3530results about "Gymnastic exercising" patented technology

The invention discloses a hip and knee joint replacement postoperative rehabilitation method and system based on mobile medical treatment, relates to the technical field of medical rehabilitation, and discloses the hip and knee joint replacement postoperative rehabilitation method and system based on mobile medical treatment. The training plan is dynamically adjusted in combination with multi-dimensional indexes, the problems of compensation recognition deficiency, feedback lag and plan stiffness in a traditional rehabilitation scheme are effectively solved, the rehabilitation effect can be improved, and the injury risk of adjacent joints can be reduced.

The invention discloses an intelligent fitness method and system. The intelligent bodybuilding method comprises the steps that the bodybuilding equipment receives a bodybuilding situation instruction and provides a corresponding motion mode for a user; the fitness equipment collects fitness data of the fitness equipment and feeds back the fitness data to the terminal; the terminal collects the fitness data and sends the fitness data to the cloud server; the cloud server processes the fitness data based on a pre-trained model and returns an interaction command to the terminal according to a processing result; and the terminal sends the interaction command returned by the cloud server to the fitness equipment, so that the fitness equipment updates the exercise mode of the fitness equipment. According to the technical scheme, efficient transmission and comprehensive analysis of the fitness data can be realized through interaction of the fitness equipment, the terminal and the cloud server, and a proper fitness situation instruction can be given by utilizing the pre-trained model in combination with the fitness condition of the user, so that the exercise mode is dynamically adjusted, and the user experience is improved. Personalized and intelligent fitness services and fitness guidance are provided for the user, and the fitness experience of the user is improved.

The invention discloses a millimeter wave radar and range finder golf sports monitoring system and method and a medium, and relates to the field of sports monitoring, the system comprises a handheld integrated terminal, a laser ranging module, a millimeter wave radar module, a processing unit and a display unit are integrated in the handheld integrated terminal, and a first communication module is connected with the processing unit; the data interaction module is used for performing data interaction with an external mobile terminal; the mobile terminal comprises a second communication module, a trajectory prediction module and a recommendation decision module, and is used for comparing the predicted flight trajectory with a target trajectory preset by a user and generating a swing suggestion in a training mode; and in the motion mode, the central processing unit is used for planning and recommending a ball hitting strategy based on the expected drop point distance input by the user and the real-time environment data measured by the handheld integrated terminal in combination with historical training data of the user. According to the invention, accurate monitoring and dynamic analysis of the golf ball flight path are realized.

The invention provides a training and examination robot system based on a multi-modal large model, equipment and a computer program product, and aims to accelerate training transformation and upgrading and improve coping ability as basic appeals, and based on regular training work of teams, training and examination robot, sensor acquisition equipment and big data platform three-terminal equipment. A multi-modal data acquisition layer for realizing real-time attitude detection and motion capture by using an edge calculation algorithm, a data processing and analysis layer for finishing real-time image processing through localized edge calculation in a network-free or power-free environment, and system control functions for finishing intelligent decision making, evaluation, error correction and the like are provided; an intelligent decision-making and control layer of a training subject rewriting decision-making mechanism is established, cross-modal collaborative learning middleware is utilized to realize modal representation consistency while training subject transposition evaluation is realized, training and assessment operations of the same subject of multiple persons or different subjects of multiple persons are supported, and the training and assessment efficiency is remarkably improved.

The invention belongs to the technical field of intelligent rehabilitation equipment control, and relates to a multi-parameter feedback regulation and control method for postoperative lung function rehabilitation training, which comprises the following steps: acquiring an electrocardiosignal, a respiration signal and a limb movement signal of a patient; identifying a heart rate fluctuation form of the electrocardiosignal to generate an abnormal fluctuation time period, and analyzing a time difference between an inspiration phase and an expiration phase of the respiratory signal to generate a starting point of respiratory rhythm disorder; judging a cardiopulmonary risk level; the exercise intensity of rehabilitation training equipment is automatically adjusted based on the cardiopulmonary risk level, and meanwhile a regulation and control mode is dynamically selected according to the proportion change of the chest fluctuation amplitude and the abdomen fluctuation amplitude; when the heart rate recovery rate is lower than a preset reference and the respiratory rhythm stabilization time exceeds a critical value, gradually improving the exercise intensity; calculating a motion intensity correction coefficient and triggering a motion posture correction instruction; and generating a rating report containing the cardiopulmonary function fitness. According to the invention, the problem of lack of comprehensive quantitative evaluation of rehabilitation efficiency in the prior art is solved.

