Attention training method based on semi-intrusive electroencephalogram signal and body posture capture

Abstract

The invention relates to an attention training method and device based on semi-intrusive electroencephalogram signals and body posture capture, electronic equipment and a storage medium. The method comprises the steps that electroencephalogram signals of a user are collected in real time, and the concentration degree is identified; body posture actions of the user are identified, and identified body posture data are sent to the interactive display module through the USB interface to be processed and displayed; the electroencephalogram signals and the concentration degree data are forwarded to the storage module in real time, and meanwhile the electroencephalogram data and the concentration degree data are sent to the interactive display module in real time; converting the body posture data into a direction control parameter for controlling the direction action of the interactive application normal form, and converting the concentration degree data into a speed control parameter for controlling the speed of the interactive application normal form; and feedback interaction training of the concentration degree is realized. According to the method, two technical means of semi-intrusive electroencephalogram signal and body posture capture are comprehensively applied, so that the attention of people is trained.

Description

Technical Field

[0001] The present disclosure relates to the field of electroencephalogram (EEG) signal processing, and more specifically, to an attention training method, device, electronic device, and computer-readable storage medium based on semi-invasive EEG signal and body posture capture. Background Art

[0002] In the medical field, traditional treatments often fail to achieve optimal therapeutic effects for certain neurological conditions, such as severe migraines, epilepsy, aphasia, and paralysis. This is particularly true for patients who require high-precision EEG signal acquisition, such as those undergoing craniotomy surgery to implant a brain-computer interface (BCI). Traditional non-invasive electroencephalography (EEG) methods, due to their limitations in signal acquisition, are no longer sufficient for clinical needs. With the advancement of BCI technology, semi-invasive BCIs offer a new solution. This technology utilizes sensors placed on the surface of the cerebral cortex, known as ECoG (electrocorticography), achieving "zero-distance" contact with the cerebral cortex, thereby acquiring more extensive and more accurate brain signals. Compared to non-invasive EEG, this semi-invasive EEG acquisition method can achieve higher signal strength and resolution while reducing the risk of immune response and nerve cell damage. Furthermore, for patients requiring craniotomy, such as those with quadriplegia, semi-invasive BCIs not only offer new treatment possibilities but also provide a preliminary solution for deep brain-computer integration. Through this interface, patients can control external devices, such as robotic arms, through "thoughts", perform daily activities, and significantly improve their quality of life.

[0003] The existing technical solutions have the following problems: traditional non-invasive EEG acquisition methods are not accurate enough in some cases, such as patients with severe migraines who need more precise EEG signal acquisition; single-type attention training is not effective; it is impossible to train multi-tasking capabilities; and it is impossible to train motor nerves.

[0004] Therefore, one or more methods are needed to solve the above problems.

[0005] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention

[0006] The purpose of the present disclosure is to provide an attention training method, device, electronic device and computer-readable storage medium based on semi-invasive EEG signal and body posture capture, thereby overcoming one or more problems caused by the limitations and defects of related technologies to at least some extent.

[0007] According to one aspect of the present disclosure, a method for attention training based on semi-invasive EEG signal and body posture capture is provided, comprising:

[0008] An EEG acquisition step collects the user's EEG signals in real time and identifies the user's concentration, and sends the EEG signals and concentration data to a communication module via wireless real-time communication;

[0009] The posture monitoring step identifies the user's posture movements and sends the identified posture data to the interactive display module through the USB interface for processing and display, and at the same time sends the posture data to the storage module;

[0010] a communication step of wirelessly receiving EEG signals and concentration data sent by the EEG acquisition module in real time, forwarding the EEG signals and concentration data to the storage module in real time, and also sending the EEG data and concentration data to the interactive display module in real time;

[0011] an interactive display step, receiving posture data sent by the posture monitoring module in real time, and converting the posture data into direction control parameters for controlling the direction movement of the interactive application paradigm; and simultaneously receiving concentration data sent by the communication module, and converting the concentration data into speed control parameters for controlling the speed of the interactive application paradigm;

[0012] In the feedback interaction training steps, users control the direction of the interaction paradigm by leaning forward, backward, turning left, turning right, and raising their hands, and control the speed of the interaction paradigm by focusing to complete the dynamic interaction tasks in the paradigm, thereby achieving feedback interaction training on concentration.

