339 results about "Training intensity" patented technology

The invention relates to the technical field of medical rehabilitation, in particular to an artificial intelligence-based orthopedic full-cycle rehabilitation management system, which comprises a rehabilitation demand evaluation module, a three-dimensional pathological modeling module, a multi-modal training generation module, a rehabilitation effect prediction module, a dynamic parameter adjustment module and a full-cycle management module. Multi-dimensional data such as bone mineral density, joint motion range, gait mechanics and psychological state of a patient are collected, an artificial intelligence algorithm is combined for analysis, a personalized rehabilitation scheme is generated, and rehabilitation parameters are predicted and adjusted in real time. The system can dynamically correct the training intensity, the nutritional supplement dosage, the psychological intervention mode and the rehabilitation schedule, and the safety and reliability of data are guaranteed through the block chain technology; according to the system, biomechanics, nutriology, psychology and environmental factors are comprehensively fused, the system has strong adaptive ability and full-period management ability, real-time optimization can be performed according to the rehabilitation process of a patient, and the rehabilitation effect of the orthopedics department and the satisfaction degree of the patient are remarkably improved.

The invention provides a time sequence fusion and health state prediction method and system for multi-dimensional physiological data, and relates to the technical field of electrical digital data processing.The method includes the steps that high-precision sensing equipment and a parameter calibration model are adopted to calibrate data, time synchronization and error compensation are achieved through a weighted fusion algorithm, and the accuracy of physiological parameters is improved; meanwhile, a fatigue index and a pressure index are corrected in real time by using a closed-loop feedback mechanism, and a comprehensive state index is generated based on an evaluation result for further analysis and prediction; the change trend of the comprehensive state index is predicted through a machine learning technology, and a targeted dynamic rehabilitation scheme including training intensity optimization, diet adjustment, rest cycle planning and the like is provided in combination with physiological data of the user; and a timing feedback mechanism is established, so that the user can obtain health state change and adjustment suggestions in real time, thereby improving scientificity and timeliness of a rehabilitation scheme, remarkably optimizing the rehabilitation effect and efficiency, and realizing intelligent health management at the same time.

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 personalized fitness system and method based on multi-modal data and an adaptive large model. According to the method, multi-modal data are integrated, and heterogeneous data collaborative analysis is realized by using a space-time alignment algorithm and a confidence coefficient weighting mechanism. A multi-task learning framework is adopted, physiological prediction, exercise risk early warning and psychological incentive strategy generation tasks are synchronously processed, a user stage target is adapted through a dynamic attention mechanism, and federal learning and transfer learning technologies are combined. A nonlinear periodic planning engine based on reinforcement learning dynamically adjusts training load and action difficulty according to real-time biomechanical simulation results and recovery state evaluation, and meanwhile, a lightweight model compression technology and end-side reverse dynamics calculation are adopted. Based on the scheme, the exercise performance prediction precision and the early warning timeliness are improved, and the exercise loss risk caused by overtraining is reduced; the cold start data bottleneck is broken through; low-delay virtual coach interaction and privacy protection are realized; and dynamically adjusting the training intensity and the incentive strategy.

The invention discloses an intelligent rehabilitation guidance system based on machine learning, and relates to the technical field of virtual rehabilitation guidance, and the system comprises an integrated multi-source sensor, collects the physiological and motion data of a user in real time, and constructs health data; fusing multi-modal data, adjusting the resistance difficulty according to the condition of the patient through virtual reality, and calculating a comprehensive health score and an action offset early warning index; setting a rehabilitation cooperation particle swarm algorithm, combining the comprehensive health score and the risk early warning index, combining the resistance difficulty and the muscle-joint cooperation coefficient to compensate action compensation, optimizing rehabilitation action parameters, and returning to the upper layer; and analyzing an abnormal root based on a structural causal model, and generating targeted rehabilitation suggestions. The problem that the risk of secondary injury is increased due to lack of dynamic regulation and control of training intensity and muscle compensation behaviors of a patient in traditional rehabilitation training is solved.

