CN116503696B - Concentration training method and device based on virtual defense mechanism and terminal equipment - Google Patents
Concentration training method and device based on virtual defense mechanism and terminal equipment Download PDFInfo
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Abstract
The invention discloses a concentration training method, a device and terminal equipment based on a virtual defense mechanism, wherein the method comprises the following steps: acquiring a scene video for concentration training, and determining a defending object based on the scene video, wherein the defending object is a fixed object in the scene video; acquiring an attacker moving towards a defending object in a scene video, and acquiring the moving time of the attacker; acquiring electroencephalogram data acquired in the movement time, determining a current concentration value according to the electroencephalogram data, and generating a virtual defense barrier based on the current concentration value, wherein the defense barrier is used for wrapping a defending object in all directions, and the defense level of the virtual defense barrier is in direct proportion to the current concentration value; and acquiring the defensive power information of the virtual defensive barrier, and determining the concentration training effect based on the defensive power information. The invention can establish the virtual defense barrier according to the concentration force to resist the attack of the attacker, has novel training mode and is beneficial to helping the user train the concentration force.
Description
Technical Field
The present invention relates to the field of concentration training technologies, and in particular, to a concentration training method and apparatus for a virtual defense mechanism, and a terminal device.
Background
Concentration training, particularly for people with attention deficit or disorder, is becoming particularly important, and various training modes already exist in the existing concentration training. For example, by raising the user's concentration to trigger a certain action, or by training the user to concentrate on raising the concentration to a target value in a fixed time. However, the existing concentration training modes are single and traditional, and the training effect is poor.
Accordingly, there is a need for improvement and advancement in the art.
Disclosure of Invention
The technical problem to be solved by the invention is to provide a concentration training method, a device and a terminal equipment for a virtual defense mechanism aiming at the defects of the prior art, and aims to solve the problems that concentration training modes in the prior art are single and traditional and the training effect is poor
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
in a first aspect, the present invention provides a method for concentration training based on a virtual defense mechanism, wherein the method includes:
acquiring a scene video for concentration training, and determining a defending object based on the scene video, wherein the defending object is a fixed object in the scene video;
acquiring an attacker moving towards the defending object in the scene video, and acquiring the moving time of the attacker;
acquiring electroencephalogram data acquired in the movement time, determining a current concentration value according to the electroencephalogram data, and generating a virtual defense barrier based on the current concentration value, wherein the virtual defense barrier is used for wrapping the defending object in an omnibearing manner, and the defense level of the virtual defense barrier is in direct proportion to the current concentration value;
and acquiring the defensive force information of the virtual defensive barrier, and determining the concentration training effect based on the defensive force information.
In one implementation, the determining a defending object based on the scene video includes:
performing picture preview on the scene video, analyzing scene environments in the scene video, and determining fixed objects in the scene environments;
and taking the fixed object as the defending object.
In one implementation, the acquiring the attacker moving towards the defending object in the scene video and acquiring the moving time of the attacker includes:
the moving objects around the defending object are obtained in real time, and the moving direction of each moving object is analyzed;
and determining a moving object with a moving direction towards the defending object as an attacker, and recording the moving time of the attacker.
In one implementation, the generating a virtual defense barrier based on the current concentration value includes:
acquiring a numerical interval corresponding to the current concentration value, and determining a defense level corresponding to the numerical interval based on the numerical interval;
based on the defensive level, the virtual defensive barrier is generated.
In one implementation, the generating the virtual defense barrier based on the defense level includes:
acquiring thickness information, color information and animation sound effect information corresponding to the defense level;
the virtual defense barrier is generated based on the thickness information, color information, and animation sound information.
In one implementation, the obtaining the defensive power information of the virtual defensive barrier, determining the concentration training effect based on the defensive power information, includes:
obtaining damage degree information of the virtual defense barrier, and determining the defense force information based on the damage degree information, wherein the damage degree information is inversely proportional to the defense force information;
and determining a training score of concentration training according to the defensive power information, and determining the concentration training effect based on the training score.
In one implementation, the obtaining the defensive power information of the virtual defensive barrier, determining the concentration training effect based on the defensive power information, further includes:
and after the attacker attacks the virtual defense barrier, acquiring the ejection distance of the attacker, and determining the defense information based on the ejection distance, wherein the ejection distance is in direct proportion to the defense information.