The invention relates to the technical field of medical health information, and particularly discloses a heart rehabilitation training control method based on muscle force and electrocardiosignal real-time monitoring, which comprises the following steps: firstly, calculating real-time myoelectricity intensity to quantify muscle load, synchronously analyzing electrocardiosignals and respiratory frequency to obtain a cardiopulmonary state, and correcting physiological indexes in combination with a trunk motion state; then, a multi-parameter fusion result is generated through a weighted fusion algorithm, and the relevance between the muscle force load and the heart response is comprehensively reflected; then, the system judges the training intensity through a preset threshold model, generates a voice feedback instruction in real time to adjust the action of the patient, and adaptively updates training parameters to match the rehabilitation progress of the individual; meanwhile, the system continuously monitors multi-parameter changes, and automatically triggers an early warning mechanism when abnormal risks are detected, so that training safety is ensured. According to the method, the limitation that a traditional scheme depends on a single index is overcome, and personalized and dynamic heart rehabilitation training closed-loop control is achieved.

The invention relates to a fitness action error correction method and device for bone key point detection, equipment and a medium. The method comprises the following steps: acquiring video data in a multi-person fitness scene, and performing skeleton key point detection on each frame of image in the video data to obtain a multi-person skeleton key point sequence; performing spatial clustering processing on the multi-person skeleton key point sequence to obtain a plurality of individual skeleton key point sequences; according to the skeleton key point sequence of each individual, generating an action track of each individual; based on a preset standard action sequence, identifying an action matching result corresponding to each action track; according to the action matching result, the action deviation value of each individual is calculated, and action error correction feedback information is generated based on the action deviation values; the error correction feedback information is used for indicating each individual to adjust the fitness action. The method can adapt to complex scenes, solves the problem that key points of scenes of multiple persons are confused, and provides effective support for fitness guidance and the like.

The invention relates to the technical field of respiratory training, in particular to a respiratory muscle training system based on thoracic induction, which comprises a thoracic dynamic monitoring module, a respiratory muscle state recognition module, a fatigue judgment and adjustment module, a training control module and a task construction module. According to the method, through combined extraction of capacitance sensing data of chest expansion change, a vertical displacement trend and chest pressure floating, the reduction precision of a real respiration traction process is effectively improved, a time axis is used as a unified reference, different types of sensing data are synchronously analyzed, the respiration traction judgment accuracy is remarkably improved, and the method is suitable for popularization and application. The probability of misjudgment caused by electromyography and body movement dislocation is eliminated, the capacity of capturing the participation state of respiratory muscles is enhanced, the variation trend between electromyography response and traction starting is tracked and captured through the time difference of continuous periods, the training execution accuracy is improved, the intervention targeting is recovered, and the training efficiency is improved. And leap-over improvement is realized in the aspects of multi-source information collaborative identification and training personalized adjustment.

The invention presents an advanced soccer training system designed to revolutionize traditional practice methods through a synergy of technology and interactivity. It features an integration of sensors, Artificial Intelligence, and Augmented Reality technologies, providing real-time feedback, immersive simulations, and personalized training experiences. The system promotes skill development via data-driven insights and dynamic training environments, supported by mobile application connectivity for customized training regimens and performance analysis. Additional attributes include energy-efficient design, user-friendly transport mechanisms, and extensive multimedia capabilities like video recording and photo capture for skill review, establishing a novel paradigm in athletic training and development.

The invention discloses a multi-link collaborative evaluation and feedback system for upper limb rehabilitation training, and belongs to the technical field of medical rehabilitation, and the system comprises a data collection module which is used for obtaining the related data of the upper limb of a patient in the rehabilitation training process, and the related data comprises the motion posture, the muscle activity condition and the joint activity degree; the data processing module responds to the data acquisition module and is used for preprocessing the acquired related data, including filtering and denoising the related data, acquiring feature information in the preprocessed related data and sending the feature information to the data acquisition module; the feature information comprises movement tracks of joints, contraction intensity and time of muscles and coordination of upper limb movement. Multi-dimensional data such as action postures, muscle movement conditions and joint movement ranges in upper limb rehabilitation training are collected, preprocessing and feature extraction are carried out through the data processing module, the upper limb rehabilitation condition of a patient can be comprehensively and accurately evaluated, and a basis is provided for formulating a personalized rehabilitation scheme.

