542 results about "Body posture" patented technology

The invention relates to the technical field of multi-modal data processing, and discloses a multi-modal data fusion processing method and system, and the method comprises the steps: collecting a multi-modal data set containing the activities of the old through an intelligent old-age care robot; constructing a timestamp calibration matrix based on the multi-modal data set, and carrying out dynamic weight correction on the timestamp calibration matrix by adopting a three-modal data envelope delay compensation algorithm to obtain a three-modal data stream with a synchronous time sequence; performing hierarchical feature extraction through a nested feature extractor to obtain a three-mode tumble feature vector group; performing vector fusion on the three-mode tumble feature vector group to obtain tumble fusion feature vectors; and inputting the tumble fusion feature vector into a multi-modal forward prediction model to perform tumble risk trajectory prediction, and outputting a tumble detection result, the method realizes prediction analysis of body posture changes in a key time window before the old man tumble, and improves the ability to distinguish a slow getting-up action and a real tumble behavior of the old man.

The invention provides a bridge swivel attitude intelligent adjustment method and system based on multi-source data fusion, and the method comprises the steps: obtaining a multi-source monitoring data set generated in a bridge swivel process, carrying out the time-space alignment and fusion processing of the multi-source monitoring data set, generating fusion monitoring data, and carrying out the adjustment of the swivel attitude of a bridge. And based on the fused monitoring data and a preset target attitude parameter set, identifying attitude deviation characteristics between a bridge swivel attitude and a target attitude, generating an attitude adjustment strategy for a bridge swivel execution mechanism according to the attitude deviation characteristics, and executing the attitude adjustment strategy to adjust the attitude of the bridge swivel execution mechanism. And carrying out real-time posture adjustment operation on the bridge turning process. According to the method, the system reliability can be enhanced while the adjustment efficiency is improved, and the problems of insufficient control precision and response delay caused by data isolation and strategy staticization in a traditional method are solved.

The invention belongs to the technical field of three-dimensional reconstruction, and discloses a three-dimensional digital human generation method and system capable of voice interaction. According to the invention, brand new speaking audios in different languages are automatically generated according to different languages of the input target text and the sampled human voice audios; the sequential stability and detail reduction capability of three-dimensional human motion are guaranteed by using multi-model joint estimation and a sequential loss function, and facial expression details and hand postures in the image can be accurately estimated. After the high-precision three-dimensional human body model is obtained through estimation, human body action and expression generation is carried out based on voice driving, accurate synchronization of actions and expressions generated through voice is achieved, and facial expression movement and body posture movement, namely a whole-body three-dimensional human body model, conforming to brand-new speaking audio are accurately generated; and finally, rendering the whole-body three-dimensional human body model into a real digital human capable of voice interaction by using a three-dimensional neural rendering model. According to the invention, the realization of single person picture input, high-precision three-dimensional digital person generation and voice interaction is facilitated.

The invention discloses a poultry behavior abnormity real-time monitoring system based on multi-modal image fusion, particularly relates to the technical field of intelligent breeding behavior recognition, and is used for solving the problem of poor behavior monitoring accuracy under feather shielding. The method comprises the following steps: firstly, through combined perception of a visible light image and an infrared image, extracting a claw track interruption point and an anus temperature gradient direction, and realizing analysis of a motion state of a sheltered area; then, in combination with the heat conduction delay characteristic and the group movement direction, the flexion and extension angle of the covered leg joint is inverted, and a complete gait sequence is generated; thirdly, multi-source features such as gaits, temperature differences and body postures are fused, and a dynamic deviation model of the individuals relative to the mass center of the group is constructed; and finally, generating a stress behavior threshold curve according to the ground temperature and the ammonia gas concentration, outputting an abnormal behavior type and confidence, and realizing intelligent distinguishing of mechanical obstacles and adaptive behaviors.

