60 results about "Training - action" patented technology

The embodiment of the invention discloses a model training method, a control method, equipment, a medium and a program product. The method comprises the steps of obtaining a training sample set; inputting a next training state in the training sample into the initial action network to obtain a next training action output by the initial action network; inputting the next training action, the current training state in the training sample, the current training action and the next training state into the initial value network to obtain a current target Q value output by the initial value network; if the iteration termination condition is not met, updating the initial value network, obtaining an updated initial value network, updating the initial action network and obtaining an updated initial action network according to the current target Q value, and returning to execute the step of obtaining the training sample set; and if the iteration termination condition is satisfied, determining the initial action network as a target control model. According to the model training method, rapid convergence of the target control model is realized, and the stability of the controlled equipment is improved.

The invention belongs to the field of evaluation assistance, and particularly relates to an interactive teaching evaluation assistance system and device based on multi-modal fusion, and the system collects multi-dimensional information through a portrait module, and constructs a user training action portrait library in combination with multi-modal feature extraction and a knowledge graph algorithm; the strategy recommendation module generates an optimal guidance scheme through a correction scheme matching model according to the portrait library, the real-time information and the teaching guidance strategy library; the auxiliary adjustment module collects training action images in real time, and obtains a guided continuous correction action sequence and a standard score by using a spatial-temporal feature extraction model and an evaluation algorithm; the traceability feedback module is combined with the action standard knowledge base to obtain transverse and longitudinal spatial-temporal change chains of non-standard actions through a forward reasoning model, and feeds back the transverse and longitudinal spatial-temporal change chains to the instructor to adjust the scheme in real time until the actions reach the standard; according to the method, accurate evaluation and personalized scheme matching of multi-modal data fusion are realized, and scientificity and interactivity of evaluation assistance are effectively improved.

The invention discloses an intelligent management method for breast cancer rehabilitation training and related equipment. The method comprises the following steps: generating rehabilitation game tasks based on breast cancer postoperative rehabilitation training actions, wherein each rehabilitation game task comprises at least one breast cancer postoperative rehabilitation training action; under the condition that the patient user executes the game task, motion sensing game video information including the patient user is collected in real time, and actual game actions of the patient user are recognized based on the motion sensing game video information; and performing comparative analysis on the actual game action and the corresponding preset rehabilitation training action, and quantifying the completion degree of the preset rehabilitation training action of the patient user so as to display the completion degree to the patient user in real time. The problems that the postoperative functional rehabilitation of the breast cancer mainly guides a patient to carry out standardized functional training through a physical therapist, but the training mode is relatively mechanical and lacks real-time feedback and interaction, the subjective participation intention of the patient is not strong, and the rehabilitation compliance is low can be solved.

The invention relates to a sports competition training action deviation detection and immediate correction method. The method comprises the following steps: collecting multi-joint dynamic data in a training process; on the basis of a preset inertial conduction continuity criterion, inertial change among all joints of the body is analyzed, and when it is detected that inertial conduction of any joint node is interrupted or an impact value is lower than a threshold value, the joint node is identified as a trigger point of action chain interruption; performing causal priority judgment on the action deviation based on the identified trigger point, determining whether the deviation is a dominant deviation or a subordinate deviation caused by an upstream joint, and if the deviation is the subordinate deviation, tracing an upstream cause and repositioning an intervention target; judging whether the current training stage is in a correction window stage suitable for feedback or not for the deviation which is confirmed to be intervened, and if not, delaying feedback output; and in the window period, trend judgment is performed on the deviation direction, if the deviation causes negative technical degradation, correction feedback is output, and if the deviation trend has positive evolution potential, the deviation is marked as acceptable deviation and is not corrected.

