71 results about "Human body structure" patented technology

Methods and systems for determining changes in muscle activity patterns based on the optical response of subcutaneous human body structures are presented, along with methods and systems for controlling assistive robotic systems based on the measured muscle activity patterns. Elements of a muscle activity measurement system are mechanically coupled to a wearable structure that fits closely to a portion of the body of a human user. The muscle activity measurement system includes multiple emitters and detectors at different spacing along the skin surface. In some embodiments, the illumination intensity of each measurement channel, the programmable gain of each measurement channel, or both, are calibrated to maximize measurement sensitivity. In some embodiments, optical measurement data is employed to more accurately locate the muscle activity measurement system with respect to the human body. In some embodiments, a muscle activity measurement system tracks changes in muscle structure over time.

The invention provides an intelligent motion generation method and system of a human body, and electronic equipment, and the method comprises the steps: obtaining motion capture data based on video data, obtaining target motion information and an initial human body skeleton key point sequence based on the motion capture data, obtaining source skeleton motion data based on a human body structure prior key point sequence of the human body skeleton, and obtaining the target motion information and the initial human body skeleton key point sequence; obtaining a virtual human image based on the target motion information, obtaining a virtual human skeleton structure based on the virtual human image, obtaining redirected skeleton data, obtaining an optical flow graph and a mask graph based on the virtual human image and the redirected skeleton data, and obtaining an initial virtual human motion image sequence based on the optical flow graph and the mask graph; and acquiring a virtual human motion image sequence based on the initial virtual human motion image sequence, and acquiring motion output of the living agent based on the virtual human motion image sequence. Therefore, coherent and natural action generation is realized.

The utility model relates to technical field of sports socks, concretely is a kind of wide-toe moisture-absorbing quick-drying split-toe sports socks, including sock main body, the sock main body includes toe, by thumb toe part and split-toe part, the thumb toe part and split-toe part are connected with widened part, the sock body includes the sock face of wrapping instep and the sock bottom of wrapping foot bottom, the sock bottom of the sock body is equipped with space bin, and the space bin is located metatarsal bone and phalanx connecting portion of sole of foot.This kind of wide-toe moisture-absorbing quick-drying split-toe sports socks, by adding widened part between thumb toe part and split-toe part, increase the distance between thumb toe and two toes, reduce the pressure and friction to thumb toe inner side when wearing, in addition, space bin is additionally arranged in metatarsal bone and phalanx connecting portion of sole of foot, so that the sports socks can better fit foot, and the wrapping property is stronger, so that the sports socks are more in line with human body structure, and wearing is more comfortable.

The invention is suitable for the technical field of pedestrian re-identification, and provides a pedestrian re-identification method and related equipment. The method comprises the following steps: acquiring a plurality of to-be-cut areas of the same human body in a target image, wherein each to-be-cut area comprises at least two target key points; respectively carrying out rotary cutting on the plurality of to-be-cut areas according to the human body posture and the image view angle by utilizing at least two target key points respectively included in the plurality of to-be-cut areas to obtain a cut image of the human body structure; and comparing the cut image of the human body structure with a reference structure image in a target database to obtain a pedestrian re-identification result. According to the method, the recognition precision of pedestrian re-recognition can be improved.

The application discloses a method for registering a skeleton model to a world coordinate system of a body surface point cloud, which comprises the following steps: S1. scanning a human structure by using a CT scanning device to obtain a CT skeleton three-dimensional model and a CT human structure body surface point cloud; S2. scanning the human structure by using a structured light 3D camera to obtain a 3D structured light body surface point cloud of a 3D structured light human structure; S3. selecting an antegrade registration or a retrograde registration mode to register the body surface and the skeleton of the human structure according to the scanned human structure; the method for registering the skeleton model to the world coordinate system of the body surface point cloud: registering the torso and the pelvic bone of the human body by using the antegrade registration mode; registering the limbs of the human body by using the retrograde registration mode; constructing a virtual puncture channel, so that even if the spatial position of a puncture instrument is adjusted at will in a process of orthopedic puncture, the relative position relationship between the puncture instrument and the human structure can be acquired in real time, and the navigation puncture based on dynamic three-dimensional visualization is realized.

