KR102230766B1 - Support method and apparatus for performance improvement of sled sports player - Google Patents

Abstract

The present invention relates to an integrated training support method for improving the performance of sled sports such as bobsled or skeleton, and a simulation device for sled sports training applied thereto, and the integrated support method for sled sports training of the present invention measures the physical strength of a training subject. A first data acquisition step (S110) for acquiring the first data, processing and managing it, and a second data acquisition step for acquiring and processing and managing second data through simulated training of the trainee ( S120), the third data acquisition step (S130) for acquiring, processing and managing the third data through actual training of the trainee, and integrating the first data, the second data, and the third data to generate integrated data And, it proceeds including a data integration step (S200) for processing and management and a data analysis step (S300) for analyzing integrated data based on artificial intelligence, and the result data analyzed through the integrated data analysis step It is characterized in that the performance of the training subject is improved through feedback based on the feedback.

Description

Integrated support method and simulation device for sledding sports training to improve performance {SUPPORT METHOD AND APPARATUS FOR PERFORMANCE IMPROVEMENT OF SLED SPORTS PLAYER}

The present invention relates to a method and apparatus for improving the performance of sledding sports, and more particularly, to a training integrated support method for improving the performance of sled sports such as a bobsled or skeleton, and a simulation device for training sledding sports applied thereto. will be.

The bobsled sport was officially started in 1884 and has a history of over 130 years and was adopted as an Olympic sport in 1924. Skeleton sports shared a bobsled and sliding track, and the official race started in 1884 and was adopted as an Olympic event in 1928, but was not adopted as an official event in 2002, 54 years later. In Korea, the bobsled team began to participate in international competitions in 2009, and the skeleton began to participate in the 2002 Olympics. Despite a very short history of competition compared to advanced countries, the ROK won medals in both events at the PyeongChang Olympics held in their country, proving its potential. This is a very rapid growth compared to other stocks, and is a promising stock that is expected to continuously improve its economic performance. However, due to the nature of the game, a sliding track is essential, so it is possible only in winter, and it is expensive to operate, so there are about 16 tracks available for international competitions around the world, and less than 10 tracks are operated during the winter season. For this reason, the number of trainees and the number of sliding training in each country is limited in track operation. In addition, most of the stadiums are located at high altitudes, so there is a need for a period for adapting to the high altitude environment, which in many ways places a great burden on the cost of field training. For this reason, there is a limit to maintaining and improving the current level.

On the other hand, it has been unilaterally absorbing the know-how of advanced countries to grow its competitive power, but in the upper-tiers, it can be said that maintaining the competitive power and systematic improvement are more important factors. However, due to the lack of a systematic big data collection system, a lack of objective data, a lack of data production and storage systems, a lack of a factor analysis system for coaching, etc., it is currently intermittent and limited by the intuitive reasoning of the coaching staff. There is a limit to coaching to improve athletic performance, such as reinforcement training and systematic motion analysis techniques are not applied.

In addition, bobsled and skeletons are unpopular events that only become an issue during the Olympics, and the athletes are very poor, so new technical measures are needed to find talents, revitalize dream tree cultivation, and prepare a system for life sports. In particular, at the international level, the bobsled speed exceeds 150 km/h and the skeleton speed exceeds 130 km/h, making it a very high risk of injury. For this reason, it is very important to reduce the risk of injuries during practice, not only for prospective players at the beginner-intermediate level, but also for national players.

Korean Registered Patent Publication No. 10-1865137

Accordingly, in order to solve the above problems, the present invention enables the reproduction of the environment of 16 stadiums around the world and the realization of an artificial high-altitude environment, so that not only does not need field training, but also training in the summer season is possible, and artificial intelligence Systematic specialized training and coaching for each player is possible through big data analysis based on the system, and furthermore, through dissemination, an integrated support method for sledding sports training that enables the discovery of talents and revitalization of dream trees, and sports for living, and sledding sports training applied thereto The purpose is to provide a simulator for use.

The integrated support method for sledding sports training of the present invention for achieving the above object acquires first data through physical fitness measurement of a training subject, and a first data acquisition step (S110) for processing and managing it, a training subject The second data acquisition step (S120) for acquiring, processing and managing the second data through mock training of the trainee, and third data for acquiring and processing and managing the third data through actual training of the trainee Acquisition step (S130), to generate integrated data by integrating the first data, second data and third data, and to process and manage the data integration step (S200) for analyzing the integrated data based on artificial intelligence Including the data analysis step (S300), it is characterized in that the performance of the training subject is improved through feedback based on the result data analyzed through the integrated data analysis step.

The present invention is for improving the performance of sledding sports such as bobsled or skeleton, and the simulation apparatus for sledding sports training of the present invention is capable of reproducing the environment of about 16 stadiums existing around the world and realizing a high altitude environment of low pressure and low oxygen atmosphere. In addition, there is no need for field training, and training is also possible in summer.

