Virtual skeleton simulation movement system

Abstract

The invention relates to the technical field of skeleton simulation movement, in particular to a virtual skeleton simulation movement system. According to the method, the humerus motion data is dynamically collected, the space around the shoulder joint is scientifically divided into eight areas, and the parameter weights are dynamically calculated based on the positions of the elbow joint in different space areas; when the elbow joint is located in the outer front space, the system distributes abduction / anteflexion parameter influence weights according to the horizontal plane angle proportion; in the outer rear space, the abduction parameters are dominant; in the inner front space, the forward bending parameter weight is the maximum; a specific limit value is applied to the inner rear space; the motion performance of the virtual skeleton is more in line with the biomechanical characteristics of the human body, and the simulation effect of animation production and medical education is remarkably improved.

Description

Technical Field

[0001] This application relates to the technical field of skeletal simulation motion, and in particular to a virtual skeletal simulation motion system. Background Technology

[0002] With the rapid development of computer graphics and virtual simulation technology, the accurate simulation of human skeletal movement has become an important research direction in fields such as animation production, medical education, game development, and virtual reality. The shoulder joint area, in particular, is one of the most complex joint systems in the human body, involving the coordinated movement of the sternoclavicular, acromioclavicular, and glenohumeral joints. Accurately simulating its biomechanical characteristics is crucial for achieving highly realistic human motion simulation.

[0003] Currently, virtual skeleton simulation systems mainly employ two methods: one is based on motion capture data to directly drive the skeleton, which calculates joint angles and applies them to the virtual skeleton by collecting changes in the positions of marker points on the real human body; the other is based on a simplified mechanical model, which simplifies the human skeleton system into a linkage system with specific degrees of freedom and motion constraints, and achieves skeleton linkage by setting kinematic rules, thereby reducing computational complexity.

[0004] In existing virtual skeleton simulation systems, the movements of the scapula and clavicle are often oversimplified, failing to accurately reflect their complex coupling relationship with the humerus. Furthermore, the lack of precise simulation of the specific movement patterns of the sternoclavicular and acromioclavicular joints at different stages of movement results in unnatural virtual skeleton movements that differ significantly from real human motion. Further improvements are needed to address this issue. Summary of the Invention

[0005] To address the issues of existing scapular and clavicle movements failing to accurately reflect the coupling relationship with humeral movements and the unnatural nature of virtual skeleton movements, this application provides a virtual skeleton simulation motion system, employing the following technical solution: A virtual skeletal simulation motion system, characterized in that it comprises: The dynamic input module is used to collect real-time motion data of the humerus and establish a reference coordinate system to obtain real-time motion input data and reference coordinate system data. The motion state determination module determines the motion parameters of the scapula and clavicle, as well as the spatial position information of the elbow movement point, based on the real-time motion input data and reference coordinate system data. The spatial region comprehensive determination module divides the space around the shoulder joint into eight regions based on the spatial location information and skeletal motion parameters, calculates the influence weight of each skeletal parameter, and limits the required values ​​of each skeletal parameter. The parameter synthesis module generates synthetic control parameters for the sternoclavicular and acromioclavicular joints based on the skeletal motion parameters and influence weights. The automated feedback output module transmits control data to the virtual joint group according to the synthesized control parameters, generates skeletal linkage control data, and realizes the coupling linkage of the sternoclavicular joint and acromioclavicular joint due to the movement of the humerus. The virtual skeleton display module displays the movement of the scapula-clavicle-humerus based on the skeleton linkage control data.

[0006] By adopting the above technical solution, this application scientifically divides the space around the shoulder joint into eight regions by dynamically collecting humeral motion data, and dynamically calculates parameter weights based on the position of the elbow joint in different spatial regions. When the elbow joint is in the anterior space, the system allocates the influence weights of abduction / flexion parameters according to the horizontal plane angle ratio. In the posterior space, abduction parameters dominate. In the anterior space, flexion parameters have the largest weight. In the posterior space, specific limit values ​​are applied. This makes the motion performance of the virtual skeleton more consistent with the biomechanical characteristics of the human body, and significantly improves the simulation effect of animation production and medical education.

[0007] Optionally, the dynamic input module includes: The elbow joint motion point setting unit is used to establish elbow joint motion points constrained to the virtual joint of the lower arm, and obtain motion data that moves with the lower end of the humerus. The elbow joint endpoint setting unit establishes an elbow joint endpoint associated with the elbow joint movement point through a parent constraint based on the activity data of the elbow joint movement point, thereby obtaining the corrected angle data. The reference point setting unit is used to establish abduction reference point and flexion reference point as static references. The X-axis of the abduction reference point is aligned with the elbow joint movement point, and the Y / Z translation relative to the shoulder joint point is 0. The flexion reference point is based on the positive Z-axis direction, and the X / Y translation relative to the shoulder joint point is 0, thus obtaining reference data for abduction and flexion movements. Multiple reconfiguration units are used to construct a hierarchical structural framework corresponding to the sternoclavicular-meninguinal-elbow joint positions, placing the elbow joint movement point, elbow joint terminal point, abduction reference point, and flexion reference point in appropriate hierarchical positions to ensure the spatial correspondence between dynamic input and static reference and the synchronization of the overall system.

[0008] By adopting the above technical solution, in order to solve the problem of unnatural skeletal linkage caused by the lack of accurate spatial reference in traditional systems, this application establishes a point constraint on the elbow joint movement point of the lower arm and its associated terminal point, and sets an abduction reference point and a flexion reference point as static references. Through the design of combining dynamic input and static reference, the system can accurately calculate the motion components of the humerus in different directions, providing a key basis for determining the spatial position of the shoulder joint. The multi-rearrangement unit ensures the rationality and synchronization of the hierarchical structure of the entire system, and improves the simulation accuracy and biomechanical rationality of the shoulder joint complex movement.

[0009] Optionally, the motion state determination module includes: The spatial position determination unit is used to determine the three-dimensional spatial position of the elbow relative to the shoulder joint through condition nodes, including vertical position, front-back position and inside-out position, and to obtain the spatial position determination result. The angle calculation unit calculates the abduction mapping angle between the elbow joint terminal point and the abduction reference point in the coronal projection plane and the flexion mapping angle between the elbow joint terminal point and the flexion reference point in the sagittal projection plane, based on the spatial position determination result, to obtain abduction angle data and flexion angle data. It also calculates the mapping angle between the elbow joint terminal point and the abduction and flexion reference points in the horizontal projection plane to obtain the angle data required for the abduction and flexion influence ratio. The abduction mapping feedback skeletal automation unit generates, based on the abduction mapping angle data, simulated human skeletal motion parameters of the sternoclavicular and acromioclavicular joints caused by the humerus driving the shoulder joint abduction, according to the abduction mapping angle segmentation. The flexion mapping feedback skeletal automation unit generates simulated human skeletal motion parameters for the sternoclavicular and acromioclavicular joints based on the flexion mapping angle data and according to the flexion angle segmentation. These parameters are formed by the humerus driving the shoulder joint to flex forward. The parameter output unit integrates the abduction and flexion motion parameters into motion parameters for the scapula and clavicle.

[0010] By adopting the above technical solution, this application uses a spatial position determination unit to locate the three-dimensional position of the elbow relative to the shoulder joint, and combines it with an angle calculation unit to calculate the abduction and flexion angles in the coronal and sagittal planes respectively, thereby achieving precise decomposition of the humeral motion components; through abduction mapping and flexion mapping feedback to the skeletal automation unit, the parameters of the sternoclavicular and acromioclavicular joints are dynamically adjusted according to different angle ranges, simulating the skeletal linkage law of the real human body in different movement stages; improving the accuracy of skeletal linkage in complex movement states, making the shoulder movement of the virtual character smoother and more natural.

[0011] Optionally, the abduction motion parameter mapping unit is used for: When the shoulder abduction angle is detected to be within the range of 0° to 30°, only the montelukast joint is activated to participate in overall abduction, while the sternoclavicular and acromioclavicular joints are set not to participate in the angle contribution, thus obtaining the first stage of motion control data. When the shoulder abduction angle is detected to be within the range of 30° to 90°, according to the 1:1 scapulohumeral rhythm ratio, the glenohumeral joint is set to occupy 30°, and the scapula achieves upward rotation of 30° through the coordinated movement of the sternoclavicular joint and the acromioclavicular joint, thus obtaining the second stage of motion control data; When the shoulder abduction angle is detected to be within the range of 90° to 180°, according to the 2:1 scapulohumeral rhythm ratio, the glenohumeral joint is set to occupy 60°, and the scapula achieves upward rotation of 30° through the coordinated movement of the sternoclavicular and acromioclavicular joints, thus obtaining the third stage of motion control data. Based on the current stage of the detected shoulder joint abduction mapping angle, the corresponding motion control data is selected as the abduction motion parameter output.

