154 results about "Biomechanical testing" patented technology

The invention belongs to the technical field of early warning of diseases, and discloses a knee joint disease early warning system based on biomechanical analysis, which comprises a data acquisition module, a data analysis module, a main control module and an early warning module, the knee joint disease early warning system based on biomechanical analysis has the expected effects that the knee joint disease early warning system based on biomechanical analysis is provided, and a patient is helped to discover and take intervention measures in the early stage of knee joint diseases through real-time monitoring and early warning, so that the disease progress is delayed, and the life quality of the patient is improved. Meanwhile, the system provides a powerful tool for clinicians and rehabilitators and is used for formulating personalized rehabilitation treatment schemes.

The embodiment of the invention relates to the technical field of man-machine interaction, and discloses a joint data feedback method and device based on a flexible sensor, a medium and a product. The method comprises the following steps: determining a time sequence calibration feature set according to a multi-source synchronization signal of a flexible sensor array; according to the time sequence calibration feature set, determining a joint function evaluation result and an action classification result; in combination with the joint function evaluation result, according to the deviation between the action classification result and a preset biomechanical standard library, joint dynamic function deviation data are determined; determining a biomechanical feedback instruction of the wearable device according to the joint dynamic function deviation data; wherein the biomechanical feedback instruction is matched with the functional state corresponding to the joint function evaluation result, and the method and device can be at least used for solving the technical problems that in the related technology, joint functions and actions are not accurate in recognition, and precise personalized control is difficult to achieve.

The invention relates to the technical field of biomechanical detection and automobile safety evaluation, and discloses an automobile collision dummy abdomen safety test device and method. The testing device comprises a human body feature modeling module which is used for establishing a target population abdomen parameterized model based on statistical analysis, determining a key size design domain covering target population percentile and constructing a target population metrology database; the abdominal mechanical property simulation module is used for obtaining a human tissue relative density distribution function based on the hyperelastic constitutive model, taking the density distribution function as an input parameter for manufacturing a gradient honeycomb structure and simulating human abdominal mechanical properties through relative density gradient distribution in the thickness direction; the multi-mode sensor integration module adopts a distributed intelligent sensing network architecture and is composed of a sensing layer, a transmission layer and a processing layer. By integrating pressure, deformation, acceleration and tissue stress sensors and combining a real-time feedback algorithm, collision parameters are dynamically optimized, and the test precision and the biological fidelity are improved.

Systems and methods are disclosed for generating and providing guided practices and coaching feedback (e.g., illustrated in 3D images, video, or audio) that allow users performing sports activities to follow along to improve their physical movements in a digital environment. The feedback may be provided with a 3D avatar using a biomechanical analysis of observed actions with a focus on representing actions through computer-generated 3D avatars. Physical quantities of biomechanical actions can be measured from the observations, and the system can analyze these values, compare them to watchlist values, animate the 3D avatar based on the measurements, and display the 3D avatar on a computer-generated user interface.

A system for acquiring, standardizing and evaluating biomechanical kinematics data of a joint includes a device for acquiring biomechanical kinematics of the joint and processing it in a computer-readable manner. A display device displays visual output to a user. A control unit processes the kinematics and determines a progression of kinematics parameters of the joint with respect to a first joint element with a first joint coordinate system and with respect to a second joint element with a second joint coordinate system. A standardization unit determines, via a predetermined target optimization, a transformation for adjusting an orientation and / or position of the first and / or second joint coordinate system to carry out a standardization, and output an evaluation via the display device. A method is used to acquire, standardize and evaluate biomechanical kinematics data of a joint, and can be executed by a computer with a computer-readable storage medium.

A method for evaluating a user's performance of a medical procedure is disclosed. The method comprises receiving a plurality of training measured metrics collected from a sensor worn by the user during training medical procedures, where these metrics include physiological and biomechanical parameters. An algorithm is trained to identify types of medical procedures, procedural segments, and performance benchmarks. During the medical procedure, the sensor collects similar metrics, which are analyzed to identify the procedure type, procedural segments, and deviations from benchmarks. Feedback is provided based on these deviations. Additional steps include using a training model comprising a neural network with machine learning algorithms to analyze metrics, updating the training model with new data, initiating sensor calibration, detecting a predetermined movement pattern to start data collection, and identifying spatial reference points. The method further comprises providing real-time feedback to the user through haptic, auditory, and visual modalities based on performance deviations.

