Building indoor learning efficiency detection method and system
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A technology of efficiency detection and construction, applied in medical science, psychological devices, diagnostic records/measurement, etc., can solve problems such as inability to accurately reflect the state of learners' attention, and achieve the effect of accurate classification
Active Publication Date: 2020-09-08
ANHUI UNIVERSITY OF ARCHITECTURE
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[0004]
The technical problem to be solved by the present invention is to provide a learning efficiency detection met
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Embodiment 1
[0093] Such as figure 1 and image 3 , figure 1 It is a flow block diagram of Embodiment 1 of the present invention, image 3 It is a system block diagram of Embodiment 1 of the present invention; a method for detecting learning efficiency in a building, comprising the following steps;
[0094] S1. Acquiring EEG signal data;
[0095] In this embodiment, the way to obtain the EEG signal data is to obtain the EEG signal acquisition experiment through the attention classification;
[0096] Concretely, described attention classification EEG signal collection experiment comprises the following steps;
[0097] S11. Acquiring the experimental online learning video;
[0098] The online learning video can be intercepted from 15 10-minute videos of Chinese University MOOC, ensuring that all students study in the same building room, and select 15 subjects respectively, and the selected content of each subject is relatively complete and interesting Not the same, this can better refl...
Embodiment 2
[0178] Such as Figure 4 , Figure 4 It is a schematic structural diagram of Embodiment 2 of the present invention; a detection system based on the detection method for indoor learning efficiency in a building, characterized in that it includes;
[0179] An acquisition module, configured to acquire EEG signal data;
[0180] A preprocessing module, configured to preprocess the collected EEG signal data;
[0181] The extraction module is used to extract the energy features under the different electrode channels of the EEG signal as the input features of the subsequent classifier through feature extraction;
[0182] The input module is used to use the energy feature under the corresponding electrode channel of the feature extraction as the input feature, and input it into the BP neural network to realize the classification of learning attention.
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Abstract
The invention relates to a building indoor learning efficiency detection method and system. The method comprises the following steps: S1, acquiring electroencephalogram signal data; S2, preprocessingthe acquired electroencephalogram signal data; S3, extracting energy features of the preprocessed electroencephalogram signals under different electrode channels through features; and S4, taking the energy features under corresponding electrode channels of the feature extraction as input features, and inputting the input features into a BP neural network to realize classification of learning attention. Energy features of the electroencephalogram signals under different electrode channels are extracted through features, and are taken as input features of a subsequent classifier, and the attention state of a learner is accurately reflected; accurate classification of electroencephalogram signals is realized; and accurate, stable and reliable measurement of the concentration degree of the attention electroencephalogram signals is realized, and wide influence is generated on attention action mechanisms in human brains in psychology and neurophysiology.
Description
technical field [0001] The invention relates to the technical field of learning attention EEG signal classification, in particular to a method and system for detecting learning efficiency in a building. Background technique [0002] In the journey of scientific research, human beings have never stopped studying themselves. The 21st century is the era of biological science and brain science. Multi-level comprehensive research on advanced cognitive functions such as human brain thinking, learning, language and attention has become one of the popular directions of contemporary scientific development. way to grow rapidly. Because of its unique properties, the EEG signals collected from the human scalp have increasingly become an indispensable experimental and analytical method in this type of research. Therefore, the analysis and processing of EEG signals has become an indispensable part of brain science research. It