CN114796790B - Brain training method and device based on electroencephalogram, intelligent terminal and storage medium - Google Patents
Brain training method and device based on electroencephalogram, intelligent terminal and storage medium Download PDFInfo
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M21/00—Other devices or methods to cause a change in the state of consciousness; Devices for producing or ending sleep by mechanical, optical, or acoustical means, e.g. for hypnosis
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/16—Devices for psychotechnics; Testing reaction times ; Devices for evaluating the psychological state
- A61B5/168—Evaluating attention deficit, hyperactivity
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/40—Detecting, measuring or recording for evaluating the nervous system
- A61B5/4058—Detecting, measuring or recording for evaluating the nervous system for evaluating the central nervous system
- A61B5/4064—Evaluating the brain
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7253—Details of waveform analysis characterised by using transforms
- A61B5/7257—Details of waveform analysis characterised by using transforms using Fourier transforms
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/70—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mental therapies, e.g. psychological therapy or autogenous training
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2503/00—Evaluating a particular growth phase or type of persons or animals
- A61B2503/06—Children, e.g. for attention deficit diagnosis
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61M—DEVICES FOR INTRODUCING MEDIA INTO, OR ONTO, THE BODY; DEVICES FOR TRANSDUCING BODY MEDIA OR FOR TAKING MEDIA FROM THE BODY; DEVICES FOR PRODUCING OR ENDING SLEEP OR STUPOR
- A61M2230/00—Measuring parameters of the user
- A61M2230/08—Other bio-electrical signals
- A61M2230/10—Electroencephalographic signals
Abstract
The invention discloses a brain training method, a brain training device, an intelligent terminal and a storage medium based on electroencephalogram, wherein the method comprises the following steps: acquiring electroencephalogram data of a user in real time, and acquiring a concentration score based on the electroencephalogram data; determining a brain training scheme according to the concentration score; wherein the brain training protocol is based on a number of computational subjects; wherein the calculation object is an object containing logical operation; and training the brain according to the brain training scheme. According to the embodiment of the invention, the concentration score is determined based on the electroencephalogram data of the user, so that a brain training scheme based on a plurality of calculation objects is determined, the brain is trained, the agility of the brain is improved, the training method is efficient, and the resource occupation is low.
Description
Technical Field
The invention relates to the technical field of electronic equipment, in particular to a brain training method and device based on electroencephalogram, an intelligent terminal and a storage medium.
Background
The human brain is divided into left and right brains, and there is a certain laterality in the human brain, i.e., the human brain is usually used to think about the left or right brain. Wherein the left brain governs abstract thinking, language, etc., and the right brain governs image thinking, music ability, etc.
Brain training has been used to improve memory and cognitive skills of users, training the brains of the elderly can improve the overall cognitive function and daily living ability of patients with Mild Cognitive Impairment (MCI) and dementia, training the brains of children can develop the potential of children, but the existing brain training methods are either artificial-based, have low efficiency, or are equipment-based, and have the problem of high resource occupancy rate.
Thus, there is a need for improvement and development of the prior art.
Disclosure of Invention
The invention aims to solve the technical problem that the brain training method based on electroencephalogram is provided aiming at overcoming the defects in the prior art, and aims to solve the problem that the brain training method in the prior art is either based on manpower and has low efficiency or based on equipment and has high resource occupancy rate.
The technical scheme adopted by the invention for solving the problems is as follows:
in a first aspect, an embodiment of the present invention provides a brain training method based on electroencephalogram, where the method includes:
acquiring electroencephalogram data of a user in real time, and acquiring a concentration score based on the electroencephalogram data;
determining a brain training regimen according to the concentration score; wherein the brain training protocol is based on a number of computational subjects; the calculation object is an object containing logical operation content;
and training the brain according to the brain training scheme.
In one implementation, the obtaining a concentration score based on the brain electrical data includes:
carrying out Fourier transformation on the electroencephalogram data to obtain a frequency spectrum corresponding to the electroencephalogram data;
and carrying out frequency analysis calculation on the frequency spectrum to obtain a concentration score corresponding to the electroencephalogram data.