Some aspects of the described technology may include a method, including inducing a wave field in a biological sample, the wave field comprising waves having a wave frequency, scanning the sample at a scanning velocity to perform a plurality of spatial measurements of the sample, determining spatial data from the plurality of spatial measurements, amplitude demodulating the spatial data based on the wave frequency and the scanning velocity, and generating displacement data for the biological sample based on the amplitude demodulated spatial data.

The invention belongs to the technical field of shoe customization, and particularly discloses a shoe adaptation customization method and system based on multi-dimensional foot feature detection, and the system comprises a multi-dimensional foot feature detection system, a balance and gait function evaluation system, a scoring system and a screening and matching system. The multi-dimensional foot feature detection system and the balance and gait function evaluation system send detected data to the scoring system for typing and scoring; the scoring system sends a scoring result to the screening and matching system, and the screening and matching system carries out screening and matching on the outsole and the insole according to the scoring result. According to the technical scheme, joint analysis of the foot form and the functional parameters can be achieved, and comprehensiveness of foot biomechanical evaluation is improved.

The invention discloses a falling risk assessment method and system based on a plantar pressure insole, equipment and a medium, and the method comprises the steps: obtaining plantar pressure data of a subject synchronously collected in a standardized TUG test process, and obtaining a clinical scale assessment result of the subject; the method comprises the following steps: preprocessing plantar pressure data of a subject, and extracting plantar pressure features and TUG time features; associating the extracted feature vector with a tumble risk tag evaluated by a subject scale, and constructing a data set with a tag; training a machine learning classification model by using the constructed data set; and inputting the feature vector of a to-be-evaluated subject into the trained classification model to obtain the fall risk level of the subject. According to the method, the falling risk can be objectively, quantitatively and comprehensively assessed in natural actions, clinical convenience and data scientificity are both achieved, TUG full-cycle biomechanical information can be completely captured in conventional environments such as communities and clinics, and a more accurate and interpretable assessment result is provided.

According to a first aspect of the present invention, it may be provided a computer- implemented athletic performance monitoring method. The method may comprise receiving input data including biomechanical measurement data captured by a sensor module of an article of footwear worn by a user engaged in an athletic activity. Furthermore, the method may include processing, preferably automatically processing, the input data using artificial intelligence to generate athletic performance information. This processing may involve generating a prompt for a generative language model based at least in part on the input data, prompting the generative language model using the prompt to obtain a reply, and generating the athletic performance information based at least in part on the reply from the generative language model. Additionally, the method may comprise causing displaying the athletic performance information to the user on a display screen of an electronic device of the user.

The invention discloses an athletic injury risk screening system based on motion capture and biomechanical analysis, and relates to the field of athletic injury risk screening, and the system comprises a standardization module which is used for establishing a grouping reference value database and a to-be-detected person exclusive file; the data acquisition module is used for acquiring three-dimensional action data of a person to be detected and preprocessing the data; the feature vector module is used for calculating joint feature parameter values of the moving joints in three moving planes based on an inverse dynamics method and constructing biomechanical feature vectors; the model construction module is used for constructing an athletic injury risk assessment model and outputting a comprehensive risk level and a specific risk mode label and probability; and the model training and verification module is used for performing staged training on the model and verifying the feasibility of the model. The method has the advantages that multi-modal biomechanical and kinematic data are fused, and accurate assessment of the sport injury risk and comprehensive identification of a specific risk mode are realized.

The invention relates to the technical field of medical imaging, in particular to a pelvic stability dynamic detection method and stress analysis system based on dynamic DR. The method comprises the steps that on the basis of sign information of a user, parameters of a three-dimensional infrared motion capture system, a force measuring table and a pressure sensor are adapted to obtain static CT or MRI image data of a pelvis of a patient, and then the pelvic stability dynamic detection method and stress analysis system are obtained; establishing a pelvis coordinate system and defining geometric features of key points; collecting to-be-detected data of a user in the load bearing state; preprocessing the collected user data, and reconstructing a three-dimensional pelvis model of the user; performing biomechanical analysis based on the reconstructed three-dimensional pelvis model of the user to generate a pelvis stability index; and according to the pelvic stability index, automatically generating a pelvic stability risk index, and outputting a clinical decision suggestion. The problems that a traditional pelvis detection method still depends on a static image, dynamic stress distribution and stability evaluation cannot be effectively quantified, and an evaluation result is not accurate enough are solved.

