CN210199810U - Internet of things-based brain wave acquisition terminal for English listening comprehension - Google Patents
Internet of things-based brain wave acquisition terminal for English listening comprehension Download PDFInfo
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- CN210199810U CN210199810U CN201920764757.6U CN201920764757U CN210199810U CN 210199810 U CN210199810 U CN 210199810U CN 201920764757 U CN201920764757 U CN 201920764757U CN 210199810 U CN210199810 U CN 210199810U
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Abstract
The utility model discloses a brain wave acquisition terminal for english listening comprehension based on thing networking, the utility model is used for monitoring the brain wave of english learning process, through the brain wave sensor, after carrying out the digital analog conversion, convert the brain wave of student's learning process into digital signal, send the remote server to through the thing networking of china telecommunication and do lasting transmission, collect the brain wave data that student's learning process produced in the long-range to match the integration with the learning result in this data and the student information management system, finally establish the machine learning model that is used for analyzing student's learning process.
Description
Technical Field
The utility model belongs to intelligence study field, concretely relates to brain wave acquisition terminal for english listening comprehension based on thing networking.
Background
The intelligent device module in the teaching function product of school relates to following four: the first is a sensor module, a sensor for detecting brain waves. The neuron activity of the brain reaches the cerebral cortex through ion conduction, the weak voltage change is sensed by the conductive electrodes fixed on the head, and the electrical signals are finally converted into the original data of brain waves through a series of means such as differential amplification, filtering, digital-to-analog conversion and the like.
Electrodes for detecting brain waves are generally classified into three categories, and wet electrodes are generally used for medical research and scientific research; the dry electrode is generally used in the non-medical fields of health monitoring, toys and the like, and the dry electrode has the advantages of use aspect by directly detecting weak electrical signals sent by the brain and digitizing the electrical signals of the brain after algorithm filtering; the implanted electrode array is formed by implanting electrodes into subcutaneous tissues to capture neuron electric signals, can shield most interference and has high precision. But the application range is affected because the subcutaneous treatment is needed.
And the second is a sound playing module which is used for solving the function of actually dictating sounds of users such as students.
And thirdly, a transmission module, wherein the data transmission comprises data transmission by using a 2G, 3G, 4G or NB network. The Internet of things of China telecom has the advantages of low power consumption, stable transmission and the like.
And fourthly, data persistence and data analysis technology. The method comprises a traditional relational database and mature open-source products such as mysql and the like, data analysis is conducted except for traditional artificial intelligence technologies such as pattern recognition, research is deeper at present, and a new tool is provided for data analysis by applying wide classification models such as a deep neural network and the like. The analysis tools may additionally include visualization analysis tools, and the like.
The brain wave sensor module has not been mature in technology all the time, and the application field is mostly focused on the medical field. The technology is immature because it is related to the principle of brain wave sensors. The detection of brain waves is divided into micro-current detection and micro-magnetic detection. The micro-current sensor is buried under the cerebral cortex or stuck on the scalp to detect the micro-current change generated during the brain activity; the micro-magnetic sensors can detect the magnetic field change generated by the brain current. Brain wave sensing requires a sensor with an extremely complicated design, and is therefore widely used in the medical field. The micro-magnetic detection is easily affected by the magnetic field, and the effect is not good. The data collected in the medical field detects the real-time brain state of the patient according to the discharge information of different cerebral cortex.
Products applying brain wave sensors to the teaching field have appeared, for example, a product efficiency master APP of a tin-free Neurosky memorial science and technology company, the product of the company monitors the learning process of students through an algorithm of research and design by the company, and gives a learning prompt in time. The product has the problems that equipment and an interface for data acquisition are not provided for a user, although application software is provided, the software can only be continuously upgraded along with the upgrade of a merchant, and a terminal user cannot know data and cannot establish or modify a brain wave model. Meanwhile, the existing data analysis technology needs to collect a large amount of real learning data of one line, and then the data can be analyzed and modeled according to the teaching process and the teaching theory.
Therefore, a set of feasible brain wave data acquisition devices needs to be provided for the market, and the devices can not only complete daily teaching activities such as English listening, but also provide data acquisition for a first-line scientific research institution or a teaching institution.
