CN112349413B - Long-distance exercise training load analysis system - Google Patents
Long-distance exercise training load analysis system Download PDFInfo
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Abstract
The invention belongs to the technical field of exercise data analysis, and discloses a long-distance exercise training load analysis system and an analysis method. The invention can more objectively reflect the competitive state of long-distance athletes or the state of personal body-building exercise load bearing, provides realistic reference and effective control for scientific exercise training or body-building health management, and has wide popularization value and commercial development prospect. The invention can realize tracking analysis of the actual exercise load bearing state of long-distance athletes or fans, and early warning over-training; the visual on-line long-distance sports training and functional training guiding functions are hung, intelligent support is provided for competitive sports training, scientific and technological service is provided for sports protection, and market value is developed.
Description
Technical Field
The invention belongs to the technical field of motion data analysis, and particularly relates to a long-distance motion training load analysis system.
Background
At present, with the rapid development of computer software and hardware technology and networks, massive sports training data can be acquired in real time by using cameras, sensors, wireless sensor networks and the like. In the face of massive sports training data, the traditional data processing mode faces new serious challenges, and the characteristics of large quantity, diversity, rapidness, low value density and the like of the sports training data enable the traditional data processing method and tool to only look at 'data'. How to effectively construct mathematical models and tools which are suitable for the exercise data and truly change massive exercise training data into valuable information is a problem to be solved in the field of analysis of sports load. The exercise load refers to the amount of physical function reflected in a stress state by the body due to the applied training amount and intensity stimulation during exercise, and includes the load amount and the load intensity. The indexes for evaluating the sport load bearing state of the athlete at present mainly comprise: heart rate, RPE, maximum oxygen uptake, urine protein, blood lactic acid, blood urea, creatine kinase, calories, and METS, among others.
The existing exercise load data analysis mainly carries out simple mathematical statistical analysis on the planned exercise load measurement or the completed training load measurement of the athlete, reflects the training load bearing state of the athlete through an intuitive graph, and rarely combines with or excessively relies on the physiological and biochemical indexes for analysis. On one hand, the statistical analysis method cannot practically reflect the state of bearing the exercise load for a period of time, because the physical function state changes in different exercise training stages, the simple physical training load measurement cannot truly reflect the exercise training effect, and an exercise load process analysis concept needs to be introduced to realize the cooperative analysis of the physical training load and the physiological load so as to early warn over-training and exercise damage; on the other hand, the physical and biochemical indicators excessively reflect the exercise load bearing state of the athlete, and cannot practically reflect the exercise level or exercise capacity of the athlete or the body-building personnel, because the physical and biochemical indicators mainly reflect the physical functions of the participants in completing the exercise from the self-organizing state, and cannot reflect the actual forces of the participants in participating in the exercise, namely the completed exercise amount and the reached training intensity (target achievement), and further because the training aims to maintain and improve the exercise achievement, and for the body-building athlete, the physical function state is indirectly reflected mainly through the level of completing the exercise, so as to realize the health management and health promotion of long-distance fans.
Through the above analysis, the problems and defects existing in the prior art are as follows: the existing exercise load statistical analysis method is inaccurate in analysis result, cannot reflect the generation and development processes of exercise fatigue in real time, and cannot perform over-training and exercise damage early warning in time.
The difficulty of solving the problems and the defects is as follows: through big data analysis, a statistical analysis index system of the long-distance exercise training load and a mathematical relation type table of deriving indexes such as working distance, working intensity, lesson load value and the like are established; converting the long-distance training load mathematical control method into a computer language, and compiling a computer application program to perform visual operation; and qualitatively evaluating the training load bearing state of the athlete in a period of time by combining indexes such as physiological and biochemical training, functional training, basic physical training and the like, and generating a visual chart of the athletic state for display.
The meaning of solving the problems and the defects is as follows: the developed long-distance exercise training load mathematical control method and the analysis model can timely track and analyze the formation, maintenance and disappearance processes of the training load state and the athletic state born by the athlete in a period of time; the complex training load data can be timely and rapidly processed through the computer language and the computer application program APP developed by the modern network technology to generate a visual exercise training prescription, so that a coach is helped to supervise and control excessive training and prevent exercise risks; with the vigorous development of the long-distance sports such as the marathon, the population of the long-distance sports is more and more, scientific training requirements are paid more and more attention to, and the development of the analysis system not only provides a scientific training method for the population of the long-distance sports, but also facilitates the management of the sports team and becomes a power assistant of a coach.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a long-distance exercise training load analysis system.
The present invention is achieved by a long-distance exercise training load analysis system comprising:
the training system comprises an athlete file management module, a training unit setting module, a training plan making module, an actual training load input module, a healthy exercise management module, a training load statistics module, a lesson load control module and an online exercise training service module;
the athlete file management module is used for acquiring athlete basic information, special profile information and international situation data and establishing an athlete file based on the acquired data; the athlete profile includes: name, gender, birth month, height, weight, blood type, hobbies, personality, and physical vigor; the special profile information comprises exercise special training years and best achievements and creation time, place and event names of the exercise special training years and best achievements and creation time, place and event names of main item segmentation achievements and best achievements; the international situation comprises long-distance Olympic project world records and the segmented average speed r thereof A Sum of achievements R A The method comprises the steps of carrying out a first treatment on the surface of the Near term best performance of long distance project and its piecewise average speed r A Sum of achievements R A ；
The training unit setting module is used for carrying out phase division and target training measurement setting on the competition period according to the period theory and the plate training theory, making an overall plan comprising a multi-period large period and a multi-period viscosity training for the phase training plan, and making a target task comprising a target training period, a target training period small period and a target training day period for the unit training plan;
the training plan making module comprises a training means setting template unit, a unit training plan making unit, a lesson load value and operation specific gravity setting unit, a functional training unit, a training means setting and unit training plan unit; the training method comprises the steps of setting optional content of training means and making a daily training unit training plan;
the actual training load input module comprises a training load acquisition unit, a training means acquisition unit and a training load input unit; the training device is used for training load data acquisition, training means adjustment and training data input;
the health exercise management module comprises a physiological and biochemical index monitoring unit, an exercise injury and nutrition monitoring unit and a self-training sensation evaluation unit; the method is used for collecting relevant indexes of healthy exercise, supervising exercise risk and judging the functional state grade epsilon and the recovery state coefficient mu of the athlete bearing training load;
The training load statistics module comprises a training load qualitative analysis unit, a training load conventional statistics unit and an athlete personal load adjustment unit; training academic analysis for completing a special skill ability training load; meanwhile, the training purpose, course property, training content, training quantity and training intensity of a training method, training density, training total quantity and segmentation speed of the athlete for a period of exercise training are counted, and a corresponding chart is generated; and performing telemobilization personal load adjustment;
the lesson load control template is used for integrating special technical capacity training, physical quality training, technical improvement, functional action training content and training load characteristics thereof which are completed by athletes according to a training plan, combining functional states and recovery states, applying a business distance law, a working intensity law, a working load law, a reasonable load principle and a reasonable recovery principle, establishing a lesson load process mathematical control model, predicting rationality of the athletes in lessons, between lessons, in small periods, in training stages and during competition periods for bearing training loads and judging the possibility of maintaining or improving the competition state;
the on-line sports training service module is used for providing competitive sports state judgment, long-distance sports training guidance, functional training guidance and competition appreciation.
Further, the training plan preparation module includes:
the training means setting template unit is used for setting optional content of the training means; the training means optional content includes: date or task, small period special training, daily unit special training, functional state monitoring, special technical action training, functional physical training and physical fitness training;
the date or task comprises training purposes, lesson properties, training contents and training methods;
the small period special training comprises: week course structure, week training times, training total amount, average score, target score, school load value and school specific gravity;
the daily unit special training comprises the following steps: the daily class structure, the working distance, the working average score, the working total score, the training total amount, the working times, the training group number, the training total time, the intermittent time, the working percentage strength, the working load value and the working proportion;
the functional status monitoring includes: target heart rate, process heart rate, immediate after training heart rate, recovery heart rate, process blood lactic acid, post training blood lactic acid, blood urea, creatine kinase, urinary protein, self-sensation;
the specialized technical action training comprises: type, content, method, job measure, total time;
The functional physical training comprises: type, content, method, job measure, total time;
the physical fitness training comprises: type, content, method, job measure, total time;
the unit training plan making unit is used for making a daily training unit training plan; the daily training unit training program comprises training purposes, course properties, training contents, training methods, training contents, load measurement and state monitoring;
the training purposes include: technical ability, physical ability, game ability, mental ability, and training theory;
the course properties include: aerobic training, mixed oxygen training, speed training, technical training, tactical training, functional action, strength training and adaptability training;
the training content comprises: aerobic special technical ability, special speed endurance, absolute speed, technical action, tactics, strength endurance, explosive force, absolute strength, functional action, psychological adaptability, environmental adaptation, opponent adaptation, field facility adaptation, wearable equipment adaptation;
the exercise method comprises the following steps: continuous training of aerobic special technology, speed repeated training, intermittent training of speed, mixed oxygen variable speed training, functional action cyclic training, general strength cyclic training, rapid strength repeated training, absolute strength repeated training, following tactics, race tactics, wheel tactics, simulated competition, teaching competition and formal competition;
The load metric includes: working distance, working average score, working total score, training total amount, working times, training group number, training total time, intermittent time, working percentage strength, working load value and working specific gravity;
the functional status monitoring includes: target heart rate, process heart rate, immediate after training heart rate, recovery heart rate, process blood lactic acid, post training blood lactic acid, blood urea, creatine kinase, urinary protein, self-sensation;
the lesson load value and operation specific gravity setting unit is used for monitoring the training load process;
the functional training unit is used for supervising the body dysfunction, ensuring the effectiveness and economy of the sport technical action and preventing sport injury;
the training means setting and unit training plan unit is used for providing a manual record list and browsing, printing and sharing training plan sample list.
Further, the actual training load entry module includes:
the training load acquisition unit is used for collecting relevant training data through modes of manual recording, electronic equipment importing, artificial intelligent system identifying and the like, screening index input reflecting a class load value according to training load setting parameters, providing an importing window and a parameter acquisition sample table, and acquiring work load data; the workload data comprises manual recording, wearing equipment and other intelligent system reading, photographing, gesture analysis SennoGait, physiological and biochemical tests, functional action screening FMS, basic physical ability assessment FCS;
The training means acquisition unit is used for comparing training plan changes to carry out actual completion content adjustment;
the training load input unit is used for inputting or importing training data actually completed according to a training plan into the system; the input mode comprises personal input and group input.
Further, the health exercise management module includes:
the physiological and biochemical index monitoring unit is used for acquiring physiological and biochemical indexes in the training process and after training and managing and monitoring the relevant physiological and biochemical indexes;
the sports injury and nutrition monitoring unit is used for collecting sports nutrition, sports injury and rehabilitation, drug treatment and stimulant detection and other related data in the training process of athletes;
the self-training feeling evaluation unit is used for collecting self-feeling and body response of the athlete, which are subjected to training load and comprise fatigue degree, dysfunction, body pain, injury expression and treatment effect.