[0013] In an exemplary embodiment of the present disclosure, the EEG acquisition step of the method further includes:

[0014] Collect the user's EEG signals in real time and identify their concentration;

[0015] Normalizing the identified concentration into normalized concentration;

[0016] The brain electrical signal and the normalized concentration are sent to a communication device in real time via wireless.

[0017] In an exemplary embodiment of the present disclosure, the posture monitoring step of the method further includes:

[0018] The distance between the human body and the posture monitoring module is identified in real time, and whether the human body is in the interactive area is determined. If it is not in the interactive area, an invalid signal is sent to the interactive display module. If it is in the interactive area, a valid signal is sent to the interactive display module.

[0019] In an exemplary embodiment of the present disclosure, the method further includes:

[0020] If the human body is in the interactive area of the posture monitoring module, the posture monitoring module identifies the data of leaning forward, leaning back, turning left, turning right, and raising the right hand, and organizes the data into a frame of 5 bytes to be sent to the interactive display module and the storage module.

[0021] In an exemplary embodiment of the present disclosure, the communication step of the method further includes:

[0022] The communication module receives the EEG signals and concentration data and stores them in a stack, and counts them up by 1. When the count is greater than a preset number, the count is cleared and the preset number of EEG signals and concentration data are sent to the interactive display module and the storage module.

[0023] In an exemplary embodiment of the present disclosure, the interactive display step of the method further includes:

[0024] The interactive display module performs mean filtering on a preset number of received EEG signals;

[0025] Performing notch processing on a preset number of EEG signals and concentration data after mean filtering;

[0026] Splitting a preset number of EEG signals subjected to notch processing into a preset number of groups, and performing mean processing on the EEG signals in the preset number of groups;

[0027] If there is data greater than the preset threshold value in the preset number of groups of EEG signals that undergo mean processing, it is determined that the contact is poor. If there is no data greater than the preset threshold value in the preset number of groups of EEG signals that undergo mean processing, it is determined that the contact is good and the interactive training paradigm is started.

[0028] In an exemplary embodiment of the present disclosure, the method further includes:

[0029] In the interactive training paradigm, the concentration data is positively correlated with the speed, and the forward leaning, backward leaning, left turning, right turning and right hand raising are positively correlated with the forward, backward, left, right and start switches.

[0030] In one aspect of the present disclosure, there is provided an attention training device based on semi-invasive EEG signal and body posture capture, comprising:

[0031] An EEG acquisition module is used to collect the user's EEG signals in real time and identify the user's concentration, and send the EEG signals and concentration data to a communication device in real time via wireless;

[0032] The posture monitoring module is used to identify the user's posture movements and send the identified posture data to the interactive display module through the USB interface for processing and display, and at the same time send the posture data to the storage module;

[0033] The communication module is used to wirelessly receive the EEG signals and concentration data sent by the EEG acquisition module in real time, forward the EEG signals and concentration data to the storage module in real time, and also send the EEG data and concentration data to the interactive display module in real time;

[0034] an interactive display module, configured to receive in real time the posture data sent by the posture monitoring module and convert the posture data into direction control parameters for controlling the direction of the interactive application paradigm; and simultaneously receive the concentration data sent by the communication module and convert the concentration data into speed control parameters for controlling the speed of the interactive application paradigm;

[0035] The storage module is used to receive the posture data transmitted by the posture monitoring module and the EEG data and concentration data sent by the communication module in real time, and store them after time stamping.

[0036] In one aspect of the present disclosure, there is provided an electronic device, comprising:

[0037] processor; and

[0038] A memory having computer-readable instructions stored thereon, wherein the computer-readable instructions, when executed by the processor, implement the method according to any one of the above items.

[0039] In one aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the method according to any one of the above items is implemented.