The application provides a visual human-imitating ankle intelligent teaching aid and a preparation method thereof, and relates to the technical field of teaching aids.The visual human-imitating ankle intelligent teaching aid comprises a human-imitating ankle body, human-imitating muscles, a position sensor, a force sensor and a controller.The human-imitating ankle body comprises human-imitating phalanges, human-imitating metatarsal bones, human-imitating cuboid bones, human-imitating wedge bones, human-imitating navicular bones, human-imitating fibula bones, human-imitating anterior tibiofibular ligaments, human-imitating calcaneus bones, human-imitating talus bones, human-imitating calcaneofibular ligaments and human-imitating tibia bones arranged according to human body structure.The position sensor and the force sensor are connected with the controller.The human-imitating muscles wrap the human-imitating ankle body, the position sensor and the force sensor.The acceleration sensor and the angular velocity sensor are arranged on the human-imitating talus near the human-imitating anterior tibiofibular ligaments.The force sensor is arranged on the human-imitating talus near the human-imitating calcaneus bone.The application can quantize the data of bone-setting methods of experts and trainers, so that the deviation of the bone-setting methods of the trainers can be obtained, and the trainers can learn better.

The invention discloses a gait recognition method based on local appearance and micro-motion perception, and belongs to the technical field of computer vision and biological feature recognition. The method comprises the following steps: firstly, preprocessing and aligning an input gait contour sequence; extracting spatial features by using a convolutional neural network, and performing non-uniform part division according to human body structure priori knowledge so as to focus on leg equal-height discriminant regions; further, an independent micro-motion sensing module is designed for each component, and unique short-distance space-time dynamic characteristics of each component are captured through a double-branch time sequence attention mechanism; and finally fusing the enhanced features of all the components to complete identity recognition. By emphasizing the local appearance difference and the micro-motion mode, the robustness and stability of the gait recognition model in a real complex scene are remarkably improved, and the method has important security monitoring and identity authentication application value.

The invention discloses a pedestrian re-identification method and system based on attitude guidance and triple cooperative loss, and belongs to the technical field of computer vision. According to the method, in an attitude guided depth supervision framework, a triple collaborative loss function fusing temperature scaling cross entropy loss, triple loss and circular ring loss is designed, and feature learning is collaboratively optimized through weight configuration; in the training stage, the knowledge distillation of the posture encoder is combined to enhance the understanding of the model on the human body structure, and in the reasoning stage, only the optimized human body encoder is used for recognition. Experiments show that the mAP of the method is improved by 3.1% on a VC-Clothes clothes change data set, the robustness of shielding and clothes change scenes is remarkably improved, and additional calculation overhead is not needed in the reasoning stage.

The utility model discloses a one-piece shapewear which comprises a chest binding area, a waist binding area, a crotch area and a back area, the chest binding area, the waist binding area, the crotch area and the back area are connected together according to the structural characteristics of a human body, switch belts are arranged on the two outer sides of the back area, secondary tightening threads are arranged on the inner sides of the switch belts, and the secondary tightening threads are connected with the switch belts. A main compact line is arranged at the central position of the back area; the back area is further provided with a hip lifting area, and a hip lifting line is arranged on the outer edge of the hip lifting area. The body-shaping underwear is good in body-shaping effect, high in air permeability, convenient to put on and take off and capable of better meeting the requirements of consumers.

