RU2698994C1 - Digital training complex for preparing for promising occupations in neurophysiology - Google Patents

Abstract

FIELD: psychophysiology.

SUBSTANCE: invention relates to the field of pedagogics, in particular to training facilities for preparation for promising occupations in the field of psychophysiology, neurophysiology and specialties in the field of neurotechnologies. Disclosed is a digital training system, which includes workstations of trainees with network computers and software, a server with software and means of communication of workstations of trainees with a server, which combine them into a local network. Each workstation of a trainee includes a neuro-headset, a headset and an engineering constructor, trainee computers comprise software, which includes a protocol network interface module, an automatic system update module, a network devices and functions scanning module, a CRM module, network address conversion module, a module for controlling functions and settings, a user interface module of different levels, a module for storing and archiving data, a module of access and safety rules, a statistics module, a module for acquaintance with the system functional, which implement algorithms for pairing workstations with external devices, a server and an Internet network, algorithms for executing training tasks, collecting and storing data, wherein the server software includes a remote calculation module and a database of the obtained results.

EFFECT: invention provides higher efficiency of training and assimilation of educational material.

6 cl, 10 dwg

Description

The invention relates to the field of pedagogy, in particular, to teaching aids for preparing for promising professions in the field of psychophysiology, neurophysiology and specialties in the field of neurotechnology.

In the modern educational process, computer technologies occupy more and more place. Various technical solutions are known in the art.

For example, the utility model “Real-time learning system” according to the patent RU 106016. The well-known utility model generally relates to the field of organization of training in the classroom with the help of a specially developed electronic educational system that allows to increase the effectiveness of collaborative learning. The system contains workstations with students' computers and means for displaying information for students in group perception mode. Trainees 'computers are connected via the Internet or WI-FI connection to the server with a software product for training and communication, the server is connected by direct and feedback to a user database containing media content, while trainees' computers have two touch screens, and to the system through The Internet or WIFI connection to the server is turned on by the teacher’s computer. Moreover, the means of displaying information for students in the group perception mode are connected to the teacher’s computer, and the server is also connected to the administrator’s computer via the Internet or WI-FI connection.

This system is designed to teach the school curriculum and does not imply training in any additional courses.

A technical solution is known “A method of teaching and mastering educational material and a device for its implementation” according to patent RU 2357294, related to the field of pedagogy, in particular to methods of using visual and sound demonstration of material to be studied. Information transfer of educational material is carried out simultaneously with additional information, receiving it in real time. The teacher coordinates the actions of students aimed at the assimilation of supplemented information. Trainees save training material on storage media of the student’s workplace. Between trainers establish a permanent connection, providing the ability to exchange messages. The workplace of the student includes subjects for studying the discipline, equipped with video cameras of video broadcasting networks and control and measuring devices, means of information display and servers, combined by means of communication in local networks. The additional server is connected by means of communication with additional servers of other disciplines in a broadcast network, configured to connect to other broadcast networks. The training server is configured to connect through communication tools to other servers teaching this discipline. The technical result of the invention is the expansion of the knowledge base used in the learning process. This technical solution was made by the authors for the prototype.

The known device does not provide training opportunities for students in promising professions in the field of psychophysiology, neurophysiology and specialties in the field of neurotechnology.

Neurophysiology is a branch of physiology that studies the functions of the nervous system and its basic structural units - neurons. Neurophysiology is closely connected with neurobiology, neurology, clinical neurophysiology, psychology, neuroanatomy and other sciences that study the brain.

Knowledge of the basics of neurophysiology is used in the development of artificial intelligence systems, in the development of mathematical models of the nervous system and brain, and can also help in marketing and many other areas. This is currently the most promising and sought-after area of study.

There are various courses for teaching neurophysiology. (e.g. https://www.inlearno.ru/event/4449-obuchayushchii-kurs-neirofiziologiya).

