16 results about "Human system" patented technology

The invention relates to a visualization method of an electronic medical record system and a visual medical record system. The method comprises the following steps: constructing a system main page; providing entry options, basic information corresponding to the patient, chief complaint information and current medical history information in the navigation bar area; loading and displaying the three-dimensional human body model in the three-dimensional human body model display area; in response to analysis of the electronic medical record information of the patient, automatically identifying and extracting lesion part information described in the medical record information; performing visual labeling on the mapped diseased region on the three-dimensional human body model; setting human body system options in the three-dimensional human body model display area; and in response to the operation that the mouse of the user hovers on the lesion part label on the three-dimensional human body model, displaying an examination result and abnormal index information related to the lesion part. According to the invention, the defects of an existing electronic medical record system in the aspects of information acquisition efficiency, spatial information presentation and information interaction modes can be effectively overcome, and the readability of medical record information and the diagnosis and treatment efficiency of doctors are remarkably improved.

A system for building a high fidelity model of a cyber physical human system (CPHS) is disclosed. The CPHS modelling system may comprise a database containing database information and an interface configured to receive a schema and operational data from a user. The CPHS modelling system may comprise an assembler configured to: receive the schema and database information; and generate a generic model of the CPHS. The CPHS modelling system may comprise a machine learning module configured to: receive the operational data; execute a machine learning process; and use the operational data to generate the high fidelity model.

The invention provides a dynamic walking exoskeleton control method and system based on man-machine complementary optimization, and the method comprises the steps: defining the step height and normal contact force of a contact point, and constructing a nonlinear complementary problem constraint and model; defining quantitative targets of nine types of motion tasks including contact point centroid position tracking, centroid linear velocity tracking, foot yaw angle alignment, frame attitude tracking, base quaternion derivative regularization, contact force regularization, joint regularization, swing height control and contact control regularization, and establishing a multi-task target function; a static nonlinear complementary problem is coupled with exoskeleton continuous dynamics, and a coupling system is constructed; solving the optimization objective function by adopting a neurodynamics algorithm to obtain the optimal control input of the exoskeleton-human body system; and the control input mapping obtained through optimization is converted into a driving instruction of a robot actuator, and a motion control closed loop is completed. According to the method, the complex movement requirements under strong coupling constraint interaction of the humanoid and the robot can be more accurately met.

The present invention relates to a cooking method based on a cooking AI large model and an AI virtual human system, and an intelligent cooking device thereof. The present invention is characterized by being applied to an intelligent cooking device, the intelligent cooking device being provided with an information collection module, a storage module, a processor, a display screen, and a wireless communication module. The information collection module is used to receive cooking demand information and virtual human demand information, and push the information to a cooking AI large model and an AI virtual human system, respectively. The AI virtual human system is a cloud platform AI virtual human system or a built-in AI virtual human system. The cooking AI large model performs analysis and generates a new cooking method. The AI virtual human system performs analysis and generates a specific AI virtual human. During cooking, the display screen or a mobile terminal of a user outputs the specific AI virtual human. The present invention achieves the application of an AI large model and an AI virtual human in the field of cooking. Moreover, a user or a specific virtual human controls the intelligent cooking device to cook food that meets user demands, and the user can enjoy delicious food cooked by using artificial intelligence technology, and can also enjoy a comfortable cooking process. The built-in AI virtual human system generates a specific AI virtual human within the intelligent cooking device, which is not subject to traffic restrictions and has low costs.

The invention relates to the technical field of interaction, in particular to a trauma bandaging simulation human system and method based on MR interaction control, and the system comprises a simulation human module which is used for providing different types of trauma parts through a simulation human model and transmitting the posture information of the trauma parts to a head-mounted display module; the head-mounted display module is used for displaying the posture information and displaying the virtual binding material and the tool data on the posture information in an overlapping manner; the user posture detection module is used for acquiring a user operation image and identifying a tool selection action and an operation posture of the user based on the operation image; and the binding material tracking module is used for deforming the binding material based on the operation posture and attaching the binding material to the bound trauma part to obtain binding material attachment data. Therefore, vivid visual experience is provided, tactile feedback and dynamic interaction are combined, and a safe and efficient practice learning space is created for a user.

