38 results about "Training - action" patented technology

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 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.

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 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.

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 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 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 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 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 invention provides a strength test method and strength test equipment, relates to the technical field of fitness equipment, and solves the problem that a user needs a long test time to complete a 1RM test once. The action speed when a user executes training actions is maintained within a preset speed range, strength values at multiple moments in the process that the user executes a single training action are detected, so that single strength data executed by the action are determined, and then the strength data of the user are determined after the user completes the first preset number of training actions. According to the scheme, the current maximum strength level of the user is determined according to the corresponding single-time strength data, so that rapid testing is achieved, the testing time can be shortened, and the user is helped to complete strength testing more conveniently and accurately.

The invention discloses a static training auxiliary device and a method thereof. The method comprises the following steps: acquiring a training action image of a training object collected by a camera; extracting a training action reference image from the background database; extracting human body posture features of the training action image and the training action reference image to obtain a training action human body posture depth feature map and a training reference human body posture depth feature map; calculating a training action semantic difference feature map between the training action human body posture depth feature map and the training reference human body posture depth feature map; and based on the training action semantic difference feature map, determining whether the training action of the training object is standard or not. Therefore, whether the training action of the training object is standard or not can be intelligently judged through the semantic difference information of the training action, so that timely feedback is provided for the training object, old people are helped to correctly understand and master the standing action, and potential risks caused by incorrect postures or actions are reduced.

The invention relates to the technical field of physiotherapy devices, and particularly discloses a seat rehabilitation training action recognition and control system and method based on artificial intelligence, and the system is provided with an action segment detection module, an artificial intelligence action recognition module and a computer training correction module. The action segment detection module automatically identifies and intercepts a training action segment set containing effective motion information; the artificial intelligence action recognition module outputs structured information such as action types, action stages and action amplitudes, and estimates an active participation degree coefficient of the user in combination with the same multi-source data set; the computer training correction module is used for generating control target parameters of the sitting rehabilitation training equipment by a controller based on the structured information and the active participation degree coefficient, and carrying out online correction on equipment output in the training process, so that the sitting rehabilitation training has the capability of adaptively adjusting assistance and rhythm while executing a correction action; therefore, action recognition and fine control of the on-machine training process are completed.

A strength test method and a strength test device, relating to the technical field of exercise machines, and solving the problem that a user needs a long test time to complete one 1RM test. In this solution, after the strength test device applying the strength test method starts a strength test in response to receiving an instruction, the strength test device maintains the action speed of a user when executing a training action within a preset speed range; detects strength values at a plurality of moments during a process in which the user executes a single training action, so as to determine single strength data in this instance of action execution; and then determines a current maximum strength level of the user on the basis of the corresponding single strength data after the user completes a first preset quantity of training actions, so as to implement a fast test. This solution can shorten the test time and help the user complete the strength test more conveniently and accurately.

The application provides a fencing training action standard quantification evaluation method, and belongs to the technical field of sports action evaluation. The method comprises the following steps: constructing a fencing standard action data set and a fencing practice action data set corresponding to each student; according to the fencing standard action data set and all the fencing practice action data sets, and by using a similarity fusion algorithm, the overall similarity between each fencing practice action of each student and the corresponding fencing standard action is calculated; and each overall similarity is used for multi-dimensional evaluation of the corresponding student. The application can realize non-contact automatic evaluation of fencing actions, output objective, quantifiable and multi-dimensional explainable score results, accurately locate action defects, and provide data support for training optimization.

The application discloses a lower limb rehabilitation training scheme making method and system based on electromyographic signal feedback and belongs to the lower limb rehabilitation guidance field, and comprises the following steps: S1, acquiring a multi-modal original data set and initializing a parameter set; S2, pre-processing the multi-modal original data set to construct a high-dimensional feature set; S3, obtaining a motion intention result and a training state parameter based on the high-dimensional feature set through an attention mechanism LSTM model; S4, dynamically outputting a target resistance torque based on the motion intention and the training state parameter; S5, designing a sliding mode controller to output a control instruction and a training action execution result based on the target resistance torque and the motion intention; and S6, outputting an optimized training scheme based on the execution result and the state parameter. The lower limb rehabilitation training scheme making method and system based on electromyographic signal feedback realize accurate perception, individualized adjustment, safe execution and full-dimensional evaluation of lower limb rehabilitation training.