The BITRONICS LAB production set is also known (http://www.bitronicslab.com/, https://nanojam.ru/products/nabor-konstruktor-iunyi-neiromodelist-bitronics-lab), as well as various gadgets for measuring various physiological parameters of a person manufactured by BioRadio (http://glneurotech.com/bioradio/wp-content/uploads/2014/08/Note_BioCapture-EEG.pdf).

All known devices are limited in their functionality. They allow you to remove only a small number of physiological parameters of a person, on the basis of which it is impossible to get a complete picture of the activity of the brain, its structure and the application of this knowledge in learning and real life.

Thus, at present, there are no universal training complexes providing a ready-made solution designed for the purpose of early career guidance and with the possibility of organizing both the educational process and research activities in psychophysiology, neurophysiology and specialties in the field of neurotechnology.

It is to solve this technical problem that the creation of the proposed digital training complex is aimed at preparing for promising professions in the field of neurophysiology.

The technical result is to increase the effectiveness of training and assimilation of information of educational material, due to the fact that:

- the proposed complex is designed for 67 lessons, includes 12 sections that allow you to study the physiology of cardiac activity, bioelectrical activity of living organisms, explain why the heart beats and how it works;

- in the classroom studies the muscle activity of a person, nerve conduction, the structure and conductivity of the skin and its resistance;

- during a series of classes, acquaintance and study of the structure and functions of the human brain, bioelectric activity of the brain, the structure of the neural network, the principles of EEG removal (electroencephalogram);

- in the course of studying educational material about human brain activity, a great emphasis is placed on the study of basic rhythms, active mental activity. The student in the learning process will be able to form the basic skills for creating interactive classifiers, to study the basics of psychophysiology and the functional state of a person, on which the effectiveness of human activity depends, including the concept of biological feedback (BFB) and teaching BFB in practice;

- part of the sections is devoted to acquaintance with modern technologies, including augmented and virtual realities, principles of control in two-and three-dimensional spaces, bionics and neuroprogramming, as well as technologies related to neurocomputer interfaces;

- the last section involves conducting an expert system of a comprehensive analysis of the personality (author developed methods aimed at determining professionally important qualities and career guidance of students).

Using the proposed complex, you can carry out the following laboratory work:

- research in the field of neurophysiology, including indications of heart rate, building the individual axis of the child’s heart, biorhythms, pulse, skin resistance, bioelectric muscle activity, etc .;

- the formation of competencies of engineers and programmers (while working with robotic designs and neuroinstallations, children will gain knowledge of cybernetics, and will also be able to control models using heart rate, brain activity, muscle electrical activity potential, skin resistance readings, by programming developed authorial neuroinstallations or by collecting models for the provided samples of assembly cards in accordance with the theme of the lesson);

- the development or assembly of robotic structures, neuroinstallations, will allow you to study brain signals, the structure of the heart, as well as gain knowledge from the field of cybernetics (neuroprogramming), modern high technologies, get acquainted with the principle of virtual and augmented reality, artificial intelligence.

Students also have the opportunity to work in an individual notebook, all created notes for the lesson can be viewed remotely from portable devices outside the classroom.

The technical result is achieved due to the fact that in a digital training complex for preparing for promising professions in the field of neurophysiology, which includes workplaces for students with network computers, a server and communication tools for workplaces of students with a server, combining them into a local network, each workplace of a student includes a neuro headset, an electric headset, and an engineering designer, students' computers contain software that includes a protocol network interface module, a mode automatic updating of the system, a module for scanning network devices and functions, a CRM module (Customer Relationship Management), a module for converting network addresses, a module for managing functions and settings, a user interface module for various levels, a module for storing and archiving data, a module for access and security rules, a module statistics module acquaintance with the functionality of the system, which  implement algorithms for pairing workstations with external devices, a server and the Internet, algorithms for completing training tasks, collecting and storing data. The server software includes a remote computing module and a database of the results.