The present application relates to the technical field of process monitoring, in particular to a personnel intrusion detection method based on an artificial intelligence loading system, comprising the following steps: acquiring a target continuous motion image sequence, calculating a node included angle and a direction deflection to generate positioning information, comparing a work boundary to determine an intrusion and generate an identification state, combining a direction vector to determine a device response instruction, loading a trajectory in a three-dimensional scene and marking a risk area, and obtaining a personnel path intrusion calibration record. In the present application, through continuous extraction of a human body structure boundary box in an image frame and dynamic displacement analysis of a trajectory node, a target path with continuous gait characteristics is identified and static and device interference areas are eliminated, whether the target has crossed the boundary is determined in combination with a real-time loading work boundary, a minimum distance between a turning point and a boundary path is calculated to complete intrusion behavior identification, real-time discrimination of a behavior trajectory and efficient linkage of alarm direction control are realized, and the accurate identification and real-time reaction capability of personnel intrusion events are enhanced.

This invention provides a toy skeleton structure, wherein the torso adopts a segmented structure. Ball heads and spherical grooves are respectively provided on the opposite end faces of the first and second torsos. The first torso can be rotatably fixed to the second torso through the rotational engagement of the ball heads and spherical grooves. Simultaneously, the ball heads are connected to the end face of the first torso through a waist-shaped transition section, allowing the torso to rotate and perform small-amplitude swaying movements, thereby increasing the torso's range of motion and fluidity. This invention also provides an assembly mecha toy including the aforementioned toy skeleton structure. The toy skeleton structure provided by this invention has the advantages of simple and compact structure, fewer component parts, simple assembly operation, and easy management. It also has the advantages of multiple and smooth range of motion, ensuring high playability and interactivity for both the skeleton structure and the assembly mecha toy. Furthermore, the structural design of the toy skeleton structure allows its shape to more closely resemble a simulated human body structure.

The utility model relates to the technical field of medical instruments, and discloses a full-porous cervical vertebra fusion cage which comprises a machining area and a porous area. The machining area is provided with a threaded hole for leading in a surgical instrument; the porous area comprises an upper surface, a lower surface, a front surface, a rear surface and two side surfaces; and the upper surface and the lower surface are provided with anti-skid surfaces. The threaded hole in the machining area is used for being matched with a surgical instrument matched with the threaded hole, and surgical implantation is facilitated. The porous area provides more growth space for cells, adhesion, migration, proliferation and differentiation of the cells are facilitated, and finally the bone ingrowth effect is achieved. The full-porous cervical vertebra fusion cage has the mechanical property matched with the human body structure and good biocompatibility, can form a tight bonding interface with the human body tissue, improves the combination stability of the fusion cage and the human body tissue, has the mechanical property matched with the human body tissue, and can be applied to clinical treatment of cervical degenerative diseases.

The present application provides a preparation method for biosynthesis of a human body structural material. A polypeptide has the amino acid sequence of SEQ ID NO. 4, 5 or 6. Recombinant type-VII humanized collagen prepared in the present application has high activity of promoting cell proliferation and does not produce an immune response when applied to a human body, and the preparation method therefor is novel and can obtain the recombinant type-VII humanized collagen on a large scale, and is widely applied in the preparation of human body structural materials.

The invention discloses a clothes changing pedestrian re-identification method based on graph attention human body part dynamic correlation modeling. The method comprises the following steps: acquiring a video sequence of a pedestrian to be identified, and performing part segmentation through a human body analysis model; a part perception multi-scale feature extraction module is used to extract the features of each part under different receptive fields and suppress the background; then, the combination of each frame and the part is constructed into a graph node, and a heterogeneous space-time part graph containing a space edge, a time edge and a non-local edge is constructed; performing message passing on the three types of edges through a graph attention part association modeling module, and fusing to obtain enhanced node features; then, the enhanced node features are mapped back to original spatial feature dimensions; carrying out adaptive weighted integration on different granularity features; and finally, an identity representation vector is generated, similarity between the identity representation vector and image library features is calculated, and a matching result is output. According to the method, by capturing time sequence dynamic association between human body parts, identity representation generated by the model is more focused on a stable human body structure instead of a variable clothing appearance.

