140 results about "Athletic injury" patented technology

The invention discloses a teenager physical exercise real-time monitoring system, and relates to the technical field of intelligent monitoring. An individualized health assessment model is constructed through space-time alignment processing of joint three-dimensional movement, electromyographic signals and plantar pressure and a bone age dynamic matching technology. Time sequence deviation is eliminated through unified clock marking and interpolation compensation, parameters such as bone stress deviation degree, muscle synergy asymmetry degree and plantar pressure unbalance degree are extracted, and comprehensive health indexes are generated through weighting. And in combination with a preset training path model, analyzing a health index trend in real time and triggering a grading adjustment instruction, dynamically optimizing training intensity, interval and action schemes, and correcting path model parameters through a closed-loop feedback mechanism to realize adaptive updating. The defects that traditional teenager physique monitoring data fusion is large in deviation and static evaluation hysteresis is high are overcome, real-time accurate monitoring and personalized training optimization of teenager physique exercise are achieved, and the sport injury risk is effectively reduced.

The invention provides a physical training posture correction method based on machine vision, which comprises the following steps: acquiring an athlete training image sequence through a multi-view image acquisition system and preprocessing the athlete training image sequence, extracting three-dimensional posture key points of a human body by utilizing a depth posture recognition model, constructing a skeleton model and calculating real-time kinematics characteristic parameters, and performing multi-dimensional comparison with standard parameters to generate a posture deviation evaluation report, thereby generating a personalized multi-modal correction feedback scheme, and establishing a personal athlete movement feature database to realize adaptive standard parameter optimization. According to the method, the training postures of athletes can be accurately recognized and corrected in real time, the training effect can be improved, sports injuries can be prevented, and training individuation and scientificity are improved.

The invention discloses a hospital obese patient intelligent weight loss dynamic matching intervention method and decision making system based on multi-modal data fusion, and relates to the field of medical health, and the method comprises the following steps: S1, carrying out the real-time collection and fusion of multi-modal data; s2, dynamic metabolism modeling and plateau period breakthrough; s3, generating a hierarchical intervention strategy; s4, performing psychological-physiological linkage intervention; and S5, performing real-time safety control and feedback optimization. By collecting multi-dimensional data, constructing the model, accurately predicting the metabolic rate, the metabolic plateau period and the sudden eating tendency, dynamically adjusting the exercise intensity and the diet scheme according to the conditions of different patients, triggering a low-intensity exercise mode for the obese patients with cardiac insufficiency and calibrating diet, ensuring the exercise safety, and improving the exercise efficiency. Operation suggestions are generated on the basis of the standard, precise preoperative evaluation is conducted, postoperative rehabilitation is optimized in combination with nerve stimulation data, dangerous postures are monitored, the sport injury risk is reduced, and personalized, safe and efficient intelligent weight reduction intervention for obese patients is achieved.

The invention relates to a sports injury real-time early warning and health optimization system based on multi-mode infrared thermal imaging and three-dimensional skeleton posture fusion, and belongs to the field of sports health management. The problems of motion analysis lagging, damage identification missing and cross-scene data splitting of a traditional monitoring means are solved. According to the technical scheme, the system comprises a multi-modal motion data sensing module which synchronously collects human thermodynamic distribution, three-dimensional skeleton postures and surface electromyogram signals through an infrared thermal imaging camera, an RGB-D camera and a bioelectric sensor; an AI driving training optimization engine is used for generating an adjustment instruction in real time based on a muscle thermal gradient and joint trajectory deviation degree dual-threshold model; and the full-scene intelligent management platform executes millisecond damage early warning, metabolic optimization and school-family health data closed-loop management. The technical effects are that the exercise safety guarantee is fundamentally improved, the training is scientifically optimized, the metabolism management accuracy is broken through, and the teaching resource allocation is intensive.

The invention provides a sports injury rehabilitation scheme generation method, system and device and a medium, and belongs to the field of sports injury medicine, and the method comprises the following steps: obtaining text data about sports injury, and constructing a sports injury knowledge graph according to the text data; the LTE-KGE is used as an encoder of the graph neural network, the hyperbolic embedding model MrpHKG is used as a decoder of a graph neural network model, and a rehabilitation assistance model LTE-MrpHKGE is obtained; according to the method, LTE-KGE is used for carrying out embedded representation on entities of a sports injury knowledge graph, a hyperbolic geometric space of a hyperbolic embedded model MrpHKG is used for capturing hierarchical structural features of the entities and the relations, reasoning is carried out according to the symptoms of a patient and the entities and the relations in the sports injury knowledge graph, the causes of injury are obtained, and the knowledge graph is used for predicting the symptoms of the patient. And analyzing a damage mechanism according to the damage reason and generating a rehabilitation scheme. According to the invention, the accuracy of rehabilitation scheme generation can be effectively improved.