The invention provides a ball game analysis method and device, electronic equipment and a storage medium, and relates to the technical field of artificial intelligence, in particular to the technical field of computer vision, deep neural networks and motion analysis. The specific implementation scheme is as follows: in response to entering a serving link, fitting to obtain a movement track of a ball based on a collected ball game video; based on the motion trail and the ball game video, determining a ball hitting coordinate and a ball hitting posture of the motion object and a ground touching coordinate of a ball; and obtaining a motion analysis result based on the ball hitting coordinate, the ball hitting posture and the ground touching coordinate so as to display the motion analysis result in real time through display equipment.

Methods and apparatuses for athletic training optimization are disclosed. In one example, a fitness level change is identified. In one example, a current training intensity is updated to reflect an updated user fitness level.

The invention discloses an intelligent backboard interaction method supporting terminal interconnection, a medium and an intelligent backboard. The intelligent backboard interaction method comprises the following steps: collecting user space motion data to generate a space-time trajectory sequence and binding a user identity label, segmenting a multi-user shooting action data stream in real time, extracting dynamic association features and combining sphere trajectory data to construct a multi-dimensional feature matrix; inputting the matrix into a distributed intention understanding engine, and fusing voice, a touch event and historical data to generate an interactive decision instruction; a dynamic content generation module is driven according to the instruction, a training difficulty coefficient and a tactical matching degree are calculated in real time, and a multi-terminal cooperative control signal is output; and aggregating multi-user and sphere state feedback data, and continuously adjusting a collaborative strategy of a shooting action evaluation standard, a multi-user confrontation rule and terminal display content. According to the method, accurate distinguishing and collaborative intention understanding of multi-user actions are realized, and the training individuation level and the self-adaptive real-time control capability of multi-user interaction are effectively improved.

Procedure for controlling a counter-current system 3 for swimming pools comprising the following steps: a. Providing a swimming pool 1 with a counter-current system 3 for generating a flow 31 of a predetermined flow velocity v in the swimming pool 1, a sensor 4, 5; 6 for generating a control signal depending on the position of a person swimming in the pool 21, 22, 23 and a control unit 7 which, based on the control signal, sets the flow velocity v generated by the counter-current system 3; b. Determining the position of a person swimming in the pool 21, 22, 23; c. Comparison of the determined position with a predetermined position range 41, 51 to generate a control signal for the control unit 7 of the counter-current system 3; d. Increase or decrease the flow velocity v generated by the counter-current system (3) by means of the control unit 7 when the person 22, 23 swimming in the pool is in the predetermined position range 41, 51.

A method for analyzing a ball game motion includes: in response to entering a serving stage, obtaining a motion trajectory of a ball by fitting based on a ball game video acquired; determining a hitting coordinate of a motion subject, a hitting posture of the motion subject, and a landing coordinate of the ball based on the motion trajectory and the ball game video; and obtaining a motion analysis result based on the hitting coordinate, the hitting posture, and the landing coordinate, to display the motion analysis result in real time through a display device.

A method of operating a fitness tracking system includes receiving at least one first value and at least one second value for at least one foot action parameter from a sensor during a user workout. The method further includes determining whether the user has experienced a first type of fatigue and a second type of fatigue based on the at least one first value and the at least one second value, wherein the first type of fatigue is defined by different rules than the second type of fatigue. When it is determined that the user experienced the first type of fatigue, a first recommended action is provided to the user via a personal electronic device of the user. When it is determined that the user experienced the second type of fatigue, a second recommended action is provided to the user via the personal electronic device.

Provided is a system for robotic collaboration. A first robotic device executes a first action and a second robotic device executes a second action upon the first robotic device completing the first action. An application of a communication device is paired with the first robotic device and the second robotic device. The application is configured to receive at least one input designating, for example, a hitting speed of a tennis ball, a hitting direction of a tennis ball, a unique tag of a subarea in a map of an environment, a task schedule of the first robotic or second robotic device, a driving speed, a selection of a particular user profile, an instruction to drive to a user-identified location, an instruction to turn in a left or right direction, an instruction to drive forwards or backwards, an instruction to stop moving, etc.