[0012] By adopting the above technical solution, this application divides the abduction angle into three key stages: the 0°~30° stage only activates the glenohumeral joint; the 30°~90° stage achieves a 1:1 scapuhumeral rhythm ratio; and the 90°~180° stage applies a 2:1 scapuhumeral rhythm ratio. Through the angle-segmented control strategy, the movement of the virtual skeleton conforms to the physiological characteristics of the human body. In particular, it avoids the phenomenon of the acromion pressing on the humeral head during large-angle abduction, effectively reducing the common problems of "shoulder joint collapse" or "bone penetration" in traditional simulation systems, and significantly improving the naturalness and visual realism of shoulder abduction movement.

[0013] Optionally, the forward flexion motion parameter mapping unit is used for: When the shoulder flexion angle is detected to be within the range of 0° to 45°, only the montelukast joint is activated to participate in the flexion movement, while the sternoclavicular and acromioclavicular joints are set not to participate in the angle contribution, thus obtaining the first stage control data of flexion. When the shoulder flexion angle is detected to be within the range of 45° to 90°, the acromioclavicular joint is rotated upward by 17.5°, the sternoclavicular joint is raised by 12.5°, the long axis is rotated backward by 17.5°, and the forward extension is 5° to obtain the second stage control data for flexion. When the shoulder flexion angle is detected to be within the range of 90° to 180°, the acromioclavicular joint is set to continue to rotate upward by 17.5°, the sternoclavicular joint is set to continue to rise by 12.5°, rotate backward along the long axis by 7.5°, and the direction of movement changes from extension to retraction and displacement by 20°, thus obtaining the control data for the third stage of flexion. Based on the current stage of the detected shoulder flexion angle, the corresponding motion control data is selected as the output of flexion motion parameters.

[0014] By adopting the above technical solution, this application divides the flexion process into three stages: the 0°~45° stage involves only the glenohumeral joint; the 45°~90° stage introduces the upward rotation of the acromioclavicular joint and the multi-dimensional movement of the sternoclavicular joint; the 90°~180° stage achieves a key change in the direction of movement of the sternoclavicular joint, from extension to retraction; through the angle segmentation control strategy, not only is the angular contribution of each joint movement considered, but the rotation angle and direction of movement in each stage are also accurately calculated, ensuring the natural coordinated movement of the sternoclavicular joint and the acromioclavicular joint during large-amplitude flexion; reducing the "shoulder stiffness" problem commonly seen when the forearm is raised overhead in traditional simulations, making the movement smoother and more natural.

[0015] Optionally, the spatial region comprehensive determination module includes: The spatial region division unit is used to divide the space around the shoulder joint into eight regions: anterolateral superior, anterolateral inferior, posterolateral superior, posterolateral inferior, anteromedial superior, anteromedial inferior, posteromedial superior, and posteromedial inferior, to obtain spatial region division data; The spatial region determination unit determines the current spatial region based on the spatial region division data and the translation X, Y, and Z coordinate values ​​of the elbow joint terminal point, and obtains the spatial region determination result. The weight calculation unit calculates the influence weights of the abduction parameter and the flexion parameter based on the spatial region determination result, and obtains the parameter weight data. The control strategy output unit generates corresponding spatial control strategy data based on the parameter weight data, which is then used by the parameter synthesis module.

[0016] By adopting the above technical solution, this application scientifically divides the space around the shoulder joint into eight precise regions and uses the three-dimensional coordinates of the elbow joint endpoint for spatial positioning, enabling the system to accurately determine the limb's movement space. The innovative weight calculation unit dynamically allocates the influence weights of abduction and flexion parameters based on the biomechanical characteristics of different spatial regions, allowing the skeletal linkage to adapt to the needs of different movement directions. The control strategy output unit transforms the calculation results into specific control commands, ensuring the consistency and accuracy of the system's response. This allows the virtual skeleton to maintain a natural and coordinated linkage relationship in complex movement trajectories, improving the simulation effect of oblique movements and combined actions.

[0017] Optionally, the spatial region determination unit and the weight calculation unit jointly implement the following control strategy: When the translation X of the elbow joint terminal point is less than or equal to 0 and the translation Z is greater than or equal to 0, it is determined to be the anterior lateral space. The abduction / flexion parameters are then assigned influence weights according to the proportion of the horizontal plane angle to obtain the anterior lateral space control strategy. The anterior lateral space includes the upper anterior lateral space and the lower anterior lateral space. When the translation of the elbow joint terminal point X < 0 and the translation of Z < 0, it is determined to be the lateral posterior space. Based on the characteristics of the lateral posterior space, the abduction parameter is triggered to have 100% influence control and the flexion parameter to have 0% influence control, thus obtaining the lateral posterior space control strategy. The lateral anterior space includes the posterolateral upper and posterolateral lower. When the translation of the elbow joint terminal point X>0 and the translation of Z<0, it is determined to be the inner posterior space. Based on the characteristics of the inner posterior space, the preset limit value is triggered to control the sternoclavicular joint / axillary joint, thus obtaining the inner posterior space control strategy. The outer anterior space includes the posteromedial upper and posteromedial lower. When the translation X of the elbow joint terminal point is greater than 0 and the translation Z is greater than or equal to 0, it is determined to be the medial anterior space. Based on the characteristics of the medial anterior space, the flexion parameter is triggered to have 100% influence control and the abduction parameter to have 0% influence control, thus obtaining the medial anterior space control strategy. The medial anterior space includes the anterior medial upper and anterior medial lower.

[0018] By adopting the above technical solution, this application achieves adaptive control of four key spatial regions based on spatial determination of the elbow joint endpoint coordinates: in the anterior space, abduction / flexion parameter weights are intelligently allocated according to the horizontal plane angle ratio; in the posterior space, abduction parameters are completely dominant, and parameter constraints and feedback allocation are carried out through posterior space control strategies; in the posterior space, specific preset limit values ​​are applied to avoid non-physiological movements; and in the anterior space, flexion parameters are completely dominant. This effectively solves the problem of uncoordinated skeletal linkage in traditional systems during oblique limb movements, ensuring that the shoulder movements of the virtual character remain natural and smooth in all directions, and improving the simulation accuracy of mixed motion trajectories.

[0019] Optionally, the parameter synthesis module calculates the control parameters of the sternoclavicular joint and acromioclavicular joint according to the formula: final parameter = abduction parameter × abduction weight + flexion parameter × flexion weight, to obtain comprehensive control parameter data.

[0020] By adopting the above technical solution, the weighted linear synthesis method not only considers the motion characteristics of different spatial regions, but also ensures the smoothness and continuity of parameter transition.

[0021] Optionally, the automated feedback output module includes: The error compensation unit is used to compensate the elbow joint movement point through the elbow joint end point, obtain the mapping data between the error compensation and the reference point, and return the calculated values ​​required for the forearm movement to obtain the error compensation through the corresponding position group feedback compensation value. The range of motion limiting unit, after backtracking the error compensation data, implements the proportional allocation of the upper arm virtual joint Y-axis rotation value and the range of motion limiting parameters of the upper arm virtual joint in the posterior space, and obtains the parameters required for the sternoclavicular and acromioclavicular joints in the posterior space of the elbow. An additional control unit, based on the aforementioned activity limit parameters, combines manual and automatic adjustments to obtain additional force control data required for human activity, excluding the effects of coupling linkage. The parameter integration unit binds the synthesized parameters to the rotational attributes of the sternoclavicular and acromioclavicular joints based on the additional control data and the comprehensive control parameter data, and performs boundary processing to obtain the final skeletal control data.

[0022] By adopting the above technical solutions, this application achieves real-time compensation of the elbow joint end point to the mapping angle and initial synchronization of upper arm motion calculation through the error compensation unit; the range of motion limiting unit is specially designed for the posterior space with a proportional allocation mechanism based on the upper arm Y-axis rotation value, which, combined with the upper arm range of motion limiting parameters, effectively avoids biomechanically unreasonable movements; the additional control unit integrates manual adjustment and automatic parameters, providing fine control capabilities for special movements; the parameter integration unit intelligently binds all calculation results to the sternoclavicular and acromioclavicular joints and achieves smooth processing of motion boundaries; significantly improving the accuracy and stability of the system response, enabling the virtual skeleton to maintain a high degree of biomechanical rationality and visual coherence even in fast or complex movements.

[0023] Optionally, the system adopts a hierarchical joint system architecture, with the virtual arm joint system from the bottom layer to the top layer being the first joint system to the fifth joint system, wherein: The first joint system is responsible for acquiring the basic input of the lower arm inverse kinematics control and obtaining basic motion data; The second joint system is responsible for performing positive kinematic control and obtaining skeletal posture control data; The third joint system receives the basic motion data and the skeletal posture control data, and is responsible for switching between forward kinematics and reverse kinematics arm control modes to obtain motion data after the motion control mode conversion. The fourth joint system receives the motion data and is responsible for performing automated motion pattern calculations of the scapula-clavicle-humerus to obtain linkage control data; The fifth joint system receives the linkage control data and, as the top-level control system, is responsible for controlling the opening and closing of the scapula-lock-humerus automated movement mode, integrating all parameters, and outputting the final skeletal control data.