The invention relates to the technical field of training teaching, in particular to an exercise training action teaching system. The system comprises a training data acquisition module, a trainee action difference analysis module, a trainee training teaching module and a demonstration teaching feedback adjustment module, and can acquire corresponding training action postures and acceleration data in real time by configuring an inertial sensor on sports equipment corresponding to a trainee; meanwhile, the corresponding body consumption load condition is obtained; performing student action difference feature analysis on the training action postures and the acceleration data based on the body consumption load condition to obtain training action difference features corresponding to different students in the daily exercise training process; training teaching resources and time limiting conditions are obtained, and student training teaching analysis and teaching feedback adjustment are carried out, so that an exercise training teaching feedback adjustment strategy corresponding to the student is generated. According to the invention, scientific and personalized action teaching services can be provided for exercise training learners, so that the exercise training effect is improved.

The application belongs to the field of evaluation assistance, and particularly relates to an interactive teaching evaluation assistance system and device based on multi-modal fusion. The system collects multi-dimensional information through a portrait module, combines multi-modal feature extraction and a knowledge graph algorithm to construct a user training action portrait library. A strategy recommendation module generates an optimal guidance scheme from a portrait library, real-time information and a teaching guidance strategy library through a correction scheme matching model. An auxiliary adjustment module collects training action images in real time, uses a space-time feature extraction model and an evaluation algorithm to obtain a continuous correction action sequence and a standard score after guidance. A traceability feedback module combines an action standard knowledge base, obtains a horizontal and vertical space-time change chain of non-standard actions through a forward reasoning model, and feeds back to the instructor to adjust the scheme in real time until the action meets the standard. The application realizes precise evaluation and personalized scheme matching of multi-modal data fusion, and effectively improves the scientificity and interactivity of evaluation assistance.

One or more radio access network nodes may determine learning model configuration information for training a learning model corresponding to a user equipment in an idle mode. The node may broadcast a training configuration resource indication in the information block, the training configuration resource indication indicating resources available for broadcasting the learning model training configuration or indicating resources available for broadcasting the training results. While idle, the user equipment may decode the training configuration according to the training configuration resource indication and perform a training action indicated in the training configuration. The learning model may be trained based on the training action while the user device is idle. While idle, the user equipment may estimate radio parameters using a model trained while the user equipment is idle, and transmit the estimated radio parameters to the node for establishing a connection with the node.

The invention discloses a video-based omni-directional remote rehabilitation training system, a video-based omni-directional remote rehabilitation training method and a medium, which are characterized in that a digital standardized training video library classified according to four stages of PT physical therapy is established, and more than 700 digital standardized training videos such as joint activity, balance training, gait correction and the like are covered; it is ensured that the training content is scientific and covers the whole period and all directions of rehabilitation training; rehabilitators generate personalized training schemes in combination with rehabilitation scene types (hospitalization / home / community / old-age care institutions) and clinical data and in combination with remote video evaluation of the rehabilitators, and training requirements in different environments are met. By capturing actions of limb joint angles, joint point motion trails and muscle force changes, a training action deviation rate is calculated and is fed back and output to a rehabilitation teacher in a grading manner, so that the training standardability is remarkably improved; rehabilitators can manage multiple patients online at the same time, remotely check training percentage data, adjust schemes and generate rehabilitation notes, and efficient, accurate and personalized rehabilitation guidance services are provided for the patients.

The present invention relates to the field of muscle function assessment based on precise measurement of perioral muscle strength, specifically a device and method for rhythmic training assessment of perioral muscle strength. The method comprises the following steps: 1) collecting the resistance value signal of the perioral muscle strength during training using a thin film pressure sensor; 2) preprocessing the resistance value signal to obtain perioral muscle strength training information for a single movement; 3) calculating the effectiveness of the single training movement; 4) determining whether the training time has reached the overall training time; if so, executing step 5); otherwise, repeating steps 1) to 3); and 5) comprehensively evaluating the training movements throughout the entire training process and outputting an evaluation score for this training session. The present invention employs automated analysis methods to evaluate each training movement in real time and output the overall training effectiveness results.