Additional features of the complex are:

- the neuro headset includes sensors for detecting electroencephalographic signals with dry type electrodes placed on a helmet worn on the student’s head, and a signal amplifier,

- sensors mounted on the helmet with the ability to change location to provide the ability to pick up signals from various parts of the brain,

- the neuro headset is connected to the workplace of the learner by wireless,

- the amplifier consists of a serially connected input block of the amplifier with a lead electrode, a switch block, a low-noise amplifier block, an amplitude limiter block with a low-pass (LF) filter and a multi-channel analog-to-digital converter (ADC) block, while the switch block is connected to the impedance meter block, and also with reference and neutral electrodes through the negative feedback block (OOS), moreover, the negative feedback block for small noise is connected in parallel to the low-noise amplifier block yaschego amplifier with a suppression circuit 50 Hz,

- as the engineering designer, the Robotic Track Basic, the Robot Track Color TFT Display Resource Kit, the Audio Sensors Robot Track Resource, the Audio Track Robot Track Resource Kit, the Worm Gear Robot Track Resource, and the Energy Track Robot Track Resource Kit were used , resource set Robotrek "Energy-mini",

 - the electric headset includes an EMG sensor (electromyograms), an ECG sensor (electrocardiograms), a RAG sensor (galvanic skin reaction), and a PPG sensor (photoplethysmograms) located in one housing.

The invention is illustrated by the following figures:

Figure 1, which shows a block diagram of the educational complex.

Figure 2, which shows a block diagram of the amplifier of the neuro headset.

Figure 3. which shows the frequency response of the first stage of the EEG amplifier.

Figure 4-10, which shows the engineering designer - Robotrek “Basic” and resource kits: Robotrack “Color TFT display”, Robotrack “Sensors”, Robotrack “Audiotrack”, Robotrek “Worm gear”, Robotrek “Energitrek”, Robotrek “ Energy Track Mini ",

Positions in the drawings:

1 ₁ - 1 _n jobs of students,

2 - neuro headset,

3 - electric headset

4 - engineering designer,

5 - software workplace students

6 - server

7 - module remote computing and a database of the results,

8 - block environmental protection,

9 - input unit of the amplifier,

10 - switch unit,

11 - block low-noise amplifier

12 - block amplitude limiter,

13 - block multi-channel analog-to-digital Converter ADC,

14 - block OOS for low-noise amplifier with a suppression circuit 50Hz,

15 - impedance meter block,

16 - lead electrode,

17 - reference electrode,

18 - the electrode is neutral.

Workplace 1 of the student is organized on the basis of a personal computer, which is connected by a local network to server 6. The personal computer is supplemented by software 5 of the workplace of students. This software received a certificate for computer program No. 2016565354 "Technical complex for preparing for promising professions in neurophysiology, including modules: network interface protocols, automatic system updates, scanning network devices and functions, CRM, network address translation, network address and function management , user interfaces of different levels, data storage and archiving, access and security rules, statistics, familiarity with the system’s functionality. ”

The program is designed to automate all aspects of the main educational activities in preparing students for new promising professions. The system provides information support for all tasks to be solved within the framework of an educational program aimed at the subject under consideration. The software part includes the protocol network interface module, the system automatic updating module, the network devices and functions scanning module, the CRM module, the network address translation module, the functions and settings management module, the user interface module of different levels, the data storage and archiving module, the access rule module and security module statistics module familiarity with the functionality of the system, which  implement algorithms for pairing workstations with external devices, a server and the Internet, as well as algorithms for completing training tasks, collecting and storing data.

A certificate for computer program No. 2018665878 “Technical complex for preparing for promising professions in neurophysiology, including a remote computing module” was received for module 11 of remote computing and a database of the results obtained installed on the server.

The program is designed to ensure the operation of complex computational algorithms during educational activities in preparing students for new promising professions. The software part solves the following tasks: ensuring the operation of complex computational algorithms in real time with available access to the network; providing access to a central database for storing user signal records.

