187 results about "Activity intensity" patented technology

The invention relates to the technical field of physical education teaching, in particular to an interactive physical education teaching method based on a large model, and aims to realize real-time monitoring and personalized training guidance of the motion state of a student through an advanced sensor technology and a machine learning model. The method comprises the following steps: firstly, collecting motion data of a student in real time through a camera and a depth sensor, including motion posture, speed, response time, heart rate and other information; then, the collected data are input into a pre-trained large model, the model comprises a convolutional neural network, a support vector machine and a random forest model which are respectively used for evaluating the action standard, the exercise intensity and the fatigue degree of students, the large model automatically generates personalized training items, and the exercise postures of the students are captured in real time; according to the motion deviation correcting system and method, by comprehensively applying various technical means, the scientificity and individuation level of physical education are improved, and the motion deviation correcting system and method have wide application prospects.

The invention relates to a human motion data processing method, and belongs to the technical field of data processing. Comprising the following steps: controlling a microwave radar to emit a detection signal, and detecting a heart rate signal and a respiration signal of a human body; performing clustering analysis on the data according to the collected heart rate and respiratory rate, and extracting heart rate, respiratory rate change, duration and exercise intensity characteristics; according to the extracted heart rate change, duration, exercise intensity and other characteristics, the exercise stage is recognized, and according to the neural network model library, an energy consumption result is output in combination with data analysis. According to the human motion data processing method provided by the invention, the microwave radar is combined with the intelligent wearable device, so that the detection precision of heart rate and respiration signals is remarkably improved, multi-modal data fusion is realized, personalized heart rate prediction is performed, motion stage division is optimized in combination with acceleration data, and the accuracy of motion data processing is improved. The accuracy of motion mode recognition is improved, and personalized motion suggestions can be provided for the user.

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

The invention 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 provides a remote monitoring method and system applied to children's watches, and relates to the technical field of children's watches, time axis synchronous alignment is carried out on collected multi-source heterogeneous data through an interpolation method, data time sequence chaos caused by sampling rate differences is prevented, and then the data time sequence chaos caused by sampling rate differences is prevented. Through dynamic coupling calculation of a light intensity mutation gradient and a heart rate stress coefficient, the cooperative influence of environment change on the physiological state of the child is quantified in real time, and the physiological state of the child is determined by further combining power spectrum centroid frequency and physiological phase difference analysis of the motion rhythm and logarithmic correlation of acoustic envelope frequency and GPS speed. In addition, an acoustic propagation delay compensation mechanism is introduced, a two-factor dynamic equation model is constructed through a time delay cross term, and a dynamic risk threshold generation mechanism based on a noise energy ratio is combined, so that the dynamic risk threshold of the motion intensity, the rhythm characteristics and the acoustic scene is effectively distinguished. Effective remote monitoring on child safety in different scenes is realized.

The invention relates to the technical field of health management and medical information, and discloses an all-dimensional intelligent cardiopulmonary health management system and method and electronic equipment, and the system comprises a biological sensing module which is used for continuously collecting key physiological indexes of the heart rate, the oxyhemoglobin saturation, the respiratory rate and the motion state of a user; the data processing module is used for storing the collected physiological data and historical exercise records of the user through a central database of a cloud computing platform; the deep learning analysis module is a prediction model built based on a deep learning framework and is used for analyzing the physiological data of the user and generating a personalized exercise plan; the real-time monitoring module is used for detecting the physiological state of the user and automatically adjusting the exercise intensity or type when the physiological state exceeds a preset threshold value. The technical scheme that the multi-mode biosensor is combined with the real-time monitoring module is adopted, and the technical effect of comprehensively monitoring the cardiopulmonary function state of the user in real time is achieved.

The invention discloses an upper limb rehabilitation training method and system based on a human body motion model, and relates to the technical field of rehabilitation training. Constructing a human body motion model and outputting simulation data; calculating a physiological index coefficient, and further calculating the exercise intensity of each training action; calculating a motion mode complexity index of each training action so as to obtain and calculate the training duration of each training action; and calculating a motion deviation value, and further calculating a comprehensive dynamic deviation index. Presetting a threshold value and judging whether the rehabilitation training plan is suitable for the current state of the patient; whether a rehabilitation training plan needs to be changed; according to the method, the suitability of the rehabilitation training plan can be evaluated in real time, and the training scheme is dynamically adjusted; the training is always fit with the condition of the patient, and the rehabilitation efficiency and success rate are improved.

