24 results about "Biomechanical testing" patented technology

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.

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.

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.

This invention discloses a method and system for adjusting assist parameters of wearable robots based on a biomechanical model, relating to the field of wearable robots. It addresses the current problem that wearable robots cannot intelligently adjust assist torque and damping coefficient. The method involves: constructing the standard deviation of the single-step cycle and the standard plantar pressure range for the wearer's legs; selecting the initial assist torque and initial damping coefficient when the wearer uses the wearable robot based on the difference values; analyzing the plantar pressure at different time points after the wearer uses the robot; analyzing whether the wearable robot needs adjustment based on the actual plantar pressure and the actual single-step cycle standard deviation; and adjusting the initial assist torque and initial damping coefficient of the wearable robot based on the plantar pressure deviation rate and the single-step cycle deviation rate. This invention achieves adaptive adjustment of the wearable robot's assist parameters based on plantar pressure deviation data and single-step cycle deviation data.

This invention relates to the field of visual monitoring technology and discloses a method and system for monitoring the safety status of nursing staff. The method includes: performing three-dimensional posture reconstruction on the monitoring video of the nursing staff to obtain skeletal posture imaging; performing pixel-level semantic segmentation on the monitoring video to obtain the nursing staff's wearing status data; conducting a compliance assessment on the skeletal posture imaging based on the nursing staff's standard operating procedure document to obtain the nursing staff's operational standardization score; performing kinematic analysis on the skeletal posture imaging to obtain the nursing staff's biomechanical load index; conducting a multi-dimensional risk assessment on the operational standardization score, wearing status data, and biomechanical load index to obtain a comprehensive safety assessment result for the nursing staff; and encapsulating the comprehensive safety assessment result into a decision to obtain a safety status report for the nursing staff. This invention can improve the efficiency of monitoring the safety status of nursing staff.

This invention discloses a method for optimizing and simulating dental implant design based on AI simulation technology, belonging to the field of artificial intelligence simulation technology in oral medicine. The method includes acquiring three-dimensional scans of the patient's oral cavity and jawbone images, fusing and reconstructing them to generate a personalized digital oral model. The model is then input into a pre-trained biomechanical simulation AI agent. This AI agent automatically explores within a solution space composed of multiple preset candidate implant models and combinations of implantation pose parameters. For each candidate scheme, dynamic mechanical load simulation is performed in the digital model, simulating stress distribution, bone interface micro-strain, and long-term stability indicators under different chewing conditions. Based on the simulation results, a multi-objective evaluation is performed to generate a comprehensive score. The scheme with the highest score is selected as the initial optimization design, and a surgical planning blueprint is generated. This invention achieves automated and intelligent optimization of implant surgery plans and quantitative prediction of biomechanical prognosis.

A biomechanically realistic brain model for impact testing comprises white matter simulant materials and gray matter simulant materials positioned to correspond with anatomical brain structure. The white matter simulant comprises anisotropic hydrogels with embedded magnetically-responsive, electrically-responsive, thermally-responsive, and / or mechanically-responsive particles that exhibit directionally-dependent stress-strain responses. The gray matter simulant comprises isotropic hydrogels or silicones, particularly siloxanes, that exhibit uniform stress-strain responses to applied forces. The materials are cast, injected, printed, or formed in anatomically correct positions and share realistic interfaces. The brain model accurately imitates physical brain responses during impact tests, particularly angular impacts, providing realistic testing results for biomechanical analysis.

The application belongs to the field of biomechanical test data processing, and discloses a skin creep compliance construction method, system, device and storage medium. The method performs negative pressure suction test on the tested skin, obtains test parameters and original displacement-time data of the tested skin in the test process; identifies a test starting point, a creep starting point and a test termination point according to the change of the displacement of the tested skin with the test time; determines a compensation factor based on the displacement change amount from the test starting point to the test termination point and the displacement change amount from the creep starting point to the test termination point; compensates the displacement value of the tested skin based on the test parameters and the compensation factor, and obtains a creep compliance sequence according to a nonlinear calculation relationship.