SUMMERY OF THE UTILITY MODEL
Utility model purpose: in order to solve the defects of the prior art, the utility model provides a brain wave acquisition terminal for english listening comprehension based on thing networking.
The technical scheme is as follows: a brain wave acquisition terminal for English listening based on the Internet of things is connected with a remote data acquisition, storage and analysis system through a narrow-band Internet of things, and comprises a data processing component, a brain wave sensor, a sound playing module and a network communication module, wherein the data processing component is respectively connected with the brain wave sensor, the sound playing module and the network communication module, the brain wave sensor acquires brain wave signals and transmits the brain wave signals to the data processing component for processing, the sound playing module plays signals transmitted by the data processing component and acquires user sound signals and transmits the user sound signals to the data processing component for processing, the chargeable module provides power for the data processing component, and the network communication module transmits working information of the data processing component to the remote data acquisition, processing and analysis system through the narrow-band Internet of things, meanwhile, the network communication module transmits the control signal transmitted by the data acquisition, processing and analysis system through the narrow-band Internet of things to the data processing assembly.
As an optimization: the brain wave sensor adopts a PCB module, and the PCB module has an analog-to-digital conversion function.
As an optimization: the network communication module can adopt an LTE BC28 NB-IoT module, and is an ultra-compact, high-performance and low-power-consumption multiband NB-IoT wireless communication module.
As an optimization: the network communication module is provided with an MCU component, and the brain wave sensor is connected with the data processing component through the MCU component.
Has the advantages that: the utility model is used for monitoring the brain wave in the english learning process, through the brain wave sensor, after carrying out the digital analog conversion, convert the brain wave of student's learning process into digital signal, send to remote server through the thing networking of china telecommunication and do lasting transmission, collect the brain wave data that the student learning process produced in the long-range, and match the integration with the learning result in this data and the student information management system, finally establish the machine learning model that is used for analyzing student's learning process. The model is used for teaching process data modeling or other scientific research purposes for education institutions or teaching units such as middle schools, colleges and universities.
The utility model discloses a concrete advantage as follows:
(1) the utility model combines the brain wave sensor and the hearing playing module, thereby reducing the purchasing cost of the user;
(2) the utility model uses the communication component of the internet of things to collect real-time electroencephalogram data in the learning process, and truly reflects the practical teaching situation of the front line;
(3) the utility model discloses to brain wave data, fuse other data among the teaching information management system, establish data model, serve the teaching field, have corresponding promotion teaching effect.
(4) The utility model discloses a thing networking communication module reduces the consumption of equipment, promotes acquisition terminal's ease for use.
Drawings
Fig. 1 is a schematic structural diagram of the present invention.
Detailed Description
Examples
As shown in FIG. 1, the utility model discloses a whole electroencephalogram analysis system based on thing networking is used for english listening comprehension comprises two important parts, includes based on thing networking is used for the electroencephalogram collection terminal and the remote data acquisition storage analysis system of english listening comprehension. Brain wave acquisition terminal of english listening comprehension is connected with remote data acquisition storage analysis system through the narrowband thing networking, brain wave acquisition terminal of english listening comprehension includes data processing subassembly, brain wave sensor, sound play module, network communication module, and the data processing subassembly is connected with brain wave sensor, sound play module, network communication module respectively, the brain wave sensor is gathered brain wave signal and is handled in conveying the data processing subassembly, sound play module broadcast processing data processing subassembly conveying comes the signal to gather user's sound signal and handle in conveying the data processing subassembly, chargeable module provides the power to the data processing subassembly, the network communication module conveys the work information of data processing subassembly to remote data acquisition processing analysis system through the narrowband thing networking, and network communication module sends the control that data acquisition processing analysis system comes through the narrowband thing networking simultaneously The signal is transmitted to the data processing component.
The working process of the whole system is that the brain wave sensor monitors brain waves in the English learning process, after digital-to-analog conversion is carried out, the brain waves in the student learning process are converted into digital signals, the digital signals are sent to a remote server through the Internet of things of China telecommunication for persistent transmission, brain wave data generated in the student learning process are collected remotely, the data and learning results in the student information management system are matched and fused, and finally a machine learning model for analyzing the student learning process is established. In the process of transmitting the brain wave data to the remote server, the sound playing module can be used for learning English, such as training and learning of English listening comprehension.