An electro- headset (EG) 3 provides registration of an electrocardiogram in one lead, electromyogram in two channels, photoplethysmogram and skin-galvanic reaction in one channel, as well as a combination of these signals and an EEG signal recorded by a neuro headset in printing mode. ECG, EMG and RAG registration sensors are installed on the human body and connected to the EG using connecting wires. The photoplethysmographic sensor is integrated directly into the EG and for the experiment it is necessary to put a finger on the side of the EG to the photoplethysmographic sensor. Also, a nine-axis inertial sensor is built into the EG, which allows you to control the position of the EG in space. The transmission of biosignals recorded by the EG to a PC or other device can be carried out via Wi-Fi or via USB. The EG has a built-in display on which the control interface is displayed, or a registered biosignal. EG is powered by a built-in battery.

EG registers the above biosignals for educational purposes only. The use of registered biosignals for medical purposes is not provided.

An electric headset consists of the following components:

- ADC-7984

- display - WF52ASLASDNGO

- controller - STM32F765
- CPLD digital integrated circuit - LCMX02-7000HC ( https://spb.terraelectronica.ru/product/2177706 )

-5 TouchProof sockets for connecting sensors - Din sockets 1.5 mm socket for RAG, ECG, EMG.

- micro USB connector for connecting to a computer.

Neuro headset

The following items are included in the neuro-headset kit:

1. The amplification unit of the neuro headset,

2. Dry electrodes of at least 8 pcs. for registration of an EEG,

3. Reference EEG electrodes - at least 2 pcs.,

4. Ground electrode - 1 pc.,

5. Set of 5 V rechargeable battery with micro USB,

6. Mounting system for the head and shoulder,

7. microUSB - USB for connecting the amplifier unit to a computer.

The amplification unit of the neuro headset is designed to record the bioelectrical activity of the brain through the connected EEG electrodes and further process and transmit the surface EEG or signals obtained on its basis to a PC or device that replaces it.

The neuro headset amplifier must have both high sensitivity and high noise immunity. The sensitivity should be at a level of 1 μV for possible input-induced network interference of up to 0.5 V, even in the presence of special suppression circuits by means of additional electrodes on the patient's body. The resistance of the electrode contact with the patient’s body in the case of “dry” electrodes lies in the range of 50-500 kOhm in the case of 6-8 contact protrusions in one electrode (average value √50 • 500 = 158 kOhm).

A sensitivity of 1 μV corresponds to the intrinsic noise of the amplifier, reduced to its input, at a level of 0.3 μV in the band from 1 to 30 Hz. This frequency band refers to infra-low frequencies, which are characterized by the manifestation of a specific “1 / f” noise, also called “pink” noise or “flicker noise”. Because of this, when designing an EEG amplifier, it is imperative to look at the noise characteristics at infralow frequencies and choose not only noise, but also the parameter '' 1 / f corner frequency '' - the transition frequency from noise of type “1 / f” to uniform white noise. One of the best amplifiers in this frequency domain is the AD8672, whose noise in the 0.1-10 Hz band is 77 nV p-p, and the '' 1 / f corner frequency '' is 1 Hz. The differential input impedance of the AD8672 is 15 MΩ, which is acceptable for a signal source with a resistance of 158 kΩ.

50 Hz mains suppression must be carried out in the first stage of the amplifier in order to obtain a large gain without introducing the amplifier into saturation from large interference. This can be done if frequency-corrected feedback is introduced into the amplifier so that there is no gain at 50 Hz (see Fig. 3).

In the proposed scheme, to suppress the gain of 50 Hz, the OOS (negative feedback) of the first stage is used, in the circuit of which a notch 2-T bridge is included. The equivalent resistance of the OOS circuit at a frequency of 50 Hz drops sharply, resulting in a decrease in the overall gain. The amount of gain reduction depends on the spread in the values of the 2-T bridge components (resistors and capacitors). For a typical 5% range, the notch will be about 40 dB (see Analog Devices - Twin T Notch Filter, Mini Tutorial (MT-225).