The invention relates to the technical field of digital health, in particular to a personalized rehabilitation exercise method for rheumatoid arthritis patients based on a BCW theory, which comprises the following steps: acquiring joint angle change and calculating a pain delay response coefficient, detecting fluctuation of supporting force and stabilizing force to obtain a joint load tolerance value, analyzing respiratory coordination to generate a respiratory coordination index, and performing rehabilitation training on the respiratory coordination index. The method comprises the steps that a joint angle sensor and pain intensity data are analyzed, a BCW capacity factor weight value is generated in a weighted mode, a fuzzy control algorithm is input to conduct hierarchical mapping adjustment on action amplitude frequency and rest intervals, and exercise adaptability feedback data are generated through monitoring completion degree and pain feedback. The exercise intensity is dynamically adjusted in real time through a data model, a personalized rehabilitation scheme is automatically optimized, the problems that subjective feedback is relied on, and physiological changes cannot be responded in time are solved, more accurate exercise amount adjustment is provided, the situation that the joint burden is increased due to improper exercise intensity is avoided, and the rehabilitation process is effectively promoted.

The invention discloses a personalized precise fitness scheme intelligent pushing method and system, and relates to the technical field of intelligent fitness, and the method comprises the steps: collecting motion data of a user in real time, and carrying out the preprocessing; the method comprises the following steps: collecting a fitness target of a user, converting the fitness target into a target vector, activating a task sub-network in a dendritic neural network according to a matching degree between motion data of the user and the target vector, dynamically adjusting weights and importance of different tasks in the task sub-network through an attention mechanism, and generating and optimizing a preliminary fitness scheme through multiple agents. The most relevant sub-networks are activated in real time, task priorities are adjusted through an attention mechanism to adapt to environment changes and user states, the exercise intensity is optimized through fuzzy logic reasoning, training tasks are automatically adjusted according to real-time feedback of users, the balance between the tasks is optimized through co-evolution between agents, and the training efficiency is improved. The personalized fitness scheme can be continuously optimized, and more accurate exercise recommendation is provided under the dynamic environment and user demand changes.

A system for remote monitoring of a workout, including: a processor; a non-transient memory; an imaging sensor; and a display device, the non-transient memory having computer-readable instructions stored thereon which, when executed by the processor, perform steps including: capturing imagery of at least a face of a subject, estimating and monitoring a peripheral blood volume pulse (BVP) or heart rate from the imagery using remote photoplethysmography (rPPG), performing facial age estimation using computer vision to analyze the imagery of the face to estimate an age of the subject, estimating a maximum heart rate using at least the age of the subject, calculating a heart rate zones as a predetermined percentage of the maximum heart rate, and displaying an indication of a current heart rate zone based on a current BVP or heart rate.

The invention discloses an intelligent tracking method and system for the rehabilitation state process of an orthopedic patient, and relates to the technical field of medical health. By integrating the wearable device, vital signs, motion states and pressure distribution data of a patient are collected and analyzed in real time, the rehabilitation state of the patient can be accurately monitored, and dynamic progress evaluation is provided; based on a rehabilitation progress evaluation result, the system can automatically generate a personalized rehabilitation exercise scheme, exercise intensity, exercise frequency and a training plan are adjusted according to specific requirements of each patient, and high efficiency and safety of the rehabilitation process are ensured; through analysis of vital sign fluctuation, motion precision and plantar pressure balance, the system can identify potential risk factors in real time and trigger early warning in time to help a patient and nursing personnel thereof to take necessary intervention measures, and smooth proceeding of the rehabilitation process is ensured.