In one implementation, the determining a brain training regimen from the concentration score includes:
determining a concentration level according to the concentration score;
and determining a brain training scheme according to the concentration grade.
In one implementation, the determining a brain training regimen from the concentration levels includes:
determining the number of calculation objects in brain training according to the concentration level;
and determining a layout scheme during brain training according to the quantity, and taking the layout scheme as a brain training scheme.
In one implementation, the determining, according to the quantity, a layout scheme in training a brain includes:
and distributing a plurality of the calculation objects corresponding to the number randomly in a target area.
In one implementation, the training the brain according to the brain training protocol includes:
when the attention point score reaches a preset threshold value and the duration of the attention point score reaching the preset threshold value is a preset first time threshold value, starting a timer and generating a plurality of calculation objects corresponding to the brain training scheme;
controlling the running tracks of a plurality of calculation objects in a target area based on a preset speed;
acquiring parameters input by a user in real time;
when the parameter is matched with any one of the calculation objects, eliminating the calculation object matched with the parameter, and generating a new calculation object at a preset position;
when the calculation object is overlapped with the edge of the target area, adjusting the area of a preset area;
and when the area of the preset area reaches a preset area threshold value or the timing time of the timer reaches a preset second time threshold value, stopping training the brain.
In one implementation, the training the brain according to the brain training protocol further comprises:
and after the brain training is stopped, determining the training score of the brain of the user according to the timing time of the timer and the eliminated calculation object.
In a second aspect, an embodiment of the present invention further provides a brain training device based on electroencephalogram, where the device includes: the acquisition module is used for acquiring electroencephalogram data of a user in real time and acquiring concentration scores based on the electroencephalogram data;
a plan determination module for determining a brain training plan based on the concentration score; wherein the brain training protocol is based on a number of computational subjects; the calculation object is an object containing logical operation content;
and the training module is used for training the brain according to the brain training scheme.
In one implementation, the obtaining a concentration score based on the electroencephalographic data includes:
carrying out Fourier transform on the electroencephalogram data to obtain a frequency spectrum corresponding to the electroencephalogram data;
and carrying out frequency analysis calculation on the frequency spectrum to obtain a concentration score corresponding to the electroencephalogram data.
In one implementation, the scheme determination module includes:
a concentration level determination module for determining a concentration level based on the concentration score;
and the scheme determining submodule is used for determining a brain training scheme according to the concentration level.
In one implementation, the scheme determination submodule includes:
the quantity determining module is used for determining the quantity of the calculation objects during brain training according to the concentration level;
and the layout determining module is used for determining a layout scheme during brain training according to the quantity and taking the layout scheme as a brain training scheme.
In one implementation, the determining, according to the quantity, a layout scheme in training a brain includes:
and distributing a plurality of the calculation objects corresponding to the number randomly in a target area.
In one implementation, the training module includes:
the generation module is used for starting a timer and generating a plurality of calculation objects corresponding to the brain training scheme when the attention point score reaches a preset threshold and the duration of the attention point score reaching above the preset threshold is a preset first time threshold;
the control module is used for controlling the running tracks of the plurality of calculation objects in the target area based on a preset speed;
the parameter acquisition module is used for acquiring parameters input by a user in real time;
the matching module is used for eliminating the calculation object matched with the parameter when the parameter is matched with any one calculation object, and generating a new calculation object at a preset position;
the adjusting module is used for adjusting the area of a preset area when the calculation object is overlapped with the edge of the target area;
and the training judgment module is used for stopping training the brain when the area of the preset area reaches a preset area threshold value or the timing time of the timer reaches a preset second time threshold value.
In one implementation, the training module further comprises:
and the score determining module is used for determining the score for training the brain of the user according to the timing time of the timer and the eliminated calculation object after the brain is stopped being trained.
In a third aspect, an embodiment of the present invention further provides an intelligent terminal, including a memory, and one or more programs, where the one or more programs are stored in the memory, and configured to be executed by one or more processors includes a computer program for executing the brain electrical brain training method according to any one of the above-mentioned embodiments.
In a fourth aspect, embodiments of the present invention also provide a non-transitory computer-readable storage medium, where instructions of the storage medium, when executed by a processor of an electronic device, enable the electronic device to perform the brain electrical training method according to any one of the above.
