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A learning monitoring and testing method based on brain-computer interface mobile terminal

A mobile terminal, brain-computer interface technology, applied in the field of robot learning, can solve problems such as easy distraction, unsatisfactory learning efficiency, and lack of a clear understanding of the degree of knowledge mastery, and achieve the effect of deepening the impression

Active Publication Date: 2020-04-07
HARBIN ENG UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the fast-paced life often makes the user's learning efficiency unsatisfactory. During the learning process, the attention is easily distracted, and there is no clear understanding of the degree of knowledge learned.

Method used

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  • A learning monitoring and testing method based on brain-computer interface mobile terminal
  • A learning monitoring and testing method based on brain-computer interface mobile terminal
  • A learning monitoring and testing method based on brain-computer interface mobile terminal

Examples

Experimental program
Comparison scheme
Effect test

Embodiment approach

[0028] Monitoring steps of learning process based on EEG data:

[0029] reference figure 1 The specific process is as follows:

[0030] Step 1: Initialize the brain-computer interface device, and establish communication between the brain-computer interface device and the mobile terminal via Bluetooth.

[0031] Step 2: The user customizes the way to rest when the brain is fatigued.

[0032] Step 3: The mobile terminal establishes the EEG data storage buffer Buf of the FIFO model, and sets the relevant parameter values, taking Size=100, T min = 30 (time unit is minutes), T max =90, T interval = 2, Att tr = 85, Wea tr =85, Str tr =90. Initialize the learning application on the mobile terminal, and the user selects the learning content to start learning.

[0033] Step 4: Every 1s, the mobile terminal reads the data packet sent by the EEG device and judges whether the signal quality value in it is greater than Str tr , If less than Str tr Ignore the packet, if it is greater than Str tr T...

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Abstract

The invention provides a learning monitoring and testing method based on a brain computer interface mobile terminal. A user wears a mobile learning terminal with brain computer interface, the user's concentration is detected by computer equipment, and the learning terminal gives a hint when the user's concentration is lower than the set threshold. At the same time, the user's using brain volume and learning duration are detected in the process, the learning terminal gives a rest hint when the user's learning duration or brain volume is higher than the preset threshold. Finally, when the user finishes a paragraph, the learning terminal can give relevant test questions, the questions can be changed randomly. Through perceiving the user's familiarity by the brain electrical device, the user's mastery of learnt content is understood, and content not well mastered by the user is presented again.

Description

Technical field [0001] The invention relates to a robot learning method, in particular to a mobile terminal learning method based on a brain-computer interface. Background technique [0002] Smart mobile terminals have become quite popular in people's lives. People can use them for communication, online shopping, travel navigation, learning knowledge, etc. It is often with everyone. The current smart mobile terminal is actually not fully "intelligent" because it does not understand people's consciousness and still passively accepts people's orders, but its functions are becoming more and more diversified. Realizing real intelligence can start from two aspects. One is to enable the terminal to have the function of autonomous learning, and finally to have the ability to understand the user's intention through data mining and deep learning of the user's operating experience; the other is to integrate the user's intention through the brain-computer interface It is converted into an ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F3/01G06Q50/20
CPCG06F3/015G06Q50/205
Inventor 孙云龙高延滨管练武曾建辉何昆鹏孟龙龙李抒桐张帆
Owner HARBIN ENG UNIV
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