Further, the training load statistics module includes:
the training load qualitative analysis unit is used for qualitatively analyzing the training work load parameters of the special technical capability from the angles of sports training science, sports biology, sports medicine and physical function training theory, counting and classifying, diagnosing the training load bearing state of athletes, providing a work load analysis parameter sample table, printing and sharing analysis results; training academic analysis for completing a special skill ability training load; the method is used for analyzing the motion dynamics of special technical action characteristics and completing technical training load; for performing a kinematic biological analysis of the completed specialized skills training load; the functional training analysis is used for carrying out functional training analysis on the functional action training and physical training load; the training device is used for analyzing nutrition, injury and psychological adaptation analysis sports medicine for completing the training load process;
The training academic analysis includes: common operation distance and corresponding average score and total score, main operation average speed and highest speed and standard deviation thereof, main operation best training score and competition score and standard deviation thereof, wing operation average speed and highest speed and standard deviation thereof, variable speed training average score and best score of main operation, variable speed training average score and best score of wing operation, competition operation distance and corresponding average score, total score, time interval, uniform speed operation distance and subsection operation score, total score, variable speed operation distance and subsection operation score, total score, special technical capability training comprising content, means and method, special technical action training comprising content, means and method, physical functional training comprising content, means, method, total time and density; the intermittent training method comprises content and the number, the time of rest, the percentage strength and the class proportion, the repeated training method comprises the content and the number, the time of rest, the percentage strength and the class proportion, the unit class training comprises the purpose, the property, the type, the average total time and the interval time, the week period class comprises the training number, the total time and the class structure, the stage division of the event period comprises the preparation period, the competition period, the transition period and the refinement and measurement thereof, the unit of the total quantity of training and the average result strength, the day, the week, the stage and the event period comprises the physical quality training of the type, the density and the total time, and the physical functional training comprises the type, the density and the total time;
The kinetic analysis includes: stride, stride frequency, stride swing angle, stability, flexibility, economy, gait characteristics, physical characteristics, technical advantages, and technical shortcomings;
the kinetic biological analysis includes: process heart rate, heart rate inflection point, resting heart rate, highest heart rate, lowest heart rate, lactic acid threshold, maximum oxygen uptake, anaerobic threshold, creatine kinase, hemoglobin, blood urea, red blood cells, white blood cells, urine protein, PH change, BMI change, altitude adaptation, temperature humidity adaptation;
the functional training parsing includes: a function action evaluation index system FMS, a selective function action evaluation index system SFMA, a balance ability evaluation YBT and a basic motion physical ability evaluation FCS;
the sports medical analysis includes: motor nutrition characteristics, accumulation and rehabilitation of injury and psychological adaptability;
the training load routine statistics unit is used for counting training purposes, course properties, training contents, training amount and training intensity, training density, training total amount and segmentation speed of the athlete during a period of sports training, and generating a corresponding chart;
the counting and generating the corresponding chart comprises: training analysis indexes according to the weekly statistical technique capability, and generating a visual chart display by using statistical data; training analysis indexes according to daily statistical technology capability, and generating statistical data into a visual chart for display; training analysis indexes according to the unit statistical technology capability, and generating a visual chart display by using statistical data; daily statistics functional training load analysis indexes, and generating a visual chart display by the statistics data; daily statistics of physiological and biochemical analysis indexes, and generation of a visual chart display by the statistical data;
The athlete personal load adjusting unit is used for reversibly adjusting the training load and revising the personal load data; the training load reversibility adjustment includes, but is not limited to, abnormal data adjustment due to entry errors and reclassification of training means.
Further, the lesson load control module includes: the system comprises a working process mathematical analysis unit, a load bearing state judgment unit and a load process control paradigm unit;
the operation process mathematical analysis unit includes: a working distance law determining subunit, a working intensity law determining subunit, a working load principle determining subunit and a reasonable load principle determining subunit;
the operation distance law determining subunit comprises a common operation distance, a mathematical relation between any operation distance and an operation result and a power index table of the common operation distance; the method is used for processing the relation between the actual working distance and the working score and providing basis for setting a training plan; meanwhile, the method is used for exploring the sensitivity and the adaptability of the operation means of the athlete by qualitatively analyzing the characteristic of the personalized training load of the athlete, and establishing a personalized operation distance and operation achievement index system of the athlete;
The operation intensity law determining subunit comprises operation achievement intensity, percentage intensity and a mathematical relation and a percentage intensity power index scale; the system is used for monitoring the training load bearing state of the athlete through the operation score, providing basis for setting a training plan, exploring the sensitivity and the adaptability of the operation means of the athlete through qualitatively analyzing the personalized training load characteristics of the athlete, and establishing a personalized operation distance and operation score index system of the athlete;
the work load principle determining subunit comprises work load value calculation, work load accumulation principle determination and work load liability principle determination; for processing the relation between the actual work load of a player at a certain distance and the load ratio generated by a competition with full strength at the distance, and converting the work percentage strength into the actual work load specific value (q B/A )；
The workload value calculation includes: calculating a master distance workload value and a non-master distance workload value;
the workload accumulation principle determination includes: the load value is used for statistically analyzing the continuous operation of the athlete;
the work load accumulation principle is determined, and is used for monitoring the load state change born by the athlete in the continuous work process through the work load value;
The work load liability principle determination comprises a lesson load value, a liability load principle, an inter-lesson liability load principle and an accumulated liability load principle and application thereof; the system is used for monitoring the load state change of the athlete in the continuous operation process and early warning the occurrence and development of excessive training through the operation load value;
the reasonable load principle determining subunit comprises the steps of determining reasonable class load values of the level athletes and calculating class load operation times; the early warning load measurement standard is used for monitoring the rationality of the player class target training load through the class load value and establishing excessive training; providing a standard for setting training main class load or full strength load class;
the method comprises the steps of determining international level reasonable lesson load values, wherein the international level reasonable lesson load values are used for calculating reasonable lesson load values of athletes of different levels at any distance based on an international level reasonable lesson load meter, a level athlete reasonable lesson load meter and a level athlete working distance reasonable lesson load meter;
the number of the lesson load operations comprises: calculating reasonable operation times of the courseload by calculating reasonable operation times of the operation distance;
the load-bearing state determination unit includes: the system comprises an actual load value calculating subunit in the course of the lesson load, a statistics unit training accumulated liability load value subunit, a statistics week training accumulated liability load value subunit, a load state judging subunit and a correction subunit; the method is used for judging the actual state of the athletes in the course of carrying training load according to the occurrence process of the actual operation score strength, the accumulated load value and the accumulated liability load value; the method comprises the steps of providing a training plan adjustment scheme for early warning over training or under training;
The real load value calculating subunit of the lesson load process comprises: the training unit is used for planning and calculating reasonable operation achievement R/R of the operation distance according to the training unit; the training unit is used for planning and calculating the reasonable operation achievement R/R percentage strength of the operation distance according to the training unit; the training unit is used for planning and calculating reasonable operation achievement R/R reasonable load values of the operation distance according to the training unit; the device is used for calculating an accumulated load value of the operation distance speed change operation score R/R according to the training unit plan; the system is used for calculating a constant-speed operation achievement R/R accumulated load value of the operation distance according to the training unit plan; the combined working distance working score R/R and the accumulated load value are calculated according to the training unit plan; the accumulated liability load value is used for calculating the combined working distance working score R/R in the class according to the training unit plan; the method is used for calculating reasonable operation times of the combined operation distance in the class according to the training unit plan; for calculating a week accumulation load value according to the training week plan; the method comprises the steps of calculating a week accumulation liability load value according to a training week plan; the method is used for calculating reasonable operation results of the operation distance according to the percentage strength and the operation means proportion; the device is used for calculating reasonable percentage strength of the working distance according to the working score and the specific gravity of the working means; the method is used for calculating reasonable operation scores of the operation distance according to the load value;
The statistics unit trains and accumulates the sub-unit of the liability load value and includes: the statistical unit is used for training and accumulating liability load values and displaying a visual chart;
the statistical week training accumulated liability load value subunit comprises: the method is used for counting the training accumulated liability load values and displaying a visual chart;
the load state judgment subunit includes: the system is used for judging the training load bearing state of the athlete unit by combining the function detection indexes;
the correction subunit includes: the training program load measurement is used for correcting the weekly training program load measurement and providing a working means correction suggestion;
the load process control paradigm unit includes: the training method comprises training means setting, unit training classes and lesson training plan making of week period; the system is used for systematic analysis of the course control of the training load of the lesson; the training program sample preparation table is used for storing training load control success cases and mathematical analysis models thereof, and providing, printing and sharing the mathematical control training load.
Another object of the present invention is to provide a long-distance exercise training load analysis method applied to the long-distance exercise training load analysis system, the long-distance exercise training load analysis method comprising:
Step one, acquiring personal basic information, special sports, sports concurrently, best personal score, sectional score and world record related data of the athlete, and establishing an athlete file;
step two, determining relevant parameters of a training date unit; and a training plan is prepared;
step three, according to different training means, load measurement and achievement of different athletes and other aspects, the actual training load data of the athletes is obtained in a mode of personal recording or group recording; or manually recording, importing electronic equipment, identifying by an artificial intelligence system and the like to obtain relevant training data;
step four, acquiring physiological load data of the athlete in the training process, establishing an index system reflecting physiological and psychological reactions of the athlete and qualitatively evaluating the level of the state bearing the training load; acquiring exercise nutrition, exercise protection and drug use data;
step five, the acquired data are arranged and analyzed, the movement load qualitative analysis is carried out, the load training adjustment is carried out based on the analysis result, and meanwhile, the analysis result is converted into a chart for visual display;
and step six, carrying out mathematical analysis on the training load data of qualitative analysis, judging the training load state and the competitive state born by the athlete, pre-warning over-training, confirming the individualized training scheme of the athlete, establishing training parameter big data of a long-distance training means, and integrating relevant parameters to provide a reasonable training load mathematical control range and a training load qualitative analysis model download.
By combining all the technical schemes, the invention has the advantages and positive effects that: the invention acquires personal basic information, special items, best personal achievements and world record related data of the athlete, and establishes an athlete file; determining relevant parameters of a training date unit, and making a training plan; acquiring actual training load data of athletes; acquiring physiological load data of an athlete in the training process, establishing an index system reflecting physiological and psychological reactions of the athlete and qualitatively evaluating the physical and motor function state level; acquiring exercise nutrition, exercise protection and medicine use data, and assisting in load process analysis; the acquired data are subjected to arrangement analysis, the operation load qualitative analysis of special technical capability training is carried out, the load training adjustment is carried out based on the analysis result, and meanwhile, the analysis result is converted into a chart for visual display; the method comprises the steps of converting qualitative analysis training load data into a lesson load value by applying an operation distance law, an operation intensity law, an operation load principle and a reasonable load principle, and establishing a load process control mathematical model to analyze the training load bearing state of athletes; acquiring accumulated liability load value early warning excessive training or insufficient training, and sharing a personalized training plan adjustment scheme; acquiring a segmented average score and a total score of a special working distance of an athlete and establishing a personalized training means database; integrating the intrinsic mathematical relationship of the parameters such as the common working distance, the working score, the percentage strength, the reasonable lesson load, the lesson specific gravity and the like of the athlete to establish a personalized reasonable lesson load process control paradigm; acquiring long-distance training big data, providing online and offline scientific and technological service for sports teams or athletes, and taking into consideration the development of commercial value; the data acquisition or storage provides a standardized template, and optional, return, batch processing, browsing, printing and sharing function items are set, so that the system functions are more flexible, convenient, visual and intelligent. The invention can more objectively reflect the athletic movement state of the athlete or the movement load bearing state of the personal body-building movement, provides real reference and effective control for scientific movement training and body-building health management, and has wide popularization value and commercial development prospect.
The invention acquires personal basic information, special items, best personal achievements and world record related data of the athlete, and establishes an athlete file; determining relevant parameters of a training date unit; and a training plan is prepared; acquiring actual training load data of athletes; acquiring physiological load data of an athlete in the training process, and establishing an index system and a qualitative assessment grade for reflecting physiological and psychological reactions of the athlete; acquiring exercise nutrition and drug use data; and performing arrangement analysis on the acquired data, performing exercise load analysis, performing load training adjustment based on the analysis result, and simultaneously converting the analysis result into a chart for visual display.
The invention can dynamically change the load statistics of athletes, has strong flexibility function, and is suitable for long-distance competitive exercise training application and long-distance mass body building application; the data calculation mode is close to the practice of exercise training, can more objectively reflect the athletic movement state of athletes or the movement load bearing state of personal body-building movement, and provides real reference and effective control for scientific exercise training and body-building health management.