The invention has the beneficial effects that: firstly, acquiring electroencephalogram data of a user in real time, and acquiring a concentration score based on the electroencephalogram data; then determining a brain training scheme according to the concentration score; wherein the brain training protocol is based on a number of computational subjects; the calculation object is an object containing logical operation content; finally, training the brain according to the brain training scheme; therefore, the concentration score is determined based on the electroencephalogram data of the user, the brain training scheme based on a plurality of calculation objects is determined, the brain is trained, the brain agility is improved, the training method is efficient, and the resource occupation is low.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments described in the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a brain training method based on electroencephalogram according to an embodiment of the present invention.
Fig. 2 is a schematic block diagram of a brain training device based on electroencephalogram according to an embodiment of the present invention.
Fig. 3 is a schematic block diagram of an internal structure of an intelligent terminal according to an embodiment of the present invention.
Detailed Description
The invention discloses a brain training method, a brain training device, an intelligent terminal and a storage medium based on electroencephalogram, and in order to make the purpose, technical scheme and effect of the invention clearer and clearer, the invention is further described in detail below by referring to the attached drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
As used herein, the singular forms "a", "an", "the" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises" and/or "comprising," when used in this specification, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. It will be understood that when an element is referred to as being "connected" or "coupled" to another element, it can be directly connected or coupled to the other element or intervening elements may also be present. Further, "connected" or "coupled" as used herein may include wirelessly connected or wirelessly coupled. As used herein, the term "and/or" includes all or any element and all combinations of one or more of the associated listed items.
It will be understood by those skilled in the art that, unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the prior art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
In the prior art, the brain training method is based on manual work and has low efficiency, or based on equipment, and has the problem of high resource occupancy rate.
In order to solve the problems in the prior art, the embodiment provides a brain training method based on electroencephalogram, which determines concentration scores based on electroencephalogram data of a user, thereby determining a brain training scheme based on a plurality of calculation objects, and further training the brain to improve the agility of the brain, and the training method is efficient and low in resource occupation. When the method is specifically implemented, firstly, electroencephalogram data of a user are acquired in real time, and concentration scores are acquired based on the electroencephalogram data; then determining a brain training scheme according to the concentration score; wherein the brain training protocol is based on a number of computational subjects; the calculation object is an object containing logical operation content; and finally, training the brain according to the brain training scheme.
Exemplary method
The embodiment provides a brain training method and device based on electroencephalogram, an intelligent terminal and a storage medium. As shown in fig. 1 in detail, the method includes:
s100, acquiring electroencephalogram data of a user in real time, and acquiring a concentration score based on the electroencephalogram data;
specifically, electroencephalogram data of a user are acquired in real time and detected through a head ring worn on the head of the user, and a plurality of electrodes are arranged on the head ring and can detect the electroencephalogram data of the user. The electroencephalogram data reflects the concentration of the user or the concentration of the user's attention. Therefore, through analysis of the electroencephalogram data, a concentration score can be obtained.
In step S100, the obtaining a concentration score based on the electroencephalogram data includes:
carrying out Fourier transform on the electroencephalogram data to obtain a frequency spectrum corresponding to the electroencephalogram data;
and carrying out frequency analysis calculation on the frequency spectrum to obtain a concentration score corresponding to the electroencephalogram data.
Specifically, the electroencephalogram data may be subjected to fourier transform, that is, frequency domain conversion, so as to obtain a frequency spectrum corresponding to the electroencephalogram data, two waves, namely, a low beta wave and a high beta wave, exist in the frequency spectrum, and when the two wave energy values are relatively high, the state that a person is in a clear-headed focus and has no bystanders is represented, and the concentration score is relatively high, and the concentration score may be analyzed and calculated by using equipment in the prior art, for example, the interface of the friend science and technology brain 360 for brain wave monitoring, and the concentration score is seen.