The invention relates to the technical field of robot joint control, and discloses a robot dog mechanical joint control method. The method comprises the following steps: acquiring a whole-body joint real-time sensing data set which covers the torque reading of a multi-axial force sensor, the angle data of a joint encoder and the body attitude data of an inertial measurement unit; motion state compensation is carried out on the sensing data based on a dynamic window mechanism, and a dynamic compensation matrix containing kinematics compensation parameters is generated; and inputting the multi-modal motion control data set into a gradient descent model under space-time constraint to complete multi-modal motion feature fusion so as to obtain a fusion motion control data set. Joint behavior abnormity is detected through a Lyapunov stability analysis algorithm, and abnormal nodes are identified; and iteratively optimizing control parameters through a fuzzy PID optimization algorithm to generate an optimized control parameter set, finally constructing a three-dimensional virtual motion space model, and establishing a dynamic mapping relationship between a virtual track and an actual mechanism.

The invention discloses a golf motion simulation method and system based on digital twinning, and the method comprises the steps: obtaining an original data set containing a timestamp and a space coordinate from the cooperative motion of a plurality of parts and equipment of an athlete body through a sensor network technology in combination with a high-speed image capture device, and obtaining a preliminary multi-source motion information record; aiming at the initial multi-source motion information record, correcting time synchronization deviation and space matching error by adopting a data preprocessing module, and determining a corrected unified data framework by comparing timestamps and coordinate mapping relationships of data sources; according to the corrected unified data framework, a feature extraction algorithm is used for separating and marking the action analysis details and key parameters at the ball hitting moment, and a feature vector set containing the body posture and the equipment state is obtained. According to the invention, a highly vivid virtual environment support is provided for exercise training and match analysis, and the simulation precision and application value of a virtual exercise scene are effectively improved.

The invention relates to a multi-modal virtual human real-time generation method based on an expression control embedding space, and belongs to the field of artificial intelligence. According to the method, an expression control embedding space is constructed and used for fusing voice semantics, a rhythm structure and multi-dimensional emotion information, and continuous and controllable multi-modal driving vectors are generated. The whole system has an end-to-end linkage mechanism from audio input to expression and action output. Semantic features, rhythm structures and emotional states jointly act on generation paths of lip and upper body postures and expression modalities, and all modal features are fused and expressed in a unified control space through a collaborative coding and time sequence alignment mechanism. And finally, a high-consistency and high-fidelity virtual human video is generated in real time through an output scheduling mechanism. The method has remarkable advantages in the aspects of modal fusion consistency, generation expression naturalness and emotion control flexibility, and can be widely applied to key scenes such as virtual human broadcasting, voice interaction agency and meta-universe digital identity construction.

The invention discloses a bedsore prevention and body position management system and method.The system comprises a mattress, a multi-mode sensing unit, a central processing unit and a body position adjusting unit, the mattress is used for providing lying support for a patient, the multi-mode sensing unit is arranged on the mattress, the central processing unit is arranged on the mattress, and the body position adjusting unit is arranged on the central processing unit. The multi-mode sensing unit is used for collecting pressure distribution data, temperature and humidity data and body posture data of a bedridden patient in real time, and the central processing unit is in communication connection with the multi-mode sensing unit and used for receiving, fusing and processing the data collected by the multi-mode sensing unit and conducting bedsore risk assessment based on a preset bedsore risk model. The central processing unit is used for generating a bedsore risk level and a body position management instruction, and the body position adjusting unit is arranged in the mattress, connected with the central processing unit and used for receiving and executing the body position management instruction so as to adjust the distribution of pressure borne by the body surface of a patient. According to the system, real-time monitoring of bedsore risks and automatic body position adjustment are achieved, the nursing load is relieved, and the nursing efficiency and quality are improved.

The invention provides an intelligent control system and method for a massage device, and relates to the technical field of massage devices, and the system comprises an identity authentication module which is used for obtaining the identity authentication information of a target user; the intelligent sensing module is used for sensing the body posture and massage requirements of a target user in real time, including pressure distribution and muscle tension, so as to automatically adjust the massage strength, speed and position parameters of the massage device; and the personalized setting module is used for performing intelligent analysis by using a wolf pack algorithm according to user preferences and historical data, and formulating a massage scheme for a target user, including massage duration, massage intensity upper limit values and massage modes of all parts. By integrating the functions of identity authentication, intelligent induction, personalized setting, execution control, fatigue degree determination, health monitoring and the like, customized, safe and efficient massage service is provided for a user, meanwhile, the health condition is monitored in real time, the user experience is improved, and the user safety is guaranteed.