A method, apparatus, and system are disclosed for a robot with tennis ball gathering capabilities. A robot is configured to collect, transport, and deposit for storage tennis balls and other light-mobile sports equipment such as are used in table tennis, badminton, squash, pickleball, golf, basketball, dodgeball, floor hockey, indoor soccer, etc., to assist a player in practice without need for additional support personnel or manual ball retrieval by the player.

Aspects of the subject disclosure may include, for example, obtaining current video content of a player repeatedly performing a physical skill, analyzing the current video content based on previous video content, the previous video content comprises other video content of the player repeatedly performing the physical skill, determining biomechanic metrics of the player performing the physical skill based on the analysis, and determining each biomechanic metric of a portion of the biomechanic metrics does not satisfy a respective biomechanic metric success rate. Further embodiments include generating a first image of the player performing the physical skill from the current video content, generating a second image of the player performing the physical skill from the previous video content, and presenting the first image and the second image simultaneously and indicating the portion of the biomechanics that did not satisfy the respective biomechanic metric success rate. Other embodiments are disclosed.

The invention discloses a badminton player action posture analysis system and method based on multi-sensor fusion, and relates to the technical field of athletic training auxiliary systems.The system comprises a wearable sensing subsystem, an environment sensing subsystem and a central processing and feedback subsystem; the wearable sensing subsystem is arranged on an inertia measurement unit and a pressure sensing insole of a body to collect movement inertia and plantar pressure data; the environment perception subsystem collects global videos through multiple cameras. The central processing and feedback subsystem performs synchronous processing on multi-source data, adopts a hierarchical fusion algorithm, restrains inertia integral drift by utilizing a plantar contact state, reconstructs a three-dimensional skeleton posture and a motion trail in combination with visual key points and skeleton restraint, drives a digital twin model, compares with a standard motion model, and performs three-dimensional motion control on the three-dimensional skeleton posture and the motion trail. Quantitative evaluation results such as joint angle deviation, time sequence difference and pressure center track are generated, and visual feedback is performed through a display device and an augmented reality terminal for badminton training evaluation and technical deviation correction.

A system for optimizing mechanics and movements in remote or outpatient physical therapy, rehabilitation, sports training, and injury prevention that uses several inertia measurement units (IMUs) to measure a user's motion while performing an action. The IMUs can have additional sensors connected to improve the system's ability to detect flaws in the user's motion. Furthermore, the system uses machine learning to detect and determine flaw in a user's motion from the IMU data. The system may generate feedback to improve the user's motion based on the detected flaws. Different feedback communication may be provided based on the performance of the user after the feedback is provided.

The invention discloses a hand rehabilitation training device, which belongs to the technical field of medical rehabilitation, and comprises a wearable glove base body, a main body structure, a wrist structure, a multi-mode driving module, a nickel-titanium alloy wire driving unit, a pneumatic driving unit, a sensor detection module, a bending sensor, a myoelectricity sensor and a pressure sensor, the multi-mode driving module comprises a sensor detection module and a wrist structure, the electroencephalogram interaction module comprises a non-invasive EEG electrode and a head band, the self-adaptive control module comprises a control box arranged on the wrist structure, and the self-adaptive control module is electrically connected with the multi-mode driving module, the sensor detection module and the electroencephalogram interaction module through wires and communicates with terminal equipment through a built-in wireless module; according to the hand rehabilitation training device with the structure, flexible adaptation, multi-mode driving, electroencephalogram-sensing closed-loop feedback and intelligent regulation and control of hand rehabilitation training are achieved through cooperative work of multiple modules, and training accuracy and individuation are improved.

The invention relates to the technical field of computer vision, in particular to a gymnastic training real-time feedback and error correction system based on image recognition and tracking, and the system comprises a data collection module which is used for obtaining a three-dimensional space coordinate system of a training field, and synchronously collecting the training actions of gymnastic athletes through a plurality of cameras, so as to obtain a multi-view real-time training video stream; and the image processing module is used for carrying out frame image decomposition on the multi-view real-time training video stream to obtain continuous multi-view action frame images. According to the invention, through the data acquisition module and the skeleton generation module, real-time three-dimensional attitude skeleton data under a three-dimensional space coordinate system of a training field can be obtained, so that the defects that the traditional video playback lacks space depth information and cannot truly restore the three-dimensional attitude are fundamentally overcome; meanwhile, the problems that the visual angle is single and motion details cannot be captured in all directions during visual observation of a coach are solved, and a complete three-dimensional space data basis is provided for subsequent accurate analysis.