The invention discloses a respiratory training device based on multi-modal data fusion. The device comprises a multi-modal sensor, a data processing server and an interaction module, the multi-modal sensor is used for collecting multi-modal data of a user in real time; the data processing server extracts feature data of the user according to the multi-modal data; constructing a physiological feature sub-graph by taking each physiological feature as a node, constructing an emotional feature sub-graph by taking the emotional feature as a node, constructing a physiological genetic map of the user, and inputting the physiological genetic map into a physiological state analysis model to obtain a physiological state of the user; generating a respiratory training scheme according to the physiological state, wherein the respiratory training scheme comprises a multi-sensory training guide step, target key feature data and training intensity; or adjusting the current breathing training scheme based on the difference value between the extracted key feature data and the target key feature data and the training intensity; the interaction module is used for displaying the breathing training scheme. According to the invention, accurate and effective respiration monitoring can be provided for the user.

The invention relates to the field of rehabilitation instruments, in particular to an intelligent pneumatic hand function rehabilitation training system which comprises a flexible exoskeleton glove provided with a pneumatic muscle array and used for assisting fingers of a user in grasping training. The fingertip position of the glove is connected with a magnetorheological damper through a flexible cable, and the magnetorheological damper is used for providing dynamic resistance in the training process. The electrical stimulation module is used for activating hand muscle groups in a targeted manner through a surface electrode and enhancing neuromuscular control; the sensor module is used for collecting physiological data of a user in real time; the physiological data comprises electromyographic signals and tissue blood oxygen saturation; the control unit is used for switching training modes, by means of the intelligent air pressure hand function rehabilitation training system, the training intensity can be matched with the real-time ability of a patient all the time, and the rehabilitation training effect is improved.

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 a chronic lumbago rehabilitation method and system combined with electromyographic signal mode recognition, and relates to the technical field of electromyographic signal recognition. By collecting electromyographic data of lumbar and abdominal muscle groups in real time, extracting characteristics such as an integral electromyographic value and a median frequency, and calculating dynamic adjustment parameters based on a change rate in a continuous time window; a dynamic fatigue threshold interval is formed, and the real-time fatigue state of the patient is judged. According to the comparison relation between the instantaneous fatigue degree data and the dynamic threshold value, an adjusting coefficient used for adjusting the output power of the rehabilitation training equipment is generated, and the training intensity can be adjusted in a self-adaptive mode along with the muscle state. According to the method, excessive training or insufficient training can be effectively avoided, the safety, individuation and intelligence level of rehabilitation training can be improved, meanwhile, the real-time intervention burden of a rehabilitator can be relieved, the training efficiency and the rehabilitation effect can be improved, and the advantages of closed-loop dynamic regulation and control can be fully embodied.

The invention discloses a tennis racket batting data monitoring system based on an intelligent sensor, and particularly relates to a training data monitoring technology, which comprises a four-layer collaborative architecture, an intelligent tennis racket, an intelligent bracelet and a communication module, the four-layer collaborative architecture is composed of a sensor layer, an unmanned aerial vehicle collaborative layer, an edge computing layer and a cloud / user layer; a first communication module is arranged in the unmanned aerial vehicle cooperation layer and used for receiving racket data and environment perception, and the unmanned aerial vehicle cooperation layer communicates with the sensor layer in real time. According to the tennis racket ball hitting data monitoring system based on the intelligent sensor, comprehensive monitoring and analysis of tennis ball hitting data are achieved, the system can capture detailed information at the ball hitting moment, and an accurate ball hitting quality score is generated in combination with physiological data and environmental factors of players; scientific training feedback and competition strategy support are provided for players; the self-adaptive feedback control function of the system can dynamically adjust the training intensity according to the physical state of the player, and the training effect is effectively improved.

The invention discloses a Parkinson's disease patient rehabilitation training method based on video gait analysis, relates to the technical field of image analysis, solves the problem of dependence on subjective evaluation in the prior art, and realizes objective quantitative analysis of a rehabilitation effect. An athletic ability index Xpzs, a gait stability index Yb and a lower limb rehabilitation progress coefficient Ws of a patient are calculated and evaluated to ensure that an evaluation result is more reliable and accurate; meanwhile, an established real-time data feedback mechanism is combined with historical data, the problem that rehabilitation effect monitoring is insufficient is solved, and through regular tracking and effect evaluation, a training scheme and a rehabilitation target are dynamically adjusted, and it is ensured that the rehabilitation progress of a patient is tracked in a whole cycle; besides, the method is high in technical adaptability, personalized analysis can be provided according to illness states and rehabilitation progresses of different patients, the training intensity and the rehabilitation target can be dynamically adjusted, the flexibility and adaptability of a rehabilitation scheme are improved, the method is particularly suitable for patient groups with different illness states, and the rehabilitation effect is improved.