The invention relates to the technical field of biomechanics, in particular to an imitated physiological load loading device and system. The simulated physiological load loading device comprises a main frame body, a sample mounting frame, a loading piece and a plurality of loading mechanisms; the sample mounting frame is connected with the main frame body and is used for mounting a sample; the plurality of loading mechanisms are connected with the main frame body, and the loading piece is in transmission connection with all the loading mechanisms; wherein the loading part is used for moving relative to the main frame body under the driving action of one or more loading mechanisms, so as to apply one or more loads of compression, rolling and sliding to the sample in the sample mounting frame. According to the simulated physiological load loading device, the simulated physiological load applying of compression, rolling and sliding coupling can be realized, so that obvious deviation between experimental data and an in-vivo actual mechanical environment can be avoided.

The invention provides a lifting displacement machine attitude optimization method and system based on biomechanical analysis, and relates to the technical attitude optimization field, and the method comprises the following steps: obtaining operator somatosensory data, building a man-machine interaction model to calculate joint stress, and mapping the somatosensory data into a control instruction; a deep reinforcement learning network online optimization model is used, and physical exhaustion minimization and task efficiency maximization are taken as targets; and acquiring stress data in real time to evaluate the motion state and generate a correction instruction to adjust the motion posture. User experience is emphasized, and uniform stress of a patient is ensured through real-time force feedback and posture optimization; establishing a data file to monitor vital signs; a friendly interaction interface and voice prompt are provided, so that the psychological burden of the patient is relieved; scientific displacement postures can assist in evaluating the rehabilitation progress. According to the invention, the working intensity of an operator can be reduced, the safety and comfort of a patient in a displacement process are obviously improved, the win-win situation of medical staff and the patient is realized, and the occupational injury risk of the medical staff is effectively reduced.

The utility model discloses an oral biomechanics capsule type detector, which comprises a main body made of an elastic material and provided with a tooth stress area for receiving tooth occlusion and a tongue and lip stress area for receiving tongue pressing and / or lip furling pressure; the capsule type detection structure comprises a plurality of cavities which are formed in the main body and are communicated with one another and a pressure sensor used for measuring the pressure of an integral cavity formed by the plurality of cavities, and the tooth stress area and the tongue and lip stress area are each provided with at least one capsule type detection structure. The measuring device can be used for measuring tooth occlusal force, lip smoothing force and tongue force in the upper jaw jacking direction, has the characteristics of simple structure, safety, sanitation, high comfort level, reliability in measurement, convenience in operation, reusability after cleaning and the like, is beneficial to clinical evaluation and diagnosis, and provides an effective auxiliary means for oral rehabilitation and orthodontic treatment.

The invention provides a running test system, method and device based on artificial intelligence, and the system comprises a dynamic airflow sensing module, a sole biomechanics collection module, an electromyographic signal processing module, an AI cooperative calculation module, and a test result output module. The dynamic airflow sensing module is used for collecting environment wind speed, running relative speed and body posture angle and generating airflow related data, and the sole biomechanical collecting module is used for collecting sole peak pressure, contact time and contact angle and generating biomechanical data; the electromyographic signal processing module is used for collecting an electromyographic energy value and an electromyographic change rate and generating electromyographic data, and the AI cooperative calculation module is electrically connected with the dynamic airflow sensing module, the sole biomechanics collecting module and the electromyographic signal processing module. The running performance evaluation accuracy and the damage early warning timeliness can be improved.

A system is provided.SOLUTION: A system comprising: means for collecting performance data of an athlete; means for performing a biomechanical analysis to identify abnormal movements and loads; means for suggesting a personalized training program based on the analysis; and means for providing real-time advice and care to the athlete.SELECTED DRAWING: Figure 1

The present application relates to the technical field of medical data processing, in particular to a preoperative femoral head collapse risk prediction system based on biomechanical analysis, the execution steps of the system comprising: obtaining the pressure monitoring set and the marker position coordinates of each monitoring point in the necrotic area of the femoral head of a plurality of patient samples; determining the daily wear performance degree and the local potential risk degree of each patient sample according to the pressure monitoring set and the marker position coordinates; and performing data fusion analysis on the daily wear performance degree and the local potential risk degree of the same patient sample to determine the multi-dimensional comprehensive risk assessment value of each patient sample. By determining the multi-dimensional comprehensive risk assessment value, the present application ensures that the prediction model can make accurate judgments based on the mechanical function of the skeleton rather than just the appearance, thereby improving the prediction accuracy of the model.