The invention relates to the technical field of crossing of artificial intelligence and sports science, in particular to a motion posture evaluation method and system based on artificial intelligence, and the method comprises the following steps: S1, multi-modal motion data collection: collecting a motion video of a user through a camera device, and synchronously obtaining basic information of the user; according to the motion posture evaluation method and system based on artificial intelligence, 9 types of core parameters are extracted by collecting 3-5 basic motions, dynamic mapping rules of the parameters and evaluation standards are established by combining age and injury history dynamic correction standards, individual differences such as height, body type, motion basis and rehabilitation progress are adapted, and the evaluation accuracy is improved. According to the method, users of different body types can obtain safe and efficient evaluation direction guidance according with own physiological structures, the body type related evaluation misjudgment rate is reduced, sports injuries caused by disjunction of the evaluation direction and the body type are avoided, meanwhile, the users can more easily reach the action standard matched with themselves, and the obtaining feeling and effect of training and rehabilitation are improved.

The invention belongs to the field of rehabilitation medicine, and particularly relates to a hospital discharge preparation degree evaluation system for sports injury patients. The system comprises an acquisition module, a processing module, an analysis module and an evaluation module. The acquisition module receives a diagnosis and treatment medical record of the patient sent by the medical care terminal, the diagnosis and treatment medical record comprises medical advices, and the three-axis acceleration of the affected part of the patient is monitored according to the content of the diagnosis and treatment medical record; the processing module is used for acquiring the three-axis acceleration, acquiring the movement duration of the affected part of the patient according to the acquisition time and the change period of the three-axis acceleration, and combining the movement duration with the change period and the peak value of the three-axis acceleration to quantify the movement intensity of the affected part of the patient; the analysis module is used for acquiring the exercise intensity and the doctor's advice of the affected part of the patient, comparing the exercise intensity with the doctor's advice and calculating the similarity between the exercise intensity and the doctor's advice. According to the scheme, the problems that the preparation degree evaluated by an existing hospital discharge preparation degree evaluation mode of the sport injury patient is inaccurate, and the actual condition of the patient is difficult to reflect truly and comprehensively are solved.

The invention discloses a body training management system based on AI intelligence, and relates to the technical field of artificial intelligence, and the system comprises a data acquisition module, an action evaluation module, a data processing module and a data processing module, the input module is used for inputting the original data sequence into a pre-trained AI model and outputting a corresponding action standard evaluation result, the feedback generation module is used for generating feedback information in real time based on the action standard evaluation result and transmitting the feedback information to terminal equipment of a user, and the posture adjustment module is used for adjusting the posture of the user. The user is guided to adjust action postures according to the feedback information to avoid sport injuries caused by improper postures; according to the AI intelligence-based body training management system, the actual activation condition of muscles can be recognized from the physiological level, the recognition deviation caused by only depending on image or motion track information is made up, and the recognition ability for tiny motion differences is effectively improved.

The invention discloses a rehabilitation exercise risk assessment method and device, and relates to the technical field of exercise rehabilitation, and the method comprises the steps: building a body load baseline according to user basic information and static medical history, collecting the exercise posture data of a user through a wearable device, and determining and triggering exercise risk monitoring through three-level abnormal event judgment; and backtracking physiological parameter data, establishing a real-time state vector, comparing the real-time state vector with a body load baseline, outputting a real-time motion risk coefficient, matching a real-time grading intervention strategy, outputting a self-adaptive intervention instruction after an ultra-short-term alarm log is corrected, and driving motion behavior intervention correction. The technical problems of one-sided data and insufficient accuracy caused by the fact that a traditional rehabilitation exercise risk assessment method does not integrate dynamic exercise postures and real-time physiological parameters are solved, accurate and comprehensive assessment, graded intervention and closed-loop tracking of rehabilitation exercise risks are achieved, the exercise injury probability is effectively reduced, and the rehabilitation exercise risk assessment efficiency is improved. And safety and effectiveness of rehabilitation of the patient are guaranteed.