The gain must be made more than 100 (40 dB), which will allow to realize the minimum noise characteristics of the amplifiers used. When the gain is increased above 100, the noise, although it decreases, is very insignificant. The proposed amplifier has a gain of approximately 316 times (50 dB). Given the depth of rejection of 50 Hz at about -40 dB, it turns out that 50 Hz interference is also amplified, not only 310 times, but only 3.16 times. To prevent the signal limiting mode from arising with such amplification, the input amplifier is powered by an increased supply voltage of ± 10 V, which allows working with 50 Hz interference up to ± 1.5 V (with a margin).

The block diagram of the amplifier is shown in figure 2. To create the proposed scheme, the following element base can be used:

Block 8 OOS for “binding” the potential of the circuit earth to the potential of the human body - RLD scheme on OPA2140AID,

The input unit 9 of the amplifier is ESD Protection, OverVoltage Protection is BAV99,

Block 10 switch modes of operation of the gain channel - ADG5209BRUZ,

Block 11 low-noise amplifier - AD8672ARZ,

Block 12 amplitude limiter with low-pass filter - BAV99,

Block 13 of the multi-channel ADC - ADS1299IPAG,

Block 14 OOS for low-noise amplifier with a 50 Hz suppression circuit -

2-T bridge on the AD8244BRMZ + integrator on the AD8622ARZ,

Block 15 of the impedance meter - AD5933YRSZ + channel switches on the ADG728BRUZ + output and input amplifiers on the AD8622ARZ.

Sensors DF6.17 are used (manufactured by Engineering Center Complex-M LLC, passport TRVC.301241.001PS). The sensor housing is made of injection molded polyamide 610 GOST 10589-87. In the upper part of the case is a fastener of the Alpha button type 12.5 mm for attaching the electrode to the headset. In the lower part of the case are six wire contacts with 316L stainless steel balls at the ends, providing electrical contact with the skin surface. All contacts are electrically interconnected and the central residential cable for connection to the measuring unit of the complex.

Engineering Designer and Resource Kits

The engineering designer and resource kits manufactured by LLC "Brain Development" are used. Below are their brief descriptions.

1. Designer Robotrek "Basic" (figure 4)

The kit includes at least 828 parts:

1. Plastic beams of various shapes (5 types), blocks (11 types) for the construction of objects.

2. Metal blocks of various shapes (10 types).

3. Wheels (5 types).

4. Gears (4 types), levers and plastic corners, a set of links for tracks.

5. A set of plastic (4 types) and metal (3 types) shafts, plastic bushings and plastic, rubber and metal couplings, iron bolts (three sizes) and nuts, washers.

6. A set of flat plastic frames (3 types) and rubber adapters (2 types).

7. A set of volumetric rectangular connecting beams (2 types).

8. A set of plastic pins in 5 sizes and fixtures for installing pins.

9. One motherboard for advanced level.

10. Two DC motors and 1 servomotor for advanced level and 2 external encoders.

11. A set of various sensors (6 types).

12. USB cable for the advanced-level board and programmer for the main-level board.

13. Case for batteries 9 V.

14. The remote control.

15. Screwdriver, wrench.

16. Disk with software ROBOTREK, instructions, at least 39 ready-made files for flashing the TREKDUINO board with algorithms for programming robots, provided that there is an additional set of ROBOTRAK SENSORS in addition.

With the help of the designer, the Basic Robotrek, you can create the basic skills and competencies for professions related to the scientific and technical field, for example, a development engineer, a modeling engineer, a design engineer, a design engineer, etc. Within the framework of the complex, the student can develop his own author's project - a neuroinstallation, where he can demonstrate the knowledge gained in the field of neuro- and psychophysiology in the development and programming of robotic models. A student using designer parts can develop a prototype of a neural installation related to the demonstration of the work of certain human organs, show its functional activity (for example, the Instinct model, illustrating one of the functions of the midbrain (maternal instinct), assemble a bathyscaphe prototype or any other robotic model, with the help of which it is possible to demonstrate the capabilities of the human body, i.e., to control robotic models using the bioelectric activity of the heart, muscles and cephalic wow brain).

