124 results about "Biomechanical model" patented technology

The invention relates to the technical field of bone implantation, and discloses a biomechanical evaluation method and system for a bone defect repair implant, and the method comprises the steps: constructing a human muscle-bone system biomechanical model and a three-dimensional digital model of the bone defect repair implant; through a finite element analysis method, the stress conditions of the bone defect repair implant in different gaits and movement modes are calculated, and the stress conditions of the implant in the actual service process are simulated; and calculating the performance of the implant under the simulated stress, and adjusting the design parameters of the implant. By combining dynamics calculation, bone regeneration process simulation, nano computed tomography image three-dimensional reconstruction and structure optimization, a bone repair implant biomechanical adaptability evaluation mechanism is established, and a comprehensive evaluation system integrating system dynamics calculation and bone healing process analysis is designed. The bone repair and regeneration process and the acting force change process are simulated, the effect of mechanical stimulation on bone regeneration is revealed, and comprehensive evaluation of the structure, the mechanical property, the environmental adaptability and the service life of the implant is achieved.

The invention provides a cervical vertebra segmentation and key point detection method based on a diffusion model, and relates to the technical field of medical image processing, and the method carries out the denoising processing of a cervical vertebra image through the diffusion model, improves the image quality, and lays a foundation for the subsequent segmentation and key point detection. A cervical vertebra region and key point positions can be accurately extracted by combining a model of a deep learning technology, and reliable data support is provided for bone age staging; the bone age staging based on the results can objectively and quantitatively evaluate the growth and development degree of a patient and assist a doctor in making a personalized orthodontic treatment scheme, and in addition, in combination with a stress distribution diagram generated by a biomechanical model and a self-adaptive segmentation model of a preprocessed image, a segmentation strategy can be adjusted according to individual differences, so that the accuracy of bone age staging is improved. The precision and the robustness are improved; meanwhile, parameters such as blood flow velocity and temperature distribution are incorporated into a machine learning model, new indexes are provided for cervical vertebra bone age staging, and the individuation and accuracy of evaluation are enhanced.

The invention relates to the technical field of intelligent inspection, and discloses an intelligent inspection method and system based on AI multi-source fusion, and the method comprises the steps: collecting multi-mode perception data when an expert carries out the touch inspection operation; analyzing the multi-modal perception data, and constructing a biomechanical model and a tactile knowledge mapping model; establishing a standard tactile operation model and an acoustic feature mapping relation database; converting the standard tactile operation model into animation guidance and tactile feedback in an augmented reality interface; actual operation data of the inspectors are collected and compared with the standard touch operation model, and operation improvement suggestions are generated; fusing the tactile inspection result, the acoustic detection result and the visual inspection result to generate a comprehensive evaluation report; according to the invention, digital inheritance and standardized application of the tactile skills are realized, and the technical problem that the tactile skills are difficult to transmit in traditional inspection is solved.

The invention belongs to the technical field of personalized insole manufacturing, particularly relates to a personalized insole manufacturing method and system based on three-dimensional motion capture and 3D printing, and aims to solve the problem that most existing insoles are generally manufactured and lack targeted design for consumers. The method comprises the following steps: preprocessing foot data of a target to obtain preprocessed foot data; performing feature extraction on the preprocessed foot data to obtain each foot feature; constructing a comprehensive feature vector of each foot feature based on the data source feature of each foot feature; performing mechanical analysis on the target based on the data source features to obtain a mechanical analysis result; performing multi-modal fusion on each comprehensive feature vector by using an algorithm to obtain a foot biomechanical model; and performing 3D printing of the insole based on the mechanical analysis result and the foot mechanical model. According to the method, scientific and objective data support is provided for comprehensive quantitative analysis of the motion state of the foot, and manufacturing of personalized insoles is guided.

