阅读说明：本技术 一种模拟实战训练系统 (Simulated actual combat training system ) 是由 王利平 于 2021-01-28 设计创作，主要内容包括：本发明涉及体育器材技术领域,具体涉及一种模拟实战训练系统,包括：沙袋,沙袋表面设有气囊,气囊通过电磁阀连接有泵体；压力检测装置,用于实时检测沙袋上的压力；肌电采集装置,用于实时采集训练者手臂部位肌肉的肌电信号；多个MEMS传感器,用于实时采集训练者不同身体部位的动作数据；控制器,用于根据肌电图的频率对初始压力阈值进行修正,得到修正压力阈值；控制器还用于根据压力检测值和修正压力阈值判断训练者击打沙袋是否为有效击打；控制器还用于控制电磁阀对气囊进行充/放气。本发明中压力阈值在训练过程中能够根据肌肉疲劳程度进行调整,可以近似模拟实战比赛中对方根据训练者的进攻情况进行抵抗的效果。(The invention relates to the technical field of sports equipment, in particular to a simulated actual combat training system, which comprises: the sand bag is provided with an air bag on the surface, and the air bag is connected with the pump body through an electromagnetic valve; the pressure detection device is used for detecting the pressure on the sandbag in real time; the myoelectricity acquisition device is used for acquiring myoelectricity signals of muscles of the arm part of a trainer in real time; the MEMS sensors are used for acquiring action data of different body parts of a trainer in real time; the controller is used for correcting the initial pressure threshold value according to the frequency of the electromyogram to obtain a corrected pressure threshold value; the controller is also used for judging whether the sandbag hit by the trainer is effective hit or not according to the pressure detection value and the corrected pressure threshold value; the controller is also used for controlling the electromagnetic valve to charge/discharge the air bag. The pressure threshold value can be adjusted according to the muscle fatigue degree in the training process, and the effect of resisting by the opposite side according to the attack condition of the trainer in the actual combat match can be approximately simulated.)

1. A simulated actual combat training system, comprising:

the sand bag is provided with an air bag on the surface, and the air bag is connected with the pump body through an electromagnetic valve;

the pressure detection device is arranged on the sandbag and used for detecting the pressure on the sandbag in real time and sending a pressure detection value to the controller;

the myoelectric acquisition device is used for acquiring myoelectric signals of muscles at the arm parts of the trainers in real time and sending the myoelectric signals to the controller;

the MEMS sensors are used for acquiring action data of different body parts of a trainer in real time and sending the action data to the controller;

the controller is used for receiving the electromyographic signals in real time, generating electromyography according to the electromyographic signals to obtain the frequency of the electromyography, and correcting the initial pressure threshold according to the frequency of the electromyography to obtain a corrected pressure threshold;

the controller is also used for receiving the pressure detection value in real time and judging whether the sandbag hit by the trainer is effective hit or not according to the pressure detection value and the corrected pressure threshold value;

the controller is also used for receiving the action data in real time and inputting the action data into a preset probability calculation model for calculation to obtain a strong attack probability; when the strong attack probability is smaller than the preset probability threshold value, the electromagnetic valve is controlled to inflate the air bag, and when the strong attack probability is not smaller than the preset probability threshold value, the electromagnetic valve is controlled to deflate the air bag.

2. The simulated actual combat training system of claim 1 wherein the controller further inputs the motion data into a predetermined motion recognition model for calculation to obtain motion correction information.

3. The simulated actual combat training system of claim 2 wherein the controller is further configured to recognize the exercise movements of the trainee based on the electromyographic data and compare the exercise movements with predetermined standard movements to obtain movement guidance data.

4. The simulated actual combat training system of claim 3 wherein the controller is further configured to import the electromyographic data into a predetermined fatigue prediction model for calculation to obtain an estimated time for the trainee to reach a fatigue state.

5. The simulated actual combat training system of claim 4 wherein the initial pressure threshold is different for different areas of the sandbag.

6. The simulated actual combat training system of claim 5 wherein the sandbag is herringbone in shape and the sandbag has a volume size that is the adult human volume size.