2. Resource set Robotrek "Sensors" (figure 5)

The kit includes at least 25 elements:

1. LED modules in three colors.

2. Accelerometer, gyroscope.

3. Two external encoders.

4. Fire sensor.

5. The sound sensor.

6. Touch sensor.

7. Tilt sensor.

8. The vibration sensor.

9. The magnetic field sensor.

10. Piezo emitter.

11. Ultrasonic distance sensor.

12. Color sensor + light sensor.

13. The remote control sensor.

14. Infrared sensor (IR sensor).

15. The speaker.

When developing your own models or creating neuroinstallations provided for by the model, this resource set with sensors allows you to create an imitation of the human body, for example, the Robotic Brain model. When developing author's unique neuroinstallations, it allows demonstrating the work of prototypes of production models or working out the theoretical knowledge obtained in the lesson with the help of a project developed specifically (for example, the laboratory work “INTERFACE“ BRAIN - COMPUTER ”, where it is necessary to develop an authorial, unique neuroinstallation that imitates the Delgado experiment.)

3. The resource set Robotrek "Color TFT display" (Fig.6)

It consists of a touch screen TFT 2.4 LGD, housing for TFT screen, cable. With the help of libraries and graphic blocks included in the Robotrek software, you can perform basic actions - draw geometric shapes, display text, turn on the touch-screen drawing mode.

Using the TFT display, the student can demonstrate the result of working with the program, can display the result of the program and its programming activities on the screen.

4. The resource set Robotrek "Worm gear" (Fig.7)

A helical gear is necessary to create complex mechanical gears, generating knowledge that is within the competence of development engineers and design engineers. With the help of this resource set, it is possible to increase the power of lifting mechanisms and transmitting movement at an angle of 90 degrees. The kit includes 1 worm gear.

5. The resource set Robotrek "Energy-mini" (Fig.8)

Consists of a battery and charger. Energitrek-mini allows you to provide long-term operation of the boards at maximum load, supports the simultaneous use of 2 DC motors, together with servomotors, and other sensors / executors. It will be useful for the development of large-scale projects using Robotrek educational kits.

6. Resource set Robotrek "Energy Track" (Fig.9)

Consists of a battery and charger. Energy Track allows for long-term operation of the boards at maximum load, supports the simultaneous use of 4 DC motors, together with servomotors, a display, an audio track and other sensors / artists. It will be useful for the development of large-scale projects using Robotrek educational kits.

7. Resource set Robotrek "Audio track (figure 10)

Consists of a speaker, case, memory card. Allows you to use the ability to play audio files when developing projects or to reproduce instructions in laboratory work (for example, the laboratory work "Autogenic training").

Audio module "Audiotrack" is designed to expand the capabilities of the designer Robotrek "Basic". Allows you to play audio in popular formats such as MP3, WAV and WMA.

The complex works as follows:

1. Software is installed on the computer.

2. The software is launched and the system is logged in with its username and password.

3. The module with the lesson is launched (the lesson schedule is compiled in the CRM system).

4. The theoretical material of the lesson is studied, prepared material is used, structured by sections and topics. A glossary is used if necessary.

5. Laboratory work is being carried out. Only 4 types of laboratory work.

Depending on the type of laboratory work for its implementation, one of the following actions is performed:

• an interactive application is launched;

• a robotic model or neuroinstallation is being assembled and controlled;

• equipment is connected (a neuro-headset or an electric headset), equipment is set up, signals are taken and bioelectric signals of the human body are studied, or an analysis of a signal received earlier is carried out;

• a robotic model is assembled, equipment (a neuro-headset or an electric headset) is connected, and a robotic model is controlled.