The application relates to a graph convolution human skeleton action recognition method based on a structural attention mechanism, and comprises the following steps: S1, constructing a structural attention module, including two submodules of a body part relationship-based attention module and a body symmetry node trajectory-based attention module; S2, adding the body part relationship-based attention module to an adaptive adjacency matrix of an intermediate result of graph convolution to obtain an adaptive adjacency matrix of reinforced body part structure; S3, constructing a related attention module by using the relationship of body symmetry node trajectories to reinforce the attention of a human skeleton action recognition model to body symmetry; and S4, feeding the features reinforced by the structural attention into a classifier to obtain scores corresponding to each action, so that a final recognition result is obtained. Compared with the prior art, the application considers the human structural behavior mechanism in action recognition, and has the advantages of high recognition precision.

The present application provides a preparation method for biosynthesis of a human body structural material. A polypeptide has the amino acid sequence of SEQ ID NO. 4, 5 or 6. Recombinant type-VII humanized collagen prepared in the present application has high activity of promoting cell proliferation and does not produce an immune response when applied to a human body, and the preparation method therefor is novel and can obtain the recombinant type-VII humanized collagen on a large scale, and is widely applied in the preparation of human body structural materials. The preparation method is applied to the fields of preparation of high-end medical instruments, such as biological dressings, human body biomimetic materials, materials for plastic surgery and aesthetics, organoid culture materials, tissue injection and filling, skin repair and regeneration, oral mucosa repair and regeneration, cervical mucosa repair and regeneration, gynaecology and obstetrics biological materials, 3D printing artificial organ biological materials; high-end cosmetic raw materials, and high-end medicinal auxiliary materials; and food additives and the like.

The utility model discloses a scoliosis orthosis intelligent detection and digital motion rehabilitation module which comprises an orthosis attached to a human body structure and an ergonomic bandage structure connected with the orthosis and used for being worn and installed, and a plurality of sensor modules are arranged on the ergonomic bandage structure and / or the orthosis. The sensor module comprises a pressure sensor, and the sensor module is interconnected with the data processing unit and the control unit. The utility model discloses an intelligent detection and digital motion rehabilitation module for a scoliosis orthosis, which realizes real-time monitoring, remote guidance and personalized use scheme creation for a scoliosis orthosis user through the integration of an intelligent orthosis, a data processing platform and cloud service, thereby remarkably improving the use effect.

The application discloses a garment image segmentation method and device based on human skeleton joints and a storage medium, and relates to the technical field of data processing. The method comprises the following steps: inputting a target image into a pre-trained human pose estimation model and a semantic segmentation model respectively, obtaining a skeleton joint graph of an image character in the target image output by the human pose estimation model, and obtaining a segmentation mask of a worn garment of the image character output by the semantic segmentation model; determining a body shape feature of the image character according to the skeleton joint graph; taking a left-right hip joint connection line in the skeleton joint graph as a segmentation reference line, and adjusting the segmentation reference line to obtain a cutting path according to an adjustment rule corresponding to the body shape feature; and cutting the segmentation mask according to the cutting path to segment the worn garment, so that the upper and lower parts of a dress conforming to a human structure are obtained, and the segmentation visualization effect of an integrated garment of a virtual character is improved.

The utility model provides a streamline office chair fitting the human body structure, which comprises a base, the top of the base is fixedly connected with a backrest, the rear side of the backrest is fixedly connected with a fixed box, the inside of the fixed box is rotatably connected with a rotating rod, the outside of the rotating rod is fixedly connected with a gear, and the gear is fixedly connected with a motor. A connecting plate is slidably connected to the interior of the fixed box, a headrest is fixedly connected to the front side of the connecting plate, a telescopic column is fixedly connected to the bottom of the headrest, a rack is fixedly connected to the inner wall of the right side of the connecting plate, a rotating circular plate is fixedly connected to the exterior of a rotating rod, and a clamping ring is fixedly connected to the rear side of the rotating circular plate; and the rear side of the fixed box is fixedly connected with a fixed column. According to the utility model, the lifting of the headrest of the streamline office chair fitting the human body structure is realized, so that the comfort of the office chair is improved, and fatigue and discomfort caused by improper head support are reduced.