Technical Field

The invention relates to the technical field of sports equipment, in particular to a simulated actual combat training system.

Background

In order to achieve the purpose of building up the body, more and more people start to enjoy various sports to improve their own physical fitness, and to actually achieve the exercise effect, continuous and targeted training is required. For fighting exercises, trainers need continuous training to improve the accuracy, flexibility and actual combat experience of skills. At present, sandbags are usually adopted for training, but the sandbags cannot monitor the hitting power of a trainer, cannot judge whether the skill of the trainer is strong, and cannot judge whether the skill action of the trainer is correct.

In view of the above, chinese patent CN107308629A discloses a fighting training system, which comprises: a sand bag; the first detection device is arranged on the sandbag and used for detecting the pressure on the sandbag and sending a pressure detection value to the controller; the controller is used for judging whether the sand bag hit by the trainer is effective hit or not according to the pressure detection value and a preset first threshold value; the controller is also used for recording scores according to the beating part of the trainer, the beating part of the sandbag, the judgment result of whether the trainer rotates or not and a preset second corresponding relation; wherein, the second corresponding relation is the corresponding relation between the score and the logical integration of the hitting part of the trainer, the hitting part of the sandbag and whether the trainer rotates or not.

In the technical scheme, when a trainer strikes the sandbag, the first detection device can detect the pressure on the sandbag, and the controller can determine whether the trainer strikes the sandbag as effective striking according to the pressure detection value detected by the first detection device and a preset first threshold value, so that whether the action used by the trainer is correct is determined, the trainer can timely monitor the striking action, and the training effect of the trainer is improved.

In the actual double fight sports, the scoring priority order is the number of knockdown times, whether the opponent is hurt (the opponent has obvious displacement) and the clear number of striking times. With the lapse of the fighting exercise time, the participants will gradually fatigue, and the physical strength will gradually decline; during ordinary training, the sandbag does not become fatigued over time. In normal training, a striking action that is not an effective strike may be an effective strike for actual combat. That is, the same force cannot cause the opponent to move significantly at ordinary times, but can cause the opponent to move significantly during actual combat. Similarly, a striking action of a valid strike in ordinary training is likely to be an excessive strike for actual combat, i.e., the same force will cause an apparent displacement of the opponent at ordinary times, more than enough to cause an apparent displacement of the opponent during actual combat. Therefore, in the technical scheme, whether the sand bag hit by a trainer is effective hit is determined according to the pressure detection value and the preset first threshold value, and the actual combat process of fighting cannot be accurately determined.

Disclosure of Invention

The invention provides a simulated actual combat training system, which solves the technical problem that the prior art can not accurately train actual combat competitions.

The basic scheme provided by the invention is as follows: a simulated actual combat training system comprising:

the sand bag is provided with an air bag on the surface, and the air bag is connected with the pump body through an electromagnetic valve;

the pressure detection device is arranged on the sandbag and used for detecting the pressure on the sandbag in real time and sending a pressure detection value to the controller;

the myoelectric acquisition device is used for acquiring myoelectric signals of muscles at the arm parts of the trainers in real time and sending the myoelectric signals to the controller;

the MEMS sensors are used for acquiring action data of different body parts of a trainer in real time and sending the action data to the controller;

the controller is used for receiving the electromyographic signals in real time, generating electromyography according to the electromyographic signals to obtain the frequency of the electromyography, and correcting the initial pressure threshold according to the frequency of the electromyography to obtain a corrected pressure threshold;

the controller is also used for receiving the pressure detection value in real time and judging whether the sandbag hit by the trainer is effective hit or not according to the pressure detection value and the corrected pressure threshold value;

the controller is also used for receiving the action data in real time and inputting the action data into a preset probability calculation model for calculation to obtain a strong attack probability; when the strong attack probability is smaller than the preset probability threshold value, the electromagnetic valve is controlled to inflate the air bag, and when the strong attack probability is not smaller than the preset probability threshold value, the electromagnetic valve is controlled to deflate the air bag.