The utility model discloses a split type upper and lower limb rehabilitation training device, which relates to the technical field of rehabilitation instruments, and comprises a base, a height adjusting mechanism, a stretching mechanism, two pressing mechanisms, a leg exercising mechanism and a supporting mechanism, fixing bolt holes are symmetrically formed in the positions, close to the front ends and the rear ends of the two sliding grooves, of the top wall of the base at equal intervals, the height adjusting mechanism is arranged on the sliding groove in the right side, the supporting mechanism is arranged on the sliding groove in the left side, and the leg exercising mechanism is arranged on the position, between the height adjusting mechanism and the supporting mechanism, of the top wall of the base. The stretching mechanism is arranged on the left side of the height adjusting mechanism, by adjusting the training device in multiple aspects, different patients can adjust the training device to proper training positions, so that the training device is suitable for being used by different patients, and by increasing different training actions, the training device can be used by patients with different requirements.

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for controlling an agent that is interacting with an environment. Implementations of the system use previously learned skills to explore states of the environment to collect and store training data, which is then used to train an action selection system. The system includes a set of skill action selection subsystems, each configured to select actions for the agent to perform for a respective skill. The set of skill action selection subsystems is used to explore states of the environment to collect the training data, keeping their individual action selection policies unchanged. A scheduler neural network selects the skill neural networks to use. The action selection system is trained on the stored training data.

The application relates to the technical field of rehabilitation training, in particular to a home environment cognitive rehabilitation training action guiding system based on visual interaction. The system can realize the following steps through mutual cooperation among multiple modules: acquiring a rehabilitation training image of a target patient in each unit training period within each preset rehabilitation training period, and acquiring a cognitive recovery score corresponding to each preset rehabilitation training period; determining a target motion vector sequence and a target state value sequence; performing interval division and clustering on the training action period; determining an action proficiency index corresponding to each training action period; and determining a target recommended guiding value corresponding to a training action represented by each target cluster. The application quantifies the target recommended guiding value corresponding to different training actions by analyzing the self condition of the target patient in the rehabilitation training process, thereby improving the rationality of cognitive rehabilitation training action recommendation and the guiding effect of cognitive rehabilitation training action.

The invention provides a hand rehabilitation training control system and method, and relates to the technical field of rehabilitation medicine. The system comprises a client, a main control unit, a power mechanism and a plurality of training suites, the client is used for determining a target training function, generating a training instruction according to the target training function and issuing the training instruction to the main control unit, and the training instruction is used for indicating a target training suite corresponding to the target training function; and the main control unit is used for controlling the power mechanism to rotate according to the training instruction so as to drive the target training suite to execute the training action. According to the rehabilitation training device, the multiple training suites can share one main control unit and one power mechanism, the equipment complexity and cost are reduced, different training suites can execute different training actions, the training requirements of multiple parts such as hand, wrist and forearm training are met, personalized and precise rehabilitation training tasks are completed, and the rehabilitation training efficiency is improved. The problem that an existing hand function rehabilitation training device cannot meet comprehensive and systematic hand function rehabilitation requirements is solved.

This invention discloses a multi-level adjustable automatic arm integrated training frame, including a training frame, a smart screen fixedly connected to the outer wall of the training frame, rotation limit components on both sides of the smart screen, an angle sensor fixedly connected to the bottom of the training frame, and a training device below the rotation limit components, the training device including a fixing frame. This multi-level adjustable automatic arm integrated training frame, through the use of the rotation limit components and the training device, enables the training arm to perform multi-angle three-dimensional adjustment. Through an automatically controllable movable arm structure, it provides two degrees of freedom: vertical swing and left-right rotation. It achieves free and automated setting of resistance fulcrums within a range of multiple curved surfaces in space, realizing the automation of the integrated training frame. It can complete most training movements, greatly reducing the required fixed equipment and improving the utilization efficiency of equipment and space.

The application discloses a rehabilitation training method and system based on a human motion model, relates to the technical field of rehabilitation training, and mainly has the following scheme: collecting multiple data of a patient; constructing a human motion model and outputting simulation data; calculating a physiological index coefficient, and further calculating the motion intensity of each training action; calculating the motion mode complexity index of each training action, and then obtaining the training duration of each training action; calculating a motion deviation value, and then calculating a comprehensive dynamic deviation index. A preset threshold value is used to determine whether the rehabilitation training plan is suitable for the current state of the patient, and whether the rehabilitation training plan needs to be changed. The method can evaluate the adaptability of the rehabilitation training plan in real time, dynamically adjust the training scheme, and ensure that the training always conforms to the state of the patient, thereby improving the rehabilitation efficiency and success rate.