The invention discloses a digital human body reloading method and device, a storage medium and a program product, and relates to the technical field of data processing, because a preset digital human body is created based on a dress-up model and a human body structure model which are separated from each other, a user only needs to obtain a reloading demand of the user for the preset digital human body; determining a target dress-up model meeting the dress-up requirement from a preset dress-up database; integrating the target dress-up model and the human body structure model of the preset digital person to obtain an integrated model, and creating a target digital person after dress changing based on the integrated model; according to the technical scheme, it can be understood that in the dress-up process, the human body structure model is not changed, and only the target dress-up model meeting the dress-up requirement needs to be obtained from the preset dress-up database, so that the digital human dress-up cost can be reduced while the personalized requirement of a user is met.

The application discloses a kind of actual combat simulation training system, it is related to training equipment technical field, the system is designed and is formed with the three-dimensional human body structure modeling of through positioning chip module and corresponding light weapon ballistic trajectory simulation together using realistic damage perception, a highly simulated training environment is formed, so that trainees are as if in the real battlefield, this realistic experience can greatly improve the concentration and input of participants, so as to enhance the training effect.In this realistic simulation environment, participants need to face various complex and unexpected situations, which helps them to exercise and improve their ability to deal with actual problems, so that participants can better master tactical deployment and combat skills, and improve their survival ability in real battlefield.The system is closer to actual combat requirements, and meets the requirements of improving the tactical action, command ability and combat awareness of participants.

The application provides a motion recognition method and system based on human skeleton structure, and the method comprises the following steps: acquiring position data of all joints of human skeleton, and constructing a first data set and a second data set according to the position data of all joints of human skeleton; constructing an adaptive adjacency matrix based on human structure symmetry coding, and respectively performing normalized spatial graph convolution on the first data set and the second data set according to the adaptive adjacency matrix; respectively performing feature extraction on third spatio-temporal features and fourth spatio-temporal features to obtain first features and second features, and fusing the first features and the second features; and inputting the fused features into a two-stage recognition model for recognition to obtain human motion category information. The application can realize high-precision recognition of multi-granularity motion while ensuring real-time performance.

The invention provides an action recognition method and system based on a human skeleton structure, and the method comprises the steps: obtaining the position data of all joints of a human skeleton, and constructing a first data set and a second data set according to the position data of all joints of the human skeleton; constructing a self-adaptive adjacency matrix based on human body structure symmetry coding, and performing normalized space graph convolution on the first data set and the second data set according to the self-adaptive adjacency matrix; performing feature extraction on the third spatial-temporal feature and the fourth spatial-temporal feature to obtain a first feature and a second feature, and fusing the first feature and the second feature; and inputting the fusion features into a two-stage recognition model for recognition to obtain human body action category information. According to the method, high-precision recognition of multi-granularity actions can be realized while the real-time performance is ensured.

This invention discloses a biomimetic model of driver injury based on the physical characteristics of a Chinese male at the 50th percentile. The model is based on a biomimetic model of a car occupant with the physical characteristics of a Chinese male at the 50th percentile. The occupant biomimetic model is modified and adjusted according to the driver's sitting posture while driving, and key angles of the human body structure and the physiological curvature of the spine are defined. The key angles include: head angle, trunk angle, upper arm angle, forearm angle, left and right hip angles, left and right knee angles, left and right leg angles, and ankle angle. The physiological curvature of the spine includes: cervical curvature, full thoracic curvature, upper thoracic curvature, lower thoracic curvature, and lumbar curvature. This invention also discloses a method for constructing the above-mentioned biomimetic model of injury, which has wide application scenarios.