The invention can more objectively reflect the athletic sports state of the athlete or the sports load bearing state of the personal body-building sports.
The invention can solve the problem of inaccurate analysis result of the motion load statistical analysis method:
the invention provides a concept of 'special exercise technology training ability', and builds a statistical analysis index for long-distance special exercise technology training ability. The difficulty is low, and qualitative analysis, screening and analysis indexes are carried out by referring to the theory of sports training science, sports competition science and the like. And compiling a long-distance exercise training load analysis index system.
The invention provides a concept of 'lesson load' of exercise training, converts the intensity of exercise achievements into a percentage load ratio, and carries out mathematical statistical analysis on actual training load data. The invention is a core part with great difficulty, and needs to compile mathematical statistics index systems such as an operation distance power index table, an operation intensity table, a percent intensity power index table, a reasonable coursework load coefficient table, a reasonable operation times table, a reasonable recovery and rest time table and the like, and analyze and adjust big data timely. Meanwhile, a mathematical statistical analysis formula of indexes such as the working distance, the working intensity, the working load value and the like is compiled, an application program is compiled, and the computer is used for carrying out operation, so that the complexity and the accuracy of manual calculation are solved.
The invention can solve the problems of the generation and development processes of the sports fatigue which can not be reflected in real time:
the invention provides a training load process control concept, and a foot drop point for statistical analysis of the training load is positioned in a process that an athlete actually completes the training load. This is also the core part of the invention, with moderate difficulty. In actual operation, a training load mathematical statistics analysis formula is used for calculating a load value, an operation score and an operation strength of a load process, and the training load state of the athlete is judged by referring to reasonable load meters and physiological and biochemical index test construction, and the possibility of exercise fatigue accumulation is early warned.
The invention can solve the problems that excessive training and sports injury early warning cannot be performed in time:
on the basis of the control of the mathematical analysis training load process, the invention combines with the physiological and biochemical test indexes to judge the motor function state grade epsilon and the recovery coefficient grade mu, correct the training load analysis value and early warn over-training or under-training.
The invention introduces a functional training theory, and timely applies evaluation tools such as a functional action evaluation system (FMS), a selective functional action evaluation System (SFMA), a body basic movement physical fitness test (FCS) and the like to test the functional movement disorder and basic physical fitness of the athlete.
The invention develops a complete training load statistical analysis system by using multidisciplinary knowledge and modern network technology: the method comprises the steps of diagnosing the initial bearing training load state of an athlete, setting and applying the training of the racing plate, collecting the actual training load, qualitatively and statistically analyzing the training load, carrying out mathematical control on the training load process, and making and implementing a training plan. Compared with the prior long-distance sports wearing equipment for supervising the training process, the training load tracking analysis problem of long-distance sports training about what, how and why is done is solved creatively.
The invention applies the current international competition rules and the high-level sport competition and training load data to carry out big data analysis, provides a novel training load statistical analysis method and a load process mathematical control model, and has higher authority and innovation.
The invention can realize tracking and analyzing the actual exercise load bearing state of long-distance athletes or lovers, provide a real reference for making personalized training plans, and make scientific predictions for the performance setting of the participating targets.
The invention uses the physiological and biochemical indexes to reflect the physical function states of long-distance athletes or lovers participating in exercise in a period, combines the functional training theory to realize exercise risk early warning, and ensures the training quality.
The invention uses track and field sports as cases to carry out practical development and inspection, and the mathematical statistical analysis method is scientific and reasonable, can be popularized to long-distance projects such as swimming, off-road, sliding and riding, is suitable for high-level sports training, can be applied to the long-distance sports body-building field because of developing class athlete courseload standards, and shows popularization and application values of the system tool.
The visual on-line long-distance exercise training and functional training guidance functions are hung externally, intelligent support is provided for competitive exercise training, scientific and technological service is provided for exercise protection, and market value is developed.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following description will briefly explain the drawings needed in the embodiments of the present application, and it is obvious that the drawings described below are only some embodiments of the present application, and that other drawings can be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of a long-distance exercise training load analysis system according to an embodiment of the present invention;
in the figure: 1. a player file management module; 2. the training unit setting module; 3. a training plan making module; 4. the actual training load input module; 5. a health exercise management module; 6. training a load statistics module; 7. a lesson load control template; 8. an on-line service module for exercise training; 31. setting a template unit by training means; 32. a unit training plan making unit; 33. a lesson load value and job specific gravity setting unit; 34. a functional training unit; 35. training means setting unit and training planning unit; 41. training a load acquisition unit; 42. a training means acquisition unit; 43. a training load input unit; 51. a physiological and biochemical index monitoring unit; 52. a sports injury and nutrition monitoring unit; 53. a self-training sensation evaluation unit; 61. training a load qualitative analysis unit; 62. training a load routine statistical unit; 63. an athlete individual load adjustment unit; 71. a working process mathematical analysis unit; 72. a load-bearing state judgment unit; 73. a load process control paradigm unit; 711. a working distance law determining subunit; 712. a job intensity law determining subunit; 713. a work load principle determination subunit; 714. determining a subunit by a reasonable load principle; 721. the actual load value calculation subunit and 722 and the statistics unit train the accumulated liability load value subunit in the course of the lesson load; 723. a sub-unit for counting and accumulating liability load values in training; 724. a load state judgment subunit; 725. and (5) correcting the subunit.
Fig. 2 is a schematic diagram of a long-distance exercise training load analysis system according to an embodiment of the present invention.
Fig. 3 is a flowchart of a method for analyzing long-distance exercise training load according to an embodiment of the present invention.
Fig. 4 is a schematic diagram of a long-distance exercise training load analysis method according to an embodiment of the present invention.
Fig. 5 is a flowchart of a method for planning long-distance exercise training according to an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
In view of the problems of the prior art, the present invention provides a long distance exercise training load analysis system, and the present invention is described in detail below with reference to the accompanying drawings.
As shown in fig. 1-2, the long-distance exercise training load analysis system provided by the embodiment of the invention includes:
the training system comprises an athlete file management module 1, a training unit setting module 2, a training plan making module 3, an actual training load input module 4, a healthy exercise management module 5, a training load statistics module 6, a lesson load control module 7 and an on-line training service module 8;
The athlete file management module 1 is used for acquiring athlete basic information, special profile information and international situation data and establishing an athlete file based on the acquired data; the athlete profile includes: name, gender, birth month, height, weight, blood type, hobbies, personality, and physical vigor; the special profile information comprises exercise special training years and best achievements and creation time, place and event names of the exercise special training years and best achievements and creation time, place and event names of main item segmentation achievements and best achievements; the international situation comprises long-distance Olympic project world records, and a segmented average speed rA and a total score RA thereof; the recent best performance of the long-distance project and the sectional average speed rA and the total performance RA thereof;
the training unit setting module 2 is used for carrying out phase division and target training measurement setting on the competition period according to the period theory and the plate training theory, making an overall plan comprising a multi-period of years of training and a multi-period of viscosity training for the phase training plan, and making a target task comprising a target training period, a target training period and a target training day period for the unit training plan;
The training plan making module 3 includes a training means setting template unit 31, a unit training plan making unit 32, a lesson load value and job specific gravity setting unit 33, a functional training unit 34, a training means setting unit, and a training plan unit 35; the training method comprises the steps of setting optional content of training means and making a daily training unit training plan;
the actual training load input module 4 comprises a training load acquisition unit 41, a training means acquisition unit 42 and a training load input unit 43; the training device is used for training load data acquisition, training means adjustment and training data input;
the health exercise management module 5 comprises a physiological and biochemical index monitoring unit 51, an exercise injury and nutrition supervision unit 52 and a self-training feel evaluation unit 53; the method is used for collecting relevant indexes of healthy exercise, supervising exercise risk and judging the functional state grade epsilon and the recovery state coefficient mu of the athlete bearing training load;
the training load statistics module 6 comprises a training load qualitative analysis unit 61, a training load routine statistics unit 62 and an athlete personal load adjustment unit 63; training academic analysis for completing a special skill ability training load; meanwhile, the training purpose, course property, training content, training quantity and training intensity of a training method, training density, training total quantity and segmentation speed of the athlete for a period of exercise training are counted, and a corresponding chart is generated; and performing telemobilization personal load adjustment;
The lesson load control template 7 comprises a working process mathematical analysis unit 71, a load bearing state judgment unit 72 and a load process control paradigm unit 73; the training system is used for integrating special technical capacity training, physical training, technical improvement, functional action training content and training load characteristics of athletes according to a training plan, combining functional states and recovery states, applying a business distance law, a work intensity law, a work load law, a reasonable load principle and a reasonable recovery principle, establishing a mathematical control model of a lesson load process, predicting the rationality of the athletes in class, between classes, in small cycles, in training stages and in competition cycles for bearing training loads and judging the possibility of maintaining or improving the competitive state;
the on-line training service module 8 is used for providing competitive sport state judgment, long-distance sport training guidance, functional training guidance and competition appreciation.
The training plan preparation module 3 provided by the embodiment of the invention comprises:
a training means setting template unit 31 for setting a training means selectable content; the training means optional content includes: date or task, small period special training, daily unit special training, functional state monitoring, special technical action training, functional physical training and physical fitness training;
The date or task comprises training purposes, lesson properties, training contents and training methods;
the small period special training comprises: week course structure, week training times, training total amount, average score, target score, school load value and school specific gravity;
the daily unit special training comprises the following steps: the daily class structure, the working distance, the working average score, the working total score, the training total amount, the working times, the training group number, the training total time, the intermittent time, the working percentage strength, the working load value and the working proportion;
the functional status monitoring includes: target heart rate, process heart rate, immediate after training heart rate, recovery heart rate, process blood lactic acid, post training blood lactic acid, blood urea, creatine kinase, urinary protein, self-sensation;
the specialized technical action training comprises: type, content, method, job measure, total time;
the functional physical training comprises: type, content, method, job measure, total time;
the physical fitness training comprises: type, content, method, job measure, total time;
a unit training plan making unit 32 for making a daily training unit training plan; the daily training unit training program comprises training purposes, course properties, training contents, training methods, training contents, load measurement and state monitoring;
The training purposes include: technical ability, physical ability, game ability, mental ability, and training theory;
the course properties include: aerobic training, mixed oxygen training, speed training, technical training, tactical training, functional action, strength training and adaptability training;
the training content comprises: aerobic special technical ability, special speed endurance, absolute speed, technical action, tactics, strength endurance, explosive force, absolute strength, functional action, psychological adaptability, environmental adaptation, opponent adaptation, field facility adaptation, wearable equipment adaptation;
the exercise method comprises the following steps: continuous training of aerobic special technology, speed repeated training, intermittent training of speed, mixed oxygen variable speed training, functional action cyclic training, general strength cyclic training, rapid strength repeated training, absolute strength repeated training, following tactics, race tactics, wheel tactics, simulated competition, teaching competition and formal competition;
the load metric includes: working distance, working average score, working total score, training total amount, working times, training group number, training total time, intermittent time, working percentage strength, working load value and working specific gravity;
The functional status monitoring includes: target heart rate, process heart rate, immediate after training heart rate, recovery heart rate, process blood lactic acid, post training blood lactic acid, blood urea, creatine kinase, urinary protein, self-sensation;
a lesson load value and job specific gravity setting unit 33 for monitoring a training load process;
a functional training unit 34 for supervising physical dysfunction, ensuring the effectiveness, economy and prevention of motor impairment of motor technical actions;
training means setup and unit training plan unit 35 for providing manual recording and browsing, printing and sharing training plan sample forms.