The working principle and the advantages of the invention are as follows:

(1) medical studies show that the frequency of electromyography decreases as the degree of muscle fatigue increases, which is inversely related to the frequency of electromyography, and changes in the frequency of electromyography may reflect changes in the degree of muscle fatigue. In an actual fighting game, both participants will become increasingly fatigued, with the amount of fatigue increasing, so that the force required to produce a significant displacement of the opponent is reduced and the criteria for effective striking should be reduced. Therefore, the pressure threshold is corrected and updated in real time in the training process, so that the pressure threshold can be adjusted according to the muscle fatigue degree in the training process, and a trainer can timely and accurately monitor the hitting action; compared with the method that a fixed and unchangeable pressure threshold value is directly set, the training process at ordinary times can be truly restored or close to the actual combat match, and therefore the training effect is improved; the method is closer to actual combat and has more guiding significance to the actual combat.

(2) In an actual combat game, when one attack is a strong attack, for example, when a punch is fast, the other party may resist the attack with a hard part; conversely, when one attack is a weak attack, for example, when the punch speed is slow, the other may resist with a relatively soft part of the body. When the air bag is not inflated, the sand bag is relatively hard, and can simulate the resistance of a hard part of a body; when the strong attack probability is smaller than the preset probability threshold value, it is indicated that the attack of the trainer is mild, the controller controls the electromagnetic valve to be opened to inflate the air bag, and the inflated air bag can simulate the resistance of the soft part of the body. In this way, the effect of the opponent resisting according to the attack condition of the trainer in the actual combat match can be approximately simulated.

The pressure threshold value can be adjusted according to the muscle fatigue degree in the training process, the effect of resisting by the opposite side according to the attack condition of the trainer in the actual combat match can be approximately simulated, and the technical problem that the training cannot be accurately carried out on the actual combat match in the prior art is solved.

Further, the controller also inputs the motion data into a preset motion recognition model for calculation so as to obtain motion correction information.

Has the advantages that: in the training process, the real-time action of the trainer can be distinguished, the action correction information of the trainer is provided, the trainer is beneficial to mastering the standard of the action of the trainer in real time, and corresponding adjustment is carried out according to the action correction information, so that the training effect is improved.

Further, the controller is also used for identifying the movement of the trainer according to the electromyography data and comparing the movement with a preset standard movement to obtain movement guidance data.

Has the advantages that: for different training items, the corresponding standard actions are different, such as fighting and tai chi; therefore, the exercise action is compared with the preset standard action to obtain the action guide data, and the training method is beneficial to guiding a trainer to improve specific training items.

Further, the controller is also used for importing the electromyographic data into a preset fatigue prediction model for calculation so as to obtain the estimated time for the trainer to reach the fatigue state.

Has the advantages that: when the trainer is in a fatigue state, if the trainer continues to train, the expected training effect can not be achieved, and the health of the trainer can be damaged; therefore, the estimated time for the trainer to reach the fatigue state is obtained, and the trainer can conveniently and reasonably master the training time.

Further, the initial pressure thresholds are different for different areas of the sandbag.

Has the advantages that: in actual competition, each area of the body of the competitor is likely to be hit, the hitting resistance of each part of the body is different, and the competition process requires that the points are reached and stopped, so that the training flexibility is improved.

Furthermore, the sandbag is in a herringbone shape, and the size of the sandbag is the size of the adult human body.

Has the advantages that: therefore, the scene can be truly restored, and the authenticity of training is improved.

Drawings

FIG. 1 is a block diagram of a system of a simulated actual combat training system according to an embodiment of the present invention.

Detailed Description

The following is further detailed by the specific embodiments:

example 1

The embodiment of the simulated actual combat training system is basically as shown in the attached figure 1: the method comprises the following steps:

the sand bag is provided with an air bag on the surface, and the air bag is connected with the pump body through an electromagnetic valve;

the pressure detection device is arranged on the sandbag and used for detecting the pressure on the sandbag in real time and sending a pressure detection value to the controller;

the myoelectric acquisition device is used for acquiring myoelectric signals of muscles at the arm parts of the trainers in real time and sending the myoelectric signals to the controller;

the MEMS sensors are used for acquiring action data of different body parts of a trainer in real time and sending the action data to the controller;