After the concentration score is obtained, the following steps can be performed as shown in fig. 1: s200, determining a brain training scheme according to the concentration score; wherein the brain training protocol is based on a number of computational subjects; the calculation object is an object containing logical operation content;
in particular, the concentration score is high or low, which means that the attention level of the user is high or low, that is, the processing power of the user is different, and the scheme for training the brain of the user is different. In this embodiment, the brain training scheme is based on a plurality of calculation objects, and the calculation objects include logical operation contents, so that the brain of the user can be trained by the objects including the logical operation contents, and the agility of the brain can be improved. The logical operation content can be a calculation formula and can also be a question for logical reasoning.
Step S200 includes the steps of:
s201, determining concentration grade according to the concentration score;
and S202, determining a brain training scheme according to the concentration level.
In particular, concentration scores are very widely distributed, and if each concentration score corresponds to one brain training solution, the solutions are too numerous, resulting in a large amount of computation. In order to reduce the calculation amount, a plurality of concentration grades are determined according to the concentration score, for example, the concentration score is 65-75, the concentration grade is four, and the like; concentration score is 75-85, concentration grade is three, etc.; when the concentration score is 85-95, the concentration grade is two grade; concentration score of 95-100, concentration grade is first grade. After the concentration level is determined, a brain training scheme corresponding to the concentration level can be determined; that is, four concentration levels correspond to four brain training protocols.
Step S202 includes the steps of:
s2021, determining the number of calculation objects during brain training according to the concentration level;
s2022, determining a layout scheme during brain training according to the quantity, and taking the layout scheme as a brain training scheme.
Specifically, the high or low concentration level means the high or low ability of the user to handle the problem at this time, and therefore, when the concentration level of the user is high, a problem with high difficulty can be arranged for the user, and when the concentration level of the user is low, a problem with low difficulty can be arranged for the user. In this embodiment, the user with a high concentration level corresponds to a small number of calculation objects, and the user with a low concentration level corresponds to a large number of calculation objects. Thus, the layout scheme for brain training formed by different numbers of calculation objects is different, and the layout scheme is the brain training scheme.
In one implementation, the determining the layout scheme for training the brain according to the number includes the following steps: and distributing a plurality of the calculation objects corresponding to the number randomly in a target area.
In this embodiment, if the number of digits is 5, 5 calculation objects are randomly distributed in the target area; if the number of the calculation objects is 10, the 10 calculation objects are randomly distributed in the target area, so that the calculation objects with more calculation objects are inevitably distributed densely in the target area and the calculation objects with less calculation objects are inevitably distributed sparsely in the target area due to different numbers of the calculation objects, and thus, the distribution density or sparseness causes different training difficulty degrees for users in the subsequent brain training process.
After the brain training program is obtained, the following steps can be performed as shown in fig. 1: and S300, training the brain according to the brain training scheme.
Specifically, the difficulty degrees of brain training schemes corresponding to different numbers of calculation objects are different, so that targeted training can be performed according to different states where the user is located, if the user is high in concentration level, a high-difficulty brain training scheme is allocated to the user, so that the brain of the user can be further trained and promoted on the basis of the existing state, if the user is low in concentration level, the user cannot be trained and promoted if the high-difficulty brain training scheme is allocated to the user, the user cannot be trained and promoted.
Step S300 includes the steps of:
s301, when the attention point score reaches a preset threshold and the duration of the attention point score reaching the preset threshold is a preset first time threshold, starting a timer and generating a plurality of calculation objects corresponding to the brain training scheme;
s302, controlling the running tracks of the plurality of calculation objects in the target area based on a preset speed;
s303, acquiring parameters input by a user in real time;
s304, when the parameter is matched with any one of the calculation objects, eliminating the calculation object matched with the parameter, and generating a new calculation object at a preset position;
s305, when the calculation object is overlapped with the edge of the target area, adjusting the area of a preset area;
and S306, stopping training the brain when the area of the preset area reaches a preset area threshold value or the timing time of the timer reaches a preset second time threshold value.