The invention relates to the technical field of muscle ultrasonic image analysis, in particular to a skeletal muscle texture feature extraction method for sports injury assessment. The method comprises the following steps: firstly, extracting an edge line, an edge direction and a texture region in an ultrasonic image; further analyzing the motion injury condition of each texture area, and weighting the texture directions of all the texture areas by taking the motion injury index as a weight to obtain the run length direction of the ultrasonic image; further, according to the gray value and spatial distribution of foreground pixel points in the amplitude spectrum, in combination with the gray fluctuation of a to-be-analyzed pixel sequence in the run direction and the run direction, a multi-dimensional index adjustment gray run matrix is constructed, skeletal muscle texture features are adaptively extracted, and the skeletal muscle texture feature extraction precision of sports injury is improved.

The invention relates to the technical field of sports science, and discloses a heart rate and exercise load synchronous monitoring training system, which comprises a multi-modal data acquisition module used for synchronously acquiring a physiological signal data set and a kinematics data set of a user; the data fusion and feature extraction module is used for generating a comprehensive state parameter set comprising real-time heart rate variability, an exercise load intensity index, a body balance coefficient and a fatigue degree evaluation value; the dynamic load evaluation module is used for calculating an optimal heart rate interval, a strength distribution optimization weight and an attitude stability compensation parameter in the current motion mode; the somatosensory feedback and decision module is used for generating a personalized training instruction set based on a reinforcement learning algorithm; and the cloud collaboration and personalized adaptation module is used for triggering a collaborative intervention mechanism based on multi-agent consensus. The training effect can be improved, the exercise safety is guaranteed, and the exercise injury probability is reduced.

The application discloses a wearing device for protecting Taijiquan sports injury, which is characterized in that an active connecting part is arranged on a leg supporting frame near the upper area of human ankle, and the upper and lower sides of the active connecting part are connected with left and right limiting components for limiting the leg supporting frame from moving; the left and right limiting components can make the calf standing posture incline forward and backward and the foot freely move; the upper and lower sides of the active connecting part near the back of the leg are further connected with a forward-inclination adjusting component for limiting the forward-inclination range of the calf and the knee joint standing posture; and the leg supporting frame is further connected with a radial adjusting device, and the leg supporting frame is tightly connected with the calf through the radial size adjustment of the leg. When the wearing device is used, the length of the forward-inclination adjusting component is adjusted to control the injury caused by the excessive forward inclination of the knee in the sports process. The application provides the soft tissue injury of the calf and the knee in the squatting and half squatting process in the sports process.

The embodiment of the invention discloses a sports injury early warning method and a storage medium. The method comprises the steps that physiological parameters collected by preset equipment in the movement process are obtained, and the preset equipment can be multiple pieces of wearable equipment; determining a real-time physiological state corresponding to the user based on the physiological parameters, and determining motion characteristics of the user in combination with the motion type engaged by the user and the real-time physiological state; determining a feature deviation degree between the motion feature and a preset motion feature, and if the feature deviation degree reaches a preset feature deviation degree threshold value or above, determining a target wearable device based on the feature deviation degree; and generating early warning information corresponding to the target wearable device, and generating a motion relieving strategy of the user based on the early warning information to prompt the user to execute the motion relieving strategy. According to the embodiment of the invention, the accuracy of sports injury early warning can be improved, the sports of the user is more scientific and reasonable, the sports effect is improved, and the user is assisted to achieve the fitness goal more quickly.

The invention discloses an athletic injury risk screening system based on motion capture and biomechanical analysis, and relates to the field of athletic injury risk screening, and the system comprises a standardization module which is used for establishing a grouping reference value database and a to-be-detected person exclusive file; the data acquisition module is used for acquiring three-dimensional action data of a person to be detected and preprocessing the data; the feature vector module is used for calculating joint feature parameter values of the moving joints in three moving planes based on an inverse dynamics method and constructing biomechanical feature vectors; the model construction module is used for constructing an athletic injury risk assessment model and outputting a comprehensive risk level and a specific risk mode label and probability; and the model training and verification module is used for performing staged training on the model and verifying the feasibility of the model. The method has the advantages that multi-modal biomechanical and kinematic data are fused, and accurate assessment of the sport injury risk and comprehensive identification of a specific risk mode are realized.