The integrated support method for sledding sports training of the present invention to which the simulation device for sledding sports training is applied, analyzes, based on artificial intelligence, complex big data in which sensing data and image data acquired through measuring devices such as sensors and cameras are integrated, Based on the analyzed result data, systematic specialized training and coaching for each player is possible. Furthermore, it is expected that through the dissemination of the present invention, it is possible to discover talents, revitalize dream tree cultivation, and make life sports.

1 is a schematic diagram of an integrated support method for sledding sports training according to an embodiment of the present invention.
2 is a schematic diagram of a simulation device for sledding sports training according to an embodiment of the present invention.
3 is a schematic diagram of a simulation device for sledding sports training according to another embodiment of the present invention.

Hereinafter, in order to fully understand the present invention, preferred embodiments of the present invention will be described with reference to the accompanying drawings. The embodiments of the present invention may be modified in various forms, and the scope of the present invention should not be construed as being limited to the embodiments described in detail below. This embodiment is provided to more completely describe the present invention to those with average knowledge in the industry. Accordingly, the shape of the element in the drawings may be exaggerated to emphasize a clearer description. It should be noted that in each drawing, the same configuration may be indicated by the same reference numeral. Detailed descriptions of known functions and configurations that are determined to unnecessarily obscure the subject matter of the present invention will be omitted.

The training target (P) referred to throughout this specification includes national representatives, athletes, or dream trees, and anyone who receives sled sports training or experience may be included therein.

The present invention relates to an integrated support method for sledding sports training for improving the performance of sled sports such as bobsled or skeleton, and a simulation apparatus applied thereto.

1 is a schematic diagram of an integrated support method for sledding sports training according to an embodiment of the present invention.

1, the integrated support method for sledding sports training of the present invention includes a first data acquisition step (S110), a second data acquisition step (S120), a third data acquisition step (S130), and a data integration step. It proceeds including (S200) and data analysis step (S300).

The first data acquisition step (S110) is a step for acquiring, processing and managing the first data through physical strength measurement of the training subject P. In this step, physical strength and performance of the training subject P are actually measured. Thus, the first data can be obtained.

The second data acquisition step (S120) is a step for acquiring, processing, and managing second data through simulated training of the training subject P. In this step, a simulation for sled sports training capable of implementing arbitrary virtual reality The second data may be acquired by performing simulation training through the device 400. The simulation device 400 for sledding sports training will be described in detail later.

The third data acquisition step (S130) is a step for acquiring, processing and managing third data through actual training of the training target P. In this step, data of the same type as the second data are acquired, Third data can be obtained by performing practical training in real stadiums such as Pyeongchang Stadium, not simulation training. Therefore, by comparing and analyzing the second data and the third data, it is possible to compare and analyze the difference between the simulation training and the actual training.

The first data, second data, and third data described above will be described in more detail.

The first data, the second data, and the third data may include all of the kinematic, psychological, muscular (physical) and physiological data affecting the performance according to the sport of sledding such as bobsled or skeleton.

The kinematic data includes data on the critical instantaneous power, subregional power, starting ground repulsion, starting posture and reaction time in the start section, important sprint time in the running section, pressure change between the feet and the ground, push time, ride time, and weight. Data on center position change, speed, acceleration, sprint and push body posture, grip strength, expression synchronicity and running parameter time, data on the center of gravity trajectory and grip strength, which are important at the time of completion of the breakman ride, and important weight in the driving section One or more of data on coherence of center movement, turning time, speed, pilot's maneuvering, center of gravity trajectory, amount of vibration and amount of impact, and data on important records at the time of finish may be included.

Psychological data may include one or more of data on important breathing control ability and breathing method before departure, pilot's control in all sections after departure, neurofeedback training, image training, meditation and breathing method, and the like.

Muscular (physical) data include upper and lower extremity strength, the ratio of reaching maximum strength (maximum force/reach time), EMG (Electromyography), TMG (Tensiomyography), Biodex & Cybex One or more of data on isokinetic dynamomter, muscle response rate and muscle power, data on muscle strength (stiffness), body composition, muscle mass, body fat mass, BMI (Body mass index), muscle fatigue, etc. that are important in the static section may be included.

The physiological data may include one or more of data on heart rate, blood oxygen saturation, blood flow rate, energy expenditure, muscle activity, brain waves, etc. that are important in all sections.

Meanwhile, in addition, the second data may further include data on the simulation environment during the simulation training, and likewise, the third data may further include data on the actual environment during the actual training. Data on pressure, oxygen content, etc. may be included.