The invention discloses a failure restoration retreatment decision-making method based on dynamic occlusion analysis, and the method comprises the steps: constructing a four-dimensional virtual biomechanical model which comprises a patient anatomical structure and a dynamic function through multi-modal data fusion, and enabling the model to be embedded into a real three-dimensional mandibular movement track of a patient to simulate functional movement, thereby breaking through a static analysis blind area, and achieving the real three-dimensional mandibular movement of the patient. The missed diagnosis rate of dynamic interference is reduced; based on quantitative indexes and thresholds such as occlusal contact displacement, occlusal contact distribution symmetry and adjustment quantity of the maximum tooth tip staggering position and the median relation position, experience judgment of doctors is replaced, objectivity, repeatability and accuracy of failure repair and retreatment decision are improved, and excessive or insufficient adjustment is avoided; the treatment effect rehearsal is realized through virtual presetting, the irreversible operation risk is avoided, and the number of times of re-visit and the trial and error cost of a patient are reduced; and meanwhile, the four-dimensional virtual model can be connected with transition and design and manufacturing of a final restoration, so that the accuracy, safety and efficiency of retreatment of a failed restoration are improved.

The invention is suitable for the technical field of 3D scanning, and provides a figure model 3D scanning and dynamic attitude capturing method and system, which dynamically triggers 3D scanning by monitoring joint movement intensity in real time, continuously collects continuous movement tracks by using an inertial sensor in a non-scanning period, and reversely deduces space-time parameters of a shielded part through multi-light-source shadow boundary evolution. And constructing a spatio-temporal joint evaluation function to adaptively adjust the scanning frequency and the sampling rate, and finally performing spatio-temporal alignment and confidence weighted fusion on the discrete point cloud, the continuous trajectory and the reverse reckoning data to generate a dynamic biomechanical model. The scheme breaks through the bottleneck of resource waste and blind area shielding of traditional fixed frequency scanning, realizes space-time complementation and precision optimization of motion monitoring, and is suitable for dynamic scenes such as movie and television animation, medical rehabilitation, physical training and the like. According to the system, through multi-modal data fusion and self-adaptive resource scheduling, the data integrity, the real-time performance and the biomechanical analysis capability are remarkably improved, and an efficient solution is provided for human motion digitization.

The invention provides an intelligent scoring method and system for joint movement. The method comprises the following steps: acquiring six-degree-of-freedom inertial motion data and surface electromyogram signals, and establishing a motion sequence topological structure containing a space-time reference based on a dynamic sampling strategy; secondly, decomposing inertial data into rigid body and physiological tremor components, and generating a three-dimensional biomechanical model containing joint rotation center drift, multi-plane coupling errors and trajectory curvature; secondly, constructing a time-varying mapping relation between the surface electromyogram signals and the exercise load, segmenting the signals based on phase mutation points, analyzing phase synchronism of an active muscle group and an antagonistic muscle group, and extracting a muscle cooperation mode; and finally, generating a motion feature tensor in a four-dimensional space-time coordinate system through technologies such as space-time coupling and a dynamic transfer function, analyzing an evolution mode of the motion feature tensor in real time to construct a scoring function cluster, and generating a composite scoring value. According to the technical scheme provided by the invention, the accuracy and reliability of joint movement quality evaluation are remarkably improved.

The invention relates to the technical field of robot control and somatosensory interaction, and particularly discloses a knee joint exoskeleton robot control system based on somatosensory interaction. The system comprises a somatosensory signal acquisition and fusion module, a personalized dynamic model construction module, an adaptive intention decision module, a variable impedance compliance control module and a rehabilitation process evaluation and parameter self-tuning module. Through cooperative work of the modules, precise recognition of the motion intention of a wearer, online construction of an individualized biomechanical model and flexible and adaptive motion control are achieved, control parameters can be automatically adjusted according to the rehabilitation process, and therefore the flexibility and individuation level of man-machine interaction and the effectiveness of rehabilitation training are improved.

The invention discloses a piano playing posture dynamic correction method and system based on multi-dimensional data, and relates to the technical field of posture correction, and the method comprises the steps: collecting the multi-dimensional data of a player in real time through vision, pressure and electromyographic signal sensors, and generating an original data set; performing cleaning, noise reduction and feature extraction on the original data set, generating a preprocessed data set, and extracting biomechanical feature parameters; based on the extracted biomechanical characteristic parameters, a biomechanical model reflecting the posture state and the potential deviation of the player is constructed, and through multi-dimensional data acquisition and fusion, deep learning model analysis and a closed-loop optimization system, the posture state and the potential deviation of the player can be analyzed. The problems that an existing piano playing posture correction method cannot dynamically monitor in real time, accurately recognize posture deviation, provide personalized correction suggestions and continuously optimize the correction effect are solved.