The brain wave acquisition terminal for English listening based on the Internet of things comprises the following four modules: the system comprises a brain wave sensor, a sound playing module, a data processing component, a network communication module, a rechargeable module and the like. The functions and the implementation modes of the modules are as follows:
the brain wave sensor is realized by adopting a TGAM (ThinkGear apparent Module) PCB module provided for an embedded system designer, the TGAM module comprises a TGAT chip, the chip is a highly integrated single-chip brain wave sensor, three Neurosky eSense parameters can be output, analog-to-digital conversion can be carried out, the abnormal state of poor contact can be detected, and the electro-ocular noise and 50/60hz alternating current interference can be filtered.
The TGAM module can be directly connected with a dry contact point, a conductive adhesive is not needed when a traditional medical wet sensor is used, a single EEG brain electric channel is provided with 3 contact points, namely an EEG (brain electric acquisition point) REF (reference point) GND (ground point), if the contact points do not acquire brain electric signals continuously for four seconds or receive poor brain electric signals continuously for seven seconds after being electrified, the device has an advanced noise filtering technology, can resist various interferences in the environment in daily life, has low energy consumption, is suitable for battery powered equipment of portable consumer products, has the maximum consumption of 15 milliamperes under 3.3 volt power supply, outputs original brain electric data at 512Hz, outputs the output signals of the device comprise original brain wave band data such as α brain wave band data, and outputs Neurosky technology to obtain the concentration degree and relaxation degree index of an eSense of the patent technology and other data developed in the future, abnormal states of poor contact or no contact at all, and the like.
The data processing component can use an MCU component provided by the network communication module and can also realize data processing in a mode of externally connecting the singlechip module. The component is responsible for receiving data sent by the brain wave sensor, and the brain wave data after analog-to-digital conversion is carried out on the data by the sensor and is sent to the data processing component through a serial port. The data processing component calls the network communication module and sends the data to the China telecom Internet of things cloud, namely the narrowband Internet of things. Meanwhile, the information sent to the remote server comprises key information which can uniquely identify the equipment, such as equipment number, sending time and the like.
The network communication module can adopt an LTE BC28 NB-IoT module of Shanghai Mobile company, the chipset is an ultra-compact, high-performance and low-power consumption multiband NB-IoT wireless communication module based on the Hi2115 chip 150 development platform, and the B1/B3/B8/B5/B20/B28 frequency band is also supported. BC28 provides rich external interfaces and network protocol stacks, including UDP/TCP/CoAP/LwM2M/MQTT, etc. The BC28 adopts an ultra-compact design, has the size of only 17.7mm multiplied by 15.8mm multiplied by 2.0mm, is one of the products with the smallest size in the industry at present, and is particularly suitable for industries such as wearable equipment, security protection, asset tracking, agricultural monitoring, intelligent household appliances and the like.
The sound playing module realizes the sound playing function.
The rechargeable module may be a module such as a lithium battery, and a photovoltaic battery may be used.
The utility model discloses an entire system's work flow as follows:
(1) a teaching management or scientific research institution purchases a brain wave acquisition terminal, initializes basic data of a remote server, and registers and provides the brain wave data acquisition terminal for a terminal user.
(2) The terminal user charges the device using the charging interface.
(3) In the learning or scientific research process, the terminal user wears the brain wave acquisition terminal.
(4) The method comprises the steps that a registration message is sent to the China telecom Internet of things cloud in a brain wave acquisition terminal, a remote server registers a notification message in the China telecom Internet of things cloud, and when the terminal is on line, a push notification is obtained. The remote server marks that the terminal user is online.
(5) After the brain wave acquisition terminal is successfully registered, students and other terminal users learn normally. The acquisition terminal acquires user electroencephalogram data at a certain frequency, performs digital-to-analog conversion and then sends the data to the data processing assembly, and the assembly simultaneously packages information such as equipment marks and acquisition time and sends the information to the cloud of the China telecom Internet of things.