In a first aspect there is provided a robot-assisted method of sorting and / or packing vine fruit into containers by a hybrid robotic and human system. The method comprises placing vine fruit onto a computer-controlled conveyor, inspecting the vine fruit for defects, removing any fruit identified as having a defect from the conveyor, weighing the vine fruit, in the event that the weight of the vine fruit is above a selected threshold, cutting the vine fruit using a robotic end effector mounted on a robotic arm to produce a cut vine having an estimated weight below the selected threshold, placing the cut vine into a container, checking the weight of the container holding the cut vine, determining whether the weight of the container holding the cut vine is within a selected threshold weight range, and in the event that the determined weight is outside the selected threshold weight range, topping up the container with vine fruit to reach the selected threshold weight range. It will be understood that the threshold weight range may simply be a target weight / target minimum or threshold weight.

The application provides a dynamic walking exoskeleton control method and system based on human-computer complementary optimization, comprising the following steps: defining the step height of the contact point, the normal contact force, constructing the nonlinear complementary problem constraint and model; defining the centroid position tracking of the contact point, the centroid linear velocity tracking, the foot yaw angle alignment, the frame attitude tracking, the base quaternion derivative regularization, the contact force regularization, the joint regularization, the swing height control, the contact control regularization, 9 types of motion task quantization targets, and establishing a multi-task objective function; coupling the static nonlinear complementary problem with the exoskeleton continuous dynamics to construct a coupled system; solving the optimization objective function by using a neural dynamics algorithm to obtain the optimal control input of the exoskeleton-human system; and mapping and converting the control input obtained by optimization into the driving instructions of the robot executor to complete the motion control closed loop. The application can more accurately adapt to the complex motion requirements under the human-robot strongly coupled constraint interaction.

The invention provides an operation method of a bionic operation robot based on a digital human. The invention discloses a bionic operation robot operation method based on a digital human. The bionic operation robot operation method comprises the following steps: S1, constructing a digital twin virtual human system and a bionic operation robot; s2, the digital twin virtual human system interacts with the bionic operation robot; and S3, a control room is constructed, and remote control over the bionic operation robot is achieved. The operation method of the bionic operation robot based on the digital human has the advantages that the calculated amount for establishing a human body digital twinning system can be greatly reduced, the quality of reconstructed twinning bodies is improved, the quality of the bionic robot is improved, and the bionic robot can replace manual work to enter a dangerous environment for work and rescue.

This document provides the MD codes, MD DYNA codes, MD ASA system, and Next Human system, as well as methods for using them in the diagnosis and treatment of aesthetic conditions or disorders.

The invention relates to the technical field of robots, in particular to a bionic operation robot system based on a digital human, which comprises a bionic operation robot, a control room and a digital twin virtual human system, and is characterized in that the digital twin virtual human system and the control room are connected with the bionic operation robot; the bionic robot comprises a walking module, a visual module, a touch module, a mechanical arm module, a manipulator module and a touch feedback module, and the control room comprises a control room body, a master hand data glove, a control console, a voice system, a display system and a communication system. The bionic operation robot system based on the digital human has the advantages that the calculated amount for establishing a human body digital twinning system can be greatly reduced, the quality of reconstructed twinning bodies is improved, and therefore the quality of a bionic robot is improved, and the bionic operation robot system can replace manual work to enter a dangerous environment for work and rescue.

The application discloses a kind of human system overall emergent property measurement method of fusion integrated learning and score card, specifically include: (1) index system construction based on analytic hierarchy process, (2) abnormal feature extraction of time series signal, (3) physical examination dataset feature dimension expansion, (4) human system overall emergent property measurement method based on "integrated learning-score card": for the index data obtained after the above processing, integrated learning model is constructed to process ten subsystems respectively, to obtain the health status of subsystem and the contribution weight to overall health.For the multi-source heterogeneous data such as physical examination static index and time series physiological signal generated by wearable device, a health evaluation scheme combining static and dynamic indicators is proposed;Under the realistic condition that the physical examination data is incomplete, the rationality of feature generation is ensured, and the prediction performance of the model and the interpretability of the score result are also considered, which is convenient for actual health management and risk stratification application.