The invention discloses a figure image generation diffusion model reasoning acceleration method based on middle state multiplexing of human body postures, and belongs to the technical field of image data generation. The method comprises the following steps: a human body posture structure condition pre-caching step; a posture cache matching retrieval step; a multiplexing cache diffusion reasoning step; the method further comprises a gesture cache updating step. According to the method, the diffusion intermediate state strongly related to the human body posture structure condition is cached in advance in the offline stage, and the intermediate state is directly reused in the online image generation stage, so that a human body posture control network does not need to be introduced again to participate in calculation in the image generation process, and the image generation efficiency is improved on the premise of ensuring the consistency of the generated image human body structure. And the calculation overhead and response delay of diffusion reasoning are obviously reduced. A posture cache updating mechanism is further introduced, and the applicability and robustness of the method in complex and diversified human body posture request scenes are guaranteed.

This invention discloses a self-supervised method and system for 3D pedestrian reconstruction based on SMPL pose constraints and a hybrid deformation field. Addressing the shortcomings of existing methods, such as the lack of prior knowledge of human structure, difficulties in adapting skin weights, and the inability to balance physical constraints with non-rigid details, this invention uses a normalized Gaussian field obtained through self-supervised optimization as input and proposes three key technologies: 1. A learnable skin weight field that directly predicts the complete skin weight vector of Gaussian elements; 2. A hybrid deformation field framework that concatenates a linear hybrid skin rigid transformation with a six-plane non-rigid residual transformation to achieve synergy between physical plausibility and detailed modeling; 3. Multi-level regularization constraints that ensure the physical plausibility of the reconstruction from three spaces: parameters, geometry, and image. Experiments show that this invention significantly outperforms baseline methods in terms of rendering quality, pose accuracy, and physical plausibility.

1. The name of the design product: intelligent motion capture sensor (observation cloud security V2.0). 2. The use of the design product: for human body, capture human data, record data and posture restoration of the displacement of the wearer's body structure, realize the analysis and identification of the wearer's action posture. 3. The design points of the design product: in shape. 4. The picture or photo that best shows the design points: perspective view 1.

1. The name of the design product: wearable motion capture instrument (observation cloud magic box V1.0). 2. The use of the design product: for human body wearing, capturing human body data, recording data and posture restoration of the displacement of the wearer's body structure, realizing the analysis and identification of the wearer's action posture. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention discloses a pathological report generation method, device and system based on double maps and a large model, and belongs to the field of large models. After an input text of a doctor is obtained, a large model is adopted to carry out semantic analysis and entity recognition on the input text, and key fields are obtained; key nodes and rule logic related to the key data are obtained from an anatomical structure body modeling map and a diagnosis and treatment guide map respectively; on the basis of the input text, the key node and the rule logic, a cue word is constructed, and the cue word is provided for a large model, so that the large model outputs a structured result set comprising a preset field on the basis of the cue word; and calling a large model to enable the structured result set to generate a pathological report in a preset form. According to the scheme, the large model is assisted in understanding the input text of the doctor through the maps recording the human body structure knowledge and the diagnosis rules, and the generation quality of the pathological report is greatly improved while the pathological report is automatically generated.

This application provides an autonomous identification and positioning system and method for rescue robots based on industrial vision, relating to the field of robotics technology. The system includes: a collaborative scanning module for constructing a robot coordinate map; a data fusion module for establishing a unified temporal data fusion frame to obtain multimodal image data; a human body recognition module for mapping thermal imaging images to visible light images, performing local human body recognition, and obtaining human structural features; a target annotation module for determining the rescue target and marking it on the robot coordinate map; and a path planning module for path planning, constructing and updating the path, and executing the rescue operation through the rescue robot. This application solves the technical problem in existing technologies where accurate target positioning is difficult due to occlusion and interference in complex environments, leading to low rescue efficiency. By combining industrial vision, it improves the accuracy of target positioning, thereby enhancing rescue efficiency.