(6) And the data acquisition server receives data push of the China telecom Internet of things cloud and records the data push in a local database.
(7) After a period of time, the operation is completed, and the student information management system, the student score management system, the data collected by the terminal and the like are fused on the remote data server to complete the initial data collection work.
(8) Teachers or scientific researchers use an artificial intelligence technology according to the collected data, for example, a deep neural network is adopted to analyze and model the data, an education theory is combined to analyze the teaching effect, the relation between electroencephalogram data and the teaching effect is counted, and the like.
The utility model is used for monitoring the brain wave in the english learning process, through the brain wave sensor, after carrying out the digital analog conversion, convert the brain wave of student's learning process into digital signal, send to remote server through the thing networking of china telecommunication and do lasting transmission, collect the brain wave data that the student learning process produced in the long-range, and match the integration with the learning result in this data and the student information management system, finally establish the machine learning model that is used for analyzing student's learning process. The model is used for teaching process data modeling or other scientific research purposes for education institutions or teaching units such as middle schools, colleges and universities.
The utility model combines the brain wave sensor and the hearing playing module, thereby reducing the purchasing cost of the user; the real-time electroencephalogram data in the learning process are collected by using the internet of things communication assembly, and the first-line teaching actual condition is truly reflected; aiming at electroencephalogram data, fusing other data in a teaching information management system, establishing a data model, serving the teaching field and improving the teaching effect in a targeted manner; and by adopting the communication module of the Internet of things, the power consumption of the equipment is reduced, and the usability of the acquisition terminal is improved.
The foregoing will clearly and completely describe the technical solutions in the embodiments of the present invention, so that those skilled in the art can better understand the advantages and features of the present invention, thereby making a more clear definition of the protection scope of the present invention. The described embodiments of the present invention are only some embodiments, but not all embodiments, and all other embodiments obtained by the person skilled in the art without creative work belong to the scope protected by the present invention based on the embodiments of the present invention.
Claims (4)
1. The utility model provides a brain wave acquisition terminal for english hearing based on thing networking which characterized in that: brain wave acquisition terminal of english listening comprehension passes through the narrowband thing networking and is connected with remote data acquisition storage analysis system, brain wave acquisition terminal of english listening comprehension includes data processing subassembly, brain wave sensor, sound play module, network communication module, and data processor is connected with brain wave sensor, sound play module, network communication module respectively, brain wave sensor gathers brain wave signal and handles in conveying the data processor subassembly, sound play module broadcast process data processor subassembly conveying signal of coming to gather user's sound signal and handle in conveying the data processor subassembly, chargeable module provides the power to the data processor subassembly, network communication module conveys the working information of data processing subassembly to remote data acquisition processing analysis system through the narrowband thing networking, and network communication module transmits the control thing networking analysis system that the data acquisition processing analysis system comes through the narrowband thing networking simultaneously The signal is transmitted to a data processor.
2. The brain wave acquisition terminal for English listening based on the Internet of things according to claim 1, characterized in that: the brain wave sensor adopts a PCB module, and the PCB module has an analog-to-digital conversion function.
3. The brain wave acquisition terminal for English listening based on the Internet of things according to claim 1, characterized in that: the network communication module can adopt an LTE BC28 NB-IoT module, and is an ultra-compact, high-performance and low-power-consumption multiband NB-IoT wireless communication module.
4. The brain wave acquisition terminal for English listening based on the Internet of things according to claim 1, characterized in that: the network communication module is provided with an MCU component, and the brain wave sensor is connected with the data processing component through the MCU component.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201920764757.6U CN210199810U (en) | 2019-05-27 | 2019-05-27 | Internet of things-based brain wave acquisition terminal for English listening comprehension |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201920764757.6U CN210199810U (en) | 2019-05-27 | 2019-05-27 | Internet of things-based brain wave acquisition terminal for English listening comprehension |
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| Publication Number | Publication Date |
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| CN210199810U true CN210199810U (en) | 2020-03-27 |
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| CN201920764757.6U Expired - Fee Related CN210199810U (en) | 2019-05-27 | 2019-05-27 | Internet of things-based brain wave acquisition terminal for English listening comprehension |
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