of the contralateral hip joint and the posterior and inferior part of the iliac crest of the pelvis; and the placement direction of the surface electromyography signal measuring device is parallel to the direction of the muscle fibers.

[0105] Optionally, when the scaling module 630 is used to perform personalized scaling processing on the general bone and muscle model using the static coordinate data of the patient to obtain the personalized bone and muscle model of the patient, the scaling module 630 is used to: Determining the marking position of the marking point attached to the patient's limb according to the static coordinate data; Using the determined marker positions to interface with the universal musculoskeletal model to determine the patient's true anatomical parameters; Determining the scaling ratio of each bone segment in the universal bone and muscle model according to the real anatomical parameters of the patient; The universal bone and muscle model is scaled according to the scaling ratio of each bone segment to determine the personalized bone and muscle model of the patient.

[0106] Optionally, when the calculation module 680 is used to calculate the gluteus medius muscle strength on the surgical side according to the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data, and respectively in combination with each candidate postoperative simulated bone and muscle model, to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model, the calculation module 680 is used to: For each candidate postoperative simulated bone and muscle model, a reverse analysis operation is performed on the candidate postoperative simulated bone and muscle model according to the dynamic coordinate data and the target plantar pressure data in the target spatial coordinate data to obtain the initial joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model; According to the muscle activation degree data, the initial joint reverse analysis data is corrected using an error reduction algorithm to determine the target joint reverse analysis data of the patient; Based on the target joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model, combined with the calculation of the gluteus medius muscle strength data of the patient during movement using the candidate postoperative simulated bone and muscle model, the estimated gluteus medius muscle strength under the candidate postoperative simulated bone and muscle model is determined.

[0107] Optionally, the initial joint reverse analysis data includes initial joint inverse kinematics data and initial joint inverse dynamics data. When the calculation module 680 is used to perform a reverse analysis operation on each candidate postoperative simulated bone and muscle model according to the dynamic coordinate data and the target plantar pressure data in the target spatial coordinate data to obtain the initial joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model, the calculation module 680 is used to: According to the dynamic coordinate data in the target space coordinate data, inverse kinematics calculation is performed in combination with the candidate postoperative simulated bone and muscle model to obtain the initial joint inverse kinematics data of the patient under the candidate postoperative simulated bone and muscle model; According to the target plantar pressure data and the initial joint inverse kinematics data, inverse dynamics calculation is performed in combination with the candidate postoperative simulated bone and muscle model to obtain the initial joint inverse dynamics data of the patient under the candidate postoperative simulated bone and muscle model.

[0108] Optionally, when the prediction module 690 is used to predict the reconstruction position of the greater trochanter in hip replacement surgery based on all estimated gluteus medius muscle strengths and standard gluteus medius muscle strengths, the prediction module 690 is used to: The muscle strength with the smallest error between the estimated gluteus medius muscle strength and the standard gluteus medius muscle strength is determined as the target gluteus medius muscle strength; The reconstruction position of the greater trochanter of the femur in hip replacement surgery is determined according to the reconstruction position of the greater trochanter of the femur in the candidate postoperative simulated bone and muscle model corresponding to the target gluteus medius muscle strength.

[0109] See also Figure 7 , Figure 7 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 7 As shown in , the electronic device 700 includes a processor 710 , a memory 720 and a bus 730 .

[0110] The memory 720 stores machine-readable instructions executable by the processor 710. When the electronic device 700 is running, the processor 710 communicates with the memory 720 via the bus 730. When the machine-readable instructions are executed by the processor 710, the above-mentioned Figures 1 to 5 The specific implementation of the steps in the method embodiment shown can be found in the method embodiment, and will not be repeated here.

[0111] The present application also provides a computer-readable storage medium on which a computer program is stored. When the computer program is executed by a processor, the computer program can execute the above-mentioned Figures 1 to 5 The specific implementation of the steps in the method embodiment shown can be found in the method embodiment, and will not be repeated here.

[0112] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0113] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0114] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0115] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0116] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium that is executable by a processor. Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0117] Finally, it should be noted that the above-described embodiments are only specific implementation methods of the present application, which are used to illustrate the technical solutions of the present application, rather than to limit them. The protection scope of the present application is not limited thereto. Although the present application is described in detail with reference to the above-mentioned embodiments, ordinary technicians in the field should understand that any technician familiar with the technical field can still modify the technical solutions recorded in the above-mentioned embodiments within the technical scope disclosed in the present application, or can easily think of changes, or make equivalent replacements for some of the technical features therein; and these modifications, changes or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application. Therefore, the protection scope of the present application shall be based on the protection scope of the claims.

