880 results about "Body posture" patented technology

In one implementation, a method of body pose estimation is performed at a device including one or more processors and non-transitory memory. The method includes obtaining a plurality of two-dimensional images of a body in a three-dimensional environment at a respective plurality of times. The method includes determining, for each of the plurality of two-dimensional images, the two-dimensional location in the two-dimensional image of one or more joints of the body at the respective plurality of times. The method includes determining, based on the two-dimensional locations, a plurality of three-dimensional locations in the three-dimensional environment of the one or more joints of the body at the respective plurality of times. The method includes determining, based on the three-dimensional locations, a plurality of updated three-dimensional locations in the three-dimensional environment of the one or more joints of the body at the respective plurality of times.

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 an examination room abnormal behavior analysis method and system for examinees in a computer examination, and the method comprises the steps: extracting the facial expression, body posture information, keyboard tapping frequency, mouse movement track and other behavior data of the examinees, and forming a comprehensive behavior feature set; a time sequence prediction algorithm based on a long and short term memory network is combined with an attention mechanism to analyze a behavior pattern in a time dimension, and abnormal behavior information is obtained; creating a target examination room environment graph through a graph neural network algorithm, analyzing abnormal behavior information, and identifying collaborative cheating behaviors; introducing a Q learning reinforcement learning framework, and dynamically adjusting a detection strategy; performing weighted fusion on the abnormal behavior information, the collaborative cheating recognition result and the detection strategy by using an extreme gradient lifting learning algorithm, calculating a comprehensive score, and generating an abnormal behavior judgment report based on the comprehensive score; according to the method, the detection capability and efficiency of the abnormal behaviors and the cheating behaviors in the online examination are improved, and the fairness and fairness of the examination can be maintained.

The invention discloses a multi-sensor fusion-based position and posture estimation method for a working device of a mining robot, which realizes accurate position and posture estimation by installing a body posture sensor and an environment sensing sensor and combining a kinematic model, visual inertia state estimation and a nonlinear least square optimization algorithm. The method comprises the following steps: firstly, carrying out preliminary prediction on a kinematic model through feedback data of an encoder and an inclinometer, and constructing a local visual inertia estimator by utilizing a camera and an MEMS to correct a prediction result; and then, a combined constraint modeling and optimization method is adopted to improve the precision of the pose of each working mechanism. Besides, geometric features of the bucket are extracted through a semantic segmentation network and a template matching technology, six-degree-of-freedom pose estimation of the bucket is completed, finally data fusion of a body pose sensor and an environment perception sensor is performed through a factor graph optimization algorithm, and comprehensive pose estimation of the whole working device is achieved. The working pose of the mining robot can be monitored in real time, the operation precision is improved, human errors are reduced, the working efficiency and safety can be optimized through data analysis, and more effective support is provided for path planning of a working device of the mining robot.

The invention relates to the technical field of robot perception, in particular to an intelligent accompanying human-type robot based on multi-mode emotion interaction and a perception method, and the method comprises the following steps: collecting facial expression and body posture data of a user through a visual perception unit, collecting intonation, speed, volume and keyword data through a voice perception unit, and carrying out the recognition of the speech, speed, volume and keyword data; data preprocessing and feature extraction are carried out; secondly, carrying out time sequence modeling on the extracted visual and voice features based on a recurrent neural network, and generating visual and voice time sequence feature vectors; the method comprises the steps that firstly, time sequence features are extracted, then, a multi-mode fusion model based on an attention mechanism is adopted, the time sequence features are fused into a comprehensive emotion feature vector used for emotion state classification, and finally, personalized interaction content such as voice, expressions and limb actions matched with the emotion state of a user is generated according to an emotion classification result. According to the method, the accuracy of robot emotion perception and the naturalness of man-machine interaction are remarkably improved, and the method is suitable for multi-scene application of education, medical treatment, old-age care and the like.

The invention discloses a digital character real-time generation method and device, and the method comprises the steps: obtaining audio content and a two-dimensional digital character image, generating a model through a pre-trained whole body motion, processing the audio content, obtaining a three-dimensional whole body posture sequence, mapping the three-dimensional whole body posture sequence into a two-dimensional whole body posture sequence, and carrying out the real-time generation of a digital character. Performing real-time posture driving on the two-dimensional whole body posture sequence and the two-dimensional digital character image through a pre-trained real-time posture driving generation model to obtain a corresponding posture video, and adjusting a face image of a digital character in the corresponding posture video in real time through a pre-constructed lip synchronization model and audio content to obtain a lip synchronization result. Enabling the lip shape in the face image to be consistent with the audio content, and obtaining a target digital figure video which is a two-dimensional digital figure video in which whole body actions, facial expressions and voice content semantically are consistent.