The actual training load input module 4 provided by the embodiment of the invention comprises:
the training load acquisition unit 41 is used for collecting relevant training data through modes of manual recording, electronic equipment importing, artificial intelligent system identifying and the like, screening index entry reflecting a class load value according to training load setting parameters, providing an importing window and a parameter acquisition sample table, and acquiring work load data; the workload data comprises manual recording, wearing equipment and other intelligent system reading, photographing, gesture analysis SennoGait, physiological and biochemical tests, functional action screening FMS, basic physical ability assessment FCS;
A training means acquisition unit 42 for comparing training plan changes to perform actual completion content adjustment;
a training load input unit 43 for inputting or importing training data actually completed according to a training program into the system; the input mode comprises personal input and group input.
The health exercise management module 5 provided by the embodiment of the invention comprises:
the physiological and biochemical index monitoring unit 51 is used for acquiring physiological and biochemical indexes during and after training and managing and monitoring relevant physiological and biochemical indexes;
a sports injury and nutrition monitoring unit 42 for collecting sports nutrition, sports injury and rehabilitation, drug treatment, and stimulant detection and other relevant data during athlete training;
the self-training sensation evaluation unit 53 is used for collecting self-sensations and body responses of athletes, including fatigue, dysfunction, body pain, injury expression and therapeutic effects, subjected to training load.
The training load statistics module 6 provided by the embodiment of the invention comprises:
the training load qualitative analysis unit 61 is used for qualitatively analyzing the training work load parameters of the special technical ability from the angles of sports training science, sports biology, sports medicine and physical function training theory, counting and classifying, diagnosing the state of the athlete bearing the training load, providing a work load analysis parameter sample table, printing and sharing analysis results; training academic analysis for completing a special skill ability training load; the method is used for analyzing the motion dynamics of special technical action characteristics and completing technical training load; for performing a kinematic biological analysis of the completed specialized skills training load; the functional training analysis is used for carrying out functional training analysis on the functional action training and physical training load; the training device is used for analyzing nutrition, injury and psychological adaptation analysis sports medicine for completing the training load process;
The training academic analysis includes: common operation distance and corresponding average score and total score, main operation average speed and highest speed and standard deviation thereof, main operation best training score and competition score and standard deviation thereof, wing operation average speed and highest speed and standard deviation thereof, variable speed training average score and best score of main operation, variable speed training average score and best score of wing operation, competition operation distance and corresponding average score, total score, time interval, uniform speed operation distance and subsection operation score, total score, variable speed operation distance and subsection operation score, total score, special technical capability training comprising content, means and method, special technical action training comprising content, means and method, physical functional training comprising content, means, method, total time and density; the intermittent training method comprises content and the number, the time of rest, the percentage strength and the class proportion, the repeated training method comprises the content and the number, the time of rest, the percentage strength and the class proportion, the unit class training comprises the purpose, the property, the type, the average total time and the interval time, the week period class comprises the training number, the total time and the class structure, the stage division of the event period comprises the preparation period, the competition period, the transition period and the refinement and measurement thereof, the unit of the total quantity of training and the average result strength, the day, the week, the stage and the event period comprises the physical quality training of the type, the density and the total time, and the physical functional training comprises the type, the density and the total time;
The kinetic analysis includes: stride, stride frequency, stride swing angle, stability, flexibility, economy, gait characteristics, physical characteristics, technical advantages, and technical shortcomings;
the kinetic biological analysis includes: process heart rate, heart rate inflection point, resting heart rate, highest heart rate, lowest heart rate, lactic acid threshold, maximum oxygen uptake, anaerobic threshold, creatine kinase, hemoglobin, blood urea, red blood cells, white blood cells, urine protein, PH change, BMI change, altitude adaptation, temperature humidity adaptation;
the functional training parsing includes: a function action evaluation index system FMS, a selective function action evaluation index system SFMA, a balance ability evaluation YBT and a basic motion physical ability evaluation FCS;
the sports medical analysis includes: motor nutrition characteristics, accumulation and rehabilitation of injury and psychological adaptability;
the training load routine statistics unit 62 is used for counting training purposes, course properties, training contents, training amounts and training intensity, training density, training total amount and segmentation speed of the athlete during a period of sports training, and generating a corresponding chart;
the counting and generating the corresponding chart comprises: training analysis indexes according to the weekly statistical technique capability, and generating a visual chart display by using statistical data; training analysis indexes according to daily statistical technology capability, and generating statistical data into a visual chart for display; training analysis indexes according to the unit statistical technology capability, and generating a visual chart display by using statistical data; daily statistics functional training load analysis indexes, and generating a visual chart display by the statistics data; daily statistics of physiological and biochemical analysis indexes, and generation of a visual chart display by the statistical data;
An athlete individual load adjustment unit 63 for reversibly adjusting and revising the training load data; the training load reversibility adjustment includes, but is not limited to, abnormal data adjustment due to entry errors and reclassification of training means.
The lesson load control module 7 provided in the embodiment of the present invention includes: a work process mathematical analysis unit 71, a load receiving state judgment unit 72, and a load process control pattern unit 73;
the work process mathematical analysis unit 71 includes: a working distance law determination subunit 711, a working intensity law determination subunit 712, a working load principle determination subunit 713, and a reasonable load principle determination subunit 714;
the working distance law determining subunit 711 includes a common working distance, a mathematical relationship between any working distance and a working result, and a power index table of the common working distance; the method is used for processing the relation between the actual working distance and the working score and providing basis for setting a training plan; meanwhile, the method is used for exploring the sensitivity and the adaptability of the operation means of the athlete by qualitatively analyzing the characteristic of the personalized training load of the athlete, and establishing a personalized operation distance and operation achievement index system of the athlete;
The job intensity law determining subunit 712 includes a job achievement intensity, a percentage intensity, a mathematical relationship thereof, and a percentage intensity power index scale; the system is used for monitoring the training load bearing state of the athlete through the operation score, providing basis for setting a training plan, exploring the sensitivity and the adaptability of the operation means of the athlete through qualitatively analyzing the personalized training load characteristics of the athlete, and establishing a personalized operation distance and operation score index system of the athlete;
the workload principle determination subunit 713 includes workload value calculation, workload accumulation principle determination, and workload liability principle determination; for processing the relation between the actual work load of a player at a certain distance and the load ratio generated by a competition with full strength at the distance, and converting the work percentage strength into the actual work load specific value (q B/A )；
The workload value calculation includes: calculating a master distance workload value and a non-master distance workload value;
the workload accumulation principle determination includes: the load value is used for statistically analyzing the continuous operation of the athlete;
the work load accumulation principle is determined, and is used for monitoring the load state change born by the athlete in the continuous work process through the work load value;
The work load liability principle determination comprises a lesson load value, a liability load principle, an inter-lesson liability load principle and an accumulated liability load principle and application thereof; the system is used for monitoring the load state change of the athlete in the continuous operation process and early warning the occurrence and development of excessive training through the operation load value;
the reasonable load principle determination subunit 714 includes determining a reasonable lesson load value for the rank athlete and calculating the number of lesson load operations; the early warning load measurement standard is used for monitoring the rationality of the player class target training load through the class load value and establishing excessive training; providing a standard for setting training main class load or full strength load class;
the method comprises the steps of determining international level reasonable lesson load values, wherein the international level reasonable lesson load values are used for calculating reasonable lesson load values of athletes of different levels at any distance based on an international level reasonable lesson load meter, a level athlete reasonable lesson load meter and a level athlete working distance reasonable lesson load meter;
the number of the lesson load operations comprises: calculating reasonable operation times of the courseload by calculating reasonable operation times of the operation distance;
the load-bearing state determination unit 72 includes: the system comprises a lesson load process actual load value calculating subunit 721, a statistics unit training accumulated liability load value subunit 722, a statistics week training accumulated liability load value subunit 723, a load state judging subunit 724 and a correction subunit 725; the method is used for judging the actual state of the athletes in the course of carrying training load according to the occurrence process of the actual operation score strength, the accumulated load value and the accumulated liability load value; the method comprises the steps of providing a training plan adjustment scheme for early warning over training or under training;
The lesson load process actual load value calculation subunit 721 includes: the training unit is used for planning and calculating reasonable operation achievement R/R of the operation distance according to the training unit; the training unit is used for planning and calculating the reasonable operation achievement R/R percentage strength of the operation distance according to the training unit; the training unit is used for planning and calculating reasonable operation achievement R/R reasonable load values of the operation distance according to the training unit; the device is used for calculating an accumulated load value of the operation distance speed change operation score R/R according to the training unit plan; the system is used for calculating a constant-speed operation achievement R/R accumulated load value of the operation distance according to the training unit plan; the combined working distance working score R/R and the accumulated load value are calculated according to the training unit plan; the accumulated liability load value is used for calculating the combined working distance working score R/R in the class according to the training unit plan; the method is used for calculating reasonable operation times of the combined operation distance in the class according to the training unit plan; for calculating a week accumulation load value according to the training week plan; the method comprises the steps of calculating a week accumulation liability load value according to a training week plan; the method is used for calculating reasonable operation results of the operation distance according to the percentage strength and the operation means proportion; the device is used for calculating reasonable percentage strength of the working distance according to the working score and the specific gravity of the working means; the method is used for calculating reasonable operation scores of the operation distance according to the load value;
The statistics unit training accumulated liability load value subunit 722 includes: the statistical unit is used for training and accumulating liability load values and displaying a visual chart;
the statistical weekly training accumulated liability load value subunit 723 includes: the method is used for counting the training accumulated liability load values and displaying a visual chart;
the load state determination subunit 724 includes: the system is used for judging the training load bearing state of the athlete unit by combining the function detection indexes;
the correction subunit 725 includes: the training program load measurement is used for correcting the weekly training program load measurement and providing a working means correction suggestion;
the load process control paradigm unit 73 includes: the training method comprises training means setting, unit training classes and lesson training plan making of week period; the system is used for systematic analysis of the course control of the training load of the lesson; the training program sample preparation table is used for storing training load control success cases and mathematical analysis models thereof, and providing, printing and sharing the mathematical control training load.
As shown in fig. 3 to 4, the method for analyzing long-distance exercise training load provided by the embodiment of the invention includes:
s101, acquiring relevant data of personal basic information, special sports, sports concurrently, best personal score, sectional score and world record of the athlete, and establishing an athlete file;
S102, determining relevant parameters of a training date unit; and a training plan is prepared;
s103, acquiring actual training load data of the athlete by adopting a mode of personal recording or group recording according to different training means, load measurement and achievement and other aspects of the athlete; or manually recording, importing electronic equipment, identifying by an artificial intelligence system and the like to obtain relevant training data;
s104, acquiring physiological load data of the athlete in the training process, establishing an index system reflecting physiological and psychological reactions of the athlete and qualitatively evaluating the level of the state bearing the training load; acquiring exercise nutrition, exercise protection and drug use data;
s105, performing arrangement analysis on the acquired data, performing qualitative analysis on the movement load, performing load training adjustment based on the analysis result, and simultaneously converting the analysis result into a chart for visual display;
s106, carrying out mathematical analysis on the training load data of qualitative analysis, judging the training load state and the competitive state born by the athlete, pre-warning over-training, confirming the individualized training scheme of the athlete, establishing training parameter big data of a long-distance training means, and integrating relevant parameters to provide a reasonable training load mathematical control range and a training load qualitative analysis model download.
The technical effects of the present invention will be further described with reference to specific examples.
Example 1:
the invention develops software (hereinafter referred to as a system) of a long-distance exercise training load analysis system from a long-distance exercise training line through common efforts for two years. At present, long-distance coaches and scientific researchers in Hunan parts are formally put into use. According to the requirements of the national management center, the early version is put into the running team for use in 11 th 2010.
The system software main program is that a training unit of a player file management template (1) is provided with a template (3), a training plan is made up of a template (4), an actual load is input into a template (5), a healthy exercise management template (6), a training load statistics template (7), a lesson load process control template (8) and an online service template (9) are withdrawn from the system.