The application discloses a kind of elbow joint rehabilitation training technical field's two-way assisted elbow joint rehabilitation training device and training method, including support base, turnover support and sliding slot base, the rear end of the turnover support can be rotatably connected in the front end of support base, sliding block and drive motor are slidably installed in the top of the sliding slot base, controller is further arranged in the support base, and electromyographic sensor is arranged on the support base and turnover support, patient can be helped to carry out passive training by the device, active training mode can also be provided, patient is forced to actively use muscle strength, impedance training is provided in the later stage of patient recovery, resistance is provided to patient training action, impedance is formed, impedance type rehabilitation training is generated for patient, effectively help patient to finally restore normal state of elbow joint muscle, and in the same stroke, three different training modes can also be combined with each other, to achieve the best training effect.

The application provides a lip muscle training device and method, relates to the field of lip muscle training equipment, and aims to solve the problems of poor guidance and difficulty in quantitative recording of the current lip muscle training. A guide plate with multiple guide grooves is arranged, a lip baffle plate is pulled by a flexible cable to slide a sliding block in the guide groove, the relative positions of the multiple guide grooves are different, the lip muscle active closure of the trainer is guided to pull the sliding block to move in different directions, the training action is guided to be shaped, and the number of times that the sliding block is moved to the position in the guide groove is collected by a counting component, so that the training process is recorded quantitatively.

The invention discloses a model training method and a virtual coach guidance strategy generation method, and relates to the technical field of computers. The method comprises the steps of obtaining a current state after a user executes a current training action; wherein the current state comprises an action quality score, a fatigue degree score, a self-satisfaction degree score, an understanding degree score and any multiple items in the sensor data of the sports equipment, inputting the current state into a DQN model, and obtaining a Q value of each strategy in a preset action space; selecting a current strategy from the action space based on the Q value of each strategy; executing the current strategy; after the user responds to the current strategy to execute the next training action, the next state of the user is obtained; and adjusting parameters of the DQN model based on the current state, the next state and the current strategy. According to the embodiment, more targeted training guidance can be provided for the user, and the training quality of the user is improved.

The invention relates to the technical field of tennis training, in particular to a tennis core strength training model establishing method, which comprises the following steps of: inducing to generate muscle activation stimulation in a core muscle group through tennis training actions, and acquiring a total training stimulation amount based on a process that the muscle activation stimulation is captured by a muscle fiber and a nerve-muscle joint movement unit; determining a core strength increase equation based on the total training stimulation amount, and integrating the individual characteristic parameters of the athletes to construct a scalable core strength increase model; a scalable fatigue recovery model based on a BP neural network is obtained and used for quantifying the dynamic relation between the fatigue index and the athlete individual characteristics, training parameters and recovery time, and training cycle planning is optimized; a core strength increasing model and a fatigue recovery model are fused, a core strength training effect scalable model is formed, the change relation between the training effect and athlete individual characteristics, training parameters and training stages is comprehensively measured, and scientific and personalized core strength training scheme design and dynamic adjustment are achieved.

The invention relates to the technical field of rehabilitation training, in particular to a family environment cognition rehabilitation training action guiding system based on visual interaction, and the system can achieve the following steps through the mutual cooperation of a plurality of modules: obtaining rehabilitation training images of a target patient in each unit training period in each preset rehabilitation training period, obtaining a cognitive recovery score corresponding to each preset rehabilitation training period; determining a target motion vector sequence and a target state value sequence; interval division is carried out, and training action time periods are clustered; determining an action proficiency index corresponding to each training action period; and determining a target recommendation guide value corresponding to the training action represented by each target cluster. According to the cognitive rehabilitation training action recommendation method and device, the target recommendation guide values corresponding to different training actions are quantified by analyzing the conditions of the target patient in the rehabilitation training process, so that the reasonability of cognitive rehabilitation training action recommendation is improved, and the cognitive rehabilitation training action guide effect is improved.