In a second aspect, an embodiment of the present invention further provides a concentration training device based on a virtual defense mechanism, where the device includes:
the defending object determining module is used for acquiring a scene video for concentration training and determining defending objects based on the scene video, wherein the defending objects are objects fixed in the scene video;
the motion time determining module is used for acquiring an attacker which moves towards the defending object in the scene video and acquiring the motion time of the attacker;
the defense barrier generation module is used for acquiring the electroencephalogram data acquired in the movement time, determining a current concentration value according to the electroencephalogram data, and generating a virtual defense barrier based on the current concentration value, wherein the virtual defense barrier is used for wrapping the defending object in an omnibearing manner, and the defense level of the virtual defense barrier is in direct proportion to the current concentration value;
and the concentration evaluation module is used for acquiring the defensive force information of the virtual defensive barrier and determining the concentration training effect based on the defensive force information.
In a third aspect, an embodiment of the present invention further provides a terminal device, where the terminal device includes a memory, a processor, and a concentration training program based on a virtual defense mechanism stored in the memory and capable of running on the processor, and when the processor executes the concentration training program based on the virtual defense mechanism, the processor implements the steps of the concentration training method based on the virtual defense mechanism in any one of the above schemes.
In a fourth aspect, an embodiment of the present invention further provides a computer readable storage medium, where the computer readable storage medium stores a concentration training program based on a virtual defense mechanism, where the concentration training program based on the virtual defense mechanism implements the steps of the concentration training method based on the virtual defense mechanism according to any one of the above schemes when the concentration training program based on the virtual defense mechanism is executed by a processor.
The beneficial effects are that: compared with the prior art, the invention provides a concentration training method based on a virtual defense mechanism. Then, an attacker moving towards the defending object in the scene video is obtained, and the moving time of the attacker is obtained. And then, acquiring the electroencephalogram data acquired in the movement time, determining a current concentration value according to the electroencephalogram data, and generating a virtual defense barrier based on the current concentration value, wherein the virtual defense barrier is used for wrapping the defending object in an omnibearing manner, and the defense level of the virtual defense barrier is in direct proportion to the current concentration value. And finally, obtaining the defensive force information of the virtual defensive barrier, and determining the concentration training effect based on the defensive force information. The invention can establish the virtual defense barrier according to the concentration force to resist the attack of the attacker, has novel training mode, is beneficial to helping the user to train the concentration force and has better training effect.
Drawings
Fig. 1 is a flowchart of a specific implementation of a concentration training method based on a virtual defense mechanism according to an embodiment of the present invention.
Fig. 2 is a functional schematic diagram of a concentration training device based on a virtual defense mechanism according to an embodiment of the present invention.
Fig. 3 is a schematic block diagram of a terminal device according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and more specific, the present invention will be described in further detail below with reference to the accompanying drawings and examples. 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.
The embodiment provides a concentration training method based on a virtual defense mechanism, and based on the method of the embodiment, the invention provides a novel concentration training mode. Then, an attacker moving towards the defending object in the scene video is obtained, and the moving time of the attacker is obtained. And then, acquiring the electroencephalogram data acquired in the movement time, determining a current concentration value according to the electroencephalogram data, and generating a virtual defense barrier based on the current concentration value, wherein the virtual defense barrier is used for wrapping the defending object in an omnibearing manner, and the defense level of the virtual defense barrier is in direct proportion to the current concentration value. And finally, obtaining the defensive force information of the virtual defensive barrier, and determining the concentration training effect based on the defensive force information. The invention can establish the virtual defense barrier according to the concentration force to resist the attack of the attacker, has novel training mode, is beneficial to helping the user to train the concentration force and has better training effect.