[0040] An exemplary embodiment of the present disclosure provides an attention training method based on semi-invasive EEG signal and posture capture, wherein the method includes: an EEG acquisition step, which acquires the user's EEG signal in real time and identifies the concentration, and sends the EEG signal and concentration data to the communication module via wireless real-time; a posture monitoring step, which identifies the user's posture movements, and sends the identified posture data to the interactive display module via a USB interface for processing and display, and at the same time sends the posture data to the storage module; a communication step, which receives the EEG signal and concentration data sent by the EEG acquisition module via wireless real-time, and forwards the EEG signal and concentration data to the storage module in real time. block, and also sends EEG data and concentration data to the interactive display module in real time; interactive display step, receiving the posture data sent by the posture monitoring module in real time, and converting the posture data into direction control parameters for controlling the direction action of the interactive application paradigm, and at the same time receiving the concentration data sent by the communication module, and converting the concentration data into speed control parameters for controlling the speed of the interactive application paradigm; feedback interactive training step, the user controls the direction in the interactive paradigm through forward leaning, backward, left turn, right turn and hand raising movements of the body, and controls the speed in the interactive paradigm through concentration to complete the dynamic interactive tasks in the paradigm, thereby realizing feedback interactive training of concentration. The present disclosure realizes the training of human attention by comprehensively using two technical means: semi-invasive EEG signals and posture capture. Semi-invasive EEG signals can reflect the activity state of the brain, while posture capture captures and analyzes the posture of the human body. The combination of the two provides a new perspective and method for attention training.

[0041] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] The above and other features and advantages of the present disclosure will become more apparent by describing in detail example embodiments thereof with reference to the accompanying drawings.

[0043] Figure 1 A flowchart of an attention training method based on semi-invasive EEG signal and body posture capture according to an exemplary embodiment of the present disclosure is shown;

[0044] Figure 2 A structural block diagram of an attention training method based on semi-invasive EEG signal and body posture capture according to an exemplary embodiment of the present disclosure is shown;

[0045] Figure 3 A schematic diagram of an interactive training paradigm of an interactive display module of an attention training method based on semi-invasive EEG signals and body posture capture according to an exemplary embodiment of the present disclosure is shown;

[0046] Figure 4 A schematic block diagram of an attention training device based on semi-invasive EEG signal and body posture capture according to an exemplary embodiment of the present disclosure is shown;

[0047] Figure 5 A block diagram schematically illustrates an electronic device according to an exemplary embodiment of the present disclosure;

[0048] Figure 6 A schematic diagram schematically illustrates a computer-readable storage medium according to an exemplary embodiment of the present disclosure. DETAILED DESCRIPTION

[0049] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. Like reference numerals in the drawings represent like or similar parts, and thus repetitive description thereof will be omitted.

[0050] In addition, the described features, structures or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, many specific details are provided to provide a full understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that the technical solutions of the present disclosure can be practiced without one or more of the specific details, or other methods, components, materials, devices, steps, etc. can be adopted. In other cases, well-known structures, methods, devices, implementations, materials or operations are not shown or described in detail to avoid obscuring various aspects of the present disclosure.

[0051] The blocks shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically separate entities. Specifically, these functional entities may be implemented in software, or in one or more software-hardened modules, or in different networks and / or processor devices and / or microcontroller devices.

[0052] In this exemplary embodiment, a method for attention training based on semi-invasive EEG signals and body posture capture is first provided; Figure 1 As shown in , the attention training method based on semi-invasive EEG signal and body posture capture may include the following steps:

[0053] EEG acquisition step S110, collecting the user's EEG signals in real time and identifying the user's concentration, and sending the EEG signals and concentration data to the communication module in real time via wireless;

[0054] Posture monitoring step S120, identifying the user's posture movements, and sending the identified posture data to the interactive display module through the USB interface for processing and display, and at the same time sending the posture data to the storage module;

[0055] Communication step S130, receiving the EEG signal and concentration data sent by the EEG acquisition module in real time via wireless, forwarding the EEG signal and concentration data to the storage module in real time, and also sending the EEG data and concentration data to the interactive display module in real time;

[0056] Interactive display step S140, receiving posture data sent by the posture monitoring module in real time, and converting the posture data into direction control parameters for controlling the direction movement of the interactive application paradigm, and simultaneously receiving concentration data sent by the communication module, and converting the concentration data into speed control parameters for controlling the speed of the interactive application paradigm;

[0057] In the feedback interaction training step S150, the user controls the direction in the interaction paradigm by leaning forward, backward, turning left, turning right, and raising the hand, and controls the speed in the interaction paradigm by focusing to complete the dynamic interaction tasks in the paradigm, thereby realizing feedback interaction training on concentration.