[0024] By adopting the above technical solution, this application achieves functional separation and data flow transmission through a five-layer joint system architecture: the first joint system focuses on acquiring basic inputs for inverse lower arm kinematics; the second joint system is responsible for executing forward kinematic control; the third joint system realizes the switching between forward and inverse kinematic modes; the fourth joint system performs automated motion calculations of the scapula-lock-humerus; and the fifth joint system, as the top-level control center, integrates all parameters and controls the on / off state of the automated mode. This not only improves the modularity and maintainability of the system but also makes the data flow clearer, reduces computational complexity, and ensures the accuracy and response speed of skeletal motion control, providing technical support for the smooth implementation of complex movements.

[0025] In summary, this application includes at least one of the following beneficial technical effects: This application scientifically divides the space around the shoulder joint into eight regions by dynamically acquiring humeral motion data, and dynamically calculates parameter weights based on the position of the elbow joint in different spatial regions. When the elbow joint is in the anterior lateral space, the system allocates the influence weights of abduction / flexion parameters according to the horizontal plane angle ratio; in the posterior lateral space, abduction parameters dominate; in the anterior medial space, flexion parameters have the largest weight; and in the posterior medial space, specific constraint values ​​are applied. This makes the motion performance of the virtual skeleton more consistent with human biomechanical characteristics, significantly improving the simulation effect of animation production and medical education. This application establishes a point constraint on the elbow joint movement point of the lower arm and its associated terminal point, and sets an abduction reference point and a flexion reference point as static references; through the design of combining dynamic input and static reference, the system can accurately calculate the motion components of the humerus in different directions, providing a key basis for determining the spatial position of the shoulder joint; the multi-rearrangement unit ensures the rationality and synchronization of the hierarchical structure of the entire system, and improves the simulation accuracy and biomechanical rationality of the shoulder joint complex motion; This application uses a spatial position determination unit to locate the three-dimensional position of the elbow relative to the shoulder joint, and combines it with an angle calculation unit to calculate the abduction and flexion angles in the coronal and sagittal planes respectively, to achieve precise decomposition of the humeral motion components; through abduction mapping and flexion mapping feedback to the skeletal automation unit, the parameters of the sternoclavicular and acromioclavicular joints are dynamically adjusted according to different angle ranges, simulating the skeletal linkage law of the real human body in different movement stages; improving the accuracy of skeletal linkage in complex movement states, making the shoulder movement of the virtual character smoother and more natural. Attached Figure Description

[0026] Figure 1 This is a schematic diagram of the scapula-clavicle-humerus model in the virtual skeleton simulation motion system of this application embodiment; Figure 2 This is a schematic diagram of the modules of the virtual skeleton simulation motion system according to an embodiment of this application. Detailed Implementation

[0027] The terminology used in the following embodiments of this application is for the purpose of describing particular embodiments only and is not intended to be limiting of this application. As used in the specification and appended claims of this application, the singular expressions “a,” “an,” “the,” “the,” “the,” and “this” are intended to include the plural expressions as well, unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used in this application refers to any or all possible combinations including one or more of the listed items.

[0028] Reference Figure 1 The method for controlling the scapula-clavicle-humerus motion relationship in the virtual skeletal simulation motion system provided in this application includes steps such as dynamic input and static reference system construction, motion state determination and parameter calculation, spatial region comprehensive determination and parameter synthesis, and automated feedback output. Specifically, by constructing a dynamic input and static reference system, real-time motion input is obtained and a reference coordinate system is established. Then, motion state determination and parameter calculation determine the parameters of skeletal motion. Next, spatial region comprehensive determination and parameter synthesis obtain the influence weights of each skeletal parameter and the synthesized control parameters. Finally, automated feedback output realizes the coupling and linkage of the sternoclavicular joint and acromioclavicular joint due to humeral motion. This achieves the effect of enabling the virtual skeletal simulation motion system to realistically and automatically simulate the scapula-clavicle-humerus motion relationship. The reason for this is that each step cooperates with the others, analyzing and controlling the motion from different angles, ensuring the accuracy and automation of the motion simulation.

[0029] Specifically, the construction of the dynamic input and static reference system includes components such as elbow joint movement points, elbow joint end points, abduction reference points, flexion reference points, and multiple reorganizations of the corresponding positions of the sternoclavicular-meninguinal-elbow joints.

[0030] The elbow joint movement point (LJXR-qD, elbow joint locator) is constrained to the lower arm virtual joint (JGJSystem1_IKXxiaBi_R, lower arm virtual joint of the first joint system inverse kinematics), and it moves with the lower arm starting point, i.e., the lower end of the humerus.

[0031] Its final output, the elbow joint endpoint (LJXR-tWZ, elbow joint endpoint locator), is associated with the elbow movement point through a parent constraint. The significance of this endpoint lies in correcting the outward projection of the elbow joint movement point LJXR-qD and the shoulder joint (i.e., the upper end of the humerus) along the horizontal direction when the shoulder joint is abducted to 90°, i.e., the angular error of the abduction reference point. The endpoint completely coincides with the abduction reference point; however, because the elbow joint movement point needs to perform joint movements in the model, the locator point cannot always be directly opposite 90° abduction. The endpoint moves along with the elbow joint movement point, serving as the dynamic input parameter output for the error-corrected movement endpoint. Both the elbow joint movement point LJXR-qD and the elbow joint endpoint LJXR-tWZ are under the group locator_JGJSystem2_XshangBi_R at the corresponding position of the glenohumeral joint.

[0032] This system adopts a hierarchical joint system architecture, with the virtual arm joint systems from bottom to top being the first to fifth joint systems. The first joint system (JGJSystem1) is primarily responsible for acquiring basic inputs, such as inverse kinematics control of the forearm; the second joint system (JGJSystem2) is responsible for forward kinematics (FK) control; the third joint system (JGJSystem3) is responsible for converting between forward kinematics (FK) and inverse kinematics (IK) arm control modes; the fourth joint system (JGJSystem4) is responsible for implementing automated scapula-clavicle-humerus movement modes; and the fifth joint system (JGJSystem5) is responsible for switching the automated scapula-clavicle-humerus movement modes on and off, and as the top-level control system, it is responsible for the final parameter integration and presentation of the final skeletal activity control mode. This hierarchical structure ensures the clarity of the data flow and the independence and integration of each functional module.

[0033] The abduction reference point (LJXR_B_WZ, abduction reference locator) and the flexion reference point (LJ2XR_B_QS, flexion reference locator) are both located under the group locator_JGJSystem2_XshangBi_R at the corresponding position of the glenohumeral joint. The abduction reference point LJXR_B_WZ has its X-axis aligned with LJXR-qD and its Y / Z translation is 0. It serves as a reference point for abduction movement, providing a fixed reference position relative to the entire chest cavity and shoulder joint movement. The flexion reference point LJ2XR_B_QS has its Z-axis as the reference direction and its X / Y translation is 0. It is used for flexion movement determination. The method of determining the positions of the abduction and flexion reference points ensures the accuracy of subsequent movement determination. The abduction reference point can be replaced by a reference point set in other stable positions, as long as it can fulfill its function as an abduction reference; the flexion reference point can also be replaced similarly.

[0034] In the multi-level grouping of the sternoclavicular-hunchback-elbow joint corresponding positions, the sternoclavicular joint group (Test1_JGJ2xiaBiYunDongJiaoDu_R, the second joint system sternoclavicular joint positioning group) is the highest level group, constrained by points and directions at the sternoclavicular joint; the locator_JGJSystem2_XshangBi_R group corresponding to the hunchback joint below it is the middle group in the multi-level grouping, constrained by points at the upper arm virtual joint JGJSystem2_shangBi_R of the second joint system. The previously mentioned LJXR-qD, LJXR-tWZ, LJXR_B_WZ, and LJ2XR_B_QS are all under this group; below this group is the elbow joint group (locator_JGJSystem2XxiaBi_R, the second joint system lower arm positioning group). The groupings of these three levels are located at the sternoclavicular joint / upper arm / lower arm points, respectively, ensuring that the reference points for dynamic input and static reference are synchronized with the movement of the entire body and shoulder joint. The multi-recombination positioning method of the sternoclavicular-meninguinal-elbow joint correspondence position ensures the anti-interference of dynamic activity points and static reference points, that is, it can provide correct parameter output under the activity of other skeletal systems and its own system.