The concentration training method based on the virtual defense mechanism can be applied to terminal equipment, wherein the terminal equipment comprises intelligent product terminals such as computers, intelligent televisions and mobile phones. The terminal device of the embodiment can be connected with an electroencephalogram head ring, the electroencephalogram head ring can be used for collecting electroencephalogram data of a user, then the collected electroencephalogram data is sent to the terminal device, and the terminal device analyzes the electroencephalogram data so as to perform concentration training. Specifically, as shown in fig. 1, the present embodiment, when executing the concentration training method based on the virtual defense mechanism, includes the following steps:
step S100, obtaining a scene video for concentration training, and determining a defending object based on the scene video, wherein the defending object is a fixed object in the scene video.
The terminal device of this embodiment first obtains a scene video for performing concentration training, where the scene video is preset, the scene video includes a defending object and an attacker, the defending object is a protected object, and the defending object is a stationary object in the scene video. In a specific application, the scene videos of the embodiment may be selected, and the scene videos may be preset with a plurality of types, and the defending objects in each scene video are different, and the sizes and shapes of the defending objects in each scene video are also different, so that the difficulty in each scene video is also different. The corresponding scene video may be determined based on a user's selection at a particular application.
In one implementation, step S100 in this embodiment specifically includes the following steps:
step S101, performing picture preview on the scene video, analyzing scene environments in the scene video, and determining fixed objects in the scene environments;
step S102, the fixed object is used as the defending object.
When the method is specifically applied, the terminal equipment of the embodiment firstly reads the scene video, then carries out picture preview on the scene video, analyzes the scene environment in the scene video and determines the fixed object in the scene environment. For example, when the scene environment in the scene video is a castellation environment, then the castellation is a stationary object, i.e., a protected object, and thus the castellation is a defending object. In this embodiment, the defending object is a relatively important object in the whole scene video, so that the defending object is analyzed based on the scene environment, which is favorable for finding out the fixed object with the highest association degree with the scene environment, thereby quickly determining the defending object.
Step 200, obtaining an attacker moving towards the defending object in the scene video, and obtaining the moving time of the attacker.
When the defending object in the scene video is determined, the defending object is a protected fixed object, and therefore, the object which is thrown towards the defending object and causes damage to the defending object is an attacker. Therefore, the embodiment can acquire the object moving towards the defending object in the scene video and determine the object as the attacker, and then the embodiment can read the movement time of the attacker, wherein the movement time is the time when the attacker appears in the scene video, because in the specific concentration training process, after the attacker appears in the scene video, the user can see the attacker, at this time, the concentration training can be started, that is, the reaction time of the user for concentration training can be determined according to the movement time of the attacker, that is, the concentration training is promoted.
In one implementation, step S200 in this embodiment specifically includes the following steps:
step S201, moving objects around the defending object are obtained in real time, and the moving direction of each moving object is analyzed;
step S202, determining a moving object with a moving direction facing the defending object as an attacker, and recording the moving time of the attacker.
Specifically, the present embodiment can acquire moving objects in a moving state among the four sides of the defending object, and then analyze the moving direction of each moving object. Since only a moving object moving toward the defending object is likely to attack the defending object, the moving object in other moving directions does not damage the defending object, for example, in the field Jing Shipin, when the defending object is a castle, birds flying over the castle are not attackers, but bombs that attack the castle are attackers. For this reason, in this embodiment, after determining the movement directions of all the moving objects, the moving object whose movement direction is toward the defending object is determined as an attacker, and then the movement time of the attacker is acquired.
Step S300, acquiring electroencephalogram data acquired in the movement time, determining a current concentration value according to the electroencephalogram data, and generating a virtual defense barrier based on the current concentration value, wherein the virtual defense barrier is used for wrapping the defending object in an omnibearing manner, and the defense level of the virtual defense barrier is in direct proportion to the current concentration value.
Because in the specific concentration training process, after the attacker appears in the scene video, the user can see the attacker, and at the moment, concentration training can be started, and concentration is improved. Therefore, the reaction time of the user for concentration training, namely the time for improving the concentration can be determined according to the movement time of the attacker. Therefore, the electroencephalogram head ring of the embodiment can collect electroencephalogram data in the movement time, then the electroencephalogram data is sent to the terminal equipment, and the terminal equipment determines the current concentration value according to the electroencephalogram data. A virtual defensive barrier is then generated based on the current concentration value, the virtual defensive barrier being used to omnidirectionally wrap the defensive object to protect the defensive object. Wherein the defensive level of the virtual defensive barrier is proportional to the current concentration value. That is, the higher the concentration value, the higher the defense level of the generated virtual defense barrier, and the higher the defense level, the greater the defense of the virtual defense barrier.
