359 results about "Body posture" patented technology

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 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 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 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 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 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 provides a virtual human interaction action generation method for unmarked augmented reality equipment, and the method comprises the steps: obtaining a head posture, a hand posture and a first-person visual angle image sequence of a user through a built-in sensor of an augmented reality helmet, and jointly reconstructing a whole-body posture of the user on the basis; generating an interaction action of a virtual human according to the reconstructed user posture; according to the method, the interactive action of the virtual human can be more natural and real and is kept consistent with the actual behavior of the user; in the field of man-machine interaction, the prior art depends on user control and needs additional hardware equipment and manual participation to maintain an interaction process; or depending on predefined conditions, generalization and practicability are poor; compared with the prior art, additional manual intervention and predefined design are not needed, interaction with the natural response virtual human can be achieved only through the lightweight augmented reality helmet, hardware dependence and labor cost are reduced, automation and usability of the method are promoted, and interaction convenience and immersion are improved.

The invention relates to the technical field of computer vision, and particularly provides a virtual digital human generation method and electronic equipment, and the method can comprise the steps: obtaining three-dimensional human body modeling data corresponding to each frame of image in a monocular video sequence of a target object; the three-dimensional human body modeling data comprises body posture data and identity offset data; processing the three-dimensional human body modeling data by using a pre-constructed to-be-trained virtual model to generate a virtual object image of each frame of image; the to-be-trained virtual model comprises a to-be-optimized three-plane feature body and a plurality of multi-layer neural network MLP models; optimizing the to-be-trained virtual model through the loss value between the virtual object image and each corresponding frame image, and obtaining a three-dimensional digital human model corresponding to the target object; the three-dimensional digital human model is used to generate a virtual digital human based on any drive data. According to the embodiment of the invention, the generation and rendering quality of the virtual digital human can be improved.

The invention discloses a privacy protection type service behavior monitoring method and system based on event-driven vision. The method comprises the following steps: collecting light intensity change in a service scene through an event-driven asynchronous visual sensor, and generating event stream data without texture information; a neural network model is utilized to extract desensitized structured action features from the event stream, and the features comprise a whole body posture, hand operation and a multi-granularity key point skeleton of a face area and do not contain any identifiable identity information; and performing behavior semantic analysis such as fall detection, service action compliance verification, people flow statistics and the like based on the features, and outputting a visual result for service quality supervision, risk early warning or responsibility tracing. On the premise of not obtaining, storing or transmitting any image frame, non-intrusive and high-precision monitoring of service behaviors in high-privacy sensitive scenes such as home door-to-door service, old-age nursing and medical rehabilitation is achieved, and privacy protection and intelligent supervision requirements are effectively balanced.

The application discloses a kind of single-point mooring chain and anchor chain disc connection damage monitoring and inhibiting device and method, it is related to the inner turret type single-point mooring safety monitoring and protection technical field, the device is set in the tower body structure under the turret of the inner turret type single-point mooring system, including: motion measurement module, contact load measurement module, mooring chain measurement module, collaborative control module and inhibiting drive module, motion measurement module is used to obtain the motion characteristics of turret;Contact load measurement module is used to measure contact interface load and wear amount;Mooring chain measurement module is used to obtain chain body posture and tension;Collaborative control module carries out damage grade determination and instruction output;Inhibiting drive module executes pre-tightening force adjustment, mechanical locking and wear compensation to realize hierarchical inhibition.The application solves the problem of insufficient in-situ monitoring capability of contact interface in the prior art, lack of active inhibition means, realizes in-situ perception, intelligent determination and hierarchical inhibition of intelligent control of the damage of mooring chain and anchor chain disc connection.

The invention discloses a cross-modal sign language recognition and real-time translation method, and the method comprises the steps: fusing the multi-level sign language features of a hand key point, a hand shape, a motion track, a facial expression and a body posture, and combining context semantic understanding and grammatical structure analysis; high-precision continuous sign language recognition and bidirectional translation are realized through sign language grammar structure analysis, a context semantic inference mechanism, continuous sign language segmentation and recognition, a sign language dialect knowledge base and a virtual sign language generator, so that the communication efficiency between hearing impaired people and healthy hearing people is improved. According to the method, isolated sign language vocabularies can be recognized, grammar structures and contexts of sign languages can be understood, bidirectional translation of sign language-text / voice and text / voice-virtual sign language animations is achieved, and recognition and conversion of sign language dialects in different regions are supported.