The invention discloses an intelligent identification method and device for rotator cuff injury, and relates to the technical field of rehabilitation medicine, and the method comprises the steps: constructing a data collection module, collecting rotator cuff motion data in a motion capture mode, an electromyographic signal mode and a medical image mode, and carrying out the time-space alignment and fusion processing of the collected data through a Kalman filter; carrying out biomechanical modeling on the basis of the fused data, carrying out intelligent identification analysis on a biomechanical model by adopting improved convolution operation, carrying out spatial information fusion in combination with a graph convolution network, and outputting global motion state representation by self-adaptive expansion convolution; and based on the global motion state representation, dividing risk levels, predicting damage risks in real time, and providing an early warning signal. According to the method, the association mechanism of the multi-dimensional sensor data and the risk level is established, so that the shoulder joint movement risk can be accurately evaluated in real time. The shoulder joint injury prevention effect is remarkably improved, and the sports injury risk is effectively reduced.

The invention provides an elbow joint prosthesis installation position evaluation method and device, electronic equipment, a storage medium and a program product, and the method comprises the steps that an elbow joint biomechanical model of an implanted prosthesis is constructed, and the model comprises a skeleton prosthesis model and a muscle model which are coupled, the skeleton prosthesis model comprises a humerus prosthesis equivalent mass block and an ulna prosthesis equivalent mass block; acquiring a plurality of pieces of to-be-evaluated position data of the prosthesis rotation axis, wherein each piece of to-be-evaluated position data is used for representing a to-be-evaluated position of the prosthesis rotation axis between the two prosthesis equivalent mass blocks; for each piece of to-be-evaluated position data, based on a prosthesis rotation axis corresponding to the to-be-evaluated position data, performing motion simulation calculation on the elbow joint biomechanical model implanted with the prosthesis by using a dynamics method to obtain muscle force data of reference muscles in the muscle model; and determining an evaluation result of each piece of to-be-evaluated position data according to the muscle force data corresponding to each piece of to-be-evaluated position data.

The invention relates to the technical field of training assistance, and provides a training assistance system for five-poultry paddling and tiger paddling actions, which comprises a data acquisition module, an action recognition module, a whole body coordination evaluation module and a user interface module. The data acquisition module is used for acquiring motion data when a user executes a tiger play action through a plurality of sensor groups; the action recognition module performs preprocessing and feature extraction on the collected data, decomposes the tiger play action into a basic action sequence, and recognizes the matching condition of the current action and a standard action template through a deep learning network; the whole body coordination evaluation module establishes a biomechanical model based on a reverse dynamics method, calculates multi-dimensional coordination indexes including joint angle change, mechanical load distribution and dynamic stability, and generates an action coordination score through a support vector regression model; and the user interface module is used for displaying identification and evaluation results and providing improvement suggestions when the actions do not conform to specifications or the coordination is insufficient.

The invention discloses an exoskeleton manipulator control method which comprises the following steps: constructing a hand biomechanical model, defining the degree of freedom of finger joints, and carrying out joint division modeling based on a drive kinetic equation of a Bowden cable; deploying a high-density sensor on the hand; s3, a hand specificity Bouc-Wen model is improved, an inter-finger coupling term is introduced to correct a lag state equation, and micro-lag parameters are identified through a hierarchical identification algorithm; s4, designing a self-adaptive cooperative control strategy, realizing fuzzy mapping from the electromyographic signals to the joint torque, and optimizing a cooperative tracking error through a multi-joint parameter coupling self-adaptive law; s5, dynamically compensating the mechanical resistance of the hand by adopting the corrected double-Kalman filter; and S6, optimizing closed-loop execution and a security policy. According to the exoskeleton manipulator control method, through the improved Bouc-Wen model and the self-adaptive cooperative control strategy, the mapping relation between the electromyographic signal and the action of the manipulator can be effectively processed, and the exoskeleton manipulator control method adapts to different operation environments.

