161 results about "Training plan" patented technology

The invention discloses a new line training demand analysis method based on data driving, and relates to the technical field of computers. The method aims at solving the problems that training demand analysis depends on subjective experience, data islands are serious, response lags and quantitative prediction models are lacked in the prior art. The method comprises the steps of collecting and integrating multi-source heterogeneous data such as physical assets, human capital and process knowledge; constructing a time sequence dynamic association map representing the preparation state; predicting a future preparation state by using the space-time diagram neural network model; quantizing a personnel capability gap based on the prediction result and the operation baseline, and generating a capability gap matrix; performing priority ranking and clustering on the training requirements in combination with the key weight of the system to form a structured training theme; and dynamically generating a training plan, and updating the atlas in a closed-loop manner through training feedback data. Accurate prediction, quantitative evaluation and adaptive optimization of training requirements are realized, and scientificity and foresight of new line preparation are improved.

The invention relates to the technical field of medical training equipment, in particular to a critical care ultrasonic image training system, which comprises a clinical data acquisition module for acquiring critical clinical case data, ultrasonic image materials and diagnosis and treatment process specifications; the training scene construction module is used for constructing a high-fidelity three-dimensional training scene according to severe clinical case data, ultrasonic image materials and diagnosis and treatment process specifications; the virtual ultrasonic practical operation module simulates the operation of an ultrasonic probe based on a high-fidelity three-dimensional training scene, and generates an ultrasonic image corresponding to an anatomical part in real time; the intelligent skill assessment center assesses operation normalization and diagnosis accuracy through practical operation data and real-time generation of an ultrasonic image corresponding to an anatomical site in combination with an improved ResNet-LSTM model, and an assessment result is obtained; and the personalized teaching unit generates a customized training scheme and knowledge strengthening content according to the evaluation result in combination with the learning track of the student. Therefore, the problems of insufficient dynamic scene simulation, poor authenticity and the like in the prior art are solved.

A system includes a processor that is configured to receive input information including a user's training goal and type of sport, generate a training plan based on the received information, capture and upload a training video of the user performing training according to the training plan, analyze the uploaded training video to identify errors in the user's movements and points for correction, and provide the identified correction points and specific methods for improvement to the user.

This invention discloses a system for recording and analyzing the growth trajectory of a person's resume based on multi-source data fusion, relating to the field of enterprise talent training and development technology. It solves the technical problem that the lack of recording and analysis of post-training ability growth feedback during the planning of internal training routes leads to incomplete dynamic growth records of abilities. This invention obtains corresponding matching states by matching multi-source heterogeneous data with set training data, develops personalized training plans for employees based on these matching states, and rates users according to their matching states and promotion standards. This allows for precise matching of users' actual abilities with promotion standards and training states, achieving quantitative assessment of ability levels. It enables full recording and iterative analysis of user ability feedback, training process, and growth changes, forming a closed-loop mechanism of "assessment—growth—rematching—re-enhancement," significantly improving the completeness, continuity, and practicality of ability growth records.

A system is provided.SOLUTION: This system includes a means for collecting necessary information from the Internet, a means for generating a training plan on the basis of the collected information, a means for providing the generated training plan to a user terminal, a means for recording a progress situation input by a user and reporting it to a server, and a means for storing progress data received by the server.SELECTED DRAWING: Figure 1

The application discloses a self-adjusting breathing training device, which comprises a gas control valve sleeve, the gas control valve sleeve comprises an inclined side wall, the gas control valve sleeve comprises a breathing interface and an atmosphere interface, a movable valve plug is arranged between the breathing interface and the atmosphere interface, and a gas path channel is formed between the edge of the movable valve plug and the inclined side wall. The application can accurately quantitatively control the size of impedance, so that the load of a patient in a training process is within a controllable range, the analysis and adjustment of a training plan of the patient are facilitated, the gas path channel can be adjusted and adapted according to the training intensity of the patient to obtain different impedance, the inspiratory muscle can be trained, and the expiratory muscle and the inspiratory muscle can be simultaneously trained in one breathing cycle.

The invention relates to the technical field of rehabilitation physiological monitoring, and discloses a nerve-muscle recovery detection method based on HRV recovery rate and sEMG frequency spectrum declination, and the method comprises the steps: firstly obtaining an effective RR interval sequence subjected to quality gating and a steady state sEMG segment of a specific muscle group; then, extracting systemic HRV recovery features and local muscle fatigue features in parallel, and respectively generating a normalized HRV recovery rate score and a myoelectricity recovery score; through multi-level fusion, a global nerve recovery score, a local muscle recovery score array and a comprehensive nerve-muscle recovery score are integrated; and finally, based on the multi-dimensional evaluation results, generating personalized training suggestions. Therefore, the nerve-muscle system preparation degree of an individual can be comprehensively and accurately reflected, and a scientific basis is provided for optimizing a training plan and preventing sport injuries.