This invention provides a digital intelligent MSE automatic design method based on biomechanical simulation, belonging to the field of biomechanical simulation technology. The method includes: acquiring three-dimensional morphological data and physiological load data of the target anatomical structure and mapping them to obtain a load distribution matrix; performing tensor operations on the load distribution matrix and tissue mechanical response characteristics to obtain a stress prediction field; identifying high-stress concentration areas and low-stiffness weak areas based on the stress prediction field; extracting contour curves and calculating the normal gradient to determine the expansion constraint direction; minimizing the stress distribution variance and the total tissue deformation energy and determining the spatial configuration parameters of the MSE device; using the spatial configuration parameters as boundary conditions to iteratively calculate the displacement field and strain field; correcting the spatial configuration parameters based on the difference between the cumulative deformation and a preset physiological threshold and the iterative deformation energy change rate; and outputting the corrected configuration parameters as design instructions when the convergence condition is met.

A passive, non-electronic wearable device (100) provides real-time visual biofeedback of soft tissue (130) elongation to prevent overstretch injuries. The device (100) comprises an elastic base layer (110) having a first periodic micro-pattern (112) and an elastic overlay layer (120) having a second periodic micro-pattern (122). The layers are superimposed and configured to elongate synchronously with the underlying soft tissue (130). When the soft tissue (130) reaches a predetermined biomechanical strain threshold, such as 22 to 34 percent elongation corresponding to a pre-pain safety limit, the relative geometric displacement between the first micro-pattern (112) and the second micro-pattern (122) generates a macroscopic Moiré interference pattern (140). This optical-mechanical interference visually exposes a hidden warning indicator (114) without requiring electronic components, power sources, or external sensors. The system can be integrated into athletic garments or worn as a standalone band.

The application relates to a posture recognition and posture evaluation method based on a wearable device and relates to the field of human posture detection. The method solves the problems of strong subjectivity, insufficient data dimension and limited evaluation accuracy of traditional posture evaluation which depends on manual observation or a single sensor. The method is as follows: a plurality of parts of an inertial measurement unit and a flexible plantar pressure sensor array are deployed and synchronously collected, time synchronization and other treatments are carried out, time windows of each action are determined by taking a sudden change point of a plantar pressure sequence as an event anchor point, a fusion feature vector is constructed, a deep evaluation is carried out in combination with a fusion feature vector for identifying a motion posture and a preset biomechanical model, differences between an action of a wearer and a standard action or a personal action feature baseline are quantified, and finally a personalized improvement report is generated. The method can be applied to the fields of football, volleyball, tennis and other sports evaluation fields, the fields of posture evaluation, motion control and intelligent manufacturing of industrial robots and man-machine cooperation.

This invention relates to the field of sports injury early warning technology, specifically to an artificial intelligence sports injury early warning system and method. The method includes: establishing a basic identity and health record for athletes; simultaneously collecting multimodal raw data including biomechanical data, physiological load data, and environmental parameter data during the athlete's exercise; processing the multimodal raw data; matching and comparing the feature dataset with a database of injury-prone behavior feature parameters; generating graded early warning information based on the risk probability interval when the probability of injury exceeds a preset dynamic threshold; and generating corresponding personalized intervention plans based on the graded early warning information. The system includes: an information filing module, a data acquisition module, a data preprocessing module, a risk assessment and early warning module, and an intervention feedback optimization module. This system enables the comprehensive capture of complex causes of sports injuries, improving the comprehensiveness and accuracy of injury risk assessment.

FIELD: stabilography.SUBSTANCE: invention relates to stabilography - quantitative assessment of biomechanical body stability (balance function), which is an important indicator of the physical characteristics of a particular person. The claimed stabilometer consists of a laser pointer and a photodetector in a light-proof box with an electronic circuit. Wherein the front wall of the box is a target with a central hole, and the laser pointer is fixed on the examined part of the body so that the subject visually controls the hitting of the laser spot on the centre of the target, wherein the amount of light passing into the photodetector per unit time interval is summed by the electronic circuit and as a quantitative measure of his psychophysiological stability is output to an electrical measuring instrument.EFFECT: creation of a stabilometer having high parameters of sensitivity and resolution, simple in design and maintenance.1 cl, 1 dwg

This application relates to a method and system for personalized teaching path planning for dance learners. The method includes: performing multimodal feature mapping based on the user's dance performance test data and physiological baseline data to obtain a dual-state profile of the user; extracting biomechanical features from demonstration movement data in a dance repertoire library to obtain a repertoire feature matrix; constructing a dance knowledge graph based on the dance repertoire library, standard movement specification library, and skill teaching syllabus; calculating collaborative filtering scores based on the user's dual-state profile, the repertoire feature matrix, and the dance knowledge graph to obtain a repertoire suitability set; and performing multi-objective path planning on the repertoire suitability set based on preset path planning constraints to obtain a personalized teaching path. This method can balance physiological safety with the coherence of teaching logic, generating a scientifically efficient personalized dance teaching path.