[0058] An exemplary embodiment of the present disclosure provides an attention training method based on semi-invasive EEG signal and posture capture, wherein the method includes: an EEG acquisition step, which acquires the user's EEG signal in real time and identifies the concentration, and sends the EEG signal and concentration data to the communication module via wireless real-time; a posture monitoring step, which identifies the user's posture movements, and sends the identified posture data to the interactive display module via a USB interface for processing and display, and at the same time sends the posture data to the storage module; a communication step, which receives the EEG signal and concentration data sent by the EEG acquisition module via wireless real-time, and forwards the EEG signal and concentration data to the storage module in real time. block, and also sends EEG data and concentration data to the interactive display module in real time; interactive display step, receiving the posture data sent by the posture monitoring module in real time, and converting the posture data into direction control parameters for controlling the direction action of the interactive application paradigm, and at the same time receiving the concentration data sent by the communication module, and converting the concentration data into speed control parameters for controlling the speed of the interactive application paradigm; feedback interactive training step, the user controls the direction in the interactive paradigm through forward leaning, backward, left turn, right turn and hand raising movements of the body, and controls the speed in the interactive paradigm through concentration to complete the dynamic interactive tasks in the paradigm, thereby realizing feedback interactive training of concentration. The present disclosure realizes the training of human attention by comprehensively using two technical means: semi-invasive EEG signals and posture capture. Semi-invasive EEG signals can reflect the activity state of the brain, while posture capture captures and analyzes the posture of the human body. The combination of the two provides a new perspective and method for attention training.

[0059] Below, an attention training method based on semi-invasive EEG signal and body posture capture in this example embodiment will be further described.

[0060] Example 1:

[0061] In the EEG acquisition step S110 , the user's EEG signals can be acquired in real time and the concentration level can be identified, and the EEG signals and concentration level data can be sent to the communication module in real time via wireless.

[0062] In the embodiment of this example, the EEG acquisition step of the method further includes:

[0063] Collect the user's EEG signals in real time and identify their concentration;

[0064] Normalizing the identified concentration into normalized concentration;

[0065] The brain electrical signal and the normalized concentration are sent to a communication device in real time via wireless.

[0066] In the posture monitoring step S120, the user's posture movements can be identified, and the identified posture data can be sent to the interactive display module through the USB interface for processing and display, and the posture data can be sent to the storage module at the same time.

[0067] In the embodiment of this example, the posture monitoring step of the method further includes:

[0068] The distance between the human body and the posture monitoring module is identified in real time, and whether the human body is in the interactive area is determined. If it is not in the interactive area, an invalid signal is sent to the interactive display module. If it is in the interactive area, a valid signal is sent to the interactive display module.

[0069] In this exemplary embodiment, the method further includes:

[0070] If the human body is in the interactive area of the posture monitoring module, the posture monitoring module identifies the data of leaning forward, leaning back, turning left, turning right, and raising the right hand, and organizes the data into a frame of 5 bytes to be sent to the interactive display module and the storage module.

[0071] In the communication step S130, the EEG signals and concentration data sent by the EEG acquisition module can be received wirelessly in real time, and the EEG signals and concentration data can be forwarded to the storage module in real time. At the same time, the EEG data and concentration data can be sent to the interactive display module in real time.

[0072] In this exemplary embodiment, the communication step of the method further includes:

[0073] The communication module receives the EEG signals and concentration data and stores them in a stack, and counts them up by 1. When the count is greater than a preset number, the count is cleared and the preset number of EEG signals and concentration data are sent to the interactive display module and the storage module.

[0074] In the interactive display step S140, the posture data sent by the posture monitoring module can be received in real time, and the posture data can be converted into direction control parameters for controlling the directional movement of the interactive application paradigm. At the same time, the concentration data sent by the communication module can be received, and the concentration data can be converted into speed control parameters for controlling the speed of the interactive application paradigm.

[0075] In the embodiment of this example, the interactive display step of the method further includes:

[0076] The interactive display module performs mean filtering on a preset number of received EEG signals;

[0077] Performing notch processing on a preset number of EEG signals and concentration data after mean filtering;

[0078] Splitting a preset number of EEG signals subjected to notch processing into a preset number of groups, and performing mean processing on the EEG signals in the preset number of groups;

[0079] If there is data greater than the preset threshold value in the preset number of groups of EEG signals that undergo mean processing, it is determined that the contact is poor. If there is no data greater than the preset threshold value in the preset number of groups of EEG signals that undergo mean processing, it is determined that the contact is good and the interactive training paradigm is started.