In one implementation manner, the step S300 specifically includes the following steps:
step 301, a numerical interval corresponding to the current concentration value is obtained, and a defense level corresponding to the numerical interval is determined based on the numerical interval;
step S302, generating the virtual defense barrier based on the defense level.
The terminal device of the embodiment acquires the electroencephalogram data acquired by the electroencephalogram head ring in real time, and then matches the intensity information of the electroencephalogram data in real time with a preset concentration analysis table, wherein the concentration analysis table records the corresponding relation between concentration values and the intensity information of the electroencephalogram data. Thus, based on the concentration analysis table, a current concentration value may be determined. Since the electroencephalogram data of the user is changed in real time, the corresponding current concentration value is also changed in real time. In this embodiment, after determining the current concentration value, a numerical interval corresponding to the current concentration value is determined, and based on the numerical interval, a defense level corresponding to the numerical interval is determined. In this embodiment, different numerical intervals correspond to different defense levels reflecting the defensive power of the virtual defensive barrier. If the current concentration value is higher, the corresponding numerical interval is higher, and the corresponding defense level is higher. Next, the present embodiment generates the virtual defense barrier based on the defense level.
When the method is specifically applied, thickness information, color information and animation sound information of different defense levels are preset, wherein the thickness information, the color information and the animation sound information are used for generating a virtual defense barrier, the thickness information is the thickness of the virtual defense barrier, the color information is the color of the virtual defense barrier, and the animation sound information is the animation effect and the sound effect of the virtual defense barrier. When the defense level is higher, the corresponding thickness information is larger, the color information is deeper, the animation effect is more obvious, and the sound effect is louder. Therefore, the embodiment can acquire the determined defense level and thickness information, color information and animation sound information, and then generate the virtual defense barrier based on the determined thickness information, color information and animation sound information.
Step S400, obtaining the defensive force information of the virtual defensive barrier, and determining the concentration training effect based on the defensive force information.
When determining the defense level of the virtual defense barrier, the present embodiment may further determine the defense information of the virtual defense barrier based on the actual attack situation. This defensive information reflects the ability of the virtual defensive barrier to withstand attack by an attacker. Since the defensive power information is related to the current concentration value of the user, the present embodiment can determine the concentration training effect based on the defensive power information.
In one implementation manner, step S400 in this embodiment specifically includes the following steps:
step S401, obtaining damage degree information of the virtual defense barrier, and determining the defense force information based on the damage degree information, wherein the damage degree information is inversely proportional to the defense force information;
step S402, determining training scores of concentration training according to the defensive power information, and determining the concentration training effect based on the training scores.
Specifically, the embodiment may obtain the damage degree information of the virtual defense barrier, where the damage degree information is the damage degree of the virtual defense barrier caused by the attack of the attacker on the virtual defense barrier. The damage degree information of the present embodiment may be determined based on the color change of the virtual defense barrier, and since the higher the defense level of the virtual defense barrier, the deeper the corresponding color information, the lighter the corresponding color of the virtual defense barrier will become after the damage, so that the damage degree information can be estimated. In addition, the embodiment may also display cracks after the virtual defense barrier is attacked by an attacker, and if the more cracks on the virtual defense barrier are, the more damage degree information is correspondingly higher. Based on this, the present embodiment determines the damage degree information of the virtual defense barrier. Further, the present embodiment may determine the defending ability information based on the damaged degree information, wherein the damaged degree information is inversely proportional to the defending ability information. That is, when the degree of damage information of the virtual defense barrier is higher, the defensive power information is also lower. If the defensive power information of the virtual defensive barrier is lower, the current concentration value of the user is not high, so that the defensive level of the generated virtual defensive barrier is not high. In another implementation manner, after the attacker attacks the virtual defense barrier, the embodiment may further obtain the ejection distance of the attacker, determine the defense force information based on the ejection distance, and if the defense force information of the virtual defense barrier is higher, the ejection distance of the attacker is further. Thus, the ejection distance is proportional to the defensive power information.