The embodiment of the invention discloses a cerebral apoplexy upper limb rehabilitation training system and method based on dynamic reward feedback. A data acquisition module is used for acquiring physiological signals, motion signals, emotional state data and training performance data; the motion intention decoding module is used for performing motion intention feature extraction and reliability evaluation on the physiological signals according to an improved MREE-Net + + fusion algorithm, performing weighted fusion after feature weights are adjusted according to a reliability result, obtaining a unified motion intention feature vector, performing motion intention decoding, and obtaining a motion intention intensity index and a motion intention vector; the dynamic reward decision module is used for processing the facial micro-expression data according to an improved VGG-Face model to obtain an emotion titer, and obtaining an emotion awakening degree according to the voice signal; a reward action is generated according to an improved deep reinforcement learning algorithm; and the adaptive training regulation and control module is used for generating a personalized virtual training scene according to the generative adversarial network and regulating and controlling the training intensity according to the fatigue index. The rehabilitation training effect can be improved.

The invention relates to the field of intelligent auxiliary rehabilitation, in particular to a virtual reality-based respiratory rehabilitation system, which comprises a data capture module, a dynamic training monitoring module and an early warning and response module. A data extraction unit is used for acquiring a user respiration examination result and a rehabilitation training category, an environment acquisition unit is used for acquiring training field information, various respiration indexes, heart rate and motion state parameter data of a user in dynamic training are acquired, and an energy supply category is identified; and further calculating the oxygen uptake in unit time and the real-time oxygen uptake ratio, judging the training intensity grade by combining with an individualized evaluation model, and providing feedback through real-time broadcasting. If it is recognized that the training intensity is abnormal or safety risks exist, an early warning mechanism is started, voice and image prompting is achieved, and the user is assisted in adjusting the training state. The system obviously improves the scientificity, safety and individuation level of rehabilitation training, and is suitable for various scenes such as medical treatment, rehabilitation and home training.

The invention discloses a balance training coordination management method based on foot data analysis, and relates to the technical field of intelligent health and motion analysis, and the method comprises the steps: extracting gait features and fatigue indexes in a user foot comprehensive data set through a deep learning model, analyzing the balance capability and fatigue state of a user, and obtaining a quantitative evaluation report; according to the quantitative evaluation report, defining a reward function of balance ability improvement, recommending targeted training actions and recovery actions for the user, and obtaining a complete training plan, the personalized customization of the training plan is realized, the training intensity is ensured to be matched with the actual ability of the user, the problem of overtraining or insufficient training is avoided, and the training efficiency is improved. And the fatigue risk is reduced while the balance ability of the user is improved.

The invention discloses a knee joint rehabilitation training device, and relates to the technical field of rehabilitation equipment. The problems that in the prior art, diversified rehabilitation requirements cannot be met according to rehabilitation stages of different patients, pedal training strength is fixed and cannot adapt to individual differences, and the patients are prone to insufficient training are solved. The device specifically comprises a base, and two symmetrical openings are reserved in the top face of the base; the top face of the base is connected with a leg training assembly through a bidirectional driving structure, and the leg training assembly comprises a thigh plate hinged to the edge of the top of the opening, two sliding grooves symmetrically formed in the outer wall of the top of the base and moving blocks slidably connected to the inner walls of the sliding grooves. The joint flexibility can be improved through repeated flexion and extension actions, hip-knee-ankle joint load distribution can be synchronously adjusted, excessive load bearing of a single joint is avoided, and the structure can meet diversified rehabilitation requirements, adapt to individual differences and assist a patient to recover a normal knee flexion angle early.