The invention relates to a supine upper limb swing training device and a training method. The training device comprises a wearable component and an action component, the wearable part comprises a pillow, a chest binding belt, a left sliding box body and a right sliding box body; the left and right sliding box bodies are in sliding connection with the pillow; one end of the pectoral girdle is connected with the left sliding box body, and the other end is connected with the right sliding box body; the right end of the left sliding box body is open; the left end of the right sliding box body is open; the action part comprises a sagittal plane motor, a U-shaped plate, a cross section motor, a two-section telescopic arm, a U-shaped connecting piece and a locking pin shaft A; the upper limb swing training device can be used at home and in a hospital, a patient is in a supine position, and compensation in the upper limb swing training process is reduced through the body gravity, the pillow and the chest binding belt; the training device can swing on the sagittal plane and can also swing left and right, and the accuracy of upper limb swing actions of a patient is guaranteed. The training method is easy to operate, the labor burden of therapists is relieved, accurate training actions of patients are guaranteed, and the rehabilitation effect is guaranteed.

The invention discloses a monitoring assessment device for auxiliary training, which belongs to the field of exercise training monitoring, and comprises a host which is used for collecting, counting and analyzing accessory data in real time, monitoring and recording stride frequency, and displaying information such as step height, step pitch and stride frequency fed back by each accessory; the first accessories are arranged on the two sides of the site and composed of a transmitting end A and a receiving end B, the step height and the step pitch are determined by transmitting ray signals through the transmitting end A and receiving signals through the receiving end B, and the multiple first accessories can be combined to form continuous monitoring; according to the invention, by arranging a multi-component cooperative structure of the host and the accessories 1 to 7, multi-dimensional action parameters such as stride frequency, step height, step pitch, arm swinging, head raising and head turning and the like can be monitored in real time at the same time. The first accessories are arranged on the two sides of the field and matched with accessories of body parts such as toe caps, heels, elbow joints, wrists and mandibular angles to form an all-around data acquisition network, and three-dimensional accurate analysis of training actions is achieved.

The invention relates to a closed-loop brain-computer interface rehabilitation training method and device, equipment and a storage medium. The method comprises the steps that the hand fine movement ability of a trainer is evaluated, and a training target strength interval value is set according to an evaluation result; the method comprises the following steps: collecting an electroencephalogram signal when a trainee grasps a hand in an actual motion / motion imagination, and collecting an electromyographic signal when the trainee grasps the hand through an electromyographic signal collection module; acquiring a motion intention strength value of the trainer as an actual strength value; the difference value between the actual force value and the training target force value is calculated, and a control instruction is generated according to the difference value to control rehabilitation training equipment; and providing tactile feedback force as large as the difference value for the trainer through rehabilitation training equipment, so that the trainer adjusts the motor imagery / actual grasping force and generates training actions for rehabilitation training. According to the method, the brain-computer interface technology and the 3D game are fused, so that the interactivity and interestingness of trainees are enhanced, and the training enthusiasm and initiative are improved.

The application discloses a training filling body, which comprises a body, a partition and a filler. The body is divided into a filling part and a closed space part by the partition. The filling part is filled with the filler, which at least comprises filling particles. The filling part filled with the filler constitutes a load part of the training filling body. The closed space part constitutes a part of the training filling body for gripping. The material constituting the filling part is softer or more elastic than the material constituting the closed space part. The filling part and the closed space part are not communicated with each other. The filler is limited in the filling part and cannot enter the closed space part. The training filling body of the application will not damage the floor or hurt the trainer. Meanwhile, the relative stability of the center of gravity can be maintained along with the action of the trainer in the training use, so that the training action of the trainer is smooth and coherent, the sports interest of the trainer is enhanced, and the persistence of the training is facilitated.

The embodiment of the invention provides a rehabilitation training scheme generation method and device based on multi-modal data fusion, computer equipment and a medium, and the method comprises the steps: obtaining video data and surface myoelectricity data in a process that a target object executes an evaluation action; for each action in the upper limb action, the hand action and the upper limb and hand comprehensive action, acquiring kinematics characteristics of the action based on the video data, and acquiring muscle activation time sequence coordination and abnormal compensation activity of the action based on the surface myoelectricity data; evaluating the function level of each function based on the kinematics characteristic of the action corresponding to each function, the muscle activation time sequence coordination and the abnormal compensation activity; matching and recommending adaptive training actions in corresponding action sub-libraries of the action library according to the upper limb function level, the hand function level and the upper limb and hand comprehensive function level of the target object. According to the scheme, the adaptive training actions can be accurately and individually matched and recommended.