We provide the system. [Solution] A means for generating an individual training plan using a trainer generated based on a virtualized character selected by the user, A means of analyzing the user's exercise in real time and providing immediate feedback according to the training performance, A means of recording training results and managing rewards based on points awarded to users, A means of providing community features to share results among users and promote competition, A system that includes this.

The utility model discloses a lower limb support training weight quantification alarm device, which comprises a bottom plate, a lifting device, a bearing plate, a plurality of pressure sensors, an operation device and an alarm, and is characterized in that the lifting device comprises a lifting assembly, and the lifting assembly is slidably arranged at the top of the bottom plate; the bearing plate is fixedly connected with the top of the lifting assembly. The plurality of pressure sensors are uniformly distributed at the top of the bearing plate and are used for monitoring the weight of the lower limb support in real time; the operation device comprises a supporting rod and an operation panel. Therefore, through cooperation of the pressure sensor and the single-chip microcomputer, the lower limb supporting weight can be accurately measured and displayed, a trainer can make a scientific training plan conveniently, a rehabilitation patient is helped to conduct accurate training, rehabilitation is accelerated, the lifting device is adjustable in height, suitable for people of different heights and high in universality, and when the training weight exceeds a set value, the alarm can give out a sound-light alarm. Users are prevented from being injured due to overweight, and safety is guaranteed.

An object of a system according to an embodiment is to provide an optimal training plan according to a fitness level, a constraint, and a goal of a user.SOLUTION: A system according to an embodiment includes a user information collection unit, a training plan generation unit, a data analysis unit, and a correction proposal unit. The user information collector collects the user's fitness level, constraints and goals. The training plan generation unit generates a training plan based on the information collected by the user information collection unit. The data analysis unit analyzes user data and sensor data during training in real time. The correction proposal unit corrects the training plan based on the data analyzed by the data analysis unit.SELECTED DRAWING: Figure 1

A system is provided.SOLUTION: A system, comprising: means for a user to input health information; means for obtaining activity data of the user from a wearable device; means for analyzing the health information and the activity data of the user to generate a personalized training plan and diet plan; means for providing the generated training plan and diet plan to a terminal of the user; and means for predicting and graphically presenting a change in health condition of the user.SELECTED DRAWING: Figure 1

The invention discloses a method for improving an industrial safety education training effect based on an AI large model. The method comprises the following steps: analyzing, vectorizing and storing latest industrial safety related documents to obtain a safety knowledge base; the related documents comprise industrial standard specifications, laws and regulations and enterprise specifications related to industrial safety; the knowledge base comprises a plurality of sub knowledge bases with different themes and different types; matching an associated target sub-knowledge base from the safety knowledge base based on the training plan, so as to generate an employee training task based on the target sub-knowledge base; based on the training task, utilizing an AI large model to generate a training problem in the training process, and using the training problem for employee training to obtain a training result of the employee; and based on the training result, using an AI large model to generate test questions corresponding to different employees, and examining the employees based on the test questions to obtain an examination result. The training effect of employee safety education can be improved, and potential safety hazards are reduced.

An AI-assisted mobile tennis training system integrates a motorized ball delivery device, multi-camera vision, autonomous navigation, and artificial intelligence for adaptive, data-driven player development. The device includes a motorized chassis, ball hopper, programmable ball delivery mechanism with variable spin, speed, and trajectory control, and a navigation subsystem employing omnidirectional wheels and localization based on court line recognition. A multi-camera array captures real-time player and ball movement, while onboard and remote computing modules process the data to determine player position, shot type, and performance metrics. An AI model predicts optimal ball delivery parameters and adapts drills based on player progress. A mobile application provides remote control, drill customization, and performance analytics. The system supports autonomous repositioning, safety monitoring, and individualized training plans, enabling dynamic, responsive, and efficient tennis practice for skill acquisition and improvement in both amateur and professional players.

The utility model discloses an adjustable thoracic surgery nursing expiration training device, and relates to the technical field of medical nursing instruments. The device comprises a main pipe, an adjusting pipe, a gas guide pipe, a gas hood, a base and a controller, the upper end of the main pipe is movably connected with the adjusting pipe, the upper end of the main pipe is in threaded connection with a limiting sleeve used for fixing the use height of the adjusting pipe, and a cavity channel for being connected with the gas guide pipe is formed in the bottom of one side of the main pipe. A patient is reminded whether the small ball is in a floating state during training through the film type pressure sensor, the processing chip, the time control panel and the buzzer, the processing chip can record the time when the buzzer makes a sound every time according to data processing, and therefore the patient can conveniently inquire historical training records through the time control panel in the later period; medical staff can make a training plan according to the rehabilitation training result of a patient, and then the device can be fixed to the smooth surface of an object through cooperation of a cross rod and an adsorption block or a suction cup.