Based on this, the present embodiment may determine a training score for concentration training based on the defensive power information, and when determining the training score, the present embodiment may first determine a value of the defensive power information, the value of the defensive power information being a percentage, the higher the defensive power information. Next, the present embodiment determines a training score corresponding to the percentage based on the percentage of the defensive power information, and the training score may be obtained by direct matching based on a mapping file between the preset defensive power information and the training score. Based on the training score, the present embodiment can intuitively determine the concentration training effect.
To sum up, the embodiment first obtains a scene video for performing concentration training, and determines a defending object based on the scene video, where the defending object is an object fixed in the scene video. Then, an attacker moving towards the defending object in the scene video is obtained, and the moving time of the attacker is obtained. And then, acquiring the electroencephalogram data acquired in the movement time, determining a current concentration value according to the electroencephalogram data, and generating a virtual defense barrier based on the current concentration value, wherein the virtual defense barrier is used for wrapping the defending object in an omnibearing manner, and the defense level of the virtual defense barrier is in direct proportion to the current concentration value. And finally, obtaining the defensive force information of the virtual defensive barrier, and determining the concentration training effect based on the defensive force information. The invention can establish the virtual defense barrier according to the concentration force to resist the attack of the attacker, has novel training mode, is beneficial to helping the user to train the concentration force and has better training effect.
Based on the above embodiment, the present invention further provides a concentration training device based on a virtual defense mechanism, as shown in fig. 2, where the device of this embodiment includes: defensive object determination module 10, movement time determination module 20, defensive barrier generation module 30 and concentration evaluation module 40. Specifically, the defending object determining module 10 in this embodiment is configured to acquire a scene video for performing concentration training, and determine a defending object based on the scene video, where the defending object is an object fixed in the scene video. The movement time determining module 20 is configured to obtain an attacker moving towards the defending object in the scene video, and obtain a movement time of the attacker. The virtual defense barrier generating module 30 is configured to acquire electroencephalogram data acquired during the exercise time, determine a current concentration value according to the electroencephalogram data, and generate a virtual defense barrier based on the current concentration value, where the virtual defense barrier is used for omnidirectionally wrapping the defending object, and the defense level of the virtual defense barrier is proportional to the current concentration value. The concentration evaluation module 40 is configured to obtain the defensive power information of the virtual defensive barrier, and determine the concentration training effect based on the defensive power information.
In one implementation, the defending object determination module 10 includes:
the picture analysis unit is used for carrying out picture preview on the scene video, analyzing the scene environment in the scene video and determining fixed objects in the scene environment;
and the object determining unit is used for taking the fixed object as the defending object.
In one implementation, the time determination module 20 includes:
the direction analysis unit is used for acquiring the moving objects around the defending object in real time and analyzing the moving direction of each moving object;
and the attacker determining unit is used for determining a moving object with the moving direction facing the defending object as an attacker and recording the moving time of the attacker.
In one implementation, the virtual defense barrier generation module 30 includes:
the grade determining unit is used for acquiring a numerical value interval corresponding to the current concentration value, and determining a defense grade corresponding to the numerical value interval based on the numerical value interval;
and the barrier generation unit is used for generating the virtual defense barrier based on the defense level.
In one implementation, the barrier generation unit includes:
the information acquisition subunit is used for acquiring thickness information, color information and animation sound effect information corresponding to the defense level;
and the barrier generation subunit is used for generating the virtual defense barrier based on the thickness information, the color information and the animation sound effect information.
In one implementation, the concentration assessment module 40 includes:
a defensive power information determining unit configured to acquire the degree of damage information of the virtual defensive barrier and determine the defensive power information based on the degree of damage information, wherein the degree of damage information is inversely proportional to the defensive power information;
and the training score determining unit is used for determining a training score of the concentration training according to the defensive power information and determining the concentration training effect based on the training score.
In one implementation, the concentration assessment module 40 includes:
and the defensive force analysis unit is used for acquiring the ejection distance of the attacker after the attacker attacks the virtual defensive barrier, and determining the defensive force information based on the ejection distance, wherein the ejection distance is in direct proportion to the defensive force information.