The invention provides a personalized exercise prescription generation method based on an analytic hierarchy process, which comprises the following steps of: acquiring body index information, psychological state information, exercise preference information and exercise environment information of a user, determining a physiological health index, a psychological health index, environment suitability and user preference of the user according to the collected user information, and recommending a plurality of candidate exercises; constructing an analytic hierarchy process evaluation model based on four factors of a physiological health index, a psychological health index, environmental suitability and user preference of the user so as to comprehensively score candidate motions; an exercise prescription is generated for the user according to the comprehensive score of the candidate exercises, and parameters in the exercise prescription comprise recommended exercises, exercise intensity, exercise frequency and duration; and acquiring exercise execution data and tracking feedback data of the user, and adjusting parameters in the current exercise prescription.

The invention discloses an exercise management method and system for musculoskeletal chronic pain, and relates to the technical field of exercise management rehabilitation, and the method comprises the steps: building a biomechanical model for a patient through finite element analysis software, determining an optimal exercise mode according to the pain mode and the activity ability of the patient, and generating an exercise track through a path planning algorithm, on the basis of micro-current collaborative feedback data, the pain change trend of the patient is calculated, and a motion adjustment plan is generated, a biomechanical model can truly reflect the force distribution conditions of the patient under different motions, the safety of a motion scheme is remarkably improved, and the potential injury risk is reduced; scientific basis is provided for dynamically adjusting the exercise intensity, the obtained exercise adjusting plan can respond to the state change of the patient in time, and the intelligent level and the long-term curative effect of rehabilitation management are further enhanced.

The invention discloses an anti-resistance exercise training system for old people based on intelligent wearable equipment, and relates to the technical field. The problems that in the prior art, a dynamic action monitoring error correction mechanism is lacked, exercise intensity adjustment is not personalized and real-time, interaction and data feedback functions do not exist, and equipment portability and wearing adaptability are insufficient are solved. The system collects data in real time through the whole body position intelligent wearable device, corrects non-standard actions through the action recognition feedback module, dynamically regulates the intensity through the exercise intensity evaluation module, reduces the risks of muscle strain, cardiovascular burden and the like, takes standardized action guidance, personalized intensity adaptation and data visualization as the core, ensures target muscle activation, and improves the training efficiency. The training effect is quantified, the operation is simple, the use threshold is reduced through voice guidance, the boring feeling is relieved through personalized plans and summary reports, the training achievement feeling and compliance of the old people are enhanced, the muscle strength can be improved through whole body position training, and the anti-resistance exercise requirement of the old people is met.

The invention provides a self-adaptive assistance system and method for adjusting an exoskeleton based on a sweat sensor, and the system comprises a sweat amount detection chip which is embedded into the surface of wearable flexible clothes, is in contact with the skin of a human body, and is used for converting the detected sweat amount into an electric signal, and further converting the electric signal into a control signal; the knapsack comprises a control system, a driving system and a sensing system, and is worn on the trunk of the human body after being connected with the wearable flexible clothing; the power assisting device comprises a power assisting boot which is worn on the foot of the human body and connected with the driving system through a Bowden cable; and the specific output value of the power assisting device is controlled through the control signal. Dynamic matching of exercise intensity and mechanical assistance is achieved through an amplification control mechanism driven by sweat amount, gait phase compensation fed back by plantar pressure is combined, the energy utilization efficiency is improved by 20% or above, the problem that a traditional exoskeleton physiological-physical interface is disjointed is effectively solved, and the energy utilization rate is increased by 20% or above. The assisting synchronism is improved, and meanwhile the wearing comfort degree and the motion freedom degree are remarkably improved.

The invention relates to the technical field of intelligent sports equipment, and provides a counting error correction and sports intensity dynamic grading method and system for an intelligent skipping rope. The method comprises the following steps: acquiring three-dimensional motion data in a rope skipping process; performing feature extraction on the three-dimensional motion data to obtain rope skipping motion features; identifying a target data segment in three-dimensional motion data through the rope skipping motion features; acquiring a time interval and displacement track repeatability of two adjacent actions in the target data segment, and when the time interval exceeds a normal rope skipping frequency range or the displacement track repeatability is lower than a preset threshold value, judging that the counting is invalid counting and removing; the abnormal rope skipping counting result is corrected; and in combination with basic information and rope skipping frequency, continuous exercise time, accumulated rope skipping times and heart rate data which are acquired in real time, calculating a current exercise intensity index so as to perform dynamic grading. According to the invention, more accurate and personalized exercise experience is provided for the user.