The invention discloses a multifunctional low-position tension training device, and belongs to the technical field of tension training device production, the multifunctional low-position tension training device comprises a main body module, a training module and an adjusting module, the main body module comprises a training main frame, one side of the training main frame is provided with a waistband, a double-hand grip and a single-hand grip, the training main frame is connected with an armrest assembly, and the armrest assembly is connected with the training module. The training module comprises four sliding rods fixedly connected to the training main frame, through arrangement of pulleys, a traction assembly, a connecting chain, a waistband, a double-hand grip and a single-hand grip, precise force line adaptation of six types of training actions is achieved, deep squat obtains downward resistance, the traction assembly supports gear angle adjustment, and the training effect is achieved. The training device is suitable for different force exerting tracks of hard pulling / side horizontal lifting, the connecting chain is matched with the waistband, the double-hand grip and the single-hand grip, second accessory quick change is achieved, whole muscle group training of buttocks, legs, the back and shoulders is covered, and the functionality of the training device is comprehensively improved.

The utility model belongs to the field of medical auxiliary instruments, and particularly relates to a training device for limb rehabilitation treatment, which comprises a base, a big arm fixing component and a forearm training component. A guide groove is formed in the base in the length direction of the base, the big arm fixing assembly is fixedly installed at one end of the base, the forearm training assembly is installed in the guide groove in a sliding mode, and a telescopic rod is connected between the big arm fixing assembly and the forearm training assembly; a wrist joint training assembly is arranged at the other end of the base, a pneumatic tendon set is connected between the wrist joint training assembly and the forearm training assembly, and the pneumatic tendon set drives the wrist joint training assembly to conduct training actions in at least two directions. The forearm rehabilitation training device has the advantages that the forearm to be subjected to rehabilitation training is rotationally pressed through the forearm training assembly and the wrist joint training assembly, the wrist is stretched, the function of limbs is helped to be recovered, the structure is simple, and the practicability is high.

The application discloses a model training method and a virtual coach guidance strategy generation method, and relates to the technical field of computers. The method comprises the following steps: acquiring a current state of a user after the user performs a current training action; wherein the current state comprises any multiple items of an action quality score, a fatigue degree score, a self-satisfaction score, an understanding degree score and sensor data of a sports device; inputting the current state into a DQN model to obtain Q values of each strategy in a preset action space; selecting a current strategy from the action space based on the Q values of each strategy; performing the current strategy; acquiring a next state of the user after the user performs a next training action in response to the execution of the current strategy; and adjusting parameters of the DQN model based on the current state, the next state and the current strategy. The embodiment can provide more targeted training guidance for the user and improve the training quality of the user.

The invention discloses a data intelligent analysis method and an integrated sports robot training system, and belongs to the technical field of training systems. The invention discloses an intelligent data analysis method and an integrated sports robot training system, and the method comprises the steps: carrying out the face recognition of a trainee, carrying out the recognition and analysis of the training movement limb movement track of the trainee, carrying out the broadcasting of a corresponding training voice instruction, carrying out the broadcasting of a guiding voice, and recording the training duration. And establishing an assessment data analysis model according to the training condition of the personnel. The system solves the problems of inaccurate assessment data, non-objective evaluation and difficulty in cheating due to the fact that existing patents cannot arrange military physical training assessment conditions, ensures objective and fair assessment and evaluation and efficient and real data acquisition, is matched with a big data analysis platform, can accurately position training problems, and improves the training efficiency. Weak items and wrong items are found in time, an improvement strategy is accurately made according to the found situation, and efficient training is promoted.

The application discloses a real-time analysis system and method for muscle activity based on electromyographic signals, and relates to the technical field of electromyographic signals, and comprises the following steps: calling signal acquisition records of user project training, extracting corresponding sampling frequencies, and obtaining target sampling frequencies; collecting electromyographic data of muscle contraction completed by the user; decomposing the training project into a plurality of training actions, obtaining a reference vector set of each limb, and obtaining an effective time period of each training action; dividing the effective time period into a plurality of time windows, establishing a time domain function corresponding to the effective time period, and obtaining a target time length of each training action; acquiring a training action at the current training time, evaluating abnormal conditions of the training action, and giving early warning and prompt to relevant instructors. The application analyzes historical signal acquisition records in combination with multi-dimensional characteristics, monitors abnormal behaviors in the project training process in real time, gives early warning and prompt to instructors in a timely manner, and is helpful to reduce the risk of muscle injury of the user.