The present application relates to human posture assessment, in particular to a fast posture assessment system and method based on millimeter wave imaging, an antenna array and a frequency source, fixed on a driving device, under the control of a controller, millimeter wave signals are emitted to the back surface of the target to be measured, and the reflected echo signals are received and sent to a signal processing and calculation module; the driving device is fixed on the support frame, under the control of the controller, the antenna array and the frequency source are driven to move along the height direction to adapt to different heights of the target to be measured; the signal processing and calculation module processes the echo signal, three-dimensional reconstruction, feature extraction and evaluation judgment, and obtains the three-dimensional image of the back surface of the target to be measured and the posture assessment result; the output module displays the three-dimensional image of the back surface of the target to be measured and the posture assessment result; the present application can effectively overcome the defects that it is difficult to meet the requirements of safe and non-radiation, objective quantitative evaluation and non-contact rapid detection at the same time.

The invention relates to a method for operating an assistance system (2) of a vehicle (1) comprising the steps of: issuing an offer to a driver (14) of the vehicle (1) to perform an automated driving maneuver, wherein a steering system (9) for automated lateral guidance of the vehicle (1) is controlled during the execution of the automated driving maneuver; checking whether the driver (14) has accepted the offer, wherein acceptance describes a turning of the gaze direction (31) and / or the head orientation towards a predetermined area (22, 23, 25, 26); detecting an operating action and / or a body posture of the driver (14) during the acceptance check; judging the acceptance as plausible if the operating action corresponds to a predetermined operating action and / or if the body posture corresponds to a predetermined body posture; and issuing a control signal to perform the automated driving maneuver.if the assumption is deemed plausible.

The invention relates to a method for determining a posture of a user (100) of a vehicle (200), comprising: Receiving sensor-based measurement data, which represent the user (100) in the vehicle (200); Determining a seat-position of the user (100), based on the measurement data; Determining positions of a plurality of reference points (P1, P2, P3, P4) of a torso (110) of the user (100) at the seat-position, based on the measurement data; Determining a torso-plane (120) of the torso (110) based on the determined positions of the plurality of reference points (P1, P2, P3, P4); Determining an angle of rotation (θ) of the torso-plane (120) around an axis (x, y, z) with respect to a reference angle of rotation; Determining a body posture by using the determined angle of rotation (θ) and a body posture classification algorithm.

The invention discloses a sinking control method and a related device, and the method is applied to an underwater robot, and comprises the steps: obtaining the body posture information of the underwater robot, and determining the relative position relation between a water inlet of the underwater robot and the water surface; motor control parameters matched with the relative position relation and the fuselage attitude information are determined, and a motor is controlled to operate according to the determined motor control parameters, so that water flow is driven by the motor to enter the underwater robot shell; and if it is detected that the underwater robot meets a preset sinking completion condition, determining that the underwater robot completes sinking. The control parameters of motor operation are adaptively adjusted based on the posture information of the machine body and the position relation of the water inlet relative to the water surface, so that water flow can effectively enter the shell of the robot in different posture states, the water filling process in the shell is accelerated, and the overall weight of the robot is increased; rapid and stable sinking of the underwater robot is achieved, and the underwater entering efficiency and the use stability of the underwater robot are improved.

The invention provides a sign language action recognition and judgment method and system based on multi-channel feature fusion, and the method comprises the steps: extracting hand and body posture features in a video frame, and generating multi-channel feature data; hand and body models of various scenes are loaded, and dynamic switching is carried out to adapt to different recognition requirements; using a machine learning model to predict multi-channel features, and outputting a sign language action recognition result and confidence thereof; and judging the correctness of the sign language action by comparing the recognition result with the expected action. The system solves the problem that an existing sign language recognition system is insufficient in accuracy and robustness under a complex background, and is suitable for various application scenes.