In this embodiment, the logic operation content is a calculation formula, the system detects electroencephalogram data of the user in real time, obtains a concentration score according to the electroencephalogram data, starts a timer when the concentration score reaches a preset threshold (for example, 65 minutes) and the concentration score reaches a preset threshold or more, for example, a duration of 65 minutes or more is a preset first time threshold (for example, 10 seconds), and generates a plurality of calculation objects corresponding to the brain training scheme. The brain training scheme is different, and predetermined speed is different, and is that when user's concentration level is high, can be with predetermined speed turn up a little, when user's concentration level is low, can be with predetermined speed turn down a little to make brain training scheme correspond with user's different concentration level. And controlling a plurality of the calculation objects to move at a preset speed (such as 1 mm/s), wherein the calculation objects can move along the horizontal direction, can move along the vertical direction and can move along the oblique line direction. That is, a plurality of the computational objects are controlled to move within a target area (e.g., a screen in an electronic device) according to a preset trajectory based on a speed corresponding to a brain training program. In the process, the user answers in a mental calculation mode according to the logic operation content in the calculation object, and then the result is used as a parameter to be input into the display interface, for example, the parameter is input by clicking a corresponding key in a screen. When the input parameter is the result of the logical operation content in any one of the calculation objects, the parameter is judged to be matched with a certain calculation object, so that the calculation object matched with the parameter is eliminated, and a new calculation object is generated at a preset position (such as the top of a target area). When the calculation object is not eliminated in the moving process and moves to the edge of the target area (which may be the upper edge, the left edge, the right edge of the target area or the upper edge of the preset area at the bottom of the target area), the area of the preset area is adjusted to be increased or decreased. In this embodiment, when the calculation object is not eliminated during the movement and moves to the preset region, the area of the preset region is increased. Meanwhile, the area of the preset area is monitored, and once the area of the preset area reaches a preset area threshold value, the brain training is stopped, and the system program is stopped. In this embodiment, a preset area threshold is labeled in the target region, and once the area of the preset region exceeds the label, the brain training is stopped, the system program is stopped, and the user can re-adjust the state and enter the system again to perform brain training. In addition, when the timing time of the timer reaches a preset second time threshold (such as 9000 seconds), at this moment, the user has already completed a complete cycle of brain training, and has completed an effective training target, and at this moment, the difficulty in training the brain in the system can be adjusted, so as to achieve more effective training of the brain of the user.
In one implementation, the training the brain according to the brain training protocol further comprises the steps of: and after the brain training is stopped, determining the training score of the brain of the user according to the timing time of the timer and the eliminated calculation object.
Specifically, the brain is trained in 100 stages, and the training is gradually performed from the first stage to the 100 th stage at a time. The timer starts to count the eliminated calculation objects after the training of the brain is stopped, and the timing time of the timer at the moment, wherein the more the eliminated calculation objects are, the more effective the training of the brain of the user is, the higher the score is, and in the case of eliminating the same calculation objects, the shorter the timing time spent by the user is, the more effective the training of the brain of the user is, the higher the score is. When the brain training stage is stage 1, the number of eliminated calculation objects is a first number threshold (such as 50), and the timing time is greater than or equal to a preset time length (such as 90 s), the training score for the brain of the user is 0.5; when the stage of training the brain is stage 1, the number of the eliminated calculation objects is a first number threshold (for example, 50), and the timing time is less than a preset time length (for example, 90 s), the score of training the brain of the user is 1. When the brain training stage is stage 2, the number of eliminated calculation objects is a first number threshold (such as 50), and the timing time is greater than or equal to a preset time length (such as 90 s), the training score for the brain of the user is 1.5 points; when the brain training phase is the 2 nd phase, the number of eliminated calculation objects is the first number threshold (such as 50), and the timing time is less than the preset time (such as 90 s), the training score for the brain of the user is 2 minutes.. the like, and when the brain training phase is the 100 th phase, the number of eliminated calculation objects is the first number threshold (such as 50), and the timing time is greater than or equal to the preset first time (such as 90 s), the training score for the brain of the user is 99.5 minutes; when the brain training stage is the 100 th stage, the number of the eliminated calculation objects is the first number threshold (for example, 50), and the timing time is less than the preset time length (for example, 90 s), the training score for the brain of the user is 100 points.