[0035] These components, combined together, provide a fundamental input and reference system for the entire control method through their individual functions and mutual constraints, enabling accurate subsequent motion analysis and control. During the aforementioned construction process, strict constraints exist between the components to ensure the accuracy of motion transmission.

[0036] In addition, this system divides the space around the shoulder joint into eight regions: anterolateral superior, anterolateral inferior, posterolateral superior, posterolateral inferior, anteromedial superior, anteromedial inferior, posteromedial superior, and posteromedial inferior. It establishes two basic spaces for the elbow in the anterolateral superior and anterolateral inferior regions of the shoulder through auxiliary points, and expresses the remaining six spaces through calculation and judgment, providing a comprehensive spatial reference system for subsequent parameter mapping and region determination.

[0037] Specifically, motion state determination and parameter calculation include operations such as spatial position and angle determination, abduction motion parameter mapping, and flexion motion parameter mapping.

[0038] Regarding spatial position and angle determination, the upper / lower spatial determination is achieved through a condition node, namely the upper / lower spatial determination node (condition_YzhengFu_r, Y-axis sign detector). It takes the translation Y-value of LJXR-tWZ as input and outputs "1" (upper space) or "-1" (lower space) to distinguish the vertical position of the elbow within the shoulder joint. This condition node can be replaced by other logical nodes with the same judgment function, such as conditional statements implemented in different programming languages. The abduction angle calculation includes coronal and horizontal plane angle calculations. The coronal plane angle is calculated as the angle between the projections of LJXR-tWZ and the abduction reference point LJXR_B_WZ onto the XY plane, and the horizontal plane angle is calculated as the angle between the projections of LJXR-tWZ and LJXR_B_WZ onto the XZ plane. Different algorithms and nodes can be used to calculate the angles, as long as the corresponding angles can be accurately calculated. The calculation of the flexion angle includes the calculation of the horizontal plane angle and the sagittal plane angle. The horizontal plane angle is calculated as the angle between the projections of LJXR-tWZ and LJ2XR_B_QS onto the XZ plane, and the sagittal plane angle is calculated as the angle between the projections of LJXR-tWZ and LJ2XR_B_QS onto the YZ plane. The combination of these angle calculations and spatial determinations can comprehensively determine the motion state of the elbow.

[0039] In practice, spatial position determination employs a series of condition nodes. The upper / lower spatial determination node (condition_YzhengFu_r, Y-axis sign indicator) receives the translation Y value of the terminal point LJXR-tWZ, compares it with 0, and outputs a positive or negative value (-1 or 1) to distinguish vertical positions. Angle calculation uses a dedicated "angleBetween" node to accurately calculate projection angles. For example, the coronal plane angle calculation node (angleBetween_r_xy_waiZhan_guanZhuangMian, XY plane abduction coronal plane angle calculator) receives the X and Y coordinates of the terminal point and the abduction reference point. Since the aforementioned points are directly under the montelukomalacia joint group at the montelukomalacia joint position, the XY plane projection angle between the two montelukomalacia joint points is calculated. Similarly, the horizontal plane angle is calculated by the node (angleBetween_r_xz_waiZhan_shuiPingMianMian, XZ plane abduction horizontal plane angle calculator) to calculate the XZ plane projection angle between the two montelukomalacia joint points. These angle values ​​are then multiplied by the spatial determination result through the "multiplication, division, and exponentiation" node to obtain angle values ​​with positive and negative signs, correctly reflecting the spatial position. The system uses a right-handed coordinate system for the right limbs, where the X-axis points to the left side of the character (i.e., the outside of the left arm), the Y-axis points upward, and the Z-axis points forward; for the left limbs, a left-handed coordinate system is used, where the X-axis points to the right side of the character (i.e., the outside of the right arm), the Y-axis points upward, and the Z-axis points backward, ensuring consistency and symmetry in angle calculation.

[0040] The system's initial position is shoulder abduction at 90°, meaning the arm is extended horizontally at the shoulder joint level. In this initial position, all shoulder joint rotation values ​​are 0°, and the feedback values ​​and initial values ​​for the sternoclavicular / acromial joints are also 0°. The influence of abduction motion parameter feedback is simulated segmentally based on the abduction mapping angle. In the shoulder abduction 0°~30° segment (the integrated rotation angle of the sternoclavicular, acromioclavicular, and glenohumeral joints, i.e., the coronal mapping angle of abduction -90°~-60°), the sternoclavicular joint rotation along the world Y-axis is fixed at -7.5°, meaning the clavicle retracts 7.5° from its initial position and remains stationary. The sternoclavicular joint rotation along the world Z-axis is fixed at -12.5°, meaning the clavicle... The shoulder joint is lowered by 12.5° from its initial position and remains stationary. The sternoclavicular joint rotates along its long axis by a fixed value of -12.5°, meaning the clavicle rotates backward 15° along its long axis and remains stationary. During shoulder abduction from 30° to 180°, the retraction angle, elevation angle, and backward rotation angle of the sternoclavicular joint increase proportionally. For shoulder abduction exceeding 180°, all rotational parameters of the sternoclavicular joint are locked at their respective extreme values. Similarly, the feedback effect of the shoulder abduction motion mapping angle on the acromioclavicular joint is simulated in segments. The calculation rules for the mapping parameters are determined based on the physiological characteristics of human shoulder movement and can be adjusted according to different needs, such as setting different parameter mapping rules for different age groups or sports scenarios. The abduction parameter mapping strictly follows the physiological principle of scapuhumeral rhythm, specifically set as follows: During shoulder abduction from 0 to 30°, only the glenohumeral joint participates in overall abduction; during shoulder abduction from 30 to 90°, the glenohumeral joint accounts for 30° of the 60° rotation, and the upward rotation of the scapula accounts for 30°, presenting a 1:1 scapuhumeral rhythm ratio; during shoulder abduction from 90 to 180°, the glenohumeral joint accounts for 60° of the 90° rotation, and the scapula accounts for 30° through upward rotation, presenting a 2:1 scapuhumeral rhythm ratio. More precisely, within the 60° range of upward rotation of the scapula, the sternoclavicular joint contributes 25° of elevation. Therefore, during a complete 180° abduction, the movement distribution is: 25° elevation of the sternoclavicular joint + 35° upward rotation of the acromioclavicular joint (total 60°) + 120° of the glenohumeral joint. These precise proportional relationships are achieved through a combination of condition nodes and multiplication / division / exponentiation nodes. For example, when the outward angle is less than or equal to -60° (corresponding to an actual outward angle of 30°), the condition judgment node (Condition_xiaoDengYuF60_1_r, less than or equal to -60 degrees judgment node) outputs a fixed value. When the angle is between -60° and 0°, the angle division node (divide_60_r, 60-degree divider) divides the angle value by 60 and multiplies it by the corresponding parameter to achieve proportional calculation.

[0041] The forward flexion parameter mapping is also based on the forward flexion angle partitioning model. In the shoulder joint 0°~45° phase, only the glenohumeral joint is involved; the sternoclavicular and acromioclavicular joint parameters are not actively adjusted. In the shoulder joint 45°~90° phase, the acromioclavicular joint rotates upward 17.5°, the sternoclavicular joint elevates 12.5°, rotates backward along its long axis 17.5°, and extends forward 5°. In the shoulder joint 90°~180° phase, the acromioclavicular joint continues to rotate upward 17.5 degrees, the sternoclavicular joint continues to elevate 12.5 degrees, rotates backward along its long axis 7.5 degrees, and then retracts 20°. Above 180°, the aforementioned parameter upper limit is reached and the position locks. The forward flexion parameter mapping is also based on human physiological characteristics and can be individually adjusted. The forward flexion parameter mapping uses a similar segmented control model but has unique parameter allocation. Specifically, during shoulder flexion from 0° to 45°, the system uses a condition node (Condition_xiaoDengYuF45_r, a 45° or less judgment device) to lock this phase at a specific value. During the 45° movement from 45° to 90°, the node (divide_45_1_r) achieves proportional increments: the acromioclavicular joint rotates upwards by 17.5 degrees, the sternoclavicular joint elevates by 12.5 degrees, rotates backwards along its long axis by 17.5 degrees, and extends forward by 5 degrees. During the 90° movement from 90° to 180°, the node (divide_90_2_r, 90° divider 2) controls parameter changes: the acromioclavicular joint continues to rotate upwards by 17.5 degrees, the sternoclavicular joint continues to elevate by 12.5 degrees, rotates backwards along its long axis by 7.5 degrees, and then retracts by 20°. These precise values ​​are derived from human motion analysis, and the smooth transition of parameter calculations is ensured through the concatenation of condition nodes and the precise calculations of multiplication, division, and exponentiation nodes.

[0042] Through these operations, the motion parameters of each bone were accurately determined according to different motion angles and stages, providing a basis for subsequent parameter synthesis and bone motion control.