The invention provides a treadmill device for studying animal energy metabolism. The treadmill device comprises a treadmill body, a respiratory metabolism monitoring system, a data acquisition controller and upper computer software. The treadmill main body is made of an aluminum magnesium alloy material, and is equipped with a running belt with the thickness of 2mm and a servo motor belt signal feedback system. The respiratory metabolism monitoring system can monitor parameters such as oxygen consumption, carbon dioxide output, respiration exchange rate, heat and the like, and can monitor animal movement, respiration and weight information at the same time. The data acquisition controller can manually adjust the current, angle and the like of the treadmill and is provided with various interfaces. The upper computer software can monitor and display multiple data of animals in real time, has data analysis and mapping functions, and can export original data in Excel, txt and jpg formats. A gas mixing fan is arranged in the device, so that the gas sampling accuracy is ensured. The energy metabolism indexes can be monitored on line in real time in the animal running process, data instantaneity and accuracy are improved, environments with different exercise intensities are simulated, and experimental application scenes are expanded.

The utility model discloses a double-track damping web plate which comprises a first web plate, a second web plate and a hinge piece arranged between the first web plate and the second web plate. A plurality of sliding rails are arranged at the tops of the first health web plate and the second health web plate; a plurality of sliding blocks are arranged at the top of the first health web plate, and a plurality of sliding pieces are arranged at the bottoms of the sliding blocks; a plurality of sliding blocks are arranged at the top of a first web exercising plate, when a user supports arms on the sliding blocks for exercising, the sliding blocks slide along the sliding rails under the cooperation of the sliding rails, the connecting blocks, the pulleys and the damping ropes, each sliding block slides on multiple rails, and the stability during sliding exercising is improved; the high-elasticity damping rope has the damping effect, the user is helped to better control the force and the speed in the exercise process, and the user can pull the exercise device by himself according to the exercise intensity needed by the user so as to achieve the personalized exercise effect.

The invention relates to the technical field of rehabilitation treatment, and discloses a lumbar vertebra rehabilitation exercise adjusting method and system based on HAPA and a storage medium. The method comprises the following steps: setting an HAPA psychological scale electronic questionnaire on a patient terminal, collecting answer data, and standardizing to obtain an HAPA psychological index; meanwhile, the waist three-axis angular speed, the myoelectricity root-mean-square value and the voice pain score are collected, and the exercise tolerance index is obtained. And inputting the HAPA psychological index and the exercise tolerance index into an exercise intensity mapping model to obtain an exercise intensity grade, and calling out corresponding parameters from a rehabilitation action library to form a basic training scheme. The exercise intensity grade, the exercise tolerance index and the corresponding threshold value are judged, the exercise parameters of the basic training scheme are correspondingly adjusted, the adjusted parameters and the patient completion degree are transmitted to a cloud end, and model self-learning is achieved. Personalized, intelligent and self-adaptive adjustment of lumbar vertebra rehabilitation training is achieved, and the training tolerance and the rehabilitation effect of a patient are improved.

The invention provides an activity level evaluation method and related equipment, and belongs to the technical field of terminals. The method comprises the following steps: screening a first heart rate of a user under low activity intensity and a second heart rate of the user under medium and high activity intensity according to walking heart rates in heart rate data of the user in the past one week; acquiring a weekly activity level assessment result of the user according to the first heart rate and the second heart rate by using an activity level assessment hierarchical model, the activity level assessment hierarchical model including a first activity level assessment model corresponding to low activity intensity and a second activity level assessment model corresponding to medium and high activity intensity, the activity acquisition module is used for acquiring the corresponding activity amount according to the heart rate, and the unit of the activity amount is Meide MET multiplied by time. According to the method, an activity level analysis result of a user is obtained by taking weekly activity data as an analysis unit through a personalized hierarchical model, so that the problem that an activity level evaluation result cannot be in butt joint with an international standard and is inaccurate is solved.

