Learning attention eValuation system based on EEG signal

Abstract

The inVention discloses a learning attention eValuation system based on an EEG signal, which comprises an EEG acquisition subsystem, which is used for acquiring an EEG signal for preprocessing to remoVe power frequency interference and a baseline, and transmitting the EEG signal to an EEG analysis subsystem; the EEG analysis subsystem, which is used for analyzing the acquired EEG signal, extracting the time domain characteristic and the frequency domain characteristic as the feature Vector of the attention classification, and inputting the feature Vector into an attention classifier to obtainthe attention leVel; a learning state display reminding subsystem, which is used for feeding back the attention leVel obtained by the EEG analysis subsystem to students and teachers, thereby achieVingreal-time monitoring of a student's attention and solVing the technical problem that the student's learning state is difficult to eValuate objectiVely.

Description

technical field [0001] The invention belongs to the technical field of attention detection, and in particular relates to a learning attention evaluation system based on electroencephalogram signals. Background technique [0002] The detection of classroom learning status is an important link in the teaching and learning process. Traditional classroom testing methods are often based on classroom questions, quizzes, and observing student expressions. Teachers often cannot take into account the learning status of each student, and the judgment results are highly random and subjective. Therefore, it is particularly important to realize the objective and effective detection of students' learning status. In recent years, with the rapid development of brain-computer interface technology, it has become possible to capture human mental activities only through the collection and analysis of EEG signals. As a kind of psychological activity, attention plays an important role in studen...

AI Technical Summary

Problems solved by technology

Traditional classroom testing methods are often based on classroom questions, quizzes, and observing student expressions. Teachers often cannot take into account the learning status of each student, and the judgment results are highly random and subjective.

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