[0080] In this exemplary embodiment, the method further includes:

[0081] In the interactive training paradigm, the concentration data is positively correlated with the speed, and the forward leaning, backward leaning, left turning, right turning and right hand raising are positively correlated with the forward, backward, left, right and start switches.

[0082] In the feedback interaction training step S150, the user can control the direction in the interaction paradigm by leaning forward, backward, turning left, turning right and raising the hand, and control the speed in the interaction paradigm by focusing to complete the dynamic interaction tasks in the paradigm, thereby realizing feedback interaction training on concentration.

[0083] In this exemplary embodiment, Figure 2 As shown, the attention training device disclosed in this disclosure and the attention training method based on semi-invasive EEG signals and body posture capture are designed to comprehensively improve the trainee's attention level and effectively enhance training efficiency. Compared with existing single concentration training systems, it has the following significant benefits:

[0084] 1. Simultaneous training of multiple types of attention: The present invention can simultaneously train multiple types of attention, including vision, hearing, and motor nerves, thereby effectively improving the trainee's comprehensive attention level.

[0085] 2. Improve multi-tasking ability: Through the training method of the present invention, the trainee can learn how to allocate and adjust attention when performing multiple tasks, thereby effectively improving the ability to handle multiple tasks simultaneously.

[0086] 3. Motor nerve training and improvement: This invention specifically trains motor nerves. Through posture capture technology, trainees can improve their motor coordination and reaction speed in games or specific tasks.

[0087] Example 2:

[0088] In this exemplary embodiment, Figure 3 As shown, the attention training method based on semi-invasive EEG signal and body posture capture disclosed in the present invention specifically includes:

[0089] 1. The semi-invasive EEG acquisition module accurately collects real-time EEG signals N1, normalizes the identified concentration into normalized concentration V1, and sends N1 and V1 to the communication module;

[0090] 2. The communication module receives N1 and V1 and stores them in the stack, and counts C1 plus 1. When C1 = 256, C1 is cleared and 256 N1 and V1 data are sent to the interactive display module and storage module;

[0091] 3. The posture monitoring module identifies the distance between the human body and the posture monitoring module in real time and determines whether the human body is in the interactive area. If not, it sends an invalid signal to the interactive display module. If so, it sends a valid signal to the interactive display module and identifies the five action data (forward leaning Q1, backward leaning H1, left turn Z1, right turn Y1, and right hand raising T1), forming a frame of 5 bytes of data and sending it to the interactive display module and storage module;

[0092] 4. The interactive display module receives 256 N1 EEG data and performs mean filtering, followed by notch processing to obtain 256 pure EEG data NC1. The 256 NC1 data are split into 16 identification groups of 16 data, and each group is averaged. As long as the mean of one group is greater than the threshold F, it is displayed that the contact is poor. When the means of all 16 groups are less than the threshold F, it is displayed that the contact is good, and the interactive training paradigm is started. In the interactive training paradigm, V1 is positively correlated with speed, and forward leaning Q1, backward leaning H1, left turn Z1, right turn Y1, and right hand raising T1 are positively correlated with front, back, left, right, and start.

[0093] 5. Users can control the direction of the interaction paradigm by leaning forward, backward, turning left, turning right, and raising their hands, and control the speed of the interaction paradigm by focusing to complete dynamic interaction tasks in the paradigm, thereby achieving feedback interaction training on concentration.

[0094] It should be noted that although the steps of the method disclosed herein are depicted in a particular order in the accompanying drawings, this does not require or imply that the steps must be performed in that particular order, or that all steps must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one, and / or one step may be decomposed into multiple steps.

[0095] In addition, in this exemplary embodiment, an attention training device based on semi-invasive EEG signal and body posture capture is also provided. Figure 4As shown, the attention training device 400 based on semi-invasive EEG signal and body posture capture may include: an EEG acquisition module 410, a body posture monitoring module 420, a communication module 430, an interactive display module 440 and a storage module 450.