Nine parts and the lower zipper thereof.
The development process and application of the present effort will be described below in terms of the order of operation of the "system".
1. Athlete file management module
For creating athlete profiles. Comprising the following steps:
basic information: name, gender, year and month of birth, height, weight, blood type, hobbies, personality, and physical vigor.
Special profile: training years and best results of sports, and creation time, place and event thereof, main item segmentation results, and also training years and best results, and creation time, place and event name thereof, etc.
International situation: long-distance Olympic project world record and segmented average speed r thereof A Sum of achievements R A The method comprises the steps of carrying out a first treatment on the surface of the Near term best performance of long distance project and its piecewise average speed r A Sum of achievements R A 。
The operation is as follows: personal information setting-popup file forms-input content-save-browse-print-share; linking training settings; return to homepage
2. Training unit setting template
The method is used for dividing the period of the event and setting target training metrics according to the period theory and the plate training theory. And making an overall plan for the stage training plan, and making a target task for the unit training plan. Comprising the following steps:
training period (years): years plate and target training quantity and target training score thereof
Annual training multi-stage (annual): annual plate and target training quantity and target training score thereof
Target training Zhou Zhouqi (stage): event plate and target training quantity and target training score thereof
Target training period (period): small period plate, target training amount and target training score
Target training day period (unit): daily unit plate, target training amount and target training score
The operation is as follows: selecting each period setting-input content-save, etc.; linking training plan preparation-date
3. Training plan making template
Training means setting template
For setting training means selectable content. Comprising the following steps:
targets or tasks: training purposes, nature of lessons, training contents, training methods and the like;
training special for a small period: week course structure, week training times, training total amount, average score, target score, lesson load value, lesson specific gravity and the like;
daily unit special training: the daily class structure, the working distance, the working average score, the working total score, the training total amount, the working times, the training group number, the training total time, the intermittent time, the working percentage strength, the working load value, the working proportion and the like;
functional state monitoring: target heart rate, process heart rate, immediate after training heart rate, recovery heart rate, process blood lactic acid, post training blood lactic acid, blood urea, creatine kinase, urine protein, self-sensation, and the like.
Training special technical actions: type, content, method, job measure, total time, etc
Functional physical training: type, content, method, job measure, total time, etc
Physical fitness training: type, content, method, job measure, total time, etc
Unit training plan formulation
The daily training unit is used for making a training plan. Comprising the following steps:
Setting training purposes: very excellent technical ability, very excellent physical ability, very excellent competition ability, very excellent psychological ability, very excellent training theory, etc.;
properties of the setup class: aerobic training, mixed oxygen training, speed training, technical training, tactical training, functional action, strength training, adaptability training and the like;
setting training content: aerobic special technical ability, special speed endurance, absolute speed, technical action, tactics, strength endurance, explosive force, absolute strength, functional action, psychological adaptability, environmental adaptation, opponent adaptation, field facility adaptation, wearable equipment adaptation and the like;
setting an exercise method: continuous training of aerobic special technology, speed repeated training, intermittent training of speed, mixed oxygen variable speed training, functional action cyclic training, general strength cyclic training, rapid strength repeated training, absolute strength repeated training, following tactics, race tactics, wheel tactics, simulated competition, teaching competition and formal competition;
setting exercise content: selecting and formulating according to training content and training method;
setting a load measure: working distance, working average score, working total score, training total amount, working times, training group number, training total time, intermittent time, working percentage strength, working load value, working proportion and the like;
Functional state monitoring: target heart rate, process heart rate, immediate after training heart rate, recovery heart rate, process blood lactic acid, post training blood lactic acid, blood urea, creatine kinase, urine protein, self-sensation, and the like.
The operation is as follows: a training small period form-selecting unit is popped up; setting training content of a unit; very good generating plan very good browsing-printing plan; sharing the plan; returning to a homepage; linking actual load entry
4. Actual load entry template
Training load acquisition
The system is used for acquiring the workload data according to the training planning means. Including manual recording, intelligent system reading (e.g., wearable device, race platform), photography, gesture analysis SennoGait, physiological and biochemical tests, functional action screening FMS, basic physical ability assessment FCS, etc.
Training means adjustment
For actually completing the content adjustment against training program variations.
Training load entry
For training data entry or importing systems that are actually completed according to the training program. Job performance intensity the total job distance performance and hundred meter average performance (0:11:10.0/hundred meter) are expressed, the strength endurance is expressed in total time, the other strength exercises are expressed in kilograms per time, and the functional training is expressed in total time. The input mode comprises personal input and group input.
The operation is as follows: the excellent selecting athlete importing equipment acquires data, adjusts training data of training program forms, generates an input interface, generates/browses/prints/shares/visualizes a training data chart
5. Sports health management template
The method is used for collecting relevant indexes of healthy exercise, supervising exercise risk and judging the functional state grade epsilon and the recovery state coefficient mu of the athlete bearing training load. Including physiological and biochemical indexes, sports injury, sports nutrition, functional action evaluation and the like.
Physiological and biochemical index monitoring
Is used for obtaining the physiological and biochemical indexes during and after training and implementing management by referring to the athlete exercise training function monitoring index system.
Sport injury and nutrition supervision
The method is used for collecting data of sports nutrition, sports injury and rehabilitation, drug treatment, stimulant detection and the like in the training process of athletes.
Self-training sensory evaluation
Is used for collecting self-feeling and body response of athletes under training load, including fatigue degree, dysfunction, body pain, injury expression, therapeutic effect, etc.
The operation is as follows: and selecting a very good player to open a test table, recording data, and generating/printing/sharing a data chart.
6. Training load statistics template
Qualitative analysis of training load
Training study analysis for completing a expertise competence training load, comprising:
common working distance and corresponding average score and total score
Average speed and highest speed of main operation and standard deviation thereof
Main item best training score and competition score and standard deviation thereof
Average speed and maximum speed of wing operation and standard deviation thereof
Average and best speed change training results of main operation
Average and best speed change training performance of wing operation
Match working distance and corresponding average score, total score and time interval
Constant speed working distance and segmented working score, total score (less than 1 standard deviation of average speed)
Speed change working distance and sectional working score, total score (greater than 1 and less than 2 average speed standard deviation)
Training special technical capability: content, means and method
Training special technical actions: content, means and method
Physical functional training: content, means, methods, total time, density
The intermittent training method comprises the following steps: content and its number of times, time of rest, percentage strength and class specific gravity
The training method is repeated: content and its number of times, time of rest, percentage strength and class specific gravity
Training unit lessons: purpose, nature, type, average total time and interval time
Week period coursework: training times, total time and class structure
Stage division of the event period: preparation period, competition period, transition period, refinement and measurement.
Unit, day, week, phase, event period: total amount of training, average score strength
Physical fitness training: type, density, total amount of time
Physical functional training: type, density, total amount of time
A kinetic analysis for specialized technical action features and completion of technical training load, comprising:
stride length
Step frequency
Pedal swing angle
Stability of
Flexibility of
Economical efficiency
Gait features
Physical characteristics
Technical characteristics of
Technical advantage
Technical disadvantage
A kinematic biological analysis for completing a expertise competence training load, comprising:
process heart rate
Heart rate inflection point
Resting heart rate
Highest heart rate
Minimum heart rate
Lactic acid threshold
Maximum oxygen uptake
Anaerobic threshold
Creatine kinase CK
Hemoglobin pigment
Blood urea
Erythrocyte cell
White blood cells
Urine protein
pH change
BMI change
Altitude adaptation
Temperature humidity adaptability
Functional training parsing for completing functional action training and physical fitness training load, comprising:
FMS (functional action evaluation index system)
SFMA (Small form factor memory) of selective function action evaluation index system
Balance ability assessment YBT
Basic athletic performance assessment FCS
Is used for analyzing nutrition, injury and psychological adaptation analysis sports medicine for completing the training load process.
Sports nutrition characteristics
Accumulation and rehabilitation of injury
Psychological adaptability
The operation is as follows: the excellent recording unit of the excellent select athlete analyzes the excellent generation/browsing/printing/sharing of the content: actual training load data chart/qualitative analysis report printing report sharing report linking courseload statistics
Training load routine statistics
The method is used for counting a certain training purpose, a certain class property, a certain training content, a training amount and training intensity of a training method, training density, training total amount and segmentation speed of a sportsman for a period of sports training, and generating a corresponding chart.
Training analysis indexes according to the weekly statistical technique capability, and generating statistical data into a visual chart for display
Training analysis indexes according to daily statistical technology capability, and generating statistical data into a visual chart for display
Training analysis indexes according to the unit statistical technology capability, and generating statistical data into a visual chart for display
Daily statistics functional training load analysis index and generating statistical data into visual chart display
Daily statistics of physiological and biochemical analysis indexes and generation of statistical data into a visual chart for display
7. Lesson load control template
The training system is used for integrating special technical capacity training, physical training, technical improvement, functional action training content and training load characteristics of athletes according to a training plan, combining functional states and recovery states, applying business distance laws, operation intensity laws, operation load laws, reasonable load principles and reasonable recovery principles, establishing a mathematical control model of a lesson load process, predicting rationality of the athletes in class, between classes, small period, training stage and competition period bearing training load and judging possibility of maintaining or improving competitive states. This is an advanced step in long distance training load analysis and is also a core part of the present invention. The lesson load control model comprises:
mathematical analysis of work processes
Law of working distance
The method is used for processing the relation between the actual working distance and the working score and providing basis for setting a training plan. The power index table comprises a common operation distance, and a mathematical relation formula of any operation distance and operation achievement. The method aims at exploring the sensitivity and the adaptability of the working means of the athlete by qualitatively analyzing the characteristics of the personalized training load of the athlete and establishing a personalized working distance and a working score index system of the athlete.
The operation is as follows: click calculation formula-input related parameters-generate result-hold to load bearing state judgment table
Law of working distance and mathematical relationship thereof
r B ＝r A (L B /L A ) K Or R is B ＝R A (L B /L A ) 1+K
Working distance power index K and mathematical relationship thereof
K i/A ＝K B/A +(lnL i -lnL B )/(lnL c -lnL B )(K c/A -K B/A )
Or K c/B ＝ln((L c /L A ) K c/A /(L B /L A ) K B/A )/ln(L c /L B )
Athlete personalized working distance and working score index system
The horizontal working distance and working score relation of the current-stage olympic games and the like are analyzed through big data.
Law of operation intensity
The training system is used for monitoring the training load bearing state of the athlete through the work score and providing basis for setting a training plan. The method comprises the steps of operation achievement intensity, percentage intensity, a mathematical relation formula of the percentage intensity and a percentage intensity power index scale. The method aims at exploring the sensitivity and the adaptability of the athlete working means by qualitatively analyzing the characteristics of the individual training load of the athlete and establishing an individual working distance and working score index system of the athlete.