[0043] Specifically, spatial region comprehensive determination and parameter synthesis includes spatial region determination and parameter diversion and synthesis.

[0044] Spatial region determination is performed through a combination of multi-layered conditional nodes. The system completely divides the space around the shoulder joint into eight regions, corresponding to the upper and lower parts of four main spatial regions (lateral anterior, medial anterior, lateral posterolateral, and medial posterolateral). Specifically, the system detects the translational X and Z coordinate values ​​of the terminal point (LJXR-tWZ, elbow joint terminal locator), and determines whether the two values ​​are greater than or less than 0 to determine the region and trigger subsequent flow parameters. It can also form a horizontal plane projection angle with the static reference point at the shoulder joint position, and then allocate the influence ratio of abduction and flexion on the feedback values ​​of the sternoclavicular / acromial joint in this space according to the horizontal plane angle accounting for 90° of the total angle of this space. Furthermore, observing on the horizontal plane, when the translation X of LJXR-tWZ is ≤0 and the translation Z is ≥0, this action locks the position of the elbow joint's movement point in the anterior aspect of the shoulder joint (including the upper and lower spaces), referred to here as the 1 total space (anterior aspect). In this space, the abduction / flexion parameters are distributed according to the proportion of the horizontal angle between the elbow joint's movement point and the static reference point at the shoulder joint within 90°, influencing the sternoclavicular / acromial joint. The elbow joint's movement point translation Z<0 and translation X≥0 are detected separately through conditional nodes, and then the summation is performed by adding and subtracting average nodes. When the summation equals 2, the elbow movement is in the posterior aspect of the shoulder joint (i.e., from the back of the person to the other hand), including the upper and lower spaces. The space referred to as the 4th total space (medial posterolateral) is where the system directly uses preset limit values ​​to control the feedback values ​​of the sternoclavicular / acromioclavicular joints, without affecting the distribution path through abduction / flexion. Elbow joint motion point translations (X<0 and Z<0) are detected separately through conditional nodes, and then summed using addition and subtraction averaging nodes. When the sum equals 2, the elbow movement is in the lateral posterolateral aspect of the shoulder joint (i.e., the direction of the hand's outer side on the back of the person), including the vertical space, referred to as the 3rd total space (lateral posterolateral). In this space, the influence weight of the flexion parameter is 0, and the abduction parameter influences the sternoclavicular / acromioclavicular joints by 100%, while also being affected by the motion limit value of the first virtual upper arm and the proportional distribution compensation after its Y-axis rotation positive and negative determination. This multi-dimensional conditional combination can not only identify the main spatial regions but also accurately distinguish all eight sub-spaces, providing a more precise spatial reference for parameter mapping. Spaces other than the 1st, 4th, and 3rd total spaces are classified as the 2nd total space (medial anterior), which is 100% affected by flexion. The system automatically applies preset parameter combinations when a region trigger node (condition_chuFaQi series, region triggers; one condition outputs 1, two conditions sum to 2, and the result is triggered by checking if it equals 2) is activated in a specific spatial region, simplifying parameter processing in complex spaces. Multiple condition node combinations can employ different logical combinations, as long as the spatial region where the elbow is located can be accurately determined.

[0045] In terms of parameter distribution and synthesis, the core is the dynamic calculation of influence weights and the accurate synthesis of parameters. In space 1, the influence ratio allocation is achieved by using multiplication and division power nodes (biZhi_QianQuDeZhiWaiZhanLaiYong_r, calculator for the ratio of flexion to abduction influence, biZhi_waiZhanDeZhiQianQuLaiYong_r, calculator for the ratio of abduction to flexion influence). This associates the ratio of the elbow joint's active point's angle at the horizontal plane of space 1 (0-90°) with the abduction / flexion parameters. In other words, the allocation of the active point's angle at the horizontal plane of space 1 at 90° yields the influence ratio of abduction / flexion on the rotational angles of the sternoclavicular / acromial joints, achieving a smooth transition of parameter influence. This allows both flexion and abduction parameters to fully function according to the horizontal plane angle ratio, providing the most flexible motion control. For space 3 (lateral posterolateral), the system sets the influence weight of the flexion parameter to 0, and skeletal movement is entirely controlled by the abduction parameter. It is also influenced by the activity limit value and proportional distribution compensation of the first virtual upper arm, ensuring that movement in the posterior region conforms to physiological characteristics. Space 4 (medial posterolateral) directly triggers preset limit values, without affecting the distribution path through abduction / flexion. In the upper region of the medial posterolateral space, for example, the system directly applies preset rotation parameter combinations for the sternoclavicular and acromioclavicular joints to ensure accurate control of extreme positions. Space 2 (medial anterior), as the default space, has its parameter processing linked to the error compensation mechanism of the initial elbow joint group, ensuring the continuity and smooth transition of movement.

[0046] After parameter processing for each spatial region, the system integrates the parameters. Skeletal parameter synthesis uses the formula: Final Parameter = Abduction Parameter × Abduction Weight + Flexion Parameter × Flexion Weight. The influence percentage is multiplied by the original parameters to generate the parameters for the acromioclavicular and sternoclavicular joints. This weighted synthesis is achieved through the biZhiXiangCheng series of ratio multiplication nodes. Preliminary parameter integration uses the JGJSystem4_XsuoGu_R_qianQuWzaiZhanZhuanHuanHeBing_r and JGJSystem4_XjianJiaGu_qianQuWzaiZhanZhuanHuanHeBing_R addition / subtraction averaging nodes to sum the parameters of each axis of the sternoclavicular and acromioclavicular joints. Then, the final regional parameters are merged using the plus_quYuHeBing series of nodes, simultaneously integrating the preset parameters, additional control parameters, and initial angle compensation parameters output by the triggers. Finally, the synthesized parameters are passed to the XYZ rotation attributes of the sternoclavicular joint (JGJSystem4_XsuoGu_R, JGJSystem4_IXsuoGu_R_rotY, JGJSystem4_XsuoGu_R_rotZ) and the X / Z rotation attributes of the acromioclavicular joint (jianJiaGu_R, JGJsystem4_XjianJiaGu_R_rotZ) via direct attribute connections. Multiplication / division exponentiation nodes and addition / subtraction averaging nodes can be replaced with other nodes that have the same mathematical operation functions to achieve parameter splitting, weighting, and merging.

[0047] By determining the spatial region and separating and synthesizing parameters, the influence of the spatial region where the elbow is located and different movements on the skeletal parameters was comprehensively considered, and accurate control parameters were obtained.

[0048] Specifically, the automated feedback output includes error compensation mechanisms, activity limit control, additional controls, and regional merging for final integrated output.

[0049] The error compensation mechanism is implemented through two complementary directions: First, the terminal point (LJXR-tWZ) compensates for the elbow joint movement point (LJXR-qD), subtracting the deviation to accurately map the angle; second, the system creates a lower arm angle target group (loc_angleTarget_xiaBi_r) under the group (locator_JGJSystem2_XshangBi_R) corresponding to the glenohumeral joint position. The system calculates the angle difference between the abduction reference point and the initial position in the horizontal plane using an angle difference calculator, and then merges this angle difference with the rotation Y-value of the upper arm virtual joint (JGJSystem1_IKXshangBi_R) of the first joint system's inverse kinematics using a parameter merger, actively generating a compensation value that matches the initial error. In this way, the initial error is included in the Y-axis rotation calculation of the first joint system, ensuring that when the arm starts moving from any initial posture, the model and virtual joint remain consistent in state before and after the influence of automated feedback.

[0050] The range of motion restriction control is primarily implemented in space 3 (outer rear). Unlike other space regions which use triggers to lock parameters, space 3 uses a condition node to detect whether the rotation Y-value of the virtual upper arm joint of the first joint system is less than 0 (indicating that the shoulder joint is pushing backward, entering space 3 or 4). The angle is then normalized to 60° using an angle normalization node, and then converted into corresponding control parameters at different ratios (-15° for the acromioclavicular joint, 5° and 7° for the sternoclavicular joint) for proportional distribution of influence. It is worth noting that this range of motion restriction based on the first joint system exists in all regions, but its limit value is difficult to reach in other regions, thus primarily affecting the motion control of space 3.