The utility model discloses a rehabilitation training device for nursing chronic obstructive pulmonary disease, a pedaling device comprises a mounting frame and a linkage assembly, and the mounting frame is arranged on the other side of a support frame; the linkage assembly is rotatably arranged in the mounting frame; the breathing device comprises a breathing box, a breathing assembly, a hose and a mask, and the breathing box is arranged on one side of the top of the mounting frame; the breathing assembly is arranged in the breathing box, and the breathing assembly is connected with the linkage assembly; one end of the hose is connected with the breathing assembly; the mask is connected with the other end of the hose; the control system comprises a microprocessor, and the microprocessor is arranged in the breathing box and connected with the breathing assembly. Therefore, the device combines pedaling and breathing training, strengthens lower limb strength and improves the breathing function, the linkage assembly ensures synchronization of the pedaling and breathing training, the training effect is improved, the built-in control system monitors breathing in real time, the training intensity is automatically adjusted, safety and comfort are guaranteed, and the training effectiveness and patient compliance are improved.

The invention discloses an intelligent lower limb rehabilitation training device based on multi-modal feedback. Comprising an adjustable exoskeleton support capable of dynamically adjusting exoskeleton driving torque, and a multi-mode feedback system installed outside the adjustable exoskeleton support and capable of capturing the motion intention of a patient. The central controller can calculate the optimal motion trail of the patient according to the data fed back by the multi-mode feedback system; the force feedback actuator can provide assistance or resistance in real time according to the muscle force of the patient; by arranging the multi-mode feedback system, the action starting of a patient can be predicted, and the action intention and the muscle activation intensity of a user can be recognized; the hip, knee and ankle joint angles and plantar pressure of the patient during movement are measured in real time, the training intensity is dynamically adjusted according to the muscle force state and the movement intention of the patient, and the training individuation is optimized; compared with traditional single-machine training, the device can avoid secondary injury of muscles and reduce the risk of muscle injury.

The invention relates to the technical field of intelligent control of fitness equipment, and provides a power roller training intensity intelligent matching method based on elastic resistance self-adaptive adjustment. The method comprises the following steps: acquiring motion state data of a user during abdominal wheel training in real time through a sensor module; the motion state data and the physiological state data are input into a training intensity matching model, and the training intensity matching model calculates the matching degree of the current training intensity and the target training intensity according to preset training target parameters in combination with basic body parameters input by the user; when the matching degree is lower than a preset matching threshold value, a resistance adjusting instruction is generated according to the training intensity matching model, and the resistance adjusting instruction correspondingly controls the deformation degree or the meshing tooth number of an elastic element in the elastic resistance adjusting device so as to change the elastic resistance moment when the power roller body rolls. The technical blank in the aspects of training intensity dynamic matching, nonlinear resistance adjustment and closed-loop feedback control provides a brand new thought for the design of intelligent fitness equipment.

The invention relates to the technical field of teenager physical health management, and discloses a teenager physical health management system based on physical test results, and the system comprises a data collection terminal, a health intervention device and a cloud management platform which are in communication connection. The data collection terminal collects teenager physical test motion indexes and physiological signals in real time, and the health intervention device receives an instruction of the cloud management platform to adjust the training intensity. The data monitoring unit records an index abnormal starting point and a recovery termination point to determine a health risk interval, and controls the equipment to operate at a safety threshold and generate a physical characteristic curve for physical prediction mapping; the evaluation processing unit corrects the intervention path to generate an execution strategy; and a conventional regulation and control unit and an emergency regulation and control unit of the health management unit control equipment to execute corresponding operation under normal and abnormal working conditions respectively. According to the system, real-time monitoring, accurate evaluation, scientific intervention and risk processing of teenager physical health are realized, teenager physical test safety is effectively guaranteed, and the physical health condition is improved.

The invention relates to the technical field of postoperative rehabilitation equipment, and provides a cardiovascular postoperative rehabilitation trainer which comprises a bed body, an upper limb training position, a lower limb training position and a bed board, the upper limb training position and the lower limb training position are arranged on the two opposite sides of the bed body, and the bed board is slidably connected to the portion, between the upper limb training position and the lower limb training position, of the bearing surface of the bed body; the upper limb training part is arranged at the upper limb training position, the upper limb training part comprises a counterweight assembly and a first driving assembly, the first driving assembly is connected to the bed board and the counterweight assembly, and the bed board drives the counterweight assembly to move through the first driving assembly; the lower limb training part is arranged at the lower limb training position, the lower limb training part comprises a pedal, a movement assembly and a resistance piece, the pedal is connected to the movement assembly and used for driving the movement assembly to move, and the resistance piece is used for providing resistance in the movement process of the movement assembly. A patient drives the equipment to work through self strength, the effect of exercising the cardiopulmonary function is achieved, meanwhile, the training intensity can be adjusted, and use is more flexible.