The operation is as follows: click calculation formula-input related parameters-generate result-hold to load bearing state judgment table
Percent strength
Main item operation score strength relation type
r x(A) ＝r 1.0(A) (x％) -K x(A) Or R is x(A) ＝R 1.0(A) (x％) -K x(A)
Performance intensity relationship for non-subject jobs
r x(B) ＝r 1.0(A) (L B /L A ) K B/A (x％) -K x(B) Or R is x(B) ＝R 1.0(A) (L B /L A ) 1+K B/A (x％) -K x(B)
Percent strength ratio
Master job performance and percent strength relationship:
x％＝(r x(A) /r 1.0(A) ) -1/K x(A) Or x% = (R x(A) /R 1.0(A) ) -1/K x(A)
Non-master job performance and percent strength relationship:
x％＝(r x(B) /r 1.0(A) ) -1/K x(B) (L B /L A ) (K B/A /K x(B) )
or x% = (R x(B) /R 1.0(A) ) -1/K x(B) (L B /L A ) (1+K B/A /K x(B) )
Percent strength power index
Percent strength power index for main operation
The x% power index of the main job is equal to the power index K of the reciprocal job distance B/A For example, operating 100 meters main item with 50% main item strength, K 0.5(1 ) The functional index of (2) is equal to the power index K of 200 m working distance 2/1 Look-up table can know K 2/1 )
Non-master job percent intensity power index relationship:
K x"(A) ＝K x(A) +{(ln(x″％)-ln(x％))/(ln(x`％)-ln(x％))}(K x`(A) -K x(A) )
or K x(C) ＝ln((L c /L A ) K c/A /(L c /x％L A ) K c/x,A )/ln(x％)
Percent strength grade
Workload intensity classification in actual training
Principle of work load
The method is used for processing the relation between the actual work load of a certain athlete at a certain distance and the load ratio generated by taking part in a competition with full strength at the certain distance. Including workload values, workload accumulation principles, workload liability principles, workload accumulation liability principles, etc. Is intended to convert the intensity of the job percentage into an actual workload specific value, i.e. a workload value (q B/A ) The ratio of the percent intensities ((x%) a) equivalent to the working distance of two by two.
The operation is as follows: click calculation formula-input related parameters-generate result-hold to load bearing state judgment table
Calculation of workload value
Master distance workload value
q A/A ＝x％＝(r x(A) /r 1.0(A) ) -1/K x(A) Or q A/A ＝x％＝(R x(A) /R 1.0(A) ) -1/K x(A)
Non-master distance workload value
q B/A ＝(r x(B) /r 1.0(A) ) -1/K x(B) (L B /L A ) (K B/A /K x(B) )+J Or (b)
q B/A ＝(R x(A) /R 1.0(A) ) -1/K x(B) (L B /L A ) (1+K B/A /K x(B) )+J (J＝0.3544)
Principle of accumulation of workload
The method is used for statistically analyzing the load value of continuous operation of the athlete. The load value of the whole continuous operation process is equal to the sum of the load values generated by each segment operated in isolation to be respectively divided by 1+J power and then multiplied by l+J power over a certain distance, whether the full strength score or a certain strength score is used. I.e. the principle of continuous workload accumulation. The training method aims at grasping the rule of increasing training load values and is applied to competition tactical design.
Mathematical relationship of workload accumulation
q (a+b)/A ＝(q a/A 1/1+J +q b/A 1/1+J ) 1+J Or (b)
Mathematical relationship of uniform intensity workload accumulation
q nl/A ＝n 1+J q l/A (n l segment unit Length)
Principle of increasing work load
For monitoring load-bearing state changes of athletes during continuous operation by means of work load valuesAnd (5) melting. In the continuous operation of athletes, with the increase of the operation distance or the continuous operation of insufficient rest time for multiple times, the actual load value of the unit distance is larger than the load value of the unit distance, and the larger value is defined as the operation load cumulative load value (P a→b/A ). For example, a player running L continuously b The actual load value generated by this distance minus the individual run L b The load value generated by this distance is the cumulative load value without a break time.
P a→b/A ＝q a→b/A -q b/A Or q a→b/A ＝q b/A +P a→b/A
Operational load increment mathematical relationship
P a→b/A ＝(q a→b/A 1/1+J -q b/A 1/1+J ) 1+J -q a/A -q b/A
P (a+b)→c/A ＝(q a/A 1/1+J +q b/A 1/1+J +q c/A 1/1+J ) 1+J -(q a/A 1/1+J +q b/A 1/1+J ) 1+J -q c/A
Constant-speed equidistant operation load cumulative mathematical relationship
Full course actual load value
q a/A ＝q b/A ＝q c/A ＝……＝q n/A ＝q i/A ，q (a+b+c+…+n)/A ＝n 1+J q i/A
Nth segment actual load value
q (a+b+c+…+(n-1))→n/A ＝[n 1+J -(n-1) 1+J ]q i/A
N-th segment cumulative load value
p (a+b+c+…+(n+1))-n/A ＝[n 1+J -(n-1) 1+J -1]q i/A
Therefore, the constant-speed equidistant whole-course work load value increases along with the unit work distance according to the multiplying power of the power of 1+J. The actual load value of the nth section of the operation is calculated according to [ n ] along with the unit distance 1+J -(n-1) 1+J The multiplying power is increased; the cumulative load value of the nth section of the operation is calculated according to [ n ] along with the unit distance 1+J -(n-1) 1+J -1 ] increase in magnification.
Therefore, the principle of workload accumulation is mainly applied to guiding speed change training and tactical capability training.
Principle of liability of school load
The method is used for monitoring the load state change of the athletes in the continuous operation process through the lesson load value and early warning the occurrence and the development of excessive training. The method comprises the following steps of a lesson load value, a liability load principle, an inter-lesson liability load principle and an accumulated liability load principle and application thereof.
The lesson load value refers to the sum Q of the load value and the cumulative load value generated by adopting different operation intensity, operation modes and various operation modes. After the athlete has gone through the last training session, the organism is not fully recovered, and the next training session is performed in the presence of a loading effect, and the partial loading value that is not recovered is called the liability loading value (Q T ). Actual load value (Q ∈q) obtained by adding the liability load value and the new work load value according to the load accumulation principle n+1 ) The load value which has not been recovered after a certain time is called accumulated liability load value (Q ∈ Tn+1 )。
Relation type of load values in class
The whole lessons are provided with m groups of different operation means, and each group comprises n operation modes of various equal intensity or variable intensity, enough time or insufficient time, and the like. With q i And p i-1 The work load value and the cumulative load value of a certain means are shown.
When the total load value of the lessons is monitored, the method further comprises the step of accumulating the load value, the step of accumulating the load value of the liabilities and the step of accumulating the load value of the liabilities.
Training recovery time relations
In practical training, the smaller the work load value, the smaller the effect of the organism is caused, the shorter the recovery time is needed, the larger the exercise load is, the larger the load effect is, and the longer the recovery time is. The time T required for training recovery without special changes in the environment and other conditions Q Is proportional to the magnitude of the workload value and inversely proportional to the functional state coefficient epsilon of the organism.
εT Q /Q＝T h /Q h Or T Q /＝(T h /εQ h )·Q
Load relation of school liabilities
According to liability load Q T The method is defined that the speed and the intensity of human body function recovery are uniformly carried out in a reasonable load range under the premise of no special change in the whole recovery process after the exercise training stimulation. That is, the load Q of liability is only required to have a certain recovery capacity in the unit time T T Expressed by a mathematical formula:
Q T ＝Q(1-T/T Q )，T Q ＝(T h /εQ h )·Q
Q T ＝Q[1-T/((T h /εQ h )·Q)]＝Q(1-εQ h /T h T/Q) (coefficient of restitution μ=epsilonq) h /T h )
Q T ＝Q(1-μ·T/Q)
Q T ＝Q-μ·T
Accumulating liability load relation
The first class load value of the athlete is Q 1 After training of (1) a recovery time T 1 There is a liability load value Q T1 In the case of (2), the second load value is Q 2 Training of (i.e. the presence of a load value Q) T1 In the case of continuous operation, the actual load value (Q ∈ 2 ) Accumulated according to the load accumulation principle.
Q↑ 2 ＝(Q T1 1/1+J +Q 2 1/1+J ) 1+J ，Q T1 ＝Q 1 -μ·T 1
If the second class load value is Q 2 Recovery time T after training 2 And the load value of accumulated liability is Q ∈ T2 ＝Q↑ 2 -μT 2 The method comprises the steps of carrying out a first treatment on the surface of the If the recovery time T passes 2 Then the third load value is Q 3 The accumulated load value and the accumulated liability load value at the end of the training are:
Q↑ 3 ＝(Q↑ T2 1/1+J +Q 3 1/1+J ) 1+J ，Q↑ T3 ＝Q↑ 3 -μ·T 3
mathematical relation of accumulated load in class
Q↑ n ＝(Q↑ Tn-1 1/1+J +Q n 1/1+J ) 1+J
Mathematical relationship of accumulated liability load in lessons
Q↑ Tn ＝Q↑ n -μ·T n
Principle of reasonable load
The method is used for monitoring the reasonability of the player lesson target training load through the lesson load value and establishing an over-training early warning load measurement standard. The method comprises the international level reasonable lesson load value, the level athlete reasonable lesson load value, the reasonable lesson times calculation principle and the like. Aims to provide a standard for setting training main class load or full strength load class.
Reasonable value of the load of the lesson
The common adherence criteria of the current international and domestic competition arrangement are the requirements of the current international and domestic competition arrangement system on the daily load capacity of athletes, are large enough and can be competent and effectively recovered, can be considered as reasonable load of training lessons, and the number of times of the competition born by different players per day can be considered as reasonable lesson load value.
International level reasonable school load meter
International level athlete reasonable school load meter
| Sports item | 100m | 200m | 400m | 800m | 1500m | 3000m | 5000m | 10000m | …… | 42.195m |
| Reasonable load value | 4.000 | 3.129 | 2.447 | 1.914 | 1.523 | 1.198 | 1.000 | 0.782 | …… | 0.470 |
Class athlete reasonable school load meter
The international level reasonable lesson load measure is a reasonable load value that an athlete with an international level has the capacity to bear, and the lower the level, the smaller the capacity to bear the load. So that the reasonable lesson load capacity of the players of other levels should be equal to the international advanced level of player's reasonable lesson load capacity multiplied by a corresponding factor d, then Q d ＝d×Q 1.0 According to the player's grade system, the grade player has reasonable class load value corresponding to international level Q 1.0 Sports health care bar Q 0.9 First-order Q 0.8 Second-order Q 0.7 Three-stage Q 0.6 Teenager group A Q 0.5 Teenager group B Q 0.4 And child athlete Q 0.3 . Using formula Q d ＝d×Q 1.0 Reasonable load class meters for athletes of different grades can be calculated.
Class athlete reasonable school load meter
Class athlete working distance reasonable class load meter
According to the current competition project arrangement rules, different players can bear the competition times per day, namely reasonable class load value Q xh 。Q Ah Represents the distance L A Reasonable class load value, Q Bh Represents the distance L B Is a reasonable class load value for the main item.
m A q A ＝m B q B ＝M c q c ＝……＝M，m A /m B ＝q A /q B ,
m A /m B ＝q A /q B ＝(L A /L B ) J ,m B ＝m A (L A /L B ) J
Q Bh ＝m B ,Q Ah ＝m A
Q Bh ＝Q Ah (L A /L B ) J
From this, reasonable lesson load values for athletes of different classes at any distance can be calculated. And (3) establishing a reasonable class load value table of athletes of different grades at different distances.
Reasonable class load operation times calculation relation
Reasonable operation times of operation distance
For a distance, the percent strength ratio of a particular job is the load value for that distance. The reasonable operation times at the distance is n h Or reasonable intensity of operation (x%) h 。
Q h ＝n h× (x％) h
n h ＝Q h /(x％)
Or (x%) h ＝Q h /n
n and x% are the percentage values of the operation times and the operation intensity respectively; n is n h (x%) h reasonable number of lesson loads and percent intensity ratio; q (Q) h Reasonable class load value.