A training course scheduling method, device and non-volatile computer readable medium, comprising sensing a maximum capacity value of performing a test exercise item in a unit time; estimating a physical fitness score according to the maximum capacity value; arranging a training exercise item schedule of a training course according to the physical fitness score; sensing a training intensity value of performing a training exercise item in a training time; estimating a unit intensity value of the training exercise item in a unit time according to the training intensity value; comparing the unit intensity value with a preset intensity value corresponding to the training exercise item; updating the preset intensity value of the training exercise item and the maximum capacity value in response to judging that the unit intensity value is greater than the preset intensity value; and estimating a physical fitness score according to the updated maximum capacity value, and updating the training exercise item schedule of the training course according to the updated physical fitness score.

The invention belongs to the field of upper limb function training, and provides an AI intelligent hand plugboard for upper limb function training, the AI intelligent hand plugboard comprises a bottom plate, a plurality of plugboard mechanisms are arranged on the top of the bottom plate in the horizontal direction of the bottom plate, each plugboard mechanism comprises a base plate, and a mounting groove is formed in one side of the top of each base plate; through cooperative cooperation of the adjusting mechanism and the inserting plate mechanism, continuous adjustment of a circular hole clamping space is achieved, inserting rods with different diameters can be stably clamped, the problems that in traditional equipment, shaking is unstable due to the fact that the inserting rods are too thin, and inserting is difficult due to the fact that the inserting rods are too thick are effectively solved, and the practicability is high. The accuracy of training actions and the comfort of the operation process are improved; meanwhile, due to the linkage design of the docking mechanism and the locking mechanism, the layout of the insertion plate mechanism on the bottom plate can be flexibly adjusted according to different rehabilitation training requirements.

The invention aims to disclose an offline rehabilitation training system based on remote interaction, which comprises a rehabilitation training terminal and a remote interaction terminal, and the rehabilitation training terminal and the remote interaction terminal are connected with each other in a wireless communication mode; the rehabilitation training terminal establishes a digital standardized training video library through a digital standardized training video library unit, so as to ensure that the training content is scientific and covers the whole period and all directions of rehabilitation training; an intelligent evaluation unit and a training scheme generation unit are combined with rehabilitation scene types and clinical data evaluation to generate personalized training schemes, and training requirements in different environments are met; actions of limb joint angles, joint point motion trails and muscle force changes are captured through the training monitoring unit, the training action deviation rate is calculated and fed back in a graded mode, and the training standardability is remarkably improved; a rehabilitation teacher can simultaneously manage multiple patients online through the remote interaction terminal, remotely check training percentage data, adjust a scheme and generate a rehabilitation report, and the purpose of the invention is achieved.

The rehabilitation training equipment comprises a supporting frame, an adjusting mechanism is arranged on the supporting frame, the adjusting mechanism comprises a seat, handles, a follower plate, a rubber sleeve, an outer friction pipe, an inner friction pipe, a guide rod, a guide sleeve, a fixing sleeve, a clamping mechanism and a rotating mechanism, the seat is installed on the supporting frame, the handles are installed on the two sides of the seat, and the follower plate is installed on the supporting frame. The follow-up plate is rotationally connected to the supporting frame, the guide rod and the guide sleeve are matched to ensure the accuracy and stability of the motion trail, the outer friction pipe and the inner friction pipe are sleeved, an adjustable resistance system is ingeniously achieved, a foundation is provided for follow-up fine adjustment through the arrangement of the fixing sleeve, and the whole mechanism is comprehensive in design consideration and high in practicability. Normativity of training actions is guaranteed, the possibility of resistance adjustment is provided, and the effect and safety of rehabilitation training are greatly improved.