The invention discloses a motion monitoring clothing system integrating nano sensing and edge intelligence, which comprises three innovative modules: 1, a nano sensing network: adopting MXene / fibroin composite nano cobweb structure sensors (response sensitivity reaches 2.5 kPa), arranging the sensors in a clothing joint area in a bionic muscle texture manner, and capturing micro strain (0.1-15%) and three-dimensional attitude in real time; 2, a self-adaptive learning engine: carrying a lightweight graph convolutional neural network (GCN), generalizing motion data of athletes in a certain winter sports event into a general model through transfer learning, and realizing that the motion recognition accuracy is greater than or equal to 98.7%; the dynamic feedback system is used for generating tactile prompts through a micro-pneumatic actuator array and correcting dangerous postures. The system breaks through the rigid limitation of traditional exercise monitoring equipment, the stretch rate exceeds 180%, the exercise injury rate can be reduced by 42% according to actual measurement of a professional speed team, and the system has been applied to the fields of competitive training, rehabilitation medicine and the like.

The invention relates to the technical field of sport injury protection, in particular to an AI auxiliary diagnosis and treatment system based on wearable sport injury active defense, which comprises a data acquisition module and a sport monitoring module, the sport monitoring module comprises a risk assessment mode for determining a risk assessment mode based on a comparison result of action coherence and preset coherence, the mode determining module is used for optimizing the preset coherence degree based on the training injury occurrence density of the monitoring main bodies and is used for determining the joint angle collaboration degree and correcting the joint angle collaboration degree based on the obstacle level of the terrain of the sports field and the tolerance level of the climate; the risk evaluation unit is used for determining the landing risk level of the monitored main body based on the joint angle collaboration degree, and the level adjusting unit is used for determining whether the landing risk level is qualified or not based on the landing stability degree and optimizing the landing risk level based on the biped pressure distribution difference. According to the invention, the safety of the monitoring main body in the movement process is improved.

The invention provides a complex scene-oriented generative AI model training efficiency improvement method, which comprises the following steps of: data acquisition, which is used for acquiring action data of a sporter; the algorithm processing is used for executing action recognition and learning effect prediction analysis; and the application feedback is connected with the algorithm processing and is used for generating a visual result and a personalized training scheme. According to the method, real-time accurate recognition and learning effect intelligent prediction in a complex action scene can be realized, the sport injury risk is reduced, and personalized training scheme generation and multi-sport scene adaptation are supported.

The invention relates to the technical field of medical instruments. The sports injury rehabilitation auxiliary equipment comprises a medical bed body, a communicating opening is formed in the position, close to the middle, of the top of the medical bed body, when the waist of a patient lies on a waist protection plate, a plurality of rehabilitation mechanisms are independently and flexibly adjusted to be attached to the waist of the patient, and a power mechanism drives the waist protection plate to continuously swing; the fumigation mechanism sprays hot air to perform hot compress on the waist of the patient, so that the swinging rehabilitation mechanisms can perform massage operation on a plurality of areas of the waist of an athlete, and under the cooperation of the fumigation mechanism, the waist of the athlete can be massaged; by means of the massage mode, the waist can be comprehensively and fully massaged and stimulated, blood circulation of the waist is effectively promoted, muscular tension is relieved, damaged tissue is repaired, and then the rehabilitation effect on waist injuries of athletes is improved to a great extent.

The invention discloses a dance posture optimization system based on real-time monitoring, and relates to the field of dance training and sports health. The system comprises the following components: a data acquisition and digital twinborn construction module, a real-time monitoring and load analysis module, a damage early warning and evaluation module, a safety substitution action generation and optimization module and an interactive feedback and collaborative management module. According to the method, the action data of the dancer is monitored in real time, the digital twinborn body and the skeletal muscle dynamics model are combined, the load condition of each part of the body of the dancer can be accurately simulated, and when the load data exceed the biomechanical limit parameters which are set in a personalized mode, the system can immediately give out early warning and point out the damaged part and the damage type; the real-time feedback mechanism helps the dancer to adjust actions in time, potential sport injuries are avoided, and meanwhile, the system can generate a safe alternative action scheme according to the physical condition and the training target of the dancer.

The invention relates to the field of training guarantee monitoring systems, in particular to an intelligent guarantee monitoring system for physical training, and aims to realize omnibearing and accurate monitoring of physical training. The intelligent guarantee monitoring system for physical training comprises the following modules: a multi-dimensional data acquisition module, a data transmission module, a data analysis and processing module, a training scheme generation module and a user interaction module. According to the intelligent guarantee monitoring system for physical training, the physical state of a trainee is deeply analyzed by integrating multi-dimensional data, and a personalized training scheme is generated according to individual differences, so that the training effect is effectively improved, meanwhile, the risk of sports injuries is reduced, and the health and safety of the trainee are guaranteed.