6. If necessary, data is entered into a personal notebook, graphic objects are drawn, or a glossary is used.

7. Testing in progress. The testing module and the developed technology for conducting the testing procedure allows both individual control of knowledge by the teacher and self-control of the knowledge received by the students themselves.

8. All test results obtained during operation and captured signals are stored on the server.

Laboratory work can be 4 types:

1. Laboratory work, which involves the study of the psychophysiology and neurophysiology of a person and the capabilities of the human body. For example, the laboratory work of section 5 of lesson 3 “Creating a personal 10-20 scheme”.

2. Integration of neurophysiology and engineering. The purpose of this type of laboratory work is to study the ability to control robotic neuroinstallations created and developed by students from the Basic Robotrek designer using resource sets or neuroinstallations assembled using assembly cards that are relevant to the lesson. Management of this type of neuroinstallation using signals from the brain, heart, muscle potential and RAG. Such laboratory work consists of two parts. In the first part (engineering), the student collects a neural installation and programs it. Programming can occur in two ways: using a ready-made program or creating a program for neural installation on your own (programming takes place in the RobotrackIDE environment). The second part of the laboratory work is the removal of human bioelectric signals and providing students with the opportunity to use this signal to control neuroinstallations. This type of laboratory work is aimed at demonstrating human capabilities and the use of physiological indications in practice. For example, the laboratory work of section 5 of lesson 4 “electrophysiological methods for studying the brain”

3. Engineering. The student develops or collects maps of the assembly of neuroinstallations demonstrating the work of human neurophysiological processes. For example, a neural network model or Robo Brain.

4. Work with an interactive application for the study and consolidation of knowledge from the field of human neurophysiology. For example, the laboratory work of section 2 of lesson 4, “medulla oblongata”.

Thus, the proposed complex can significantly increase the effectiveness of teaching and learning material in the study of the basics of psychophysiology, neurophysiology and specialties in the field of neurotechnology in comparison with well-known analogues.

Claims (6)

1. A digital training complex for preparing for promising professions in the field of neurophysiology, including students' workstations with network computers and software, a server with software and communication tools for students' workstations with a server, combining them into a local network, characterized in that each student's workplace includes a neuro headset, an electric headset and an engineering designer, students' computers contain software which includes the protocol network interface module, the system automatic updating module, the scanning module for network devices and functions , CRM module, network address translation module, functions and settings management module, user interface module of different levels, data storage and archiving module, access and security rules module, statistics module, system functionality acquaintance module that implement workstation interface algorithms with external devices, a server and the Internet, algorithms for completing training tasks, collecting and storing data, while the server software includes a remote computing module and database obtained results. 2. The complex according to claim 1, characterized in that the neuro-headset includes “dry” sensors and a signal amplifier placed on a helmet worn on the student’s head. 3. The complex according to claim 2, characterized in that the sensors are configured to change the location on the helmet to provide the ability to remove signals from various parts of the brain. 4. The complex according to claim 2, characterized in that the signal amplifier consists of a series input amplifier block with a lead electrode, a switch block, a low-noise amplifier block, an amplitude limiter block with a low-pass (low-pass) filter and a multi-channel analog-to-digital converter (ADC) ), while the switch unit is connected to the impedance meter unit, as well as to the reference and neutral electrodes through the negative feedback unit (OOS), and a parallel is connected to the low-noise amplifier unit a negative feedback unit for the low noise amplifier with a suppression circuit 50 Hz. 5. The complex according to claim 1, characterized in that the designer uses the Basic Robotrack, the Color TFT Display Robotrack, the Sensors Robotrack, the Audio Track Robotrack, and the Robotrack Resource Kit Worm gear ”, resource kit Robotrek“ Energyjetrek ”, resource kit Robotrek“ Energitrek-mini ”. 6. The complex according to claim 2, characterized in that as the "dry" sensors use sensors DF6.17.

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