In one implementation, when the concentration score reaches a preset standard concentration score (e.g., 85) and the time when the concentration score is greater than the preset standard concentration score is maintained for a preset second duration (e.g., 1 minute), a specific computing object is laid out in the target area, the specific computing object is different from the previously-appeared computing object and also contains logic operation contents, and when the parameters input by the user in a clicking manner are matched with the logic operation contents in the specific computing object, all the computing objects and the specific computing object in the target area are eliminated, so that the user can keep a continuous concentration level and perform special training on the continuous concentration of the brain of the user.
Exemplary device
As shown in fig. 2, an embodiment of the present invention provides a brain training apparatus based on electroencephalogram, which includes an acquisition module 401, a scheme determination module 402, and a training module 403:
the acquisition module 401 is configured to acquire electroencephalogram data of a user in real time and acquire a concentration score based on the electroencephalogram data;
a solution determination module 402 for determining a brain training solution based on the concentration score; wherein the brain training protocol is based on a number of computational subjects; the calculation object is an object containing logical operation content;
a training module 403, configured to train the brain according to the brain training scheme.
In one implementation, the obtaining a concentration score based on the brain electrical data includes:
carrying out Fourier transformation on the electroencephalogram data to obtain a frequency spectrum corresponding to the electroencephalogram data;
and carrying out frequency analysis calculation on the frequency spectrum to obtain a concentration score corresponding to the electroencephalogram data.
In one implementation, the scheme determination module includes:
a concentration level determination module for determining a concentration level based on the concentration score;
and the scheme determining submodule is used for determining a brain training scheme according to the concentration level.
In one implementation, the scheme determination submodule includes:
the quantity determining module is used for determining the quantity of the calculation objects during brain training according to the concentration level;
and the layout determining module is used for determining a layout scheme during brain training according to the quantity and taking the layout scheme as a brain training scheme.
In one implementation, the determining, according to the quantity, a layout scheme in training a brain includes:
and distributing a plurality of the calculation objects corresponding to the number randomly in a target area.
In one implementation, the training module includes:
the generation module is used for starting a timer and generating a plurality of calculation objects corresponding to the brain training scheme when the attention point score reaches a preset threshold and the duration of the attention point score reaching above the preset threshold is a preset first time threshold;
the control module is used for controlling the running tracks of the plurality of calculation objects in the target area based on a preset speed;
the parameter acquisition module is used for acquiring parameters input by a user in real time;
the matching module is used for eliminating the calculation object matched with the parameter when the parameter is matched with any one calculation object, and generating a new calculation object at a preset position;
the adjusting module is used for adjusting the area of a preset area when the calculation object is overlapped with the edge of the target area;
and the training judgment module is used for stopping training the brain when the area of the preset area reaches a preset area threshold value or the timing time of the timer reaches a preset second time threshold value.
In one implementation, the training module further comprises:
and the score determining module is used for determining the score for training the brain of the user according to the timing time of the timer and the eliminated calculation object after the brain is stopped being trained.
Based on the above embodiment, the present invention further provides an intelligent terminal, and a schematic block diagram thereof may be as shown in fig. 3. The intelligent terminal comprises a processor, a memory, a network interface, a display screen and a temperature sensor which are connected through a system bus. Wherein, the processor of the intelligent terminal is used for providing calculation and control capability. The memory of the intelligent terminal comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile storage medium. The network interface of the intelligent terminal is used for being connected and communicated with an external terminal through a network. The computer program is executed by a processor to implement a brain training method based on brain electrical activity. The display screen of the intelligent terminal can be a liquid crystal display screen or an electronic ink display screen, and the temperature sensor of the intelligent terminal is arranged inside the intelligent terminal in advance and used for detecting the operating temperature of internal equipment.
It will be understood by those skilled in the art that the schematic diagram in fig. 3 is only a block diagram of a part of the structure related to the solution of the present invention, and does not constitute a limitation to the intelligent terminal to which the solution of the present invention is applied, and a specific intelligent terminal may include more or less components than those shown in the figure, or combine some components, or have different arrangements of components.