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 Pick ball athlete action recognition and analysis system based on multi-modal data fusion, and the system comprises the steps: collecting the video image data and sensor data of a Pick ball athlete in the motion process, and carrying out the feature extraction of the body posture of the athlete in the video image data through a convolutional neural network; according to the method, a recurrent neural network is combined to perform action classification on a feature sequence, meanwhile, sensor data are fused, accurate recognition of actions of an athlete is achieved, meanwhile, detailed technical parameters of the athlete in the ball hitting action can be obtained by deeply analyzing the recognized actions, accurate guidance is provided for training of the athlete, and the training efficiency is improved. And the technical level and the competitive ability of athletes can be improved.

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 discloses an automobile performance display method and system based on VR, and relates to the technical field of automobile VR. The system is composed of a plurality of functional modules, and comprises a multi-modal data acquisition module for acquiring multi-modal data; the multi-modal data comprises human body posture capture, seat mechanics monitoring data and vehicle state synchronization data; the dynamic fusion module is used for extracting modal features based on the multi-modal data; the modal features comprise attitude features, pressure features and performance features, a joint feature vector is obtained through splicing fusion, a multi-head attention mechanism is introduced, and each modal weight is dynamically allocated; a Transform + CNN hybrid architecture is used, modal features are input, a generative adversarial network is used, somatosensory simulation control signals are output, and a vehicle performance mapping model is constructed; and vehicle performance display: obtaining the body posture data of the experiencer, and carrying out self-adaptive performance adjustment on the experiencer according to the vehicle performance mapping model in combination with the current vehicle performance state.

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 embodiment of the invention discloses an information display method and device, equipment, a storage medium and a program product, and relates to the technical field of computers.The method comprises the steps that a three-dimensional model of a target object is rendered and displayed in a preset display area of a current page at a first rendering view angle; in response to the detected view angle conversion trigger event, obtaining event data corresponding to the view angle conversion trigger event; wherein the view angle conversion trigger event comprises a terminal posture change event of the current terminal and / or a body posture change event of the current user, the event data corresponding to the terminal posture change event comprises terminal posture data, and the event data corresponding to the body posture change event comprises body posture data; rendering and displaying the three-dimensional model of the target object at a second rendering view angle based on the event data; wherein the first rendering view angle is different from the second rendering view angle, and the effect that the rendering view angle of the three-dimensional model changes along with changes of the terminal posture and / or the body posture of the user is achieved.

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 pressure sore nursing, discloses an intelligent nursing system for pressure sore nursing of a patient suffering from cerebral infarction and a back raising optimization method, and is particularly used for solving the problem that the risk of pressure sore deterioration is caused due to the fact that the patient suffering from cerebral infarction cannot sense local pressure and abnormal shearing force in the back raising process in time due to feeling and dyskinesia. The system comprises a data acquisition module, a feature extraction module, a feature fusion module, a feature dimension reduction module, a pressure sore risk prediction module, a feedback control module and a back-up execution module, and the method is based on a target function, and dynamically adjusts back-up execution parameters in combination with acquired data and pressure sore risk scores and grades obtained through analysis. According to the method, multi-modal data are collected in real time, the body posture, motion trail, local stress, shearing force and pressure of the patient in the back raising process are comprehensively considered, closed-loop control is optimized through an objective function, the back raising speed, angle and supporting force are dynamically adjusted, and pressure sore aggravation or secondary injury of the patient after cerebral infarction in the back raising process is prevented.

The invention relates to the technical field of 3D modeling, and discloses a 3D modeling-based teenager body posture intelligent evaluation method, which comprises the following steps of: 1, performing spatial modeling on teenager body postures by using a topology method, and representing the teenager body postures as a high-dimensional manifold space, the topological relation between postures in the posture space is captured by conducting homology group analysis on the high-dimensional manifold space; and 2, after the topological structure of the body posture of the teenager is obtained, carrying out dimension reduction on high-dimensional posture data by applying a manifold learning technology, and optimizing the expression of the data by using a local linear embedding method. Through combination of a topology method and homology group analysis, modeling of teenager body postures in a high-dimensional manifold space is realized, topological relations among postures in a posture space can be effectively captured, a 3D posture model is obtained, and the problem that complex posture changes cannot be accurately described in the prior art is solved.