The invention provides a football player comprehensive ability evaluation method, system and device based on big data and a medium, and belongs to the technical field of sports data analysis. The method comprises the steps that technical data, tactical data, physical ability data and physiological data of football players are collected; performing feature extraction and standardization processing on the data; acquiring contextual information of the match, presetting weights of technical features, tactical features, physical fitness features and physiological features in different match scenes, and weighting the standardized features to obtain a fused weighted feature vector; constructing a high-order ability quantification model, and calculating a high-order ability index of the player according to the weighted data; simulating the ability performance of the players under different opponent strengths based on the CGAN, calculating the deviation degree between the performance of the players and the reference performance, determining the stability coefficient, generating the comprehensive contribution index of the players in combination with the high-order ability index, and evaluating the comprehensive ability of the players. According to the method, the accuracy of player ability evaluation is improved, and the method can be used for optimizing team lineup configuration.

A leg training device comprises a support frame and a seat installed on the support frame, wherein a leg exercise component and a counterweight bearer are further provided on the support frame, and a load transfer component for transferring a load is provided between the leg exercise component and the counterweight bearer; the load transfer component comprises a connecting element and a guiding element; at least two ends of the connecting element are respectively attached to the leg exercise component and the counterweight bearer.

This disclosure pertains to a sports training system that utilizes deep learning and computer vision technologies to analyze biomechanical sport motions. The system is equipped with AI-powered functionalities to enhance training, including those related to creating and managing motion templates that integrate video sequences with extracted motion features. These templates serve as benchmarks, accessible to trainees for improving their technique and performance. The system also can employ an advanced motion synchronization process, which combines dynamic time warping and computer vision technologies to align trainee videos with reference motions captured in motion templates. Additionally, a motion feature database can be updated with features extracted from both trainee and trainer videos, storing visual information in a structured format to facilitate various analytic functions. The system supports analysis of a wide range of sports motions.

The invention belongs to the technical field of intelligent sports and computer vision crossing. The adaptive training method based on Tai Chi action recognition is provided, and space action features are extracted according to three-dimensional human skeleton key point coordinates of a human body; extracting multi-scale motion features of the human body in a time domain according to the spatial motion features; global attention aggregation is carried out according to the multi-scale motion features of the human body in the time domain, and a human body motion recognition result is obtained; according to a human body action recognition result, matching a corresponding Tai Chi style drawing theory; superposing multi-dimensional visual prompts into a Tai Chi motion video according to the Tai Chi motion style theory so as to intuitively prompt a user about action key points; calculating an action problem based on priori knowledge or a preset template, prompting an error position and an error reason by adopting graphs and / or characters, and giving an adjustment suggestion; according to the invention, more personalized training experience can be provided, cognitive load can be reduced, and training efficiency, training effect and cognitive learning fluency can be improved.

A golf ball identification apparatus and system for is disclosed herein. The golf ball identification apparatus includes a housing, a cover, a helical track within the housing, and an antenna. The antenna is positioned at a bottom of the housing and is configured to identify a golf ball that has a wireless identification device.

Disclosed are methods and systems for creating an avatar (102) of a real-world athlete (104) using artificial intelligence. A corresponding method may comprise providing (802) an avatar (102) corresponding to a real-world athlete (104), receiving (806) athlete feedback (300) from the real-world athlete (104) in response to a behavior of the avatar (102), and adjusting (808) the avatar (102) based on the received athlete feedback (300).

Exemplary task-agnostic exoskeleton control system and method are disclosed that are task-agnostic utilizing instantaneous estimates of biological joint moments from deep neural networks to assist the user movements. The exemplary control system employs multiple body sections and joints in-the-loop estimation to provide multi-joint assistance operation, e.g., within an autonomous, clothing-integrated exoskeleton. The exemplary control system may deploy a deep domain adaptation (DDA) method configured to translate human movement data between a simulated sensor domain and a real sensor domain.