Reasonable number of operations of class load
In practice, few lessons are singly trained by taking a certain distance as a training means, but a plurality of lessons are comprehensively trained by taking a plurality of training means, and in this case, the reasonable load times of a certain training means can be calculated only by determining the specific gravity of the training means in the lesson. Let a certain means be the specific gravity β in the class.
n h ＝Q h /x％×β，(x％) h ＝Q h /n×β，
The operation is as follows: click calculation formula-input related parameters-generate result-hold to load bearing state judgment table
Load bearing status determination
Actual load value calculation in course of lesson load
Calculating reasonable operation achievement R/R of the operation distance according to the training unit plan;
calculating reasonable operation achievement R/R percentage strength of operation distance according to training unit plan
Calculating reasonable load value of reasonable operation result R/R of operation distance according to training unit plan
Calculating the R/R accumulated load value of the working distance variable speed working result according to the training unit plan
Calculating the R/R accumulated load value of the constant-speed operation result of the operation distance according to the training unit plan
Calculating the combined working distance working score R/R and the accumulated load value in class according to the training unit plan
Calculating accumulated liability load value of combined working distance working score R/R in class according to training unit plan
Calculating reasonable operation times of combined operation distance in class according to training unit plan
Calculating week accumulated load values according to a training week plan
Calculating a weekly accumulated liability load value according to a training weekly plan
Calculating reasonable operation results of the operation distance according to the percentage strength and the specific gravity of the operation means
Calculating reasonable percentage strength of the working distance according to the working score and the specific gravity of the working means
Calculating reasonable operation results of the operation distance according to the load value
The statistics unit trains and accumulates liability load values and displays visual charts
Counting week training accumulated liability load value and making visual chart display
Judging the load bearing state of the training of the athlete unit by combining with the function detection index
Correcting the weekly training plan load measure and proposing a working means correction proposal
Load process control paradigm
The system is used for systematically analyzing the course control of the training load of the lessons, and comprises training means setting, unit training lessons, and the establishment of a training plan of the lessons of a week period.
Reasonable lesson training task
The main task is as follows: improving the special technical ability of athletes; develop physical quality and improve exercise specific technology.
The improvement of the athlete's special skills should be trained with reasonable lesson load and a restorative activity or rest should be scheduled the third day after such lesson training.
Training to develop physical fitness and improve exercise skills is best achieved with 50% load values corresponding to reasonable load lessons. The training lesson can be basically recovered after 24 hours, and training can not be performed on the premise of excessive fatigue.
Unit class arrangement paradigm
The target sprint runner has the score of 10' 4, and the main operation means of a training class are shown in the following table, and the reasonable operation times of various operation means are obtained.
| Working means | Intensity of work% | Specific gravity beta in the class |
| n 0.3 Running at x 30 m | 20％ | 25％ |
| n 0.5 Run at x 50 meters | 25％ | 25％ |
| n 1.2 Running at x 120 m | 40％ | 50％ |
Solution: running 100 meters with 10"4 players corresponds to a fitness level with a main item distance of 3.60 for reasonable lesson load values and number of jobs at 30 meters, 50 meters, 120 meters distances.
Q Bh ＝Q Ah (L A /L B ) J
Q 0.3h ＝q 1h (1/0.3) 0.3544 ＝3.6×(1/0.3) 0.3544 ＝5.52
n h ＝Q h /x％×β
n 0.3h ＝Q 0.3h 20% ×25% =6.9 times
Q 0.5h ＝q 1h (1/0.5) 0.3544 ＝3.6×2 0.3544 ＝4.6
n 0.5h ＝Q 0.5h 25% ×25% =4.6 times
Q 1.2h ＝q 1h (1/1.2) 0.3544 ＝3.6×0.833 0.3544 ＝3.38
N 1.2h ＝Q 1.2h /40% ×50% =4.22 times
Since the number of jobs can only be an integer, a reasonable number of jobs is
| Working means | Intensity of work% | Specific gravity beta in the class |
| 7X 30 meter running start | 20％ | 25％ |
| Run at 5X 50 meters | 25％ | 25％ |
| Running 4X 120 m | 40％ | 50％ |
Lesson load values for main items
q B/A ＝x％×(L B /L A ) J
∑q 0.3/1 ＝7×0.2×(0.3/1) 0.3544 ＝0.915
∑q 0.5/1 ＝5×0.25×(0.5/1) 0.3544 ＝0.975
∑q 1.2/1 ＝4×0.4×(1.2/1) 0.3544 ＝1.707
Therefore, the total load value 3.597 of the current school plan is 3.60 which is more reasonable in the school load value, and the current school plan accords with reasonable load operation.
The sportsmen 400 m in the number have a competitive level of 0:46.0, and the following main operation means are adopted in a day to obtain reasonable percentage strength and operation results.
Solution: the athlete has 400 m level belonging to domestic health level athlete, the grade coefficient is 0.9, and the table is checked Q 1.2h ＝3.38，Q 2h ＝2.81,Q 4.2h =2.15, according to the formula,
(x％) h ＝Q h /n×β
(1)(x％) 1.2h ＝3.38×0.2/4＝0.169
the percent strength score is according to the formula:
R x(1.2) ＝R 1.0(A) (L 1.2 /L 4 ) 1+K 1.2/4 (x％) -K x(1.2)
＝0:46.0×0.3 1.07950 ×0.169 -0.115
＝0:46.0×0.279×1.227＝0:15:24
(2)(x％) 2h ＝2.81×0.3/4＝0.211
R x(2) ＝R 1.0(A) (L 2 /L 4 ) 1+K 2/4 (x％) -K x(2)
＝0:46.0×0.3 1.1492 ×0.169 -0.1850
＝0:46.0×0.454×1.0292＝0:21:29.6
(3)(x％) 2h ＝2.15×0.5/2＝0.5375
R x(4.2) ＝R 1.0(A) (L 4.2 /L 4 ) 1+K 4.2/4 (x％) -K x(4.2)
＝0:46.0×1.05 1.1904 ×0.538 -0.2216
＝0:46.0×1.0598×1.147＝0:55:55
therefore, the obtained reasonable strength and reasonable result are shown in the table
Therefore, only one training lesson is required to select a lesson load value, the percentage strength of the training means can be confirmed firstly, or the number of times of the operation means of the percentage strength can be confirmed firstly, and the training load process can be controlled.
Week cycle class arrangement paradigm
The sum of the weekly program load values of a certain 800M running master is 6.50, and the training scheme is as follows:
suppose that the pre-planned athlete is not under liability load and has the ability to resume reasonable load lessons (their load value 1.914) for 48 hours. The accumulated liability load value before training the two schemes to the next monday to execute the new training program is calculated.
Solution: assuming that the training session is performed at the same time in the morning (or afternoon) every day, that is, the recovery time between the classes is 24 hours (strictly speaking, the time spent on the job itself should be deducted), the recovery coefficient is calculated first:
according to the formula: q ≡ Tn ＝Q↑ n -μ·T n
μ＝εQ h /T h (Q h ＝1.914,T h =48 hours, epsilon=1.0
μ＝1×1.914/48＝0.0399
Then, the accumulated liability load value of scheme 1 is as follows:
the accumulated liability load value for scheme 2 is as follows:
8. on-line services for athletic training
The method is used for judging the athletic movement state, guiding long-distance exercise training, guiding functional training and enjoying competition, and considering the development commercial value.
The invention is a dynamically changing operation tool, has stronger flexibility and function, gradually approaches to training practice in a data calculation mode, and also reflects the athletic status of athletes more objectively.
The foregoing is merely illustrative of specific embodiments of the present invention, and the scope of the invention is not limited thereto, but any modifications, equivalents, improvements and alternatives falling within the spirit and principles of the present invention will be apparent to those skilled in the art within the scope of the present invention.
Claims (4)
1. A long-distance exercise training load analysis method, characterized in that the long-distance exercise training load analysis method is implemented based on a long-distance exercise training load analysis system, the long-distance exercise training load analysis method comprising:
step one, acquiring personal basic information, special sports, sports concurrently, best personal score, sectional score and world record related data of the athlete, and establishing an athlete file;
step two, determining relevant parameters of a training date unit; and a training plan is prepared;
step three, according to different training means, load measurement and achievement of different athletes and other aspects, the actual training load data of the athletes is obtained in a mode of personal recording or group recording; or manually recording, importing the electronic equipment and acquiring relevant training data in an artificial intelligence system identification mode;
step four, acquiring physiological load data of the athlete in the training process, establishing an index system reflecting physiological and psychological reactions of the athlete and qualitatively evaluating the level of the state bearing the training load; acquiring exercise nutrition, exercise protection and drug use data;
step five, the acquired data are arranged and analyzed, the movement load qualitative analysis is carried out, the load training adjustment is carried out based on the analysis result, and meanwhile, the analysis result is converted into a chart for visual display;
Step six, carrying out mathematical analysis of the lesson load on the qualitatively analyzed training load data, judging the training load state and the competitive state born by the athlete, carrying out early warning over-training, confirming the individualized training scheme of the athlete, establishing training parameter big data of a long-distance training means, and integrating relevant parameters to provide a reasonable training load mathematical control range and a training load qualitative analysis model download;
the long-distance exercise training load analysis system includes:
the training system comprises an athlete file management module, a training unit setting module, a training plan making module, an actual training load input module, a healthy exercise management module, a training load statistics module, a lesson load control module and an online exercise training service module;
the athlete file management module is used for acquiring athlete basic information, special profile information and international situation data and establishing an athlete file based on the acquired data; the athlete profile includes: name, gender, birth month, height, weight, blood type, hobbies, personality, and physical vigor; the special profile information comprises exercise special training years and best achievements and creation time, place and event names of the exercise special training years and best achievements and creation time, place and event names of main item segmentation achievements and best achievements; the international situation comprises long-distance Olympic project world records and the segmented average speed r thereof A Sum of achievements R A The method comprises the steps of carrying out a first treatment on the surface of the Near term best performance of long distance project and its piecewise average speed r A Sum of achievements R A ；
The training unit setting module is used for carrying out phase division and target training measurement setting on the competition period according to the period theory and the plate training theory, making an overall plan comprising a multi-period large period and a multi-period viscosity training for the phase training plan, and making a target task comprising a target training period, a target training period small period and a target training day period for the unit training plan;
the training plan making module comprises a training means setting template unit, a unit training plan making unit, a lesson load value and operation specific gravity setting unit, a functional training unit, a training means setting and unit training plan unit; the training method comprises the steps of setting optional content of training means and making a daily training unit training plan;
the actual training load input module comprises a training load acquisition unit, a training means acquisition unit and a training load input unit; the training device is used for training load data acquisition, training means adjustment and training data input;
the health exercise management module comprises a physiological and biochemical index monitoring unit, an exercise injury and nutrition monitoring unit and a self-training sensation evaluation unit; the method is used for collecting relevant indexes of healthy exercise, supervising exercise risks and judging the functional state grade epsilon and the recovery state coefficient mu of an athlete bearing training load;
The training load statistics module comprises a training load qualitative analysis unit, a training load conventional statistics unit and an athlete personal load adjustment unit; meanwhile, the training purpose, course property, training content, training quantity and training intensity of a training method, training density, training total quantity and segmentation speed of the athlete for a period of exercise training are counted, and a corresponding chart is generated; and adjusting personal load of the athlete;
the lesson load control template is used for integrating special technical capacity training, physical quality training, technical improvement, functional action training content and training load characteristics thereof which are completed by athletes according to a training plan, combining functional states and recovery states, applying a business distance law, a working intensity law, a working load law, a reasonable load principle and a reasonable recovery principle, establishing a lesson load process mathematical control model, predicting rationality of the athletes in lessons, between lessons, in small periods, in training stages and during competition periods for bearing training loads and judging the possibility of maintaining or improving the competition state;
the on-line exercise training service module is used for providing competitive exercise state judgment, long-distance exercise training guidance, functional training guidance and competition appreciation;
The training plan making module comprises:
the training means setting template unit is used for setting optional content of the training means; the training means optional content includes: date or task, small period special training, daily unit special training, functional state monitoring, special technical action training, functional physical training and physical fitness training;
the date or task comprises training purposes, lesson properties, training contents and training methods;
the small period special training comprises: week course structure, week training times, training total amount, average score, target score, school load value and school specific gravity;
the daily unit special training comprises the following steps: the daily class structure, the working distance, the working average score, the working total score, the training total amount, the working times, the training group number, the training total time, the intermittent time, the working percentage strength, the working load value and the working proportion;
the functional status monitoring includes: target heart rate, process heart rate, immediate after training heart rate, recovery heart rate, process blood lactic acid, post training blood lactic acid, blood urea, creatine kinase, urinary protein, self-sensation;
the specialized technical action training comprises: type, content, method, job measure, total time;
The functional physical training comprises: type, content, method, job measure, total time;
the physical fitness training comprises: type, content, method, job measure, total time;
the unit training plan making unit is used for making a daily training unit training plan; the daily training unit training program comprises training purposes, course properties, training contents, training methods, training contents, load measurement and state monitoring;
the training purposes include: technical ability, physical ability, game ability, mental ability, and training theory;
the course properties include: aerobic training, mixed oxygen training, speed training, technical training, tactical training, functional action, strength training and adaptability training;