Sports shoe system (1) with integrated sensors, comprising a sensor insole (10) with piezoelectric pressure sensors (21-28) for measuring the pressure distribution under the foot and with bioimpedance electrodes (11-14) for measuring the electrical body impedance, characterized in that the sensor insole (10) and an electronic module (30) connected to it are jointly designed to calculate body weight from the pressure sensor signals (21-28), to determine body composition from the bioimpedance signals (11-14), to perform a three-dimensional reconstruction (60) of the foot position and gait pattern and to automatically generate personalized recommendations for orthopedic insoles (70) from this, wherein all measurements are performed simultaneously during sporting activity.

This invention provides a method and system for piglet weight assessment based on temporal features and attention mechanisms. The assessment method includes the following steps: S1, video stream preprocessing and dynamic target separation and tracking; S2, obtaining multi-dimensional dynamic features based on biomechanical dynamic features; S3, spatiotemporal attention feature fusion; S4, weight regression; S5, model training; and S6, dynamic weight assessment. This assessment method and system can effectively solve the problems of low effective data rate, lack of dynamic information, and insufficient robustness in existing single-frame static image piglet weight assessment, thereby improving the effective data utilization rate in complex breeding scenarios, increasing the accuracy of piglet fullness perception, and reducing the stringent environmental and posture requirements for engineering deployment.

This invention discloses a method for analyzing neck muscle impact injuries based on dummy experimental data, relating to the fields of biomechanical engineering and safety protection technology. The method includes the following steps: using neck motion trajectory parameters collected during dummy impact testing as boundary conditions for musculoskeletal model simulation; importing a pre-defined neck musculoskeletal model into the OpenSim platform, and geometrically scaling the model according to standardized dummy dimensions to obtain cervical joint angles, cervical joint loads, and the activation and force distribution of each muscle; and conducting an impact-induced muscle injury risk assessment based on the extracted peak muscle force, muscle activation sequence, and unit mass muscle energy absorption rate. This invention solves the problem that traditional methods cannot quantify deep muscle injuries under controllable conditions, providing a highly reliable engineering analysis tool for automotive safety design and protective equipment optimization.

The application provides a pillow supporting performance test method and system, and relates to the pillow detection technical field. In view of the problem that the test method in the prior art does not meet the test requirements, the application selects a corresponding standardized human body model according to a target human group of a pillow to be tested, and arranges a pressure sensing device at key anatomical test points; according to the human body biomechanics characteristics, the key contact areas of the standardized human body model are structurally modified; the modified human body model is adjusted to a preset sleeping posture, and multi-degree-of-freedom posture compensation fine adjustment is performed, so that the position relationship between the modified human body model and the pillow sample to be tested meets a set reference; the pressure related data of each test point is continuously collected; the preset sleeping posture is repeatedly tested for a preset number of times, and the collected pressure related data is analyzed and calculated to obtain supporting performance quantitative indexes, and the quantitative indexes include average pressure, pressure peak value and pressure gradient. The test method meets the objective, repeatable and bionic quantitative test requirements.

Various aspects of an object weight estimation system are described, to enable weight estimation of an object to be transferred from an object source (e.g., a human or an ambulatory robot) that holds the object using one or more arms. One technique includes: tracking an object to be transferred from the object source to a robot; identifying, from at least one image captured by the robot, a posture of the object source; identifying respective segments of the object source from the posture of the object source; determining an estimated weight of the object based on a center of gravity of the object source, as the center of gravity of the object source is calculated in real-time from a balance of the respective segments; and causing a responsive action with the robot, based on the estimated weight of the object.

A synthetic patient specific A benchtop beating heart simulator that is custom-fabricated using 3D printing technology based on patient-specific imaging data has been developed. The simulator employs soft robotics to accurately mimic the motion and biomechanics of the left atrium, with a particular focus on the left atrial appendage and conditions associated with Heart failure with preserved ejection fraction (HFpEF). This simulator is designed to recreate hemodynamics in a controlled benchtop setting, allowing for precise testing and evaluation of medical device designs and interventions.