The brain function improvement promotion device comprises: a brain function improvement contribution exercise intensity measurement unit; a target brain function improvement contribution exercise intensity calculation unit; a first determining unit for determining whether or not the measured brain function improvement contribution exercise intensity of a user has become equal to or greater than a target brain function improvement contribution exercise intensity; a sustain time measurement control unit that, when it is determined that the user's brain function improvement contribution exercise intensity has become equal to or greater than the target brain function improvement contribution exercise intensity, performs control so as to measure the sustain time, which is the duration for which the user's brain function improvement contribution exercise intensity is equal to or greater than the target brain function improvement contribution exercise intensity; and a display control unit that, when it is determined that the total of the sustain time has reached a target time, performs control so as to display, on a display screen, the target health function improvement contribution exercise intensity calculated by the target health function improvement contribution exercise intensity calculation unit, actual related data and time, and display data generated by a display data generation unit.

Aspects relate to systems, methods, and apparatuses relating to a portable device that may be used to identify a critical intensity and an anaerobic work capacity of an individual. The device may utilize muscle oxygen sensor data, speed data, or power data. The device may utilize data from multiple exercise sessions, or may utilize data from a single exercise session. The device may additionally estimate a critical intensity from a previous race time input from a user.

The invention provides a knee joint straightening auxiliary exerciser which comprises a thigh frame, a connecting base arranged on the thigh frame in a sliding mode, a shank frame hinged to the end of the thigh frame, a sliding block arranged on the shank frame in a sliding mode, a resistance mechanism arranged on the shank frame and connected with the sliding block and applying resistance to sliding of the sliding block through the resistance mechanism and further comprises a driving rope. The two ends of the driving rope are connected with the sliding block and the connecting base respectively, an adjusting mechanism connected with the thigh frame and the driving rope is arranged on the connecting base, and the position of the sliding connecting base is locked through the adjusting mechanism, and the tensioning length of the driving rope is adjusted through the adjusting mechanism. According to the exercise device, the exercise strength can be quickly adjusted, elastic components with different elasticity coefficients do not need to be replaced when the exercise strength is adjusted, the adjusting process is convenient and quick, a patient can adjust the exercise strength by himself / herself conveniently, meanwhile, the exercise device can be used by the patient at home conveniently, and the practical value of the exercise device is effectively improved.

The application discloses a kind of simulation exercise devices for preventing dysphagia of cerebral apoplexy patient, it is related to cerebral apoplexy patient swallowing simulation technical field, including: placement bottom plate, adjustable dysphagia exercise mechanism and feedback analysis mechanism, adjustable dysphagia exercise mechanism is located in the right side of feedback analysis mechanism, adjustable dysphagia exercise mechanism: adjustable dysphagia exercise mechanism includes adjustable exercise component for swallowing mastication exercise intensity adjustment, by adjustable dysphagia exercise mechanism adjustable exercise component And the setting of flexible sensitivity promoting component, it is different from the function of rehabilitation training equipment in the prior art is relatively single, and the training device is replaced back and forth during rehabilitation training, and the linkage of training between devices cannot be guaranteed, effectively achieve when mastication training, patient lip and tongue are trained simultaneously with sensory force, close to life, effective simulation, better effect.

An adjustable-weight vibrating exercise bar includes a vibrating bar body, comprising a main body, a handheld end at one end of the main body, and a counterweight end at the other end of the main body. At least one counterweight ring is slidably fitted onto the main body. This counterweight ring can slide towards the counterweight end to increase its weight, or towards the handheld end to decrease its weight. The counterweight ring is an elastic body that is interference-fitted with the outer circumference of the main body, preventing it from sliding on the main body when no external force is applied. This vibrating exercise bar allows for adjustment of exercise intensity, thus meeting the user's needs for different levels of strength training.