[0096] in:

[0097] The EEG acquisition module 410 is used to collect the user's EEG signals in real time and identify the user's concentration, and send the EEG signals and concentration data to the communication device in real time via wireless;

[0098] The posture monitoring module 420 is used to identify the user's posture movements and send the identified posture data to the interactive display module through the USB interface for processing and display, and at the same time send the posture data to the storage module;

[0099] The communication module 430 is used to wirelessly receive the EEG signals and concentration data sent by the EEG acquisition module in real time, forward the EEG signals and concentration data to the storage module in real time, and also send the EEG data and concentration data to the interactive display module in real time;

[0100] The interactive display module 440 is configured to receive the posture data sent by the posture monitoring module in real time and convert the posture data into direction control parameters for controlling the direction of the interactive application paradigm. The interactive display module 440 is configured to receive the concentration data sent by the communication module and convert the concentration data into speed control parameters for controlling the speed of the interactive application paradigm.

[0101] The storage module 450 is used to receive the posture data transmitted by the posture monitoring module and the EEG data and concentration data sent by the communication module in real time, and store them after time stamping.

[0102] The specific details of each of the above-mentioned attention training device modules based on semi-invasive EEG signals and body posture capture have been described in detail in the corresponding attention training method based on semi-invasive EEG signals and body posture capture, so they will not be repeated here.

[0103] It should be noted that although several modules or units of an attention training device 400 based on semi-invasive EEG signal and body posture capture are mentioned in the above detailed description, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided to be embodied by multiple modules or units.

[0104] In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.

[0105] Those skilled in the art will appreciate that various aspects of the present invention may be implemented as systems, methods, or program products. Accordingly, various aspects of the present invention may be implemented as a complete hardware embodiment, a complete software embodiment (including firmware, microcode, etc.), or a combination of hardware and software embodiments, which may be collectively referred to herein as "circuits," "modules," or "systems."

[0106] Refer to the following Figure 5 An electronic device 500 according to such an embodiment of the present invention will be described. Figure 5 The electronic device 500 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0107] like Figure 5 As shown, electronic device 500 is implemented as a general-purpose computing device. Components of electronic device 500 may include, but are not limited to, the aforementioned at least one processing unit 510, the aforementioned at least one storage unit 520, a bus 530 connecting various system components (including storage unit 520 and processing unit 510), and a display unit 540.

[0108] The storage unit stores program codes, which can be executed by the processing unit 510, so that the processing unit 510 performs the steps according to various exemplary embodiments of the present invention described in the above “Exemplary Method” section of this specification. For example, the processing unit 510 can perform the following steps: Figure 1 Steps S110 to S150 shown in FIG.

[0109] The storage unit 520 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 5201 and / or a cache memory unit 5202 , and may further include a read-only memory unit (ROM) 5203 .

[0110] The storage unit 520 may also include a program / utility 5204 having a set (at least one) of program modules 5205, such program modules 5205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0111] Bus 530 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0112] The electronic device 500 can also communicate with one or more external devices 570 (e.g., a keyboard, a pointing device, a Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 500, and / or any device that enables the electronic device 500 to communicate with one or more other computing devices (e.g., a router, a modem, etc.). Such communication can occur via an input / output (I / O) interface 550. Furthermore, the electronic device 500 can communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 560. As shown, the network adapter 560 communicates with other modules of the electronic device 500 via a bus 530. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device 500, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0113] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0114] In exemplary embodiments of the present disclosure, a computer-readable storage medium is also provided, storing a program product capable of implementing the aforementioned methods of this specification. In some possible embodiments, various aspects of the present invention may also be implemented in the form of a program product comprising program code. When the program product is executed on a terminal device, the program code is configured to cause the terminal device to perform the steps according to various exemplary embodiments of the present invention described in the "Exemplary Methods" section of this specification.

[0115] refer to Figure 6 , a program product 600 for implementing the above-described method according to an embodiment of the present invention is described. The program product 600 may be a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium may be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0116] The program product may be implemented in any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or component, or any combination thereof. More specific examples (a non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination thereof.

[0117] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0118] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0119] The program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages such as Java, C++, and the like, as well as conventional procedural programming languages such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0120] Furthermore, the above-described figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention and are not intended to be limiting. It is readily understood that the processes illustrated in the above-described figures do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0121] Other embodiments of the present disclosure will readily occur to those skilled in the art after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow from the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the claims.