The invention discloses a leg rehabilitation exercise device convenient for household use, and relates to the technical field of medical instruments, the leg rehabilitation exercise device comprises a rehabilitation chair, one side of the rehabilitation chair is provided with a rehabilitation training assembly, one side of the rehabilitation chair is provided with a control panel, and the rehabilitation training assembly comprises a thigh support, a shank support and a foot support. The number of the thigh supports, the number of the shank supports and the number of the foot supports are all two, the rehabilitation training assembly further comprises an automatic training unit and an autonomous training unit, through the dual-mode arrangement of the whole leg rehabilitation training device, the full-stage requirements of family rehabilitation of patients can be met, and in the initial-stage automatic training mode, the rehabilitation training efficiency is improved. Patients are passively trained at home by means of the hydraulic rod, the medical risk and operation errors are avoided, the autonomous training mode is switched in the later period, the patients can autonomously control the training intensity and recover the muscle and joint functions, continuous and flexible transition of family rehabilitation is achieved through the dual modes, dependence on professional sites and personnel is reduced, and the family rehabilitation efficiency and convenience are improved.

This application relates to the field of intelligent control technology for fitness equipment, and provides a method for intelligent matching of training intensity for an ab wheel based on adaptive adjustment of elastic resistance. The method acquires real-time motion state data of the user during ab wheel training through a sensor module; inputs the motion state data and physiological state data into a training intensity matching model, which calculates the matching degree between the current training intensity and the target training intensity based on preset training target parameters and the user's input basic body parameters; when the matching degree is lower than a preset matching threshold, a resistance adjustment command is generated according to the training intensity matching model. The resistance adjustment command controls the deformation degree or the number of meshing teeth of the elastic element in the elastic resistance adjustment device to change the elastic resistance torque when the ab wheel rolls. This method fills the technological gaps in dynamic matching of training intensity, nonlinear resistance adjustment, and closed-loop feedback control, providing a new approach for the design of intelligent fitness equipment.

The invention relates to the technical field of medical instruments and digital health, in particular to an intelligent device of a child respiratory training device and a using method thereof, and the intelligent device comprises a silica gel nozzle, a plastic inlet piece, a mode disc, a silica gel suction valve, an adjusting spring, a frequency ball, an airway cavity, a strength disc, a detection module, an air inlet and outlet grating, a spring sliding piece, a silica gel exhalation valve and a mapping system; the mapping system comprises a self-adaptive algorithm module and a game mapping module. The self-adaptive algorithm module is used for calculating a gear and a training mode required by a user based on personal information of the user; the game mapping module sets a game scene and a training feedback mode based on breathing training of a user. The breathing mode and the training intensity are adjusted through a pure mechanical structure, the problem of insufficient user compliance is solved by combining breathing training with a game dynamic mapping engine, and the problem of individual difference is solved through a self-adaptive algorithm.

The invention discloses a physical fitness rehabilitation training device and method based on physical exercise, and relates to the technical field of physical training devices.The physical fitness rehabilitation training device comprises a fixing frame and a holding rod, vertical rods are arranged on the two sides of the top of the fixing frame, and height adjusting assemblies used for adjusting the height of the holding rod are arranged on the vertical rods; a position adjusting assembly is arranged on the fixing frame, a sliding rod is arranged on the position adjusting assembly, a mounting plate is arranged on the top of the sliding rod, and the resistance assemblies with the required number are fixed to the mounting plate through connecting assemblies according to the training requirement of a trainee, so that when the trainee pulls up, the resistance assemblies are fixed to the mounting plate through the connecting assemblies. According to the pull-up training device, the legs need to overcome the resistance brought by the connected resistance assemblies, so that the resistance needing to be overcome by the legs during pull-up becomes larger, rehabilitation of a trainee can be better facilitated, the strength of the upper limbs and the lower limbs can be exercised at the same time during rehabilitation training, and different training intensities can be adjusted according to the rehabilitation degree of the trainee.