The invention relates to the technical field of management, in particular to a personnel ability training method based on multi-information fusion. A personnel ability training method based on multi-information fusion comprises the following steps: S1, acquiring an organization structure and personnel training information, defining a personnel type set and a training type set according to the organization structure and the personnel training information, and constructing a personnel initial ability sequence; s2, collecting training questionnaire data based on a Korotkoff four-level questionnaire, calculating a basic utility factor of each type of training according to the training questionnaire data, and generating a basic utility factor sequence; s3, establishing a personnel ability evolution model according to the basic utility factor and the personnel initial ability sequence; and S4, obtaining personnel data, a training plan and a task demand plan of an enterprise, and calculating and obtaining a personnel on-duty threshold sequence based on the personnel data, the task demand plan and the personnel capability evolution model. According to the invention, pertinence and efficiency of personnel ability training can be improved.

The application provides a sports competition training prediction method and system based on AI and image analysis, and relates to the technical field of sports competition training prediction. The method comprises the following steps: acquiring a video of a badminton match of an athlete; determining a plurality of ball fault points by using a fault point determination model based on the video of the badminton match of the athlete; determining a K value based on the plurality of ball fault points; performing clustering based on the plurality of ball fault points and the K value to determine K fault regions; constructing a fault region atlas; processing the fault region atlas based on a graph neural network to determine at least K hitting training points, wherein each fault region has at least one hitting training point; and determining a target training plan based on the at least K hitting training points. The method can accurately formulate an optimal targeted training scheme according to the badminton match faults of the athlete.

This invention relates to the field of underwater dam inspection technology, and discloses a method and system for recommending virtual training scenarios for underwater robot dam inspection. This invention combines an assessment attribute set and a training scenario dataset to conduct virtual training skills assessments for underwater robots in multiple training scenarios. This clearly verifies the underwater robot's inspection capabilities in different scenarios, making the training more targeted, and providing a comprehensive understanding of the trainees' mastery of various skills in different scenarios. Furthermore, by using multiple skill assessment results to predict untested scenarios, it is possible to understand the underwater robot's performance in new scenarios in advance, providing a reference for developing training plans and enhancing the system's adaptability and foresight. Finally, by combining real-world case attribute datasets, existing assessment results, and prediction results to determine target recommended scenarios, it comprehensively considers actual conditions and future needs, making the recommended scenarios more accurate and practical.

A system is provided.SOLUTION: A system comprising: means for registering personal data of each user; means for automatically acquiring measurement data of each user in conjunction with a fitness device and a body composition meter; means for analyzing the acquired personal data and measurement data and generating an optimal training plan and meal menu; means for notifying the user of the generated training plan and meal menu; means for inputting progress data of the user; and means for reanalyzing the input progress data and modifying the training plan and meal menu.SELECTED DRAWING: Figure 1

A system is provided.SOLUTION: A system comprising: means for receiving user registration information; means for setting a user profile; means for interacting with and training a pet using a virtual reality environment; means for generating a training plan optimized for the user and the pet using generative artificial intelligence; and means for providing feedback to the user in real-time.SELECTED DRAWING: Figure 1

A method includes obtaining an exercise intensity of a user, determining a training intensity of the user according to the exercise intensity, and generating an exercise training plan according to the training intensity. An electronic device is configured to perform the method. A computer-readable storage medium storing at least one computer program that, when executed, causes the method to be implemented.

The invention discloses an intelligent weighing feeding bowl and an intelligent control method thereof, and relates to the field of medical nursing, and the feeding bowl comprises a bowl body and an intelligent base; the intelligent base comprises a suction cup structure, a weighing module, a main control unit, an alarm prompt unit, a communication module and a power management module. The suction cup structure is used for fixing the bowl body on a smooth table top; the weighing module is used for detecting weight data of food in the bowl in real time; the main control unit is used for processing the weight data and generating an alarm prompt instruction; the alarm prompting unit comprises an annular multi-color LED indicating lamp and a buzzer, and is used for giving out a sound-light alarm based on the alarm indicating instruction when the food is excessive or the food is eaten too fast; the communication module is used for carrying out data interaction with a mobile terminal. Digitalized recording and visual analysis of feeding behaviors are realized, and an accurate basis is provided for a doctor to evaluate the recovery progress of the swallowing function and adjust a training plan.