The invention provides an anti-rollover control method and system for an electric automobile, and relates to the field of automobile body posture control. The control method comprises the following steps: collecting vehicle driving data; calculating a transverse load transfer rate based on the vehicle driving data, and calculating a comprehensive risk index in combination with the transverse load transfer rate and a sprung mass roll angle; the method comprises the following steps: presetting a comprehensive risk index early warning threshold value and a comprehensive risk index danger threshold value, judging the rollover working condition and the comprehensive risk index of the automobile, and executing a corresponding rollover prevention control strategy: when the rigidity of the suspension is changed, the comprehensive risk index still increases and exceeds the comprehensive risk index danger threshold value; the anti-rollover moment is changed by changing the control force of the suspensions on the two sides. After the suspension control force suppresses roll for a certain period of time, the comprehensive risk index is still not reduced to be below the early warning threshold value, the active steering system intervenes in combined control, the active steering system has two steering modes including front wheel steering and four-wheel steering, and different steering modes are used under different working conditions.

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 provides a vehicle damping control method and device, electronic equipment and a readable medium, which are applied to a continuous damping control system, and vehicle damping is associated with the control intensity of a vehicle body posture. The vehicle speed, the pitch angle speed, the roll angle speed and the unsprung acceleration of the vehicle in the running process are obtained; according to the unsprung acceleration and / or the vehicle speed, the driving road condition of the vehicle is determined; the driving pavement condition is used for indicating whether the driving pavement of the vehicle is a flat pavement and whether a vehicle impact object exists on the driving pavement; based on the pitch angle speed and / or the roll angle speed, the vehicle body posture state of the vehicle is determined; the vehicle body posture state is used for indicating whether the vehicle has vehicle body posture out-of-control risk; judging whether the vehicle meets a damping improvement condition or not based on the driving road condition, the vehicle speed and the vehicle body posture state; and if the vehicle meets the damping improvement condition, the control strength of the vehicle on the vehicle body posture is improved by improving the damping of the vehicle, and it is guaranteed that the comfort on the flat road surface is not deteriorated.

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 discloses a cognitive movement dual-task intelligent testing and training system. The system comprises a three-dimensional rotating platform, a door frame type auxiliary frame, a plantar pressure film, a head top scanning radar, a tension traction component and a dual-screen display control unit. The plantar pressure film is laid on the upper surface of the three-dimensional rotating platform; the overhead scanning radar, the tension traction part and the double-screen display control unit are installed on the door frame type auxiliary frame. The three-dimensional rotating platform provides a three-dimensional non-linear unstable motion environment with presettable difficulty for a patient, the double-screen display control unit provides cognitive recognition information, and the head top scanning radar, the plantar pressure film and the tension traction component collect body posture data of the patient. According to the invention, a cognitive motion dual-task evaluation and training means based on a three-dimensional nonlinear unstable motion environment is provided for doctors and physicians, so that the evaluation accuracy and the training pertinence are remarkably improved.

The invention provides a patient state auxiliary judgment and posture adjustment method, device and system, and relates to the technical field of medical equipment. The method comprises the following steps: acquiring real-time state data of a patient; generating a three-dimensional posture model and emotion parameters of the current body posture of the patient based on the real-time state data; according to the difference degree of the preset target posture and the three-dimensional posture model, a posture adjustment instruction is generated in combination with a manual adjustment instruction of a doctor; and based on the posture adjustment instruction, prompting the patient to adjust the posture until the difference degree is smaller than a preset threshold value and the emotion parameters are in a target emotion range and lasts for a preset duration, and confirming that the patient completes examination preparation. Through the technical scheme provided by the invention, the problems that accurate state judgment is difficult to obtain and posture auxiliary adjustment cannot be performed on the patient before the patient is examined are solved, the accuracy of state perception of the patient and the efficiency of posture adjustment are improved, and the examination experience of the patient is improved.

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.

Various embodiments of the teachings herein include systems and methods for monitoring the posture of a user during use of an electronic device. An example includes: reading an image from a camera associated with the electronic device; determining a value representing the posture shown in the image; and transmitting a warning signal if the value falls in a warning range.