A biomechanical testing system includes a reactor module, a storage unit and a pneumatic pressure source. The reactor module includes an upper board, a lower board, a positioning board disposed between and cooperating with the upper and lower boards to define an airtight space, a position-limiting member received in the airtight space, and at least one biological culture material positioned in the airtight space by the position-limiting member. The storage unit is adapted to supply a liquid to the airtight space. The pneumatic pressure source is controllable to supply gas to the storage unit so as to drive the liquid to flow from the storage unit into the airtight space and through the at least one biological culture material.

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 application relates to a biomechanical detection device for disease diagnosis, comprising: a pressure measurement module for measuring a pressing force, the pressure measurement module comprising a pressure sensor, a sensing contact of the pressure sensor being in contact with a to-be-detected surface; the displacement measurement module is used for measuring the pressing displacement, the displacement measurement module comprises a displacement sensor, the displacement sensor comprises a measurement sliding block, and the measurement sliding block is matched with the sensing contact; when the biomechanical detection device is in a detection state, the sensing contact extends out of the measuring sliding block to press the to-be-detected surface, so that the to-be-detected surface is deformed, and meanwhile, the pressure value of the to-be-detected surface and the displacement of the sensor contact are obtained and measured. The invention further relates to a detection system. By pressing the detection device, the measurement sliding block moves relative to the sensing contact, the detection device can measure the pressure value of the surface to be measured and the displacement of the sensor contact at the same time, and the measurement result is accurate and reliable.

An in-vivo testing device is disclosed for dynamically measuring the mechanical properties of skin. The device includes a horizontal reciprocating tensile stress-strain detection unit configured to contact the skin surface and acquire displacement and tensile force data, wherein the detection unit comprises at least two contact heads. A driving unit, equipped with a motor capable of outputting reciprocating linear motion perpendicular to the skin surface, is provided to drive the contact heads. A reversing unit converts the perpendicular reciprocating linear motion into a horizontal reciprocating tensile motion of the contact heads relative to the skin surface. The reversing unit includes at least one right-angle reversing lever connecting the driving unit and the detection unit. The disclosed device enables reliable evaluation of the dynamic viscoelastic properties of skin in a non-destructive manner, thereby providing accurate and repeatable characterization of skin biomechanics under in-vivo conditions.

The present application relates to the technical field of biomechanical detection and automobile safety evaluation, and discloses a device and method for testing the abdomen safety of a car crash dummy. The testing device comprises a human feature modeling module, a parameterized model of the abdomen of a target population is established based on statistical analysis, a key size design domain covering the target population percentile is determined, and an anthropometry database of the target population is constructed; an abdomen mechanical property simulation module, a human tissue relative density distribution function is obtained based on a super-elastic constitutive model, the density distribution function is taken as an input parameter for manufacturing a gradient honeycomb structure, and the abdomen mechanical properties of the human body are simulated through the relative density gradient distribution in the thickness direction; and a multi-modal sensor integration module, a distributed intelligent sensing network architecture is adopted, and the multi-modal sensor integration module is composed of a perception layer, a transmission layer and a processing layer. Through integration of pressure, deformation, acceleration and tissue stress sensors, and in combination with a real-time feedback algorithm, collision parameters are dynamically optimized, and the testing precision and biological fidelity are improved.

The invention provides a pillow bearing performance test method and system, and relates to the technical field of pillow detection. Aiming at the problem that a test method in the prior art does not meet test requirements, the method comprises the following steps: selecting a corresponding standardized human body model according to a to-be-tested pillow type target population, and arranging pressure sensing devices at key dissection test points; according to the biomechanical characteristics of the human body, carrying out structure correction on the key contact area of the standardized human body model; adjusting the corrected human body model to a preset sleep posture, and performing multi-degree-of-freedom posture compensation fine adjustment to enable the position relationship between the corrected human body model and the pillow sample to be tested to meet a set reference; continuously collecting pressure related data of each test point; the same preset sleep posture is repeatedly tested for preset times, the collected pressure related data are analyzed and calculated, bearing performance quantitative indexes are obtained, and the quantitative indexes comprise the average pressure, the pressure peak value and the pressure gradient. The test method provided by the invention meets objective, repeatable and bionic quantitative test requirements.