[0051] In the additional control mechanism, a seamless integration of manual adjustment and automatic parameters is achieved. The translation Y / Z values ​​of the FK controller (danceBC_suoGu_r, clavicle forward motion controller) for clavicle additional movements are independently input through multiplication and division nodes; these values ​​directly correspond to the anterior-posterior and posterior-hypertraction of the sternoclavicular joint. These manually adjusted parameters are merged with automatically calculated parameters through a region parameter merger (plus_quYuHeBing series, region parameter merger), achieving a balance between additional control and automation. Specifically, the system implements a parameter priority mechanism, ensuring that in specific spatial regions, the fixed parameters output by region trigger nodes (condition_chuFaQi series, region triggers) have higher priority than conventionally calculated parameters. This is achieved by connecting the trigger output to a higher-priority input of the region parameter merger (plus_quYuHeBing node). Furthermore, the system implements an antipop mechanism to ensure smooth transitions between parameters in different spatial regions, avoiding abrupt changes in skeletal movement. Multiplication and division exponentiation nodes can be replaced with other nodes that perform the same multiplication and division operations. The antipop mechanism is implemented through smooth interpolation transitions, boundary blurring, state caching, and parameter rate limiting. When the elbow moves between different spatial regions, the system does not directly switch parameter values. Instead, it employs a progressive update strategy, calculating appropriate transition values ​​in the region parameter merger (plus_quYuHeBing series nodes) to ensure smooth changes in the rotational parameters of the sternoclavicular and acromioclavicular joints. This mechanism effectively prevents sudden "pops" of bones at spatial boundaries, ensuring the continuity of posture transitions and visual comfort during animation, maintaining natural and fluid movement even in fast and complex motions.

[0052] The final integrated output of the region merging process achieves accurate parameter binding and boundary handling. The system binds the merged X / Y / Z-axis parameters of the sternoclavicular joint to the rotation X of the virtual node (JGJSystem4_XsuoGu_R) for clavicle X-axis rotation, the rotation Y of the virtual node group (JGJSystem4_IXsuoGu_R_rotY) for clavicle Y-axis rotation, and the rotation Z of the virtual node group (JGJSystem4_XsuoGu_R_rotZ) for clavicle Z-axis rotation in the fourth joint system, respectively. Similarly, the merged acromioclavicular joint parameters are bound to the rotation X of the virtual node (jianJiaGu_R) for scapula X-axis rotation and the rotation Z of the virtual node group (JGJsystem4_XjianJiaGu_R_rotZ) for scapula Z-axis rotation in the fourth joint system, thus completing the automated control of the acromioclavicular joint. During the binding process, the system also implements boundary handling to ensure that the parameters do not exceed the physiological limitations of the joint. For example, the upper limit of the sternoclavicular joint elevation angle is 12.5°, and the lower limit is -15°; the upper limit of the acromioclavicular joint rotation angle is 17.5°, and the lower limit is -14°. When the calculated parameters exceed these limits, the system automatically restricts them to the effective range through conditional nodes, avoiding non-physiological skeletal deformation. This precise parameter control and boundary handling ensures the physiological realism and visual consistency of skeletal movement. Binding methods can be implemented using different program statements or methods.

[0053] Through automated feedback output, the synthesized control parameters are accurately transmitted to the virtual joint group, achieving coupled linkage with humeral movement. This parameter transmission establishes a synergistic relationship between the humerus, clavicle, and scapula, ensuring the physiological realism of complex shoulder movements. It is worth noting that the complete shoulder movement system also needs to incorporate the scapular sliding mechanism; by controlling the sliding and adduction of the scapula, the realism of shoulder movements is further enhanced.

[0054] The implementation principle of this embodiment is as follows: This control method constructs a comprehensive dynamic input and static reference system, utilizes multi-level condition nodes, angle calculation nodes, and parameter mapping mechanisms to accurately determine the motion state and calculate parameters, comprehensively considers the influence of eight precisely divided spatial regions on the parameters of the sternoclavicular and acromioclavicular joints, and finally achieves automated feedback output including error compensation, range of motion limitation, and smooth parameter transition, as well as additional control outputs required for human activity in addition to automatic feedback. Compared with existing technologies, this method not only solves problems such as simplified linkage relationships, insufficient spatial dimension coverage, and poor physiological realism, but also provides a complete automatic control solution for upper limb spatial motion, achieving joint coordinated motion that strictly conforms to the scapulohumeral rhythm. Through precise parameter splitting and synthesis algorithms, it ensures that accurate control parameters can be obtained for motion starting from any initial posture, greatly improving the motion realism and ease of operation of the virtual skeleton simulation system, and providing a high-precision shoulder motion control solution for animation production, biomechanical research, and virtual reality.

[0055] Secondly, referring to Figure 2 This application provides a virtual skeletal simulation motion system. The virtual skeletal simulation motion system of this application will be described below in conjunction with the above-mentioned control method for the scapula-clavicle-humerus motion relationship.

[0056] A virtual skeletal simulation motion system, comprising: The dynamic input module is used to collect real-time motion data of the humerus and establish a reference coordinate system to obtain real-time motion input data and reference coordinate system data. The motion state determination module determines the motion parameters of the scapula and clavicle, as well as the spatial position information of the elbow movement point, based on real-time motion input data and reference coordinate system data. The spatial region comprehensive determination module divides the space around the shoulder joint into eight regions based on spatial location information and skeletal motion parameters, calculates the influence weight of each skeletal parameter, and limits the required values ​​of each skeletal parameter. The parameter synthesis module generates synthetic control parameters for the sternoclavicular and acromioclavicular joints based on skeletal motion parameters and influence weights. The automated feedback output module transmits control data to the virtual joint group based on the synthesized control parameters, generates skeletal linkage control data, and realizes the coupling linkage of the sternoclavicular joint and acromioclavicular joint due to the movement of the humerus. The virtual skeleton display module displays the movement of the scapula, clavicle, and humerus based on skeleton linkage control data.

[0057] In one embodiment, the dynamic input module includes: The elbow joint motion point setting unit is used to establish elbow joint motion points constrained to the virtual joint of the lower arm, and obtain motion data that moves with the lower end of the humerus. The elbow joint endpoint setting unit establishes an elbow joint endpoint associated with the elbow joint movement point through a parent constraint based on the movement data of the elbow joint movement point, thereby obtaining the corrected angle data. The reference point setting unit is used to establish abduction reference point and flexion reference point as static references. The X-axis of the abduction reference point is aligned with the elbow joint movement point, and the Y / Z translation relative to the shoulder joint point is 0. The flexion reference point is based on the positive Z-axis direction, and the X / Y translation relative to the shoulder joint point is 0, thus obtaining reference data for abduction and flexion movements. Multiple reconfiguration units are used to construct a hierarchical structural framework corresponding to the sternoclavicular-meninguinal-elbow joint positions. The elbow joint motion point, elbow joint terminal point, abduction reference point, and flexion reference point are placed in appropriate hierarchical positions to ensure the spatial correspondence between dynamic input and static reference and the synchronization of the overall system.

[0058] In one embodiment, the motion state determination module includes: The spatial position determination unit is used to determine the three-dimensional spatial position of the elbow relative to the shoulder joint through condition nodes, including vertical position, front-back position and inside-out position, and to obtain the spatial position determination result. The angle calculation unit calculates the abduction mapping angle between the elbow joint terminal point and the abduction reference point in the coronal projection plane and the flexion mapping angle between the elbow joint terminal point and the flexion reference point in the sagittal projection plane, based on the spatial position determination result. It obtains abduction angle data and flexion angle data, and calculates the mapping angle between the elbow joint terminal point and the abduction and flexion reference points in the horizontal projection plane, thus obtaining the angle data required for the abduction and flexion influence ratio. The abduction mapping feedback skeletal automation unit generates simulated human skeletal motion parameters for the sternoclavicular and acromioclavicular joints based on abduction mapping angle data and segmented according to the abduction mapping angle. The flexion mapping feedback skeletal automation unit generates simulated human skeletal motion parameters for the sternoclavicular and acromioclavicular joints based on flexion mapping angle data and segmented according to the flexion angle. These parameters are generated by the humerus driving the shoulder joint to flex forward. The parameter output unit integrates abduction and flexion motion parameters into motion parameters for the scapula and clavicle.

[0059] In one embodiment, the abduction motion parameter mapping unit is used for: When the shoulder abduction angle is detected to be within the range of 0° to 30°, only the montelukast joint is activated to participate in overall abduction, while the sternoclavicular and acromioclavicular joints are set not to participate in the angle contribution, thus obtaining the first stage of motion control data. When the shoulder abduction angle is detected to be within the range of 30° to 90°, according to the 1:1 scapulohumeral rhythm ratio, the glenohumeral joint is set to occupy 30°, and the scapula achieves upward rotation of 30° through the coordinated movement of the sternoclavicular joint and the acromioclavicular joint, thus obtaining the second stage of motion control data; When the shoulder abduction angle is detected to be within the range of 90° to 180°, according to the 2:1 scapulohumeral rhythm ratio, the glenohumeral joint is set to occupy 60°, and the scapula achieves upward rotation of 30° through the coordinated movement of the sternoclavicular and acromioclavicular joints, thus obtaining the third stage of motion control data. Based on the current stage of the detected shoulder joint abduction mapping angle, the corresponding motion control data is selected as the abduction motion parameter output.