A robot-assisted method of sorting and / or packing vine fruit into containers 142 by a hybrid robotic and human system comprises placing vine fruit 133 onto a computer-controlled conveyor 130a, 130b, inspecting the vine fruit 133 for defects, removing any fruit identified as having a defect from the conveyor130a, 130b, weighing the vine fruit, in the event that the weight of the vine fruit 133 is above a selected threshold, cutting the vine fruit using a robotic end effector 120 mounted on a robotic arm 110 to produce a cut vine having an estimated weight below the selected threshold, placing the cut vine into a container 142, checking the weight of the container 142 holding the cut vine, determining whether the weight of the container 142 holding the cut vine is within a selected threshold weight range, and in the event that the determined weight is outside the selected threshold weight range, topping up the container with vine fruit to reach the selected threshold weight range. Placing the cut vine into a container 142 may comprise using a robotic end effector 122 mounted on a robotic arm 114. Weighing the vine fruit 133 may comprise making a determination based upon received image data of the vine fruit 133. Inspecting the vine fruit 133 for defects may comprise applying a trained machine learning model to received image data of the vine fruit 133. Determining whether the weight of the container 142 holding the cut vine is within a selected threshold weight range may comprise passing the container 142 over an in-line weight scale 260.

In a first aspect there is provided a robot-assisted method of sorting and / or packing vine fruit into containers by a hybrid robotic and human system. The method comprises placing vine fruit onto a computer-controlled conveyor, inspecting the vine fruit for defects, removing any fruit identified as having a defect from the conveyor, weighing the vine fruit, in the event that the weight of the vine fruit is above a selected threshold, cutting the vine fruit using a robotic end effector mounted on a robotic arm to produce a cut vine having an estimated weight below the selected threshold, placing the cut vine into a container, checking the weight of the container holding the cut vine, determining whether the weight of the container holding the cut vine is within a selected threshold weight range, and in the event that the determined weight is outside the selected threshold weight range, topping up the container with vine fruit to reach the selected threshold weight range. It will be understood that the threshold weight range may simply be a target weight / target minimum or threshold weight.

The present invention discloses a dynamic adaptation method for docking the B-end interface in the human resources system based on JAVA dynamic loading, and relates to the field of software adaptation technology. It includes demand disassembly, which specifies that the demand is disassembled into fixed demand and dynamic demand; basic code positioning, which locates the target code source in the basic source code according to the fixed demand and the dynamic demand, and splits it into independent code sources, which are compiled separately to jointly realize the specified demand; dynamic loading engine parameter adjustment, which uses the dynamic loading engine to dynamically adjust the parameters in the target code source corresponding to the dynamic demand, and the dynamic loading engine obtains the parameter adjustment data from the front-end interface of the B-end. The dynamic demand of the present invention disassembles the demand of the B-end of the enterprise, so that the basic source code of the human resources system in the entire cloud is divided into two target code sources of fixed demand and dynamic demand, and then cooperates with dynamic compilation and loading, so that only the functional requirements corresponding to the parameter adjustment items can be modified.

The invention belongs to the technical field of virtual interaction, and relates to an interaction system in a human-machine-virtual human mode, which comprises a data acquisition module used for acquiring multi-modal data; the multi-modal data comprises voice data, text data, image data or video stream data; the intention recognition module is used for performing intention recognition on the multi-modal data to obtain an intention recognition result; the intention recognition comprises secret language recognition, question and answer library recognition and large language model recognition; and the virtual human module is used for identifying the identity of the user before acquiring the multi-modal data, inputting the identity information as a cue word into a large language model to adjust an interaction mode, and rendering an intention identification result in a target format in a text streaming manner on a virtual human page. According to the method, the virtual human system driven by the large language model is used as a core medium to interact with a full-stack platform and multiple devices, and rapid and natural operation experience and the capability of efficiently processing point tasks are provided.

The invention relates to the technical field of release process optimization and authority management, and discloses an authority management method and device for system release, computer equipment and a medium, and the method comprises the steps: receiving system release request information comprising system information, release time, a transfer node and a processor corresponding to the transfer node; according to the system information and the transfer nodes, authorities are distributed to corresponding processing persons; determining a permission review level according to the system information and the release time; in the process of processing the transfer node by the processor, detecting whether the processor has an unauthorized behavior or not according to the authority review level; and if the unauthorized behavior exists, determining an alarm level according to the unauthorized behavior and the authority review level to give an alarm. According to the method, all stages of system publishing are subjected to refined integrated management and control, the authority management level in the system publishing process is improved, an unauthorized behavior is detected and reminded in real time in the system publishing process, and the safety of the system publishing process is improved.