In one embodiment, an intelligent terminal is provided that includes a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for:
acquiring electroencephalogram data of a user in real time, and acquiring a concentration score based on the electroencephalogram data;
determining a brain training regimen according to the concentration score; wherein the brain training protocol is based on a number of computational subjects; the calculation object is an object containing logical operation content;
and training the brain according to the brain training scheme.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile 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), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
In summary, the invention discloses a brain training method, a brain training device, an intelligent terminal and a storage medium based on electroencephalogram, wherein the method comprises the following steps: acquiring electroencephalogram data of a user in real time, and acquiring a concentration score based on the electroencephalogram data; determining a brain training regimen according to the concentration score; wherein the brain training protocol is based on a number of computational subjects; wherein the calculation object is an object containing logical operation; and training the brain according to the brain training scheme. According to the embodiment of the invention, the concentration score is determined based on the electroencephalogram data of the user, so that a brain training scheme based on a plurality of calculation objects is determined, the brain is trained, the agility of the brain is improved, the training method is efficient, and the resource occupation is low.
Based on the above embodiments, the present invention discloses a brain training method based on brain electricity, and it should be understood that the application of the present invention is not limited to the above examples, and it is obvious to those skilled in the art that modifications and variations can be made based on the above description, and all such modifications and variations should fall within the scope of the appended claims.
Claims (8)
1. A brain training device based on brain electricity, the device comprising:
the acquisition module is used for acquiring electroencephalogram data of a user in real time and acquiring concentration scores based on the electroencephalogram data;
a plan determination module for determining a brain training plan based on the concentration score; wherein the brain training protocol is based on a number of computational subjects; the calculation object is an object containing logical operation content;
the training module is used for training the brain according to the brain training scheme;
the training module comprises:
the generation module is used for starting a timer and generating a plurality of calculation objects corresponding to the brain training scheme when the attention point score reaches a preset threshold and the duration of the attention point score reaching above the preset threshold is a preset first time threshold;
the control module is used for controlling the running tracks of the plurality of calculation objects in the target area based on a preset speed; wherein the speed corresponds to a concentration level;
the parameter acquisition module is used for acquiring parameters input by a user in real time;
the matching module is used for eliminating the calculation object matched with the parameter when the parameter is matched with any one calculation object, and generating a new calculation object at a preset position;
the adjusting module is used for adjusting the area of a preset area when the calculation object is overlapped with the edge of the target area;
and the training judgment module is used for stopping training the brain when the area of the preset area reaches a preset area threshold value or the timing time of the timer reaches a preset second time threshold value.
2. The brain electrical based training device of claim 1, wherein said obtaining a concentration score based on said brain electrical data comprises:
carrying out Fourier transform on the electroencephalogram data to obtain a frequency spectrum corresponding to the electroencephalogram data;
and carrying out frequency analysis calculation on the frequency spectrum to obtain a concentration score corresponding to the electroencephalogram data.
3. The brain electrical based training device of claim 1, wherein the protocol determination module comprises:
a concentration level determination module for determining a concentration level based on the concentration score;
and the scheme determining submodule is used for determining a brain training scheme according to the concentration level.
4. The brain-electrical based training device of claim 3, wherein said protocol determination sub-module comprises:
the quantity determining module is used for determining the quantity of the calculation objects during brain training according to the concentration level;
and the layout determining module is used for determining a layout scheme during brain training according to the quantity and taking the layout scheme as a brain training scheme.
5. The brain electricity based brain training device according to claim 4, wherein the determining the layout scheme for training the brain according to the number comprises:
and distributing a plurality of the calculation objects corresponding to the number randomly in a target area.
6. The brain electrical based training device of claim 1, wherein said training module further comprises:
and the score determining module is used for determining the score for training the brain of the user according to the timing time of the timer and the eliminated calculation object after the brain is stopped being trained.
7. An intelligent terminal comprising a memory, and one or more programs, wherein the one or more programs are stored in the memory, and wherein the one or more programs configured to be executed by the one or more processors comprise instructions for execution by the brain electrical based brain training apparatus of any one of claims 1-6.
8. A non-transitory computer readable storage medium, wherein instructions in the storage medium, when executed by a processor of an electronic device, are adapted to be loaded and executed by a processor of an electroencephalogram based brain training apparatus of any one of claims 1-6.
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| CN116370788B (en) * | 2023-06-05 | 2023-10-17 | 浙江强脑科技有限公司 | Training effect real-time feedback method and device for concentration training and terminal equipment |
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