The working principle of each module in the concentration training device based on the virtual defense mechanism in this embodiment is the same as the principle of each step in the above method embodiment, and will not be repeated here.
Based on the above embodiment, the present invention also provides a terminal device, and a schematic block diagram of the terminal device may be shown in fig. 3. The terminal device may include one or more processors 100 (only one shown in fig. 3), a memory 101, and a computer program 102 stored in the memory 101 and executable on the one or more processors 100, e.g., a program based on concentration training of virtual defense mechanisms. The one or more processors 100, when executing the computer program 102, may implement the various steps in an embodiment of a method for virtual defense mechanism based concentration training. Alternatively, the functions of the modules/units in the apparatus embodiments of the virtual defense mechanism-based concentration training may be implemented by one or more processors 100 when executing computer program 102, without limitation.
In one embodiment, the processor 100 may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
In one embodiment, the memory 101 may be an internal storage unit of the electronic device, such as a hard disk or a memory of the electronic device. The memory 101 may also be an external storage device of the electronic device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) card, a flash card (flash card) or the like, which are provided on the electronic device. Further, the memory 101 may also include both an internal storage unit and an external storage device of the electronic device. The memory 101 is used to store computer programs and other programs and data required by the terminal device. The memory 101 may also be used to temporarily store data that has been output or is to be output.
It will be appreciated by persons skilled in the art that the functional block diagram shown in fig. 3 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the terminal device to which the present inventive arrangements are applied, and that a particular terminal device may include more or fewer components than shown, or may combine some of the components, or may have a different arrangement of components.
Those skilled in the art will appreciate that implementing all or part of the above-described methods may be accomplished by way of a computer program, which may be stored on a non-transitory computer readable storage medium, that when executed may comprise the steps of the embodiments of the methods described above. Any reference to memory, storage, operational database, or other medium used in embodiments provided herein may include non-volatile and/or volatile memory. The nonvolatile memory can include Read Only Memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual operation data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), memory bus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), among others.
In summary, the invention discloses a concentration training method, a device and a terminal device based on a virtual defense mechanism, wherein the method comprises the following steps: acquiring a scene video for concentration training, and determining a defending object based on the scene video, wherein the defending object is a fixed object in the scene video; acquiring an attacker moving towards a defending object in a scene video, and acquiring the moving time of the attacker; acquiring electroencephalogram data acquired in the movement time, determining a current concentration value according to the electroencephalogram data, and generating a virtual defense barrier based on the current concentration value, wherein the defense barrier is used for wrapping a defending object in all directions, and the defense level of the virtual defense barrier is in direct proportion to the current concentration value; and acquiring the defensive power information of the virtual defensive barrier, and determining the concentration training effect based on the defensive power information. The invention can establish the virtual defense barrier according to the concentration force to resist the attack of the attacker, has novel training mode and is beneficial to helping the user train the concentration force.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (7)
1. A method of concentration training based on a virtual defense mechanism, the method comprising:
acquiring a scene video for concentration training, and determining a defending object based on the scene video, wherein the defending object is a fixed object in the scene video;
acquiring an attacker moving towards the defending object in the scene video, and acquiring the moving time of the attacker;
acquiring electroencephalogram data acquired in the movement time, determining a current concentration value according to the electroencephalogram data, and generating a virtual defense barrier based on the current concentration value, wherein the virtual defense barrier is used for wrapping the defending object in an omnibearing manner, and the defense level of the virtual defense barrier is in direct proportion to the current concentration value;
acquiring the defensive force information of the virtual defensive barrier, and determining the concentration training effect based on the defensive force information;
the acquiring the electroencephalogram signal data acquired in the movement time and determining the current concentration value according to the electroencephalogram signal data comprises the following steps:
acquiring electroencephalogram data acquired by an electroencephalogram head ring in real time, and matching intensity information of the electroencephalogram data with a preset concentration analysis table, wherein the concentration analysis table records the corresponding relation between concentration values and the intensity information of the electroencephalogram data;
determining a current concentration value based on the concentration analysis table;
the generating a virtual defense barrier based on the current concentration value includes:
acquiring a numerical interval corresponding to the current concentration value, and determining a defense level corresponding to the numerical interval based on the numerical interval;
generating the virtual defense barrier based on the defense level;
the generating the virtual defense barrier based on the defense level includes:
acquiring thickness information, color information and animation sound effect information corresponding to the defense level;
generating the virtual defense barrier based on the thickness information, color information, and animation sound information;
the obtaining the defensive power information of the virtual defensive barrier, and determining the concentration training effect based on the defensive power information comprises the following steps:
obtaining damage degree information of the virtual defense barrier, and determining the defense force information based on the damage degree information, wherein the damage degree information is inversely proportional to the defense force information;
and determining a training score of concentration training according to the defensive power information, and determining the concentration training effect based on the training score.