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 training, in particular to a double-leg buckling function rehabilitation device. Comprising a supporting table, a base plate, a backrest plate, guide rails, movable blocks, a limiting frame and the like, the base plate and the backrest plate are installed on the supporting table, the guide rails are symmetrically arranged on the supporting table, the movable blocks are arranged in the guide rails in a sliding mode, and the limiting frame used for containing the feet of a patient is rotatably installed on the movable blocks. The double-shaft motor drives the ejector rod to achieve passive flexion movement, and the device is suitable for an early postoperative stage or a patient with weak muscle force; meanwhile, the patient is supported to autonomously generate force to complete active buckling training, progressive resistance can be applied through a spring system to enhance the training intensity, passive training, active training and resistance training are integrated through the design, the patient does not need to replace equipment in the whole rehabilitation process, the equipment investment and management cost of a medical institution are effectively reduced, and the rehabilitation training efficiency is improved. And continuity and efficiency of rehabilitation training are improved.

The utility model relates to the technical field of dance training devices, and discloses a tiptoe holding device which comprises a bottom plate, a foot placing plate and a leg fixing plate, the foot placing plate is rotatably installed on one side of the top of the bottom plate, two fixing vertical strips are welded to one side of the top of the bottom plate, and the leg fixing plate is installed on the bottom plate. And the leg fixing plate is fixed between the two fixed vertical bars. According to the tiptoe holding device, the downward rotation degree of the tiptoe is controlled by the moving distance of the transmission block, and the downward rotation angle is larger if the distance is far larger, so that the tiptoe holding device can be controlled and adjusted according to the training intensity required by a trainee to adapt to different people to do exercises at different stages, the progressive exercise effect can also be achieved, and meanwhile, the tiptoe holding device is convenient to use. After adjustment is completed, the foot placing plate cannot rotate clockwise due to disordered movement of the foot sole, and the inclination angle of the tiptoe is guaranteed.

The invention discloses an orthopedic postoperative rehabilitation training method based on biomechanical feedback. The method comprises the following steps: synchronously collecting joint kinematics, myoelectricity and plantar pressure multi-source data of a patient; performing time sequence alignment and noise suppression on the data; constructing an individualized biomechanical function evaluation model, and generating a dynamic score covering the joint motion range, the muscle symmetry, the gait stability and the load tolerance; the training intensity, the auxiliary support and the rest time are adjusted in a self-adaptive mode based on the deviation between the score and the stage target; voice with clinical semantics and visual feedback are generated; and the evaluation and regulation strategy is continuously optimized through the closed-loop learning module. According to the technical scheme, precision, individualization and intelligentization of rehabilitation training are achieved, the recovery efficiency is effectively improved, and the risk of secondary injury is reduced.

The utility model relates to the technical field of medical instruments, in particular to an ankle pump exercise training device which comprises a pedal plate, adjusting shafts are movably installed at the left end and the right end of the pedal plate in a penetrating mode, a connecting assembly is jointly movably installed between the two adjusting shafts in a penetrating mode, and an elastic assembly is movably connected to the front end of the connecting assembly. And the lower end of the elastic component is fixedly connected with the lower inner wall surface of the pedal plate. According to the ankle pump exercise training device, the angle between the connecting assembly and the pedal can be adjusted through the arranged adjusting shaft, the ankle pump exercise training device adapts to leg lengths and exercise requirements of different users, it is guaranteed that the optimal training effect can be achieved when the users conduct ankle pump exercise, and meanwhile the ankle pump exercise training device is convenient to use. A force adjusting knob in the elastic assembly can adjust the elastic force of the elastic belt according to the rehabilitation process and the physical condition of the user, the training intensity is gradually increased, and the muscle strength and the joint flexibility are improved.

The invention relates to the field of fitness equipment, in particular to fitness equipment for intelligently adjusting the training intensity of fitness personnel, which comprises a training intensity adjusting module for executing at least one training intensity adjusting action; the state monitoring module comprises at least two types of physiological parameter sensors and is used for collecting biological characteristic data of fitness personnel in real time; the intelligent adjusting system is in communication connection with the training intensity adjusting module and the state monitoring module and comprises a data processing unit adopting a multi-modal data fusion engine; dynamically adjusting the algorithm model, and adopting a reinforcement learning framework; and the executing mechanism drives the training intensity adjusting module to perform real-time adjustment according to the adjusting instruction. The technical problems that in the aspect of training intensity adjustment of existing fitness equipment, a fixed mode exists, the adjustment mode is extensive, and data processing is inaccurate and incomplete are solved.