A method of measuring at least one biomechanical property of a reproductive cellular structure is provided. The method includes illuminating the reproductive cellular structure with radiation; detecting at least a portion of radiation scattered from the illuminated reproductive cellular structure; analyzing a frequency spectrum of the detected scattered radiation to identify at least one Brillouin frequency shift in the frequency spectrum; and determining the at least one biomechanical property based on the Brillouin frequency shift. The method further includes determining a viability index of the reproductive cellular structure based on the at least one biomechanical property.

The invention discloses a method and device for tracking foot movement in a shoe wearing state in the technical field of movement tracking, and the method comprises the steps that a test shoe body matched with a tester is selected, the test shoe body comprises a detachable upper vamp and a running shoe midsole, and the upper vamp is provided with a plurality of test holes. The detachable upper vamp and the running shoe midsole are installed in a matched mode, the multiple testing holes are formed in the upper vamp, when the testing shoe body is matched with the foot of a tester, the multiple testing holes are used for installing the identification body, the identification body stably and accurately displays the corresponding motion tracking point position of the foot externally, and therefore the testing shoe body is convenient to use. Motion information of the motion capture system is conveniently captured, then a motion model is established through motion analysis software, foot motion postures are accurately analyzed, biomechanical properties of materials and structural design of the running shoe midsole are evaluated, meanwhile, the detachable running shoe midsole is replaced according to different requirements, and then performance evaluation is conducted on different running shoe midsoles. The application range is wide.

The invention discloses a cervical cancer interpolation after-loading treatment plan determination method and device, equipment and a medium, and belongs to the technical field of medical treatment. According to the embodiment of the invention, a biomechanical simulation technology is utilized, only the diagnosis image shot by the patient recently needs to be acquired, and more personalized interpolation template shape design is realized, so that repeated CT shooting is avoided, the problems of complex process and discomfort of the patient are solved naturally, the working process is simplified, and the working efficiency is improved. According to the method, the efficiency of personalized design of the interpolation template is improved, the 3D printing template which has more degrees of freedom and conforms to the characteristics of the focus of a patient can be designed in the biomechanical simulation process, the defects of incomplete target region coverage and poor conformity are overcome, the degree of adaptation is high, and the applicability of the method is also improved.

This invention provides a rapid prediction method for the mechanical response of carpal tunnel structures based on a surrogate model, belonging to the field of biomechanical analysis technology. The method includes: constructing a complete three-dimensional geometric model of the carpal tunnel structure and applying palmar tensile loads and harmonic excitation loads; generating multiple sets of material property parameter combinations through random sampling, and constructing static and dynamic training datasets by combining the corresponding static and dynamic displacement responses; training a PCE surrogate model based on the static training dataset, and training both the PCE surrogate model and the SVR surrogate model based on the dynamic training dataset; inputting the material property parameters of the carpal tunnel structure to be predicted into the corresponding trained surrogate models, and outputting the predicted static and dynamic displacement responses of the carpal tunnel structure. This method overcomes the shortcomings of low efficiency and high computational cost in traditional finite element analysis, significantly improving computational efficiency while maintaining prediction accuracy, providing a scientific basis for the assessment of carpal tunnel syndrome.

A computer-implemented method for recommending an item of equipment, which comprises: gathering sensed data from a sensor; processing the sensed data in accordance with a biomechanical protocol to determine at least one performance indicator associated with a subject's execution of the biomechanical protocol; and determining at least one recommended feature of an item of equipment based at least in part on the at least one performance indicator. Also, an equipment recommendation system with specific application to hockey, which comprises: a camera configured to produce images representative of execution of a hockey shot of a given type by a subject; an I / O interface; and a processor connected to the camera via the I / O interface and configured to extract parameters from the images and to output, via the I / O interface, a hockey stick recommendation for the subject that is based on the parameters and on the given type of hockey shot.

The invention provides a scoliosis biomechanical testing method, and belongs to the technical field of scoliosis testing, and the scoliosis biomechanical testing method comprises sheep spine bending and nail bar implantation. Sheep spine bending comprises the steps of cutting a sheep spine, fixing an end cover, connecting a translation tool and a clamping tool, driving a middle vertebral body of the sheep spine to move so as to bend the sheep spine, releasing an intervertebral disc with the maximum bending degree, filling denture powder for fixing, and turning segments above and below a lateral convex part of the sheep spine back to be vertical; nail and bar implanting comprises bone nail hole drilling, bone nail implanting and bar implanting. The sheep spine is selected to simulate the human spine, high similarity is achieved, human scoliosis is completely simulated through specific steps of bending and nail bar implantation, and biomechanical testing on human scoliosis is facilitated.