The invention relates to the technical field of heart rate detection, in particular to a wearable underwear heart rate detection method and system.The method comprises the following steps that motion information of a user is obtained, and specific body posture changes are recognized based on the motion information of the user; generating a physiological artifact signal related to the specific body posture change based on the specific body posture change; removing a physiological artifact signal from the original physiological signal to obtain a purified physiological signal; heart rate abnormity judgment is conducted on the purified physiological signals. According to the scheme, the physiological artifact signals can be effectively removed, and the accuracy of heart rate detection is improved.

The invention relates to the technical field of piano teaching and computers, discloses a multi-dimensional scoring auxiliary system and method in piano teaching, and aims to solve the problems that existing piano teaching is single in evaluation dimension, one-sided in data acquisition and lagged in feedback. According to the method, a five-dimensional scoring model covering rhythm, strength, timbre, posture and fingering is constructed by synchronously collecting a key triggering time sequence, an audio frequency spectrum, limb posture and finger joint tracks, and quantitative scores are output through time alignment, feature extraction and neural network fusion calculation. The system comprises a key sensing module, an audio acquisition module, a posture capture module, a score calculation module and an AR visual feedback module, and supports teaching suggestion generation, historical trend analysis, difficulty self-adaption and multi-person comparison functions. Through multi-modal data closed-loop evaluation and intelligent intervention, the teaching accuracy and individuation level are remarkably improved, and scientific quantification and efficient improvement of the piano playing ability are achieved.

The invention provides an autonomous navigation and intelligent obstacle avoidance method of a biomimetic robot, and relates to the technical field of biomimetic robots, which realizes real-time estimation of six-degree-of-freedom poses by collecting environmental data; visual features are extracted by using a convolutional network, an enhanced memory unit is constructed in combination with pose information, a triple index path memory library is maintained through a dynamic memory updating mechanism, and feature similarity retrieval and navigation instruction generation in a backtracking mode are supported; defining a state vector based on a resultant force of a robot pose, a target direction and an artificial potential field, training a strategy network through deep reinforcement learning, and outputting a motion instruction according to Q value maximization; fusing an artificial potential field and a dynamic window method, and optimizing an objective function to obtain optimal linear velocity and angular velocity; and solving a joint angle through inverse kinematics, and combining attitude error feedback to realize body attitude maintenance and foot end trajectory tracking.

The invention discloses a double-foot wheel-legged robot pose control method and device based on hierarchical cooperative control, a medium and a product, and relates to the field of robot control, and the method comprises the steps that a hierarchical cooperative control framework is constructed; the layered cooperative control framework comprises a balance controller and a whole body attitude controller; the balance controller determines a reference wheel joint driving torque based on a simplified inverted pendulum dynamic model according to the pose information of the upper mass center of the biped wheel-leg robot; the whole-body attitude controller performs optimization control on all joints of the biped wheel-leg robot by adopting an incremental model prediction control algorithm combined with a reference wheel joint driving moment based on a whole-body dynamic model; state information of the biped wheel-legged robot is obtained; according to the state information, a driving torque instruction of each joint is obtained based on a hierarchical cooperative control framework; and driving the double-foot wheel-leg robot to move according to the driving torque instruction of each joint. The precision, robustness and real-time performance of robot motion control can be improved.

The invention relates to the technical field of health state monitoring, in particular to a real-time health state monitoring system and method based on a biosensor. According to the scheme, through multi-mode data fusion, physiological data such as postures, heart rates and blood oxygen collected by the biosensor are combined with postures and environment videos of image collection, the limitation of single data source monitoring is solved, and the situation that traditional falling early warning is misreported due to normal actions such as stooping is avoided; or altitude stress early warning only prompts oxygen deficit but cannot be associated with the falling risk. A pre-trained risk assessment model is combined to output grading risk levels, targeted early warning such as low-risk prompt deceleration and high-risk sound-light alarm is triggered, more accurate and timely health monitoring service is provided for the elderly in the plateau area, and the falling risk caused by interaction of the environment and the physiological state is effectively reduced.