The present application relates to a kind of traditional Chinese medicine liquid and traditional Chinese medicine paste for regulating muscle strength balance and preparation method thereof, the traditional Chinese medicine liquid for regulating muscle strength balance is prepared from the following raw materials by weight percentage: 8-12 parts of jieseng, 12-18 parts of eucommia ulmoides, 10-15 parts of taxillus, 15-20 parts of radix puerariae, 12-18 parts of radix astragali, 6-10 parts of chuanxiong, 9-12 parts of radix paeoniae alba, 10-15 parts of radix anemarrhena, 5-8 parts of mentha, and 6-8 parts of licorice.The preparation method of the traditional Chinese medicine liquid includes the following steps: a. pretreatment of raw materials; b. double extraction; c. concentration and mixing; d. blending and homogenization; and e. sterilization and packaging.The traditional Chinese medicine liquid and traditional Chinese medicine paste for regulating muscle strength balance are used for the regulation of spastic, atrophic and mixed muscle strength imbalance, and the relief of muscle spasm, muscle atrophy, and incoordination of limb movement, etc., and are suitable for post-stroke rehabilitation, secondary imbalance of cervical and lumbar spondylosis, and recovery of sports injury, etc., and have the advantages of bidirectional regulation and targeted penetration, etc.

The invention discloses a sports injury risk real-time assessment and early warning system. The system comprises an intelligent wearable device for collecting multi-dimensional physiological data and a remote analysis server for deep analysis; the server performs real-time risk assessment and graded early warning according to a personalized threshold value by fusing and analyzing the heart load, the body fluid balance state and muscle and joint stability characteristics extracted from kinematics parameters, and issues a specific intervention instruction; according to the invention, real-time perception of multiple risk factors of sports injury is realized through an end-cloud collaborative architecture, professional laboratory-level analysis ability is integrated into daily wearable equipment, the contradiction between single early warning dimension of existing equipment and incapability of real-time convenient application of a professional system is solved, accurate and prospective injury prevention guidance can be provided for a user, and the user experience is improved. And the safety of movement is greatly improved.

The present invention discloses a real-time monitoring system for teenagers' physical exercise, which relates to the field of intelligent monitoring technology. Through the spatiotemporal alignment processing of joint three-dimensional motion, electromyographic signals, and plantar pressure and the dynamic matching technology of bone age, an individualized health assessment model is constructed. Timing deviation is eliminated through unified clock marking and interpolation compensation, and parameters such as bone stress deviation, muscle synergy asymmetry, and plantar pressure imbalance are extracted, and weighted comprehensive health indicators are generated. Combined with a preset training path model, the health indicator trend is analyzed in real time and hierarchical adjustment instructions are triggered, the training intensity, interval and action plan are dynamically optimized, and the path model parameters are corrected through a closed-loop feedback mechanism to achieve adaptive updates. It solves the defects of large fusion deviation and strong lag of static evaluation of traditional teenagers' physical fitness monitoring data, realizes real-time and accurate monitoring of teenagers' physical exercise and personalized training optimization, and effectively reduces the risk of sports injuries.

1. The name of the design product: rehabilitation evaluation graphical user interface of electronic equipment. 2. The use of the design product: an electronic device. 3. The design points of the design product: in the graphical user interface. 4. The picture or photo that best indicates the design points: design 1 front view. 5. Design 1 is designated as the basic design. 6. The use of the graphical user interface: for the evaluation of rehabilitation after sports injury and postoperative rehabilitation. 7. The human-computer interaction mode of the graphical user interface: design 1: after selecting and clicking the "rehabilitation evaluation" column in the design 1 front view, enter the design 1 change state diagram interface, in which the rehabilitation is evaluated after completing the required action of the rehabilitation project; design 2: after selecting and clicking the "rehabilitation evaluation" column in the design 2 front view, enter the design 2 change state diagram interface, in which the rehabilitation is evaluated after completing the required action of the rehabilitation project.

The utility model aims to provide the auxiliary recovery equipment for the leg sport injury, which can improve the recovery speed of a patient with the leg injury and has the function of activating deep muscles. The lifting assembly is arranged on the base and used for adjusting the height, the sliding seat is in sliding fit with the lifting assembly and used for adjusting the front-back position, the angle adjusting assembly is rotationally connected to the sliding seat, and the leg fixing seat is rotationally connected with the angle adjusting assembly. A placing cavity for placing legs is formed in the leg fixing seat, a plurality of micro-current sheets are arranged in the placing cavity, and a plurality of fixing belts for fixing the legs are arranged at the upper part of the leg fixing seat. The leg rehabilitation assisting device is applied to the technical field of leg rehabilitation assisting devices.