the training content comprises: aerobic special technical ability, special speed endurance, absolute speed, technical action, tactics, strength endurance, explosive force, absolute strength, functional action, psychological adaptability, environmental adaptation, opponent adaptation, field facility adaptation, wearable equipment adaptation;
the exercise method comprises the following steps: continuous training of aerobic special technology, speed repeated training, intermittent training of speed, mixed oxygen variable speed training, functional action cyclic training, general strength cyclic training, rapid strength repeated training, absolute strength repeated training, following tactics, race tactics, wheel tactics, simulated competition, teaching competition and formal competition;
The load metric includes: working distance, working average score, working total score, training total amount, working times, training group number, training total time, intermittent time, working percentage strength, working load value and working specific gravity;
the lesson load value and operation specific gravity setting unit is used for monitoring the training load process;
the functional training unit is used for supervising the body dysfunction, ensuring the effectiveness and economy of the sport technical action and preventing sport injury;
the training means setting and unit training plan unit is used for providing a manual record list, browsing, printing and sharing a training plan sample list;
the health exercise management module includes:
the physiological and biochemical index monitoring unit is used for acquiring physiological and biochemical indexes in the training process and after training and managing and monitoring the relevant physiological and biochemical indexes;
the sports injury and nutrition monitoring unit is used for collecting sports nutrition, sports injury and rehabilitation, drug treatment and stimulant detection and other related data in the training process of athletes;
the self-training feeling evaluation unit is used for collecting self-feeling and body response of the athlete, which bear training load and comprise fatigue degree, dysfunction, body pain, injury expression and treatment effect;
The training load statistics module comprises:
the training load qualitative analysis unit is used for qualitatively analyzing the training work load parameters of the special technical capability from the angles of sports training science, sports biology, sports medicine and physical function training theory, counting and classifying, diagnosing the training load bearing state of athletes, providing a work load analysis parameter sample table, printing and sharing analysis results; training academic analysis for completing a special skill ability training load; the method is used for analyzing the motion dynamics of special technical action characteristics and completing technical training load; for performing a kinematic biological analysis of the completed specialized skills training load; the functional training analysis is used for carrying out functional training analysis on the functional action training and physical training load; the training device is used for analyzing nutrition, injury and psychological adaptation analysis sports medicine for completing the training load process;
the training academic analysis includes: common operation distance and corresponding average score and total score, main operation average speed and highest speed and standard deviation thereof, main operation best training score and competition score and standard deviation thereof, wing operation average speed and highest speed and standard deviation thereof, variable speed training average score and best score of main operation, variable speed training average score and best score of wing operation, competition operation distance and corresponding average score, total score, time interval, uniform speed operation distance and subsection operation score, total score, variable speed operation distance and subsection operation score, total score, special technical capability training comprising content, means and method, special technical action training comprising content, means and method, physical functional training comprising content, means, method, total time and density; the intermittent training method comprises content and the number, the time of rest, the percentage strength and the class proportion, the repeated training method comprises the content and the number, the time of rest, the percentage strength and the class proportion, the unit class training comprises the purpose, the property, the type, the average total time and the interval time, the week period class comprises the training number, the total time and the class structure, the stage division of the event period comprises the preparation period, the competition period, the transition period and the refinement and measurement thereof, the unit of the total quantity of training and the average result strength, the day, the week, the stage and the event period comprises the physical quality training of the type, the density and the total time, and the physical functional training comprises the type, the density and the total time;
The kinetic analysis includes: stride, stride frequency, stride swing angle, stability, flexibility, economy, gait characteristics, physical characteristics, technical advantages, and technical shortcomings;
the kinetic biological analysis includes: process heart rate, heart rate inflection point, resting heart rate, highest heart rate, lowest heart rate, lactic acid threshold, maximum oxygen uptake, anaerobic threshold, creatine kinase, hemoglobin, blood urea, red blood cells, white blood cells, urine protein, PH change, BMI change, altitude adaptation, temperature humidity adaptation;
the functional training parsing includes: a function action evaluation index system FMS, a selective function action evaluation index system SFMA, a balance ability evaluation YBT and a basic motion physical ability evaluation FCS;
the sports medical analysis includes: motor nutrition characteristics, accumulation and rehabilitation of injury and psychological adaptability;
the training load routine statistics unit is used for counting training purposes, course properties, training contents, training amount and training intensity, training density, training total amount and segmentation speed of the athlete during a period of sports training, and generating a corresponding chart;
the counting and generating the corresponding chart comprises: training analysis indexes according to the weekly statistical technique capability, and generating a visual chart display by using statistical data; training analysis indexes according to daily statistical technology capability, and generating statistical data into a visual chart for display; training analysis indexes according to the unit statistical technology capability, and generating a visual chart display by using statistical data; daily statistics functional training load analysis indexes, and generating a visual chart display by the statistics data; daily statistics of physiological and biochemical analysis indexes, and generation of a visual chart display by the statistical data;
The athlete personal load adjusting unit is used for reversibly adjusting the training load and revising the personal load data; the training load reversibility adjustment includes, but is not limited to, abnormal data adjustment due to entry errors and reclassification of training means;
the lesson load control module comprises: the system comprises a working process mathematical analysis unit, a load bearing state judgment unit and a load process control paradigm unit;
the operation process mathematical analysis unit includes: a working distance law determining subunit, a working intensity law determining subunit, a working load principle determining subunit and a reasonable load principle determining subunit;
the operation distance law determining subunit comprises a common operation distance, a mathematical relation between any operation distance and an operation result and a power index table of the common operation distance; the method is used for processing the relation between the actual working distance and the working score and providing basis for setting a training plan; meanwhile, the method is used for exploring the sensitivity and the adaptability of the operation means of the athlete by qualitatively analyzing the characteristic of the personalized training load of the athlete, and establishing a personalized operation distance and operation achievement index system of the athlete;
the operation intensity law determining subunit comprises operation achievement intensity, percentage intensity and a mathematical relation and a percentage intensity power index scale; the system is used for monitoring the training load bearing state of the athlete through the operation score, providing basis for setting a training plan, exploring the sensitivity and the adaptability of the operation means of the athlete through qualitatively analyzing the personalized training load characteristics of the athlete, and establishing a personalized operation distance and operation score index system of the athlete;
The work load principle determining subunit comprises work load value calculation, work load accumulation principle determination and work load liability principle determination; for processing the relation between the actual work load of a player at a certain distance and the load ratio generated by a competition with full strength at the distance, and converting the work percentage strength into the actual work load specific value (q B/A ）；
The workload value calculation includes: calculating a master distance workload value and a non-master distance workload value;
the workload accumulation principle determination includes: the load value is used for statistically analyzing the continuous operation of the athlete;
the work load accumulation principle is determined, and is used for monitoring the load state change born by the athlete in the continuous work process through the work load value;
the work load liability principle determination comprises a lesson load value, a liability load principle, an inter-lesson liability load principle and an accumulated liability load principle and application thereof; the system is used for monitoring the load state change of the athlete in the continuous operation process and early warning the occurrence and development of excessive training through the operation load value;
the reasonable load principle determining subunit comprises the steps of determining reasonable class load values of the level athletes and calculating class load operation times; the early warning load measurement standard is used for monitoring the rationality of the player class target training load through the class load value and establishing excessive training; providing a standard for setting training main class load or full strength load class;
Determining international level reasonable lesson load values comprises calculating reasonable lesson load values of athletes of different levels at any distance based on the international level reasonable lesson load scale, the level athlete reasonable lesson load scale and the level athlete working distance reasonable lesson load scale;
the number of the lesson load operations comprises: calculating reasonable operation times of the courseload by calculating reasonable operation times of the operation distance;
the load-bearing state determination unit includes: the system comprises an actual load value calculating subunit in the course of the lesson load, a statistics unit training accumulated liability load value subunit, a statistics week training accumulated liability load value subunit, a load state judging subunit and a correction subunit; the method is used for judging the actual state of the athletes in the course of carrying training load according to the occurrence process of the actual operation score strength, the accumulated load value and the accumulated liability load value; the method comprises the steps of providing a training plan adjustment scheme for early warning over training or under training;
the real load value calculating subunit of the lesson load process comprises: the training unit is used for planning and calculating reasonable operation achievement R/R of the operation distance according to the training unit; the training unit is used for planning and calculating the reasonable operation achievement R/R percentage strength of the operation distance according to the training unit; the training unit is used for planning and calculating reasonable operation achievement R/R reasonable load values of the operation distance according to the training unit; the device is used for calculating an accumulated load value of the operation distance speed change operation score R/R according to the training unit plan; the system is used for calculating a constant-speed operation achievement R/R accumulated load value of the operation distance according to the training unit plan; the combined working distance working score R/R and the accumulated load value are calculated according to the training unit plan; the accumulated liability load value is used for calculating the combined working distance working score R/R in the class according to the training unit plan; the method is used for calculating reasonable operation times of the combined operation distance in the class according to the training unit plan; for calculating a week accumulation load value according to the training week plan; the method comprises the steps of calculating a week accumulation liability load value according to a training week plan; the method is used for calculating reasonable operation results of the operation distance according to the percentage strength and the operation means proportion; the device is used for calculating reasonable percentage strength of the working distance according to the working score and the specific gravity of the working means; the method is used for calculating reasonable operation scores of the operation distance according to the load value;
The statistics unit trains and accumulates the sub-unit of the liability load value and includes: the statistical unit is used for training and accumulating liability load values and displaying a visual chart;
the statistical week training accumulated liability load value subunit comprises: the method is used for counting the training accumulated liability load values and displaying a visual chart;
the load state judgment subunit includes: the system is used for judging the training load bearing state of the athlete unit by combining the function detection indexes;
the correction subunit includes: the training program load measurement is used for correcting the weekly training program load measurement and providing a working means correction suggestion;
the load process control paradigm unit includes: the training method comprises training means setting, unit training classes and lesson training plan making of week period; the system is used for systematic analysis of the course control of the training load of the lesson; the training program sample preparation table is used for storing training load control success cases and mathematical analysis models thereof, and providing, printing and sharing the mathematical control training load.
2. The long-range sports training load analysis method of claim 1, wherein the actual training load entry module comprises:
the training load acquisition unit is used for collecting relevant training data through manual recording, electronic equipment importing and artificial intelligent system identification modes, screening index input reflecting a class load value according to training load setting parameters, providing an importing window and a parameter acquisition sample table, and acquiring work load data; the workload data comprises manual recording, wearing equipment and other intelligent system reading, photographing, gesture analysis SennoGait, physiological and biochemical tests, functional action screening FMS, basic physical ability assessment FCS;
The training means acquisition unit is used for comparing training plan changes to carry out actual completion content adjustment;
the training load input unit is used for inputting or importing training data actually completed according to a training plan into the system; the input mode comprises personal input and group input.
3. A computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the long range exercise training load analysis method of any one of claims 1 to 2.
4. A computer readable storage medium storing instructions which, when run on a computer, cause the computer to perform the long distance exercise training load analysis method of any one of claims 1 to 2.
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