The present application relates to a kind of vehicle steering body posture and control method of handling stability, comprising the following steps: the signal input required for control is collected, vehicle total anti-lateral moment is calculated by body posture feedforward-feedback controller, front and rear axle anti-roll moment distribution ratio is calculated by handling stability feedforward-feedback controller, total anti-roll moment and its front and rear axle distribution ratio are calculated, revised by control comprehensive module, finally output each suspension angle vertical force control instruction of vehicle.The present application has the following advantages:1) vehicle body posture control and handling stability control are comprehensively considered, and both are simultaneously optimized;2) vehicle body posture control and handling stability control both use feedback-feedforward, avoid the problem of pure feedforward control or feedback control, so that the overall performance of vehicle is more "natural";3) steering input and road input are decoupled, and four high sensors are saved.

The invention provides a monocular vision and sparse IMU rehabilitation action whole body posture estimation method and system, and the method comprises the steps: synchronously collecting video data and inertial data of human body rehabilitation actions through a monocular RGB camera and a plurality of IMUs, and cutting and zooming an image to a preset resolution; extracting a key point thermodynamic diagram from continuous N frames of images by using a sliding window and a residual neural network, and calculating 2D key point pixel coordinates of each frame; splicing the N frames of 2D key point pixel coordinates, the rotation matrix of the IMU and the acceleration signal into an input sequence; cross-modal time sequence modeling is carried out on an input sequence through time Transform, and after high-dimensional features are extracted, weighted average is carried out through a convolutional layer, and 3D relative key point coordinates of the last frame are output through a regression head. According to the method, by fusing monocular vision and sparse IMU cross-modal data, the problem of visual information loss caused by limb self-shielding is effectively solved, and the defect that a traditional pure vision method is insufficient in precision in rehabilitation actions is overcome.

An avatar animation generation method includes obtaining video data of a physical object; extracting posture information of the object based on the video data, wherein the posture information indicates a body posture and an expression posture presented by the object in the video data; performing 3D reconstruction on the object based on the posture information to obtain motion data representing a body motion of an avatar and expression data representing a facial expression of the avatar, wherein the motion data is obtained through reconstruction based on the body posture, and wherein the expression data is obtained through reconstruction based on the expression posture; and obtaining animation data of the avatar through synthesis based on an appearance resource of the avatar, the motion data, and the expression data, wherein the animation data indicates that the avatar wears the appearance resource, presents the facial expression, and performs the body motion.

The invention relates to the technical field of body posture recognition, and particularly discloses an automatic body posture recognition system based on video analysis, which comprises a video acquisition module, a preprocessing module, a key point detection module, a skeleton tracking module, an action recognition module and a cross-view fusion module. According to the scheme, a parallel detection and information fusion mode is adopted, and the detection precision of the key points of the human body is remarkably improved by utilizing the accurate position of the high-resolution feature and the rich semantics of the low-resolution feature; the target is tracked according to the topological structure and the key point position of the human skeleton, the method has extremely high robustness for illumination and dressing changes, and a more stable and continuous human skeleton movement track is generated; the time sequence convolution and the space-time diagram convolution are combined to carry out joint modeling on the space and time double-domain features, complete action representation is obtained, and the stability, the accuracy and the adaptability of body posture recognition are effectively improved.

The invention discloses a remote 3D clothing intelligent customization system based on virtual reality, which comprises a customization primary selection module, a try-on experience simulation analysis module and a try-on experience simulation module, and is characterized in that the customization primary selection module is used for primarily selecting and screening customized clothing styles and categories according to the body type of a customer and customer selection; the try-on experience simulation analysis module is used for analyzing the stress condition of the body parts of the customer after try-on, and the try-on experience simulation module is used for simulating the garment wearing experience feelings under different body postures after real try-on according to the analysis result of the try-on experience simulation analysis module. The customization primary selection module is electrically connected with the try-on experience simulation analysis module, the try-on experience simulation analysis module is electrically connected with the try-on experience simulation module, and the system has the characteristics of real try-on experience and personalized optimization design.