Claims

1. A method for predicting the reconstruction position of the greater trochanter of the femur during hip replacement surgery, characterized in that: The prediction method comprises: Acquire the patient's target spatial coordinate data, the patient's target plantar pressure data, and the original medical image of the patient's designated limb area; wherein the designated limb area includes a hip joint, and the target spatial coordinate data includes static coordinate data and dynamic coordinate data; Performing three-dimensional reconstruction processing according to the original medical image to determine an initial personalized three-dimensional skeletal model of the patient; Performing personalized scaling processing on the general bone and muscle model using the static coordinate data of the patient to obtain a personalized bone and muscle model of the patient; The initial personalized three-dimensional bone model is separately integrated with each prosthesis model designed for hip replacement to achieve different greater trochanter reconstruction positions, to determine at least one postoperative simulated bone model of the patient; wherein different postoperative simulated bone models have different femoral greater trochanter reconstruction positions; For each postoperative simulated bone model, using the postoperative simulated bone model to perform bone replacement processing on the corresponding bone area in the personalized bone and muscle model, to obtain at least one candidate postoperative simulated bone and muscle model of the patient; wherein the reconstruction position of the greater trochanter of the femur in different candidate postoperative simulated bone and muscle models is different; identifying whether the patient is a patient undergoing unilateral hip replacement; If yes, obtaining an electromyographic measurement signal at the gluteus medius muscle position on the opposite side of the patient, and determining muscle activation degree data according to the electromyographic measurement signal; According to the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data, the gluteus medius muscle strength on the surgical side is calculated in combination with each candidate postoperative simulated bone muscle model to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone muscle model, and the gluteus medius muscle strength on the contralateral side is calculated in combination with the personalized bone muscle model to obtain the standard gluteus medius muscle strength of the patient; Prediction of greater trochanteric reconstruction position during hip arthroplasty based on total estimated gluteus medius strength and standard gluteus medius strength.

2. The prediction method according to claim 1, characterized in that: If the patient is not a patient undergoing unilateral hip replacement, the prediction method further comprises: According to the personal information of the patient, searching for the electromyographic measurement signal corresponding to the patient, and determining muscle activation degree data according to the electromyographic measurement signal; According to the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data, and in combination with each candidate postoperative simulated bone and muscle model, the gluteus medius muscle strength of the surgical side is calculated to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model; Prediction of greater trochanter reconstruction position during hip arthroplasty based on all estimated gluteus medius muscle strength.

3. The prediction method according to claim 1, characterized in that: The electromyographic measurement signal at the gluteus medius muscle position on the contralateral side of the patient is determined by the following steps: A surface electromyography signal measuring device is used to measure the electromyography signal at the gluteus medius muscle position on the opposite side when the patient walks; wherein the surface electromyography signal measuring device is arranged at the gluteus medius muscle position at the posterior and superior part of the contralateral hip joint and the posterior and inferior part of the iliac crest of the pelvis; and the placement direction of the surface electromyography signal measuring device is parallel to the direction of the muscle fibers.

4. The prediction method according to claim 1, characterized in that: The method of performing personalized scaling processing on the general bone and muscle model using the static coordinate data of the patient to obtain the personalized bone and muscle model of the patient includes: Determining the marking position of the marking point attached to the patient's limb according to the static coordinate data; Using the determined marker positions to interface with the universal musculoskeletal model to determine the patient's true anatomical parameters; Determining the scaling ratio of each bone segment in the universal bone and muscle model according to the real anatomical parameters of the patient; The universal bone and muscle model is scaled according to the scaling ratio of each bone segment to determine the personalized bone and muscle model of the patient.

5. The prediction method according to claim 2, characterized in that: The target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data are used to calculate the gluteus medius muscle strength of the surgical side in combination with each candidate postoperative simulated bone and muscle model to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model, including: For each candidate postoperative simulated bone and muscle model, a reverse analysis operation is performed on the candidate postoperative simulated bone and muscle model according to the dynamic coordinate data and the target plantar pressure data in the target spatial coordinate data to obtain the initial joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model; According to the muscle activation degree data, the initial joint reverse analysis data is corrected using an error reduction algorithm to determine the target joint reverse analysis data of the patient; Based on the target joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model, combined with the calculation of the gluteus medius muscle strength data of the patient during movement using the candidate postoperative simulated bone and muscle model, the estimated gluteus medius muscle strength under the candidate postoperative simulated bone and muscle model is determined.