The invention relates to a method for predicting a user's performance at a sports event, the method being implemented by data processing means (10) of a device (1) and comprising the following steps: - obtaining (a) data relating to at least one training session carried out from a training plan followed by the user in preparation for the sports event, referred to as past data; - calculating (b), from the past data, at least one score, each score being assigned to a training session on the basis of compliance with said session by the user; - determining (c) at least one variable relating to the at least one score; - applying (d) a performance prediction model taking as input the variable and the past data.

This invention discloses a postoperative rehabilitation training and health management system and method for breast cancer patients, belonging to the field of smart healthcare and rehabilitation training technology. The system includes a local smart terminal, a cloud server, and a medical staff terminal. The local terminal integrates a millimeter-wave radar sensor, which generates upper limb point cloud data by transmitting and processing echo signals. A three-dimensional human skeleton model is reconstructed using a deep learning network, and motion parameters such as joint angles and movement trajectories are extracted. The system is then compared with a standard template to calculate the motion completion score and provides real-time corrective feedback. The cloud server deploys a finely tuned large language model, which, combined with a rehabilitation knowledge base, performs enhanced retrieval and generation, providing personalized suggestions based on the patient's rehabilitation history and consultation questions. The rehabilitation plan generation module dynamically adjusts the training plan based on long-term data analysis. This invention achieves a deep integration of non-contact precise perception, real-time motion assessment, and intelligent health management.

The application discloses a hip-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-knee joint replacement postoperative rehabilitation method and system based on mobile medical treatment. The wearable sensor is used for monitoring patient motion data in real time and recognizing compensatory behavior. A training plan is dynamically adjusted in combination with multidimensional indexes, the problems of missing compensation recognition, feedback lag and plan rigidity in the traditional rehabilitation scheme are effectively solved, the rehabilitation effect can be improved, and the risk of adjacent joint injury can be reduced.

A system for providing personalized performance coaching to an artist of a specific discipline includes an Al-powered performance coaching and evaluation platform, a camera and / or a microphone, and a database. The Al-powered performance coaching and evaluation platform includes a user interface, an Al engine, a feedback module and a coaching module. The database includes datasets of professional artists' performances in the artist's specific discipline, and the Al engine is trained with the datasets of the professional artists' performances. The Al engine analyzes video and / or audio performance data of the artist and derives specific performance elements relevant to the artist's discipline and evaluates the specific performance elements by comparing them to specific professional performance benchmark metrics for each performance element derived from analyzing the datasets of professional artists' performances in the artist's specific discipline. The feedback module generates detailed feedback based on the Al engine's analysis and evaluation, and the coaching module generates a personalized training plan that includes exercises and resource recommendations tailored to the artist's performance data.

The invention discloses an intelligent rehabilitation evaluation system and method based on multi-modal data fusion, and relates to the field of rehabilitation medicines.The system comprises a multi-modal data acquisition terminal integrated on physical rehabilitation equipment and used for synchronously acquiring multi-modal data of a user in the rehabilitation training process; the cloud platform intelligent processing center is connected with the multi-modal data acquisition terminal and is used for receiving, storing, fusing and analyzing the multi-modal data, generating a rehabilitation evaluation report and issuing a control instruction to the multi-modal data acquisition terminal according to the rehabilitation evaluation report so as to dynamically adjust training parameters of the physical rehabilitation equipment; and the multi-element interaction application end comprises a user end APP and a therapist end Web platform, and is used for receiving the rehabilitation evaluation report and supporting a therapist to remotely adjust a training plan. According to the invention, core pain points in the aspects of evaluation precision, training efficiency, resource utilization and user compliance in the prior art can be comprehensively solved.

An exercise system is disclosed that includes a walking exercise device having a pedal stepped on by a patient and one or more linked pedal drives driving the pedal, and a system control device that performs a patient walking training in accordance with a patient's individual training plan, the system control device includes: an index prediction unit that determines a walking evaluation index of a patient based on basic information including patient personal information and initial walking state information; a training planning unit having a self-discipline training planning model for establishing a patient individual-targeted training plan performed by the walking exercise unit on the basis of the result of the walking training; and a training evaluation unit that evaluates a training result on the basis of training result data of a rehabilitation training result of the patient performed by the walking exercise unit.

Embodiments herein relate to methods and systems for fine-tuning, selecting, and deploying machine learning models in communication systems (100) to enhance security and robustness in interactions with communication devices (120) exhibiting varying levels of adversarial behavior. According to some embodiments, a method performed by a training node (111) is provided. Based on auditing a plurality of data segments, the training node (111) develops (503) a training plan for fine-tuning a first set of candidate models comprising a set of robust models, a set of default models, and a set of incomplete models. Based on the training plan, the training node (111) fine-tunes (504) a second set of candidate models comprising at least one robust model and at least one default model. The training node (111) deploys (505) the fine-tuned second set of candidate models in an execution environment (112).