The invention relates to the field of rehabilitation monitoring, in particular to an intelligent monitoring device for exercise rehabilitation of chronic diseases, which comprises a box body with a top opening and a controller, a water cavity used for containing liquid is formed in the box body, a running function assembly is arranged at the bottom of the water cavity, and the running function assembly is used for enabling a patient to run or walk underwater after being started; a water body fluctuation sensor is arranged in the water cavity and used for detecting water body fluctuation caused by underwater running of the patient; the controller is used for judging and recording the exercise intensity of the patient according to the water body fluctuation amplitude detected by the water body fluctuation sensor, and the water body fluctuation amplitude is in positive correlation with the exercise intensity of the patient. According to the technical scheme, whether the patient enters the traveling state or not is judged by detecting the heart rate change of the patient, and the exercise intensity of the patient is analyzed through the water fluctuation amplitude.

This application relates to the field of cardiopulmonary testing technology, and in particular to a cardiopulmonary endurance testing system and method based on a power bicycle. The method includes: acquiring basic information about the test subject; analyzing the basic information to determine the test subject's testing mode; acquiring real-time cycling video; analyzing the real-time cycling video to determine cycling operations; and determining a cycling adjustment plan based on the real-time cycling video and the cycling operations. By acquiring and analyzing the test subject's basic information, a testing mode suitable for the individual's physical fitness level and exercise intensity can be customized, improving the relevance and effectiveness of the test. The analysis of the real-time cycling video can provide immediate feedback on the test subject's exercise status, helping the test subject to adjust their posture in a timely manner and avoid incorrect movements and excessive fatigue.

The utility model discloses an adjustable respiratory rehabilitation training tool which comprises a box body and a steel wire hose, the box body is fixedly connected with the steel wire hose, one end, far away from the box body, of the steel wire hose is in threaded connection with a blowing nozzle, a dial is fixedly connected to the box body, a sliding groove is formed in the dial, a sliding plate is connected to the sliding groove in a sliding mode, and an air outlet is formed in the box body. The side, away from the filter element, of the push plate is fixedly connected with a second spring. When a patient needs breathing rehabilitation training, the patient bends the steel wire hose, the steel wire hose can keep the shape after being bent, at the moment, the patient does not need to be assisted by hands, the purpose of liberating the two hands of the patient is achieved, and the patient can observe the displacement distance of the indicating plate through the dial and know the exercise intensity of the patient. And after the patient finishes blowing, the indicating plate automatically resets, so that the patient can conveniently carry out next rehabilitation training.

The application discloses a metabolic equivalent driven endurance training intensity gradient generation system and method thereof, and belongs to the technical field of intelligent sports training. The system comprises a non-contact physiological signal acquisition module, a multi-dimensional metabolic state modeling module, a floating threshold generation module, a multi-channel feedback regulation module and an edge abnormality filtering module. Respiratory and heart rate and other multi-dimensional physiological parameters are collected through the fusion of a millimeter wave radar and a PPG sensor. A three-dimensional metabolic state dynamic evaluation model is constructed based on a GRU network, and real-time MET values are output. Intensity adjustment threshold values are adaptively generated according to MET deviation. The exercise intensity is cooperatively regulated through the tactile feedback of intelligent running shoes and the slope adjustment of a treadmill. Abnormal data are filtered at the edge by using a LOF algorithm. The application solves the problems of single physiological signal dimension, static metabolic state evaluation and abnormal data interference in the prior art, and realizes the precise real-time regulation of endurance training intensity.

The invention relates to the field of data processing, in particular to an intelligent extraction method and system for reference information of a patient in a recovery period, and the method comprises the steps: recognizing the motion condition and motion intensity of a user through motion data collected by an intelligent wearable device, and accumulating the current motion duration of the patient when the motion intensity reaches a certain value; meanwhile, collecting physical sign data of the user in real time, determining reference physical sign data matched with the patient from a physical sign reference database in combination with the current exercise intensity, and calculating the similarity between the actually measured physical sign data and the reference physical sign data. If the similarity is too low, it can be deduced that the patient possibly feels uncomfortable during movement, at the moment, a question answering process is executed through a pre-constructed question template, and a symptom entity possibly appearing during movement of the patient is found. Finally, the accumulated exercise duration, the symptom entity, the actually-measured sign data and the exercise intensity data serve as key data to be extracted and provided for doctors, and the doctors have related data to refer to and judge the recovery condition of the patient.