[0060] In one embodiment, the forward flexion motion parameter mapping unit is used for: When the shoulder flexion angle is detected to be within the range of 0° to 45°, only the montelukast joint is activated to participate in the flexion movement, while the sternoclavicular and acromioclavicular joints are set not to participate in the angle contribution, thus obtaining the first stage control data of flexion. When the shoulder flexion angle is detected to be within the range of 45° to 90°, the acromioclavicular joint is rotated upward by 17.5°, the sternoclavicular joint is raised by 12.5°, the long axis is rotated backward by 17.5°, and the forward extension is 5° to obtain the second stage control data for flexion. When the shoulder flexion angle is detected to be within the range of 90° to 180°, the acromioclavicular joint is set to continue to rotate upward by 17.5°, the sternoclavicular joint is set to continue to rise by 12.5°, rotate backward along the long axis by 7.5°, and the direction of movement changes from extension to retraction and displacement by 20°, thus obtaining the control data for the third stage of flexion. Based on the current stage of the detected shoulder flexion angle, the corresponding motion control data is selected as the output of flexion motion parameters.

[0061] In one embodiment, the spatial region comprehensive determination module includes: The spatial region division unit is used to divide the space around the shoulder joint into eight regions: anterolateral superior, anterolateral inferior, posterolateral superior, posterolateral inferior, anteromedial superior, anteromedial inferior, posteromedial superior, and posteromedial inferior, to obtain spatial region division data; The spatial region determination unit determines the current spatial region based on the spatial region division data and the translation X, Y, and Z coordinate values ​​of the elbow joint terminal point, and obtains the spatial region determination result. The weight calculation unit calculates the influence weights of the abduction and flexion parameters based on the spatial region determination results, and obtains the parameter weight data. The control strategy output unit generates corresponding spatial control strategy data based on the parameter weight data, which is then used by the parameter synthesis module.

[0062] In one embodiment, the spatial region determination unit and the weight calculation unit jointly implement the following control strategy: When the translation X of the elbow joint terminal point is less than or equal to 0 and the translation Z is greater than or equal to 0, it is determined to be the anterior lateral space. The abduction / flexion parameters are then assigned influence weights according to the proportion of the horizontal plane angle to obtain the anterior lateral space control strategy. The anterior lateral space includes the upper anterior lateral space and the lower anterior lateral space. When the translation of the elbow joint end point X < 0 and the translation of Z < 0, it is determined to be the lateral posterior space. Based on the characteristics of the lateral posterior space, the abduction parameter is triggered to have 100% influence control and the flexion parameter to have 0% influence control, thus obtaining the lateral posterior space control strategy. The lateral anterior space includes the posterolateral upper and posterolateral lower. When the translation X of the elbow joint terminal point is greater than 0 and the translation Z is less than 0, it is determined to be the inner posterior space. Based on the characteristics of the inner posterior space, the preset limit value is triggered to control the sternoclavicular joint / acromial joint, thus obtaining the inner posterior space control strategy. The outer anterior space includes the posteromedial upper and posteromedial lower. When the translation X of the elbow joint endpoint is greater than 0 and the translation Z is greater than or equal to 0, it is determined to be the medial anterior space. Based on the characteristics of the medial anterior space, the flexion parameter is triggered to have 100% influence control and the abduction parameter has 0% influence control, thus obtaining the medial anterior space control strategy. The lateral anterior space includes the anteromedial upper and anteromedial lower.

[0063] In one embodiment, the parameter synthesis module calculates the control parameters of the sternoclavicular joint and acromioclavicular joint according to the formula: final parameter = abduction parameter × abduction weight + flexion parameter × flexion weight, and obtains comprehensive control parameter data.

[0064] In one embodiment, the automated feedback output module includes: The error compensation unit is used to compensate the elbow joint movement point through the elbow joint end point, obtain the mapping data between the error compensation and the reference point, and return the calculated values ​​required for the forearm movement to obtain the error compensation through the corresponding position group feedback compensation value. The range of motion limiting unit, after backtracking based on the error compensation data, implements the proportional allocation of the upper arm virtual joint Y-axis rotation value and the range of motion limiting parameters of the upper arm virtual joint in the posterior space, and obtains the parameters required for the sternoclavicular and acromioclavicular joints in the posterior space at the elbow. An additional control unit, based on the activity limit parameters, combines manual and automatic parameters to obtain additional force control data required for human activity, excluding the effects of coupled linkage. The parameter integration unit binds the synthesized parameters to the rotational attributes of the sternoclavicular and acromioclavicular joints based on the additional control data and the comprehensive control parameter data, and performs boundary processing to obtain the final skeletal control data.

[0065] In one embodiment, the system adopts a hierarchical joint system architecture, with the virtual arm joint systems from the bottom to the top being the first joint system to the fifth joint system, wherein: The first joint system is responsible for acquiring the basic input of the lower arm inverse kinematics control and obtaining basic motion data; The second joint system is responsible for performing positive kinematic control and obtaining skeletal posture control data; The third joint system receives basic motion data and skeletal posture control data, and is responsible for switching between forward kinematics and reverse kinematics arm control modes to obtain motion data after the motion control mode conversion. The fourth joint system receives motion data and is responsible for performing automated motion pattern calculations of the scapula-clavicle-humerus to obtain linkage control data; The fifth joint system receives the linkage control data and, as the top-level control system, is responsible for controlling the opening and closing of the scapula-clavicle-humerus automated movement mode, integrating all parameters, and outputting the final skeletal control data.

[0066] It is worth noting that the specific parameters described in this application (such as the upper limit of the sternoclavicular joint elevation angle being 12.5 degrees and the lower limit being -15 degrees; the upper limit of the acromioclavicular joint rotation angle being 17.5 degrees and the lower limit being -14 degrees, etc.), the topological hierarchy naming of virtual joints (such as the hierarchical division from "first joint system to fifth joint system"), the organization of point group structures (such as the nesting relationship of "multiple groups of corresponding positions of sternoclavicular-menopausal-elbow joints"), and the specific implementation forms of some auxiliary calculation steps (such as the functional division of "angleBetween node" and "multiplication and division power node") are merely exemplary narrative methods adopted for the convenience of understanding the technical solution. Those skilled in the art should understand that the above exemplary content is not the only limitation of the technical solution, and in actual applications, adjustments can be made according to specific needs (such as different initial postures, individual differences in shoulder range of motion, or characteristics of the software platform) without departing from the core technical framework. This includes, but is not limited to: the specific values ​​of parameters, the specific naming method of nodes, the specific implementation of some auxiliary calculation steps, and the fineness of spatial region division. For example, when the initial posture of the skeletal model is adjusted from "arm abducted at 90 degrees" to "arm hanging down naturally", auxiliary details such as the position settings of the abduction reference point and the flexion reference point, the reference coordinate system for spatial region determination, or the calculation method of parameter influence weight may need to be calibrated accordingly. However, these adjustments do not affect the core control principle of the scapula-clavicle-humerus motion relationship disclosed in this application.

[0067] The above are all preferred embodiments of this application, and are not intended to limit the scope of protection of this application. Therefore, all equivalent changes made in accordance with the structure, shape and principle of this application should be covered within the scope of protection of this application.

Claims

1. A virtual skeletal simulation motion system, characterized in that, include: The dynamic input module is used to collect real-time motion data of the humerus and establish a reference coordinate system to obtain real-time motion input data and reference coordinate system data. The motion state determination module determines the motion parameters of the scapula and clavicle, as well as the spatial position information of the elbow movement point, based on the real-time motion input data and reference coordinate system data. The spatial region comprehensive determination module divides the space around the shoulder joint into eight regions based on the spatial location information and skeletal motion parameters, calculates the influence weight of each skeletal parameter, and limits the required values ​​of each skeletal parameter. The parameter synthesis module generates synthetic control parameters for the sternoclavicular and acromioclavicular joints based on the skeletal motion parameters and influence weights. The automated feedback output module transmits control data to the virtual joint group according to the synthesized control parameters, generates skeletal linkage control data, and realizes the coupling linkage of the sternoclavicular joint and acromioclavicular joint due to the movement of the humerus. The virtual skeleton display module displays the movement of the scapula-clavicle-humerus based on the skeleton linkage control data.

2. The virtual skeleton simulation motion system according to claim 1, characterized in that, The dynamic input module includes: The elbow joint motion point setting unit is used to establish elbow joint motion points constrained to the virtual joint of the lower arm, and obtain motion data that moves with the lower end of the humerus. The elbow joint endpoint setting unit establishes an elbow joint endpoint associated with the elbow joint movement point through a parent constraint based on the activity data of the elbow joint movement point, thereby obtaining the corrected angle data. The reference point setting unit is used to establish abduction reference point and flexion reference point as static references. The X-axis of the abduction reference point is aligned with the elbow joint movement point, and the Y / Z translation relative to the shoulder joint point is 0. The flexion reference point is based on the positive Z-axis direction, and the X / Y translation relative to the shoulder joint point is 0, thus obtaining reference data for abduction and flexion movements. Multiple reconfiguration units are used to construct a hierarchical structural framework corresponding to the sternoclavicular-meninguinal-elbow joint positions, placing the elbow joint movement point, elbow joint terminal point, abduction reference point, and flexion reference point in appropriate hierarchical positions to ensure the spatial correspondence between dynamic input and static reference and the synchronization of the overall system.