The application provides a dam surface animal intelligent identification and tracking method, a large number of thermal imaging pictures of animals possibly intruding into a dam range in different postures are collected in advance by using an infrared thermal imaging camera, a deep learning algorithm is used to train thermal imaging samples labeled with animal positions, and automatic detection of animal regions in the thermal imaging pictures is realized; then, intelligent classification of animal body types is realized based on a color step gradient algorithm of the infrared thermal imaging pictures; for large animals, an animal type identification algorithm is constructed by taking body posture characteristics and body surface temperature distribution as characteristic parameters; for small animals, a deep learning model is constructed by taking walking track characteristics and walking speed as characteristic parameters, and intelligent identification of target animal types is realized. The application is highly consistent with the living habits of wild animals, can accurately identify animal types, action tracks and cave positions on the dam at night, and reduces the possibility of dam collapse caused by cave leakage channels.

A vital signs measuring device includes a posture measuring unit attachable within a pentahedral space of a body, a biosignal measuring unit detachably connected to the posture measuring unit and capable of measuring at least one of the body's vital signs, a wireless communication unit that transmits data calculated from the biosignal measuring unit externally when the posture measuring unit determines the body to be in a specific posture, and a power supply unit that supplies power to the posture measuring unit, biosignal measuring unit and wireless communication unit. This enables vital signs data to be obtained that is stable and reliable for specific body postures.

The invention relates to a method, in particular a computer-implemented method, for determining the occupant weight of an occupant on a vehicle seat, the method comprising detecting, using a body posture sensor device, one or more body postures of the occupant, determining, by means of a processing device, whether the body posture corresponds to a predetermined body posture, and if the body posture corresponds to the predetermined body posture, reading out, by means of an occupant weight sensor device, sensor measured values and determining, by means of the processing device, the occupant weight from the sensor measured values, and wherein in particular sensor measured values are not read out and in particular the occupant weight is not determined if the body posture does not correspond to the predetermined body posture.

The application discloses a kind of space positioning method and system of four-foot inspection robot based on barycenter perception, to pass through foot end contact force and body posture information, barycenter potential field is constructed, combined with wave spectrum analysis, barycenter disturbance mode is formed, and disturbance propagation mechanism is revealed;Adopt reverse compensation technology to generate anti-disturbance sequence, reconstruct foot end force distribution topology, realize active disturbance suppression;Introduce multi-frequency detection beam and coherent superposition technology, generate environment hologram and reconstruct geometric topology, establish high-precision environment perception system;Through energy density analysis, identify high and low impedance areas, combined with potential field bypass and streamline tracking double strategy, construct energy optimal path;Establish oscillation analysis space to carry out path projection simulation, identify resonance risk points and determine stabilization parameters;Finally, quantum entanglement type multi-anchor point synchronization mechanism is generated to generate coordinate reference, and precise positioning is realized by fusing environment geometric information, realize the technical closed loop from barycenter dynamics analysis to environment perception navigation.

Disclosed is a training swimwear garment which include a base layer suitable to cover at least a portion of the upper torso of a wearer, the base layer having an abdomen region, a shoulder region, and a back region, and the base layer includes compressive and non-compressive fabric. The training swimwear includes a plurality of elastic straps spanning from an anterior of the shoulder region to the back region, configured to provide tension to produce a desired shoulder posture of the wearer. The training swimwear includes a plurality of panels connected with the base layer, the panels including an abdomen panel covering the abdomen region, and a back panel covering the back region, and the panels are configured to be buoyant to produce a desired body posture of the wearer.

The present application relates to the technical field of medical image analysis, in particular to a patient post-anesthesia pain grading evaluation method based on artificial intelligence. The method acquires multi-time body posture images in a complete respiratory cycle, constructs a trunk reference system, defines the end of the limb as an analysis point and a preset defense position as a target point; constructs a limb scheduling consumption matrix based on the distance between the analysis point and the target point, calculates the limb wandering confusion degree combined with the element distribution, and fuses to obtain the defense intention focus degree reflecting the order of whole body movement; the consumption matrix is subjected to geometric cost matching to obtain a limb scheduling total consumption index, and the focus degree is combined to generate a defense interference index; finally, the grading evaluation coefficient is determined according to the numerical distribution and stability of the index in the complete respiratory cycle, thereby objectively distinguishing the pain state and the wake-up period agitation state, and significantly improving the automation level and reliability of post-anesthesia pain evaluation.