The invention discloses a hip joint rehabilitation method and system based on multi-parameter real-time monitoring and digital twinning, and the method and system are used for postoperative monitoring of hip joints of patients, and the method comprises the steps: S1, collecting medical image data of the patients, and constructing a hip joint biomechanical model of the patients; acquiring a myoelectricity activity signal, a hip joint activity angle and joint bearing pressure of the hip of the patient after the operation; s2, constructing a hip joint digital twinning model of the patient, and dynamically updating the state of the hip joint digital twinning model; s3, guiding the patient to perform rehabilitation training through the intelligent display terminal; s4, collecting and recording rehabilitation myoelectricity activity signals, rehabilitation hip joint activity angles and rehabilitation joint bearing pressure of the hip of the patient in the rehabilitation process in real time, judging the rehabilitation stage of the patient, and dynamically adjusting a rehabilitation training scheme. In the rehabilitation process, the rehabilitation training scheme is dynamically adjusted according to the rehabilitation condition of the patient, and the effectiveness and safety of the rehabilitation process of the patient are guaranteed.

The invention belongs to the field of numerical modeling, and particularly relates to a human body biomechanical model generation method, human body geometric models of different age groups are obtained based on anatomy and a reverse modeling method, and rapid mapping generation of human body biomechanical models of corresponding age groups can be rapidly completed only through matching of a plurality of geometric feature points. The generation difficulty of human body biomechanical models of other age groups is greatly reduced, the modeling efficiency is improved, and meanwhile, the precision of generating the human body grid model can also be ensured. According to the method, high-fidelity biomechanical models of key impact parts such as the head, the neck and the chest are established on the basis of anatomy, then connection between the head and the neck and connection between the neck and the chest are achieved by referring to the connection mode of human organs / tissues, physical verification of the effectiveness of the models is carried out on the basis, and the precision and reliability of the models are guaranteed.

The invention relates to the technical field of gait analysis, and discloses a Transform structure-based gait plantar pressure intelligent prediction system, which comprises a gait acquisition platform, a plantar pressure acquisition device, a gait kinematics acquisition device, a central processing server and a display terminal. The system obtains initial plantar pressure distribution through a lower limb multi-rigid-body chain type biomechanical model and foot-ground contact mechanics solution; and a gating prefix memory sliding window Transform is constructed in the central processing server, time sequence modeling and spatial correction are performed on the initial pressure matrix and the gait features, and a plantar pressure prediction result conforming to the biomechanical law is generated. The system effectively solves the problems that a traditional method is unstable in prediction, weak in generalization ability and lack of interpretability, plantar pressure prediction with higher precision is achieved, and the system can be used for gait evaluation, rehabilitation training and orthosis customization.

The invention relates to the technical field of bone biomechanical simulation, and discloses a bone biomechanical modeling method and system based on a multi-modal image, and the method comprises the steps: S1, collecting a CT image and an MRI image of a to-be-detected bone structure, and generating a multi-modal image; s2, adopting a depth variation inference algorithm to extract common features of the multi-modal images, adopting a generative adversarial network algorithm to optimize the common features, and performing information fusion on the multi-modal images to generate comprehensive image data; s3, reconstructing a three-dimensional bone structure model based on the comprehensive image data; s4, simulating mechanical property parameters of the three-dimensional bone structure model under different external loads and physiological states by adopting a nonlinear finite element method based on the three-dimensional bone structure model, and outputting mechanical properties of bone tissues; and S5, based on the three-dimensional bone structure model and the mechanical characteristics of the bone tissue, generating a personalized bone biomechanical model by using a depth variation inference algorithm. According to the method, an accurate personalized bone biomechanical modeling scheme can be provided.

The invention discloses an exercise management method and system for musculoskeletal chronic pain, and relates to the technical field of exercise management rehabilitation, and the method comprises the steps: building a biomechanical model for a patient through finite element analysis software, determining an optimal exercise mode according to the pain mode and the activity ability of the patient, and generating an exercise track through a path planning algorithm, on the basis of micro-current collaborative feedback data, the pain change trend of the patient is calculated, and a motion adjustment plan is generated, a biomechanical model can truly reflect the force distribution conditions of the patient under different motions, the safety of a motion scheme is remarkably improved, and the potential injury risk is reduced; scientific basis is provided for dynamically adjusting the exercise intensity, the obtained exercise adjusting plan can respond to the state change of the patient in time, and the intelligent level and the long-term curative effect of rehabilitation management are further enhanced.