The invention relates to the technical field of voice analysis, and particularly discloses a vocal music training method and system based on artificial intelligence, and the method comprises the steps: collecting and analyzing the body posture parameters of a target vocal music training person, carrying out the preprocessing, detecting the posture abnormality, forming a first abnormal training set, capturing and analyzing the pronunciation feature parameters, and recognizing the pronunciation abnormality, thereby obtaining a vocal music training result; and integrating the first abnormal training set and the second abnormal training set to generate a total abnormal parameter training set, matching a correction set, and visually displaying the body posture abnormal degree and the abnormal reason and the pronunciation abnormal degree and the reason, so that the target vocal music training personnel can visually see own posture and pronunciation problems, and self-adjustment and correction are facilitated.

The invention discloses an interaction method and device, electronic equipment and a readable storage medium, and belongs to the technical field of electronic equipment, and the method comprises the steps: obtaining a video stream of a user; determining a behavior state of the user according to the video stream; wherein the behavior state comprises at least one of the following items: an emotional state, an attention state, a facial expression, a body posture and an action; and outputting first interaction content according to the behavior state of the user.

The invention provides a quadruped robot body attitude control system and method, and the method comprises the steps: sensing a first contact force when each foot is in contact with the ground based on a force feedback device, and collecting a first real-time roll angle and a first real-time pitch angle of a body based on an inertia measurement sensor; determining a first roll angle deviation based on the target roll angle and the first real-time roll angle, and determining a first pitch angle deviation based on the target pitch angle and the first real-time pitch angle; determining a first supporting foot based on the first contact force of each foot, and determining a first height adjustment amount of the first supporting foot in the vertical direction based on the first roll angle deviation and the first pitch angle deviation in combination with position coordinates of the first supporting foot relative to the gravity center of the fuselage; joint movement of the first supporting foot is driven based on the first height adjustment amount of the first supporting foot, so that the first supporting foot is subjected to position adjustment in the vertical direction according to the first height adjustment amount. The adaptive capacity and the motion reliability of the quadruped robot in a complex environment are improved.

The invention relates to the technical field of postpartum rehabilitation equipment, and provides a pelvic floor muscle repairing instrument, a pelvic floor electromyographic signal interference removing method and related equipment. The pelvic floor muscle electromyographic acquisition module is configured to acquire pelvic floor muscle surface electromyographic signals containing adjacent muscle group interference to obtain target electromyographic signals; the interference muscle group monitoring module is configured to collect physiological activity signals of muscle groups adjacent to pelvic floor muscles so as to obtain interference reference signals; the posture sensing module is configured to collect a body posture time sequence signal related to pelvic floor muscle activity so as to obtain a scene auxiliary signal; and the signal processing module is configured to perform suppression processing on adjacent muscle group interference in the target electromyographic signal based on the interference reference signal and the scene auxiliary signal, and output a purified pelvic floor electromyographic signal. Pelvic floor muscle real signals and dynamic interference are distinguished through the scene auxiliary signals obtained by the posture sensing module, and the purity and reliability of output signals of the pelvic floor muscle repairing instrument are improved.

The invention relates to the technical field of intelligent traditional Chinese medicine diagnosis and treatment, and discloses a thermosensitive moxibustion tracking algorithm and system based on long-acting moxibustion therapy sensing and posture three-dimensional sensing, and the algorithm comprises a long-acting flexible thermosensitive sensing subsystem, a three-dimensional posture sensing module, a multi-modal data fusion processing unit, a dynamic thermal field modeling algorithm, and a self-adaptive moxibustion applying control subsystem. Through full-chain innovation of long-acting sensing, three-dimensional sensing, coupling modeling and intelligent control, the performance stability problem (drift error is less than or equal to + / -0.3 DEG C) of the flexible sensor under long-term work (more than or equal to 72 hours) is solved; establishing a posture-thermal field-time four-dimensional coupling model, and realizing submillimeter thermosensitive point tracking under a dynamic posture; a millisecond-level response (less than or equal to 50ms) closed-loop control system is constructed, and the adaptability to complex clinical scenes is improved; therefore, the key technical problem in the dynamic moxibustion therapy scene is systematically solved.