2. The virtual defense mechanism-based concentration training method of claim 1 wherein the determining a defensive object based on the scene video comprises:
performing picture preview on the scene video, analyzing scene environments in the scene video, and determining fixed objects in the scene environments;
and taking the fixed object as the defending object.
3. The method for training focus based on virtual defense mechanism according to claim 1, wherein the steps of obtaining an attacker moving toward the defending object in the scene video and obtaining a movement time of the attacker include:
acquiring the defending objects in real time, and analyzing the motion direction of each moving object;
and determining a moving object with a moving direction towards the defending object as an attacker, and recording the moving time of the attacker.
4. The method of claim 1, wherein the obtaining the defensive power information of the virtual defensive barrier, determining the concentration training effect based on the defensive power information, further comprises:
and after the attacker attacks the virtual defense barrier, acquiring the ejection distance of the attacker, and determining the defense information based on the ejection distance, wherein the ejection distance is in direct proportion to the defense information.
5. An attentive training apparatus based on a virtual defense mechanism, the apparatus comprising:
the defending object determining module is used for acquiring a scene video for concentration training and determining defending objects based on the scene video, wherein the defending objects are objects fixed in the scene video;
the motion time determining module is used for acquiring an attacker which moves towards the defending object in the scene video and acquiring the motion time of the attacker;
the defense barrier generation module is used for acquiring the electroencephalogram data acquired in the movement time, determining a current concentration value according to the electroencephalogram data, and generating a virtual defense barrier based on the current concentration value, wherein the virtual defense barrier is used for wrapping the defending object in an omnibearing manner, and the defense level of the virtual defense barrier is in direct proportion to the current concentration value;
the concentration evaluation module is used for acquiring the defensive force information of the virtual defensive barrier and determining a concentration training effect based on the defensive force information;
the virtual defense barrier generation module is specifically configured to:
acquiring electroencephalogram data acquired by an electroencephalogram head ring in real time, and matching intensity information of the electroencephalogram data with a preset concentration analysis table, wherein the concentration analysis table records the corresponding relation between concentration values and the intensity information of the electroencephalogram data;
determining a current concentration value based on the concentration analysis table;
the virtual defense barrier generation module further includes:
the grade determining unit is used for acquiring a numerical value interval corresponding to the current concentration value, and determining a defense grade corresponding to the numerical value interval based on the numerical value interval;
a barrier generation unit configured to generate the virtual defense barrier based on the defense level;
the barrier generation unit includes:
the information acquisition subunit is used for acquiring thickness information, color information and animation sound effect information corresponding to the defense level;
a barrier generation subunit, configured to generate the virtual defense barrier based on the thickness information, the color information, and the animation sound effect information;
the concentration assessment module comprises:
a defensive power information determining unit configured to acquire the degree of damage information of the virtual defensive barrier and determine the defensive power information based on the degree of damage information, wherein the degree of damage information is inversely proportional to the defensive power information;
and the training score determining unit is used for determining a training score of the concentration training according to the defensive power information and determining the concentration training effect based on the training score.
6. A terminal device, characterized in that it comprises a memory, a processor and a virtual defense mechanism based concentration training program stored in the memory and executable on the processor, the processor implementing the steps of the virtual defense mechanism based concentration training method according to any one of claims 1-4 when executing the virtual defense mechanism based concentration training program.
7. A computer readable storage medium, wherein a virtual defense mechanism based concentration training program is stored on the computer readable storage medium, which when executed by a processor, implements the steps of the virtual defense mechanism based concentration training method of any one of claims 1-4.
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