There is provided a system for generating a motion performance metric of a moving human subject. The system includes a single stationarily supported motion capture device in the form of a smartphone having a camera configured to capture from a predetermined capture position, visual data of the subject as the subject moves (for example, by walking, jogging and / or running) between two distance calibration markers that are disposed at a predetermined distance apart from each other and in a field of vision of the camera. The system further includes a central data processing server in communication with the smartphone. The server is configured to initially recognise, from the captured visual data, a plurality of human pose points on the subject. The server then is able to extract kinematic data of the subject based on the recognised human pose points and then subsequently construct, based on the extracted kinematic data, a biomechanical model of the motion of the subject. The server then formulates a motion performance metric based on the constructed biomechanical model.

The invention relates to the technical field of shoes, and discloses a foot self-adaptive support adjusting method based on a biomechanical model, which comprises the following steps: S1, foot biomechanical modeling: acquiring foot geometric data of a user through three-dimensional scanning, acquiring dynamic load parameters in combination with gait analysis, and constructing a personalized foot finite element model; s2, stress distribution calculation: sampling according to 0-100% phase intervals of 10% in a gait cycle; s3, material gradient design: determining a gradient material rigidity mapping relation according to Pmax distribution; and S4, realizing a self-adaptive structure: constructing a gradient sole structure through 3D printing. A high-shear-force area is judged through double threshold values, and a pressure gradient self-adaptive non-uniform honeycomb structure and configuration classification are arranged in the area, so that local deformation is dynamically regulated and controlled in a pedaling and stretching period and a landing period, and the effects of reducing a stress peak value of the high-shear area and reducing friction heat accumulation are achieved.

A system for surgical planning and assessment of spinal pathology or spinal deformity correction in a subject, the system comprises a control unit configured to align one or more vertebral bodies of a biomechanical model to one or more vertebral bodies of the radiograph. The control unit is configured to receive one or more spinal correction inputs. The control unit is configured to, based on the received one or more spinal correction inputs, simulate the biomechanical model in a predetermined posture. The control unit is configured to provide for display one or more characteristics of the simulated biomechanical model.

A computer implemented method includes retrieving data from a patient's updated electronic medical record relevant to a diagnosis of a disease. The data includes medical images and at least one of the patient's demographic data, morbid symptoms, vital signs, medications, surgery history, family medical history, genetic data, laboratory test data, diseases records, allergies, and medical insurance information. The method includes generating available treatment path options including at least one surgical treatment or intervention, using at least one model to predict at least one implication for each of the available treatment path options based on the data and simulated adverse outcomes of the at least one surgical treatment or intervention simulated by predictive models including a biomechanical model based on the medical images. The method includes interactively updating and displaying a decision tree including the available treatment path options each with a corresponding at least one objective function.

The present application relates to the technical field of gait analysis, and discloses a gait plantar pressure intelligent prediction system based on a Transformer structure, which comprises a gait collection platform, a plantar pressure collection device, a gait kinematics collection device, a central processing server and a display terminal. The system obtains initial plantar pressure distribution through a lower limb multi-rigid-body chain biomechanical model and foot-ground contact mechanics solution; and constructs a gated prefix memory sliding window Transformer in the central processing server, performs time series modeling and spatial correction on the initial pressure matrix and gait characteristics, and generates plantar pressure prediction results conforming to the biomechanical law. The system effectively solves the problems of unstable prediction, weak generalization ability and lack of interpretability of traditional methods, realizes higher-precision plantar pressure prediction, and can be used for gait evaluation, rehabilitation training and orthosis customization.