the controller is used for receiving the electromyographic signals in real time, generating electromyography according to the electromyographic signals to obtain the frequency of the electromyography, and correcting the initial pressure threshold according to the frequency of the electromyography to obtain a corrected pressure threshold;

the controller is also used for receiving the pressure detection value in real time and judging whether the sandbag hit by the trainer is effective hit or not according to the pressure detection value and the corrected pressure threshold value;

the controller is also used for receiving the action data in real time and inputting the action data into a preset probability calculation model for calculation to obtain a strong attack probability; when the strong attack probability is smaller than the preset probability threshold value, the electromagnetic valve is controlled to inflate the air bag, and when the strong attack probability is not smaller than the preset probability threshold value, the electromagnetic valve is controlled to deflate the air bag. That is, the air pressure of the air bag is adjusted according to the hitting position, and corresponding feedback is formed.

In the embodiment, a fighting training is taken as an example for explanation, the pressure detection device is a pressure sensor, the pressure sensor is arranged on the surface of a sandbag, the sandbag is in a herringbone shape, the size of the sandbag is the size of an adult, the ratio is 1:1, an air bag is arranged on the surface of the sandbag, the air bag is connected with a pump body through an electromagnetic valve, and the air bag can be inflated by the pump body; the myoelectric acquisition device is a myoelectric signal collector, the MEMS sensors are all InveSenseMPU-91509 axis MENS motion tracking sensors, and the myoelectric signal collector is worn on the arm of the trainer; the MEMS sensors are respectively worn on different parts of the body of a trainer, such as hands, heads, necks, waists and legs, and can acquire motion data of the speed, acceleration, angles, angular velocities and the like of the specified part of the trainer at a certain moment; the controller is a server, the pressure detection device, the myoelectricity acquisition device and the MEMS sensor are in signal connection with the controller, and the controller is electrically connected or in signal connection with the electromagnetic valve.

The specific implementation process is as follows:

before the training begins, the balloon is in a deflated state, and no gas is present inside the balloon. When training begins, all parts of the body of a trainer start to move, the myoelectric signal of the muscle of the arm part of the trainer can be collected in real time by the myoelectric collecting device, and the myoelectric signal is sent to the controller; the plurality of MEMS sensors can also collect the motion data of different body parts of the trainer in real time and send the motion data to the controller, such as the speed, the acceleration, the angle, the angular velocity and the like of each designated part of the hand, the head, the neck, the waist and the leg at each moment. If a trainer strikes the sandbag, the pressure detection device can detect the pressure on the sandbag and send a pressure detection value to the controller, and the controller can receive the electromyographic signals, the pressure detection value and the action data in real time.

Firstly, after the controller receives the electromyogram signal, the electromyogram is generated according to the electromyogram signal to obtain the frequency of the electromyogram, and the initial pressure threshold value is corrected according to the frequency of the electromyogram to obtain the corrected pressure threshold value. In this embodiment, the initial pressure threshold is set manually in advance, and the initial pressure threshold is different for different areas of the sandbag. For example, for the head region of a sandbag, the initial pressure threshold is set to 20N; for the hand area of the sandbag, the initial pressure threshold was set at 40N. As the degree of muscle fatigue increases, so that the force required for the opponent to produce a significant displacement decreases, it is believed that the initial pressure threshold is the minimum force required for the opponent to produce a significant displacement, and thus the initial pressure threshold also decreases as the degree of muscle fatigue increases. Considering that the muscle fatigue degree is in negative correlation with the frequency of the electromyogram, the regression equation of the initial pressure threshold value and the frequency of the electromyogram is obtained through data of various match sites obtained in advance, such as the electromyogram signal, the electromyogram, the muscle fatigue degree and the initial pressure threshold value, and then the initial pressure threshold value is corrected according to the regression equation to obtain the corrected pressure threshold value.