This application relates to the field of computer vision technology, and provides a method and system for sports action recognition and judgment based on computer vision. The processing module realizes the parallel output of action intention category and initial skeleton points based on a multi-task learning network, generates a standard trajectory based on the action intention category, and constructs individual ability boundaries based on historical motion data. The matching module uses the standard trajectory as prior information, the initial skeleton points as observation information, and the individual ability boundaries as constraints to complete the iterative optimization of skeleton point positions and generate a skeleton point sequence through a state estimation algorithm. The inference module generates residual features by comparing the skeleton point sequence with the standard trajectory, combines user physiological data and historical motion data to determine the root cause of deviation through causal inference, and outputs the sports injury level. The adjustment module generates error correction instructions according to the root cause of deviation, and dynamically adjusts the intervention intensity according to the sports injury level to achieve the adaptation of intervention intensity with deviation type and injury risk.

The invention relates to the technical field of track and field training management, and discloses a big data-based track and field training management system, which comprises a training acquisition module and an intelligent management module. According to the system, management data of all athletes, management data of a training field and environment sensing data are acquired through a training acquisition module and are classified to form a data set, and an intelligent management module accurately quantifies individual competitive ability and generates ability indexes for speed-strength type, speed-endurance type and endurance type athletes of different items; data support is provided for personalized training, multi-dimensional evaluation accuracy is high, an intelligent management module evaluates the degree of influence of site conditions on athletic performance of athletes, generates influence indexes, avoids poor training effect or sports injury caused by site problems, evaluates the degree of influence of environmental factors on athletic performance of athletes, generates environmental scores, and improves training efficiency. And then corresponding track and field training management suggestions are output, various safety risks caused by adverse environments are avoided, and the targeted management training effect is good.

The utility model discloses a sitting posture chest pushing training device grip angle adjusting mechanism which comprises a shell, an adjusting ring, a rotary disc and a grip assembly, one end of the shell is provided with an opening, one end of the adjusting ring is fixedly connected with the end, provided with the opening, of the shell, a plurality of adjusting holes distributed in a surrounding mode are sequentially formed in the adjusting ring, and the rotary disc is arranged on the rotary disc. Any two adjacent adjusting holes are communicated through a slide way; the turntable is rotationally connected with the other end of the adjusting ring; the grip assembly comprises a grip pipe, a top pressing rod, a clamping head, a pressing head, a limiting ring, a baffle ring and a spring. Therefore, the adaptability and comfort of fitness operation can be effectively enhanced, a body builder can easily adjust the angle of the grip according to the body conditions of the body builder, and therefore muscles can be exercised more accurately and fully in the training process; meanwhile, the problem of uneven stress caused by improper postures can be effectively avoided through the reasonable grip angle, and the sports injury risks such as muscle strain and joint sprain are greatly reduced.

The present invention provides a method and system for evaluating sports injuries, belonging to the technical field of data evaluation. Specifically, it includes: using an associated monitoring data group to perform monitoring processing on a target person to obtain the monitoring data of the target person, determining the severity and occurrence probability of different types of sports injuries of the target person based on the analysis result of the monitoring data, and when it is determined that the severity of the target person's injury meets the requirements by using the severity and occurrence probability of the sports injury, determining the target of secondary acquisition of the monitoring data of the target person through the severity and occurrence probability of different types of sports injuries of the target person, and determining the evaluation result of the sports injury of the target person through the secondary acquisition target and the monitoring data of the target person, thereby improving the accuracy of the evaluation result of the sports injury.

The invention relates to the technical field of fitness equipment, and discloses a chest pushing training machine which comprises a training mechanism and a traction mechanism, the training mechanism comprises a machine frame, a cushion frame, two sets of sliding frames, an arm strength frame, two sets of handles, a shoulder pad frame, an adjusting pipe and a front pedal and is used for chest pushing training, and the traction mechanism comprises a vertical frame, a pulley, a traction rope and a guide rod. The training mechanism is arranged on the right side of the traction rope and is matched with the training mechanism to conduct balance weight resistance transmission, the weight adaptation mechanism comprises a gear knob, an adjusting box and a training box, and the gear knob of a pressure bearing plate is installed in the middle of the right side handle; the real-time training state of a user is reflected on the basis of the actual stress condition of the traction rope in the training process, an unstable force generation signal is captured in advance, the user can recover physical strength with the help of low resistance without stopping action through transient resistance reduction buffering, and effect damage caused by training interruption and sports injury during exhaustion are avoided.