6. The prediction method according to claim 5, characterized in that: The initial joint reverse analysis data includes initial joint reverse kinematics data and initial joint reverse dynamics data. For each candidate postoperative simulated bone and muscle model, a reverse analysis operation is performed on the candidate postoperative simulated bone and muscle model according to the dynamic coordinate data in the target spatial coordinate data and the target plantar pressure data to obtain the initial joint reverse analysis data of the patient under the candidate postoperative simulated bone and muscle model, including: According to the dynamic coordinate data in the target space coordinate data, inverse kinematics calculation is performed in combination with the candidate postoperative simulated bone and muscle model to obtain the initial joint inverse kinematics data of the patient under the candidate postoperative simulated bone and muscle model; According to the target plantar pressure data and the initial joint inverse kinematics data, inverse dynamics calculation is performed in combination with the candidate postoperative simulated bone and muscle model to obtain the initial joint inverse dynamics data of the patient under the candidate postoperative simulated bone and muscle model.

7. The prediction method according to claim 1, characterized in that: The above method predicts the position of the greater trochanter reconstruction in hip arthroplasty based on all estimated gluteus medius muscle strength and standard gluteus medius muscle strength, including: The muscle strength with the smallest error between the estimated gluteus medius muscle strength and the standard gluteus medius muscle strength is determined as the target gluteus medius muscle strength; The reconstruction position of the greater trochanter of the femur in hip replacement surgery is determined according to the reconstruction position of the greater trochanter of the femur in the candidate postoperative simulated bone and muscle model corresponding to the target gluteus medius muscle strength.

8. A device for predicting the reconstruction position of the greater trochanter of the femur during hip replacement surgery, characterized in that: The prediction device comprises: A first acquisition module is used to acquire the patient's target spatial coordinate data, the patient's target plantar pressure data, and the original medical image of the patient's designated limb area; wherein the designated limb area includes a hip joint, and the target spatial coordinate data includes static coordinate data and dynamic coordinate data; A reconstruction module, used for performing three-dimensional reconstruction processing according to the original medical image to determine an initial personalized three-dimensional bone model of the patient; A scaling module, used for performing personalized scaling processing on the general bone and muscle model using the static coordinate data of the patient to obtain a personalized bone and muscle model of the patient; An integration module is used to perform model integration processing on the initial personalized three-dimensional bone model and each prosthesis model designed for hip replacement to achieve different greater trochanter reconstruction positions, so as to determine at least one postoperative simulated bone model of the patient; wherein different postoperative simulated bone models have different femoral greater trochanter reconstruction positions; A replacement module is used for performing bone replacement processing on the corresponding bone area in the personalized bone and muscle model using the postoperative simulated bone model for each postoperative simulated bone model, so as to obtain at least one candidate postoperative simulated bone and muscle model of the patient; wherein the reconstruction position of the greater trochanter of the femur in different candidate postoperative simulated bone and muscle models is different; An identification module, used for identifying whether the patient is a patient undergoing unilateral hip replacement surgery; a second acquisition module, for acquiring an electromyographic measurement signal at a gluteus medius muscle position on the opposite side of the patient if the patient is a patient undergoing unilateral hip replacement surgery, and determining muscle activation degree data according to the electromyographic measurement signal; a calculation module, for calculating the gluteus medius muscle strength of the surgical side according to the target spatial coordinate data, the target plantar pressure data, and the muscle activation degree data, respectively in combination with each candidate postoperative simulated bone and muscle model, to obtain the estimated gluteus medius muscle strength under each candidate postoperative simulated bone and muscle model, and calculating the gluteus medius muscle strength of the contralateral side in combination with the personalized bone and muscle model, to obtain the standard gluteus medius muscle strength of the patient; Prediction module for predicting greater trochanter reconstruction position in hip arthroplasty based on all estimated gluteus medius muscle strength and standard gluteus medius muscle strength.

9. An electronic device, characterized in that: include: A processor, a memory and a bus, wherein the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor and the memory communicate through the bus, and the machine-readable instructions are executed by the processor to execute the steps of the prediction method as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the prediction method according to any one of claims 1 to 7 are executed.

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