[0122] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for attention training based on semi-invasive EEG signals and body posture capture, characterized in that: The method comprises: An EEG acquisition step collects the user's EEG signals in real time and identifies the user's concentration, and sends the EEG signals and concentration data to a communication module via wireless real-time communication; The posture monitoring step identifies the user's posture movements and sends the identified posture data to the interactive display module through the USB interface for processing and display, and at the same time sends the posture data to the storage module; a communication step of wirelessly receiving EEG signals and concentration data sent by the EEG acquisition module in real time, forwarding the EEG signals and concentration data to the storage module in real time, and also sending the EEG data and concentration data to the interactive display module in real time; an interactive display step, receiving posture data sent by the posture monitoring module in real time, and converting the posture data into direction control parameters for controlling the direction movement of the interactive application paradigm; and simultaneously receiving concentration data sent by the communication module, and converting the concentration data into speed control parameters for controlling the speed of the interactive application paradigm; In the feedback interaction training steps, users control the direction of the interaction paradigm by leaning forward, backward, turning left, turning right, and raising their hands, and control the speed of the interaction paradigm by focusing to complete the dynamic interaction tasks in the paradigm, thereby achieving feedback interaction training on concentration.

2. The method according to claim 1, wherein The EEG acquisition step of the method further includes: Collect the user's EEG signals in real time and identify their concentration; Normalizing the identified concentration into normalized concentration; The brain electrical signal and the normalized concentration are sent to a communication device in real time via wireless.

3. The method according to claim 1, wherein The posture monitoring step of the method further includes: The distance between the human body and the posture monitoring module is identified in real time, and whether the human body is in the interactive area is determined. If it is not in the interactive area, an invalid signal is sent to the interactive display module. If it is in the interactive area, a valid signal is sent to the interactive display module.

4. The method according to claim 3, wherein The method further comprises: If the human body is in the interactive area of the posture monitoring module, the posture monitoring module identifies the data of leaning forward, leaning back, turning left, turning right, and raising the right hand, and organizes the data into a frame of 5 bytes to be sent to the interactive display module and the storage module.

5. The method according to claim 1, wherein The communication step of the method further includes: The communication module receives the EEG signals and concentration data and stores them in a stack, and counts them up by 1. When the count is greater than a preset number, the count is cleared and the preset number of EEG signals and concentration data are sent to the interactive display module and the storage module.

6. The method according to claim 5, wherein The interactive display step of the method further includes: The interactive display module performs mean filtering on a preset number of received EEG signals; Performing notch processing on a preset number of EEG signals and concentration data after mean filtering; Splitting a preset number of EEG signals subjected to notch processing into a preset number of groups, and performing mean processing on the EEG signals in the preset number of groups; If there is data greater than the preset threshold value in the preset number of groups of EEG signals that undergo mean processing, it is determined that the contact is poor. If there is no data greater than the preset threshold value in the preset number of groups of EEG signals that undergo mean processing, it is determined that the contact is good and the interactive training paradigm is started.

7. The method according to claim 6, wherein The method further comprises: In the interactive training paradigm, the concentration data is positively correlated with the speed, and the forward leaning, backward leaning, left turning, right turning and right hand raising are positively correlated with the forward, backward, left, right and start switches.

8. An attention training device based on semi-invasive EEG signal and body posture capture, characterized in that: The device comprises: An EEG acquisition module is used to collect the user's EEG signals in real time and identify the user's concentration, and send the EEG signals and concentration data to a communication device in real time via wireless; The posture monitoring module is used to identify the user's posture movements and send the identified posture data to the interactive display module through the USB interface for processing and display, and at the same time send the posture data to the storage module; The communication module is used to wirelessly receive the EEG signals and concentration data sent by the EEG acquisition module in real time, forward the EEG signals and concentration data to the storage module in real time, and also send the EEG data and concentration data to the interactive display module in real time; an interactive display module, configured to receive in real time the posture data sent by the posture monitoring module and convert the posture data into direction control parameters for controlling the direction of the interactive application paradigm; and simultaneously receive the concentration data sent by the communication module and convert the concentration data into speed control parameters for controlling the speed of the interactive application paradigm; The storage module is used to receive the posture data transmitted by the posture monitoring module and the EEG data and concentration data sent by the communication module in real time, and store them after time stamping.

9. An electronic device, characterized in that: include processor; and A memory having computer-readable instructions stored thereon, wherein the computer-readable instructions are executed by the processor to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that A computer program is stored thereon, and when the computer program is executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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