This application belongs to the field of numerical modeling, and particularly relates to a method for generating a human biomechanical model. By using anatomical and inverse modeling methods, geometric models of the human body at different ages are obtained. Through the matching of only several geometric feature points, the rapid mapping generation of the human biomechanical model corresponding to the age can be quickly completed, greatly reducing the difficulty of generating the human biomechanical model of other ages, improving the modeling efficiency, and at the same time ensuring the accuracy of the generated human mesh model. Based on anatomy, highly realistic biomechanical models of key impact parts such as the head, neck, and chest are established. Then, referring to the connection methods of human organs / tissues, the connection between the head and the neck, and between the neck and the chest is realized. On this basis, physical verification of the model effectiveness is carried out to ensure the accuracy and reliability of the model.

The application discloses a kind of Chinese fifth percentile old male passenger injury bionical model with sign, also called biomechanical model, is the digital computing tool in the technical field of intelligent high-end detection equipment of automobile safety.This application is based on the fifth percentile male automobile passenger injury bionical model of thurstone, its each part is adjusted with age-related change to represent old male.The injury bionical model provided by the application meets the Chinese fifth percentile old male sign parameter;The model has detailed human anatomy structure characteristics.The Chinese fifth percentile old male passenger injury bionical model developed and constructed in the application not only provides a high-fidelity simulation tool for studying the injury mechanism of Chinese old passengers during the collision process, but also helps to deepen the understanding of the complex relationship between age change, body geometry and tissue mechanical properties and injury risk.

The invention discloses a wearable robot assistance parameter adjusting method and system based on a biomechanical model, relates to the field of wearable robots, and solves the problem that a current wearable robot cannot intelligently adjust an assistance torque and a damping coefficient. The method comprises the following steps: constructing a test single-step period standard deviation and a standard plantar pressure interval of legs of a wearer; according to the difference value, selecting an initial assistance torque and an initial damping coefficient when the current wearer uses the wearable robot; analyzing plantar pressure at different time nodes after the wearer uses the wearable robot to assist; whether the wearable robot needs to be adjusted or not is analyzed according to the actual plantar pressure and the actual single-step cycle standard deviation; according to the plantar pressure deviation rate and the single-step period deviation rate, the initial power assisting torque and the initial damping coefficient of the wearable robot are adjusted. According to the method, adaptive adjustment of the power assisting parameters of the wearable robot is achieved according to the plantar pressure deviation data and the single-step period deviation data.

The present invention discloses a control method for an exoskeleton manipulator, including: constructing a hand biomechanical model, defining the degrees of freedom of finger joints, and performing joint-by-joint modeling based on the driving dynamics equation of the Bowden cable; deploying high-density sensors on the hand; S3: improving the hand-specific Bouc-Wen model, introducing an interphalangeal coupling term to correct the hysteresis state equation, and identifying the micro-hysteresis parameters through a hierarchical identification algorithm; S4: designing an adaptive cooperative control strategy to achieve a fuzzy mapping from electromyogram signals to joint torques, and optimizing the cooperative tracking error through a multi-joint parameter coupling adaptive law; S5: using a modified dual Kalman filter to dynamically compensate for the mechanical resistance of the hand; S6: optimizing the closed-loop execution and safety strategy. The control method for the exoskeleton manipulator of the present invention can effectively process the mapping relationship between electromyogram signals and the actions of the manipulator and adapt to different operating environments through the improved Bouc-Wen model and the adaptive cooperative control strategy.

The present invention relates to a device (1) and method for generating a geometrical model (33) and a 3D biomechanical model (31) of a spine of a patient and assisting a user in planning a spine treatment for said patient's spine. The present invention further relates to a surrogate model. The 3D biomechanical model (31) and the surrogate model may be configured to generate biomechanical performance indicators and clinical indicators.

The application relates to a method for estimating the biomechanical parameters of in-vivo organ tissues, which comprises the following steps: in-vivo organ tissue geometry modeling is performed to obtain a tetrahedral mesh structure of the in-vivo organ tissues; according to the obtained tetrahedral mesh structure of the in-vivo organ tissues, in-vivo organ tissue biomechanical model modeling is performed; according to the in-vivo organ tissue biomechanical model, in-vivo organ tissue boundary condition estimation is performed; and the strong tracking Kalman filter is used to estimate the biomechanical parameters of the in-vivo organ tissues under the current boundary condition estimation result. The application can estimate the biomechanical parameters of in-vivo organ tissues of human bodies under complex boundary conditions, and the estimated biomechanical parameters are more accurate.