The invention discloses a virtual image clothes changing method and system, and the method comprises the steps: carrying out the preprocessing of a figure image inputted by a user, and obtaining standardized image data; recognizing a face region in the standardized image data, and constructing a three-dimensional face model; body parameters corresponding to the three-dimensional face model are determined, and a three-dimensional human body model is generated based on the body parameters; based on a matching result between the measured size of each key part in the three-dimensional human body model and a design size of a corresponding part in a preset clothing template, deforming the clothing template to obtain a three-dimensional clothing model, and simulating virtual clothing changing effect data when the three-dimensional human body model wears the three-dimensional clothing model; and updating the three-dimensional human body model according to the facial features of the user and the body posture of the user, updating the virtual clothes changing effect data according to the updated three-dimensional human body model, and obtaining a virtual image preview picture corresponding to the dynamic performance behavior of the user.

The invention discloses a multifunctional automatic comprehensive optometry combined operation table and a use method thereof. The operating platform comprises a mechanical main body structure, a posture sensing system and a central processing and control unit. The mechanical main body structure comprises an optometry chair driven by a rotating disc, a lifting mechanism and an electric rotating shaft, and the posture sensing system is composed of a sitting and leaning posture recognition mechanism used for recognizing body postures and a head posture recognition mechanism used for capturing head movement. The central processing and control unit judges the posture of the optometry person according to the sensing data, and if the posture does not meet the preset standard, the seat height, the backrest angle and the horizontal position are adjusted through voice prompt and an automatic driving mechanism; when the posture reaches the standard, the optometry equipment is automatically controlled to complete operation, automatic and accurate correction of the posture before optometry and intelligentization of the optometry process are achieved, and the accuracy and efficiency of optometry results are effectively improved.

The invention relates to the technical field of robot control, in particular to a humanoid robot control method and device and a humanoid robot. Acquiring upper body operation posture data corresponding to an operator; the upper body operation attitude data comprises pitching data, roll data and yaw data; performing component processing on the upper body operation attitude data to generate upper body target attitude data corresponding to the humanoid robot; obtaining current upper body posture data corresponding to the humanoid robot; and controlling the humanoid robot based on the upper body target attitude data and the upper body current attitude data. A closed loop of collection-processing-feedback-control is formed, posture deviation is dynamically corrected, it is ensured that the robot accurately rewrites the intention of an operator, and meanwhile action stability and running stability are considered.

The invention relates to the technical field of intelligent equipment. A trajectory diffusion imitation learning method based on single human video demonstration comprises the steps that a demonstration video is analyzed to obtain an operation body posture motion trajectory and an object pose motion trajectory, and the demonstration video is a video of a human or machine operation object; respectively carrying out interpolation calculation on the positions and postures of the operation body posture motion trail and the object pose motion trail to obtain a training data set; using the training data set to train a diffusion strategy model to obtain a target diffusion strategy model; and during deployment, the real-time pose of an end effector of the robot serves as observation input of the target diffusion type strategy model, an operation body pose movement track and an object pose movement track in the deployment stage are formed, and a joint control instruction of a target operation body is obtained. And the task success rate is kept, and the practicability and the expandability of the imitation learning method are improved at the same time.

The invention relates to an attention training method and device based on semi-intrusive electroencephalogram signals and body posture capture, electronic equipment and a storage medium. The method comprises the steps that electroencephalogram signals of a user are collected in real time, and the concentration degree is identified; body posture actions of the user are identified, and identified body posture data are sent to the interactive display module through the USB interface to be processed and displayed; the electroencephalogram signals and the concentration degree data are forwarded to the storage module in real time, and meanwhile the electroencephalogram data and the concentration degree data are sent to the interactive display module in real time; converting the body posture data into a direction control parameter for controlling the direction action of the interactive application normal form, and converting the concentration degree data into a speed control parameter for controlling the speed of the interactive application normal form; and feedback interaction training of the concentration degree is realized. According to the method, two technical means of semi-intrusive electroencephalogram signal and body posture capture are comprehensively applied, so that the attention of people is trained.

In one embodiment, a computing system may determine a pose of a device held by or attached to a hand of a user based on sensor data captured by the device. The system may determine a pose of a headset worn by the user based on sensor data captured by the headset. The system may detemline positions of a first set of keypoints associated with a first portion of a body of the user based on (1) one or more first images captured by one or more cameras of the device, (2) the pose of the device, (3) one or more second images captured by one or more cameras of the headset and (4) the pose of the headset. The system may determine a body pose of the user based at least on the positions of the first set of keypoints.