In addition, the second data may further include data on the sled simulator used during simulation training, and likewise, the third data may further include data on the actual sled used during actual training. Data on runners (sledge blades), which act as a key factor in improving performance, may include data on the coefficient of friction between the runner and ice, and the finish of the runner surface to reduce the friction between the runner and ice. have. In addition, it can be expected that through data analysis on runners, it is possible to secure independent technology for runners, which are heavily dependent on foreign technology.

Meanwhile, the types of the first data, the second data, and the third data are not particularly limited, and various types of data are possible.

The first data, second data, and third data described so far are each of the first data acquisition step (S110), the second data acquisition step (S120), and the third data through various known measuring devices according to the type of data. It can be acquired in the acquisition step (S130).

In particular, in the case of the second and third data measured by performing simulated training and practical training of the training target (P), sensing data measuring devices such as various types of sensors (S) or image data such as cameras (C) It is preferably obtained through a measuring device. As the sensor S, various wearable sensors, biosensors, force sensors, pressure sensors, and inertial measurement unit (IMU) sensors can be used.

In the data integration step S200, as shown in FIG. 1, the first data acquired through the first data acquisition step S110, the second data acquired through the second data acquisition step S120, and the third data acquisition step ( This is a step for integrating the third data acquired through (S130) into big data to enable labeling, search, and data extraction, and to process and manage the generated integrated data.

The data analysis step (S300) is a step for analyzing the integrated data integrated through the data integration step (S200), as shown in FIG. 1, and in this step, an analysis software based on artificial intelligence (AI) technology is used. Through this, it is possible to analyze data on various factors that affect the improvement of the performance. Artificial intelligence (AI) technology is preferably a technology including an artificial neural network (Neural network) and machine learning (Machine learning), in addition to a variety of known artificial intelligence technology can be applied.

Furthermore, in the data analysis step (S300), it is possible to establish a coaching program such as optimized training tactics and strategies for improving performance for each training target (P) based on the analyzed results. (P) will be able to improve his performance.

For example, derivation of detailed elements for the analysis of factors for competing performance, derivation of the status of body composition and management plan of the training target (P), comparison and linkage of factors determining competition performance, composition of the data standardization classification system of the derived factors, evaluation and verification of the effectiveness of determinants, etc. You can do the job.

Hereinafter, the second data acquisition step of the integrated support method for sledding sports training described so far, that is, the simulation apparatus 400 for sledding sports training of the present invention applied to the simulation training will be described in detail.

2 is a schematic diagram of a simulation device for sledding sports training according to an embodiment of the present invention, and more specifically, a schematic diagram of a simulation device for skeleton training. 3 is a schematic diagram of a simulation device for sledding sports training according to another embodiment of the present invention, and more specifically, a schematic diagram of a simulation device for training bobsled.

As shown in Figs. 2 and 3, the simulation apparatus 400 for sledding sports training of the present invention includes a chamber 410, a footboard simulator 420, a sled simulator 430, a virtual reality implementation unit, and a data acquisition unit 450. ) And a monitoring unit 460.

As shown in Figs. 2 and 3, the chamber 410 allows entry and exit of one or more trainees P, and is connected to a pressure regulating device 411 such as a pressure pump to control internal air pressure, and oxygen It is preferable to implement a high altitude environment in a low pressure, low oxygen atmosphere by enabling control of the gas content such as, etc.

The scaffold simulator 420 is installed on the inner floor of the chamber 410, as shown in FIGS. 2 and 3, and may be formed in the form of a treadmill that receives power by movement of the training subject P, such as walking or running. It is preferable that the scaffold simulator 420 is installed so as to be provided one per training target (P) as shown in FIGS. 2 and 3.

The sled simulator 430 is installed on the inner floor of the chamber 410, as shown in FIGS. 2 and 3, and may be formed and positioned so that the training subject P can run on the scaffold simulator 420 and board it. In addition, in order to increase the similarity with the actual training, it is desirable to be formed in a shape similar to the actual sled as much as possible. The sled simulator of FIG. 2 is for skeleton simulation training, and FIG. 3 is for bobsled simulation training.

The virtual reality realization unit is to implement this so that the training target (P) can experience random virtual reality when performing simulation training, and it is possible to implement a 3D model in the same environment as the environment of about 16 stadiums around the world. Do. More specifically, the virtual reality implementation unit may include an image providing unit 440 and a motion control unit.

As shown in FIGS. 2 and 3, the image providing unit 440 is formed in the form of a wearable device such as a Virtual Reality (VR) gear that can be mounted on a helmet worn by the training subject P, and is based on a panoramic video. This is to provide an image to the training target (P) through virtual reality content, and through this, the training target (P) can experience virtual reality.