3. The virtual skeletal simulation motion system according to claim 2, characterized in that, The motion state determination module includes: The spatial position determination unit is used to determine the three-dimensional spatial position of the elbow relative to the shoulder joint through condition nodes, including vertical position, front-back position and inside-out position, and to obtain the spatial position determination result. The angle calculation unit calculates the abduction mapping angle between the elbow joint terminal point and the abduction reference point in the coronal projection plane and the flexion mapping angle between the elbow joint terminal point and the flexion reference point in the sagittal projection plane, based on the spatial position determination result, to obtain abduction angle data and flexion angle data. It also calculates the mapping angle between the elbow joint terminal point and the abduction and flexion reference points in the horizontal projection plane to obtain the angle data required for the abduction and flexion influence ratio. The abduction mapping feedback skeletal automation unit generates, based on the abduction mapping angle data, simulated human skeletal motion parameters of the sternoclavicular and acromioclavicular joints caused by the humerus driving the shoulder joint abduction, according to the abduction mapping angle segmentation. The flexion mapping feedback skeletal automation unit generates simulated human skeletal motion parameters for the sternoclavicular and acromioclavicular joints based on the flexion mapping angle data and according to the flexion angle segmentation. These parameters are formed by the humerus driving the shoulder joint to flex forward. The parameter output unit integrates the abduction and flexion motion parameters into motion parameters for the scapula and clavicle.

4. The virtual skeletal simulation motion system according to claim 3, characterized in that, The abduction motion parameter mapping unit is used for: When the shoulder abduction angle is detected to be within the range of 0° to 30°, only the montelukast joint is activated to participate in overall abduction, while the sternoclavicular and acromioclavicular joints are set not to participate in the angle contribution, thus obtaining the first stage of motion control data. When the shoulder abduction angle is detected to be within the range of 30° to 90°, according to the 1:1 scapulohumeral rhythm ratio, the glenohumeral joint is set to occupy 30°, and the scapula achieves upward rotation of 30° through the coordinated movement of the sternoclavicular joint and the acromioclavicular joint, thus obtaining the second stage of motion control data; When the shoulder abduction angle is detected to be within the range of 90° to 180°, according to the 2:1 scapulohumeral rhythm ratio, the glenohumeral joint is set to occupy 60°, and the scapula achieves upward rotation of 30° through the coordinated movement of the sternoclavicular and acromioclavicular joints, thus obtaining the third stage of motion control data. Based on the current stage of the detected shoulder joint abduction mapping angle, the corresponding motion control data is selected as the abduction motion parameter output.

5. The virtual skeletal simulation motion system according to claim 4, characterized in that, The forward flexion motion parameter mapping unit is used for: When the shoulder flexion angle is detected to be within the range of 0° to 45°, only the montelukast joint is activated to participate in the flexion movement, while the sternoclavicular and acromioclavicular joints are set not to participate in the angle contribution, thus obtaining the first stage control data of flexion. When the shoulder flexion angle is detected to be within the range of 45° to 90°, the acromioclavicular joint is rotated upward by 17.5°, the sternoclavicular joint is raised by 12.5°, the long axis is rotated backward by 17.5°, and the forward extension is 5° to obtain the second stage control data for flexion. When the shoulder flexion angle is detected to be within the range of 90° to 180°, the acromioclavicular joint is set to continue to rotate upward by 17.5°, the sternoclavicular joint is set to continue to rise by 12.5°, rotate backward along the long axis by 7.5°, and the direction of movement changes from extension to retraction and displacement by 20°, thus obtaining the control data for the third stage of flexion. Based on the current stage of the detected shoulder flexion angle, the corresponding motion control data is selected as the output of flexion motion parameters.

6. The virtual skeletal simulation motion system according to claim 5, characterized in that, The spatial region comprehensive determination module includes: The spatial region division unit is used to divide the space around the shoulder joint into eight regions: anterolateral superior, anterolateral inferior, posterolateral superior, posterolateral inferior, anteromedial superior, anteromedial inferior, posteromedial superior, and posteromedial inferior, to obtain spatial region division data; The spatial region determination unit determines the current spatial region based on the spatial region division data and the translation X, Y, and Z coordinate values ​​of the elbow joint terminal point, and obtains the spatial region determination result. The weight calculation unit calculates the influence weights of the abduction parameter and the flexion parameter based on the spatial region determination result, and obtains the parameter weight data. The control strategy output unit generates corresponding spatial control strategy data based on the parameter weight data, which is then used by the parameter synthesis module.

7. The virtual skeleton simulation motion system according to claim 6, characterized in that, The spatial region determination unit and the weight calculation unit jointly implement the following control strategy: When the translation X of the elbow joint terminal point is less than or equal to 0 and the translation Z is greater than or equal to 0, it is determined to be the anterior lateral space. The abduction / flexion parameters are then assigned influence weights according to the proportion of the horizontal plane angle to obtain the anterior lateral space control strategy. The anterior lateral space includes the upper anterior lateral space and the lower anterior lateral space. When the translation of the elbow joint terminal point X < 0 and the translation of Z < 0, it is determined to be the lateral posterior space. Based on the characteristics of the lateral posterior space, the abduction parameter is triggered to have 100% influence control and the flexion parameter to have 0% influence control, thus obtaining the lateral posterior space control strategy. The lateral anterior space includes the posterolateral upper and posterolateral lower. When the translation of the elbow joint terminal point X>0 and the translation of Z<0, it is determined to be the inner posterior space. Based on the characteristics of the inner posterior space, the preset limit value is triggered to control the sternoclavicular joint / axillary joint, thus obtaining the inner posterior space control strategy. The outer anterior space includes the posteromedial upper and posteromedial lower. When the translation X of the elbow joint terminal point is greater than 0 and the translation Z is greater than or equal to 0, it is determined to be the medial anterior space. Based on the characteristics of the medial anterior space, the flexion parameter is triggered to have 100% influence control and the abduction parameter to have 0% influence control, thus obtaining the medial anterior space control strategy. The medial anterior space includes the anterior medial upper and anterior medial lower.

8. The virtual skeletal simulation motion system according to claim 7, characterized in that, The parameter synthesis module calculates the control parameters of the sternoclavicular and acromioclavicular joints according to the formula: final parameter = abduction parameter × abduction weight + flexion parameter × flexion weight, and obtains comprehensive control parameter data.

9. The virtual skeleton simulation motion system according to claim 8, characterized in that, The automated feedback output module includes: The error compensation unit is used to compensate the elbow joint movement point through the elbow joint end point, obtain the mapping data between the error compensation and the reference point, and return the calculated values ​​required for the forearm movement to obtain the error compensation through the corresponding position group feedback compensation value. The range of motion limiting unit, after backtracking the error compensation data, implements the proportional allocation of the upper arm virtual joint Y-axis rotation value and the range of motion limiting parameters of the upper arm virtual joint in the posterior space, and obtains the parameters required for the sternoclavicular and acromioclavicular joints in the posterior space of the elbow. An additional control unit, based on the aforementioned activity limit parameters, combines manual and automatic adjustments to obtain additional force control data required for human activity, excluding the effects of coupling linkage. The parameter integration unit binds the synthesized parameters to the rotational attributes of the sternoclavicular and acromioclavicular joints based on the additional control data and the comprehensive control parameter data, and performs boundary processing to obtain the final skeletal control data.

10. The virtual skeletal simulation motion system according to claim 9, characterized in that, The system adopts a hierarchical joint system architecture, with the virtual arm joint system from the bottom to the top being the first joint system to the fifth joint system, wherein: The first joint system is responsible for acquiring the basic input of the lower arm inverse kinematics control and obtaining basic motion data; The second joint system is responsible for performing positive kinematic control and obtaining skeletal posture control data; The third joint system receives the basic motion data and the skeletal posture control data, and is responsible for switching between forward kinematics and reverse kinematics arm control modes to obtain motion data after the motion control mode conversion. The fourth joint system receives the motion data and is responsible for performing automated motion pattern calculations of the scapula-clavicle-humerus to obtain linkage control data; The fifth joint system receives the linkage control data and, as the top-level control system, is responsible for controlling the opening and closing of the scapula-lock-humerus automated movement mode, integrating all parameters, and outputting the final skeletal control data.

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