And then, after the controller receives the pressure detection value, judging whether the sandbag hit by the trainer is effective hit or not according to the pressure detection value and the corrected pressure threshold value. In the present embodiment, the effective hit is defined as: so that the opponent generates an obvious displacement, namely, the pressure detection value is larger than the minimum force required for the opponent to generate the obvious displacement. When the pressure detection value is larger than the corrected pressure threshold value, the hitting power of the trainer is larger, the opponent can generate obvious displacement, and the trainer is judged to hit the sandbag effectively; when the pressure detection value is smaller than or equal to the corrected pressure threshold value, the fact that the hitting power of the trainer is small and the opponent cannot generate obvious displacement is shown, and the fact that the trainer hits the sandbag is judged to be invalid. Through the mode, the pressure threshold value is corrected and updated in real time in the training process, so that the pressure threshold value can be adjusted according to the muscle fatigue degree in the training process, a trainer can conveniently and accurately monitor the beating action in time, and the usual training process is ensured to be truly restored or close to a real combat match.

And finally, after the controller receives the action data, inputting the action data into a preset probability calculation model for calculation to obtain a strong attack probability. In this embodiment, it is considered that in the actual combat game, when one attack is a strong attack, the other may resist the attack with a relatively hard part of the body, such as a double arm holding the hands; when one attack is a weak attack, the other may resist it with a softer body part, such as the back. For strong attack and weak attack, the faster the punch speed is, the higher the punch acceleration is, the more likely it is that the strong attack is; the slower the punch velocity and the smaller the punch acceleration, the more likely it is a weak attack. From the conventional course data, for example, the course data of the first round and the second round … N of the same game, a probability calculation model can be obtained by using a neural network algorithm, and the probability that the trainer is a strong attack at a certain moment can be calculated and obtained on the basis of the action data such as the speed, the acceleration, the angle, the angular velocity and the like of each designated part of the hand, the head, the neck, the waist and the leg at each moment through the probability calculation model.

When the strong attack probability is smaller than the preset probability threshold value, the strong attack probability indicates that the attack of the trainer is mild, and the other party can resist the attack by using the soft part of the body in the actual combat match, so that the electromagnetic valve is controlled to inflate the air bag to simulate the resistance by using the soft part of the body; on the contrary, when the strong attack probability is not less than, namely greater than or equal to the preset probability threshold value, the strong attack of the trainer is shown to be more fierce, and the other party in the actual combat match can be resisted by the part with a harder body, so that the electromagnetic valve is controlled to deflate the air bag to simulate the resistance by the part with the harder body. In this way, the effect of the opponent resisting according to the attack condition of the trainer in the actual combat match can be approximately simulated.

Example 2

The only difference from embodiment 1 is that,

the controller also inputs the action data into a preset action recognition model for calculation so as to obtain action correction information; and identifying the movement of the trainer according to the electromyographic data, and comparing the movement with a preset standard movement to obtain movement guidance data. In this embodiment, the motion recognition model is obtained in advance through a machine learning algorithm on the basis of the previous match field data, and in the training process, the real-time motion of the trainer can be judged through motion data such as the speed, the acceleration, the angle, the angular velocity and the like of each designated part of the hand, the head, the neck, the waist and the leg at each moment; on the basis of the motion guidance data, the trainer's motion correction information is given, for example, adjusted according to the difference to gradually narrow the difference. By the mode, the trainer can master the standard of self action in real time and carry out corresponding adjustment according to the action correction information, thereby improving the training effect.

Example 3

The only difference from embodiment 2 is that,

the controller is also used for importing the electromyographic data into a preset fatigue prediction model for calculation so as to obtain the estimated time for the trainer to reach the fatigue state. In the embodiment, the fatigue prediction model is obtained by a machine learning algorithm in advance on the basis of the previous match field data, and the estimated time for the trainer to reach the fatigue state can be calculated according to the myoelectric data, so that the trainer can conveniently and reasonably master the training time.

The foregoing is merely an example of the present invention, and common general knowledge in the field of known specific structures and characteristics is not described herein in any greater extent than that known in the art at the filing date or prior to the priority date of the application, so that those skilled in the art can now appreciate that all of the above-described techniques in this field and have the ability to apply routine experimentation before this date can be combined with one or more of the present teachings to complete and implement the present invention, and that certain typical known structures or known methods do not pose any impediments to the implementation of the present invention by those skilled in the art. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.