Although the motion control unit is not shown in the drawing, it is interlocked with the image providing unit 440 to provide vibration to the training subject P and the sled simulator 430 according to the conditions of the stadium that the training subject P is experiencing as an image. For this purpose, vibration may be provided to the body or part of the body of the training subject P, and through this, a sliding change effect according to the surface condition of the sliding track can be implemented in a responsive manner.

In addition, since the motion controller can control the motion of the sled simulator 430 through 6-degree of freedom motion platform technology, etc., it is possible to implement interactive content that maximizes sensibility, realization of exercise space, responsiveness, and realistic immersion. You can do it.

Therefore, it is possible to build a cutting-edge living lab that enables training without restrictions according to time, space, season, weather, etc. through such a virtual reality implementation unit.

The data acquisition unit 450 is for acquiring the second data in real time, and as shown in Figs. 2 and 3, a plurality of data are directly or indirectly attached to the training target (P), the scaffold simulator 420, and the sled simulator 430, respectively. It may be configured to include two sensors (S) and a camera (C) installed on the inner upper side of the chamber 410. The plurality of sensors S may include any one or more of a wearable sensor, a biosensor, a force sensor, a pressure sensor, and an inertial measurement unit (IMU) sensor.

Through this, kinematic, psychological, muscular and physiological data such as speed, posture, heart rate, EEG, etc. of the training subject (P) that can be included in the second data, the speed of the footstool simulator 420, posture, and training subject (P ), along with data on the pressure applied to the scaffolding simulator 420 and the speed, posture, and pressure applied to the sled simulator 430 by the training subject (P) of the sled simulator 430 and the runner (sled Various types of data, such as data for day), can be acquired as second data.

The monitoring unit 460 is for receiving, monitoring and storing the second data acquired through the data acquisition unit 450 through the gateway G, as shown in FIGS. 2 and 3. Air pressure and oxygen content control, scaffolding simulator 420, sled simulator 430, can also play the role of a control unit that controls the virtual reality realization unit and data acquisition unit 450, and instructions from managers such as supervisors and coaches Can be operated by

The present invention described so far is for improving the performance of sled sports such as bobsled or skeleton, and the simulation device for sled sports training of the present invention reproduces the environment of about 16 stadiums existing around the world and realizes a high altitude environment of low pressure and low oxygen atmosphere By making this possible, not only does not need field training, but also there is an effect that training is possible in summer.

The integrated support method for sledding sports training of the present invention applying such a simulation device for sledding sports training analyzes complex big data based on artificial intelligence, and enables systematic specialized training and coaching for each player based on the analyzed result data. There is. Furthermore, it is expected that through the dissemination of the present invention, it is possible to discover talents, revitalize dream tree cultivation, and make life sports.

Embodiments of the present inventors integrated support method and simulation device for sledding sports training for improving athletic performance are only preferred embodiments that enable those skilled in the art to easily implement the present invention in the technical field to which the present invention pertains. Since it is not limited to one embodiment, this does not limit the scope of the present invention. Therefore, the true technical protection scope of the present invention should be determined by the technical spirit of the appended claims. In addition, it will be apparent to those skilled in the art that various substitutions, modifications, and changes are possible within the scope of the technical spirit of the present invention, and it is obvious that parts that can be easily changed by those skilled in the art are included in the scope of the present invention. .

S110: First data acquisition step
S120: second data acquisition step
S130: third data acquisition step
S200: data integration phase
S300: data analysis stage
400: Sled sports training simulator
410: chamber
411: pressure control device
420: scaffolding simulator
430: sled simulator
440: video provider
450: data acquisition unit
460: monitoring unit
P: Trainee
S: sensor
C: camera
G: gateway

Claims (6)

A first data acquisition step for acquiring, processing and managing the first data through physical fitness of the training subject;
A second data acquisition step for acquiring, processing and managing second data through simulated training of the training subject;
A third data acquisition step for acquiring, processing and managing third data through actual training of the training subject;
A data integration step for generating integrated data by integrating the first data, the second data, and the third data, and processing and managing the same; And
It proceeds including a data analysis step for analyzing the integrated data based on artificial intelligence,
Improve the performance of the training subject through feedback based on the result data analyzed through the analysis step of the integrated data,
The simulation device for sledding sports training applied to the second data acquisition step
A chamber capable of accessing and entering the training subject and controlling internal air pressure and oxygen content;
A scaffold simulator installed inside the chamber;
A sled simulator installed inside the chamber;
A virtual reality implementation unit for implementing virtual reality so that the training subject can experience virtual reality;
A data acquisition unit for acquiring the second data in real time; And
And a monitoring unit for monitoring the second data acquired through the data acquisition unit. The method of claim 1,
The integrated support method for sled sports training,
Integrated support method for sleigh sports training, characterized in that the integrated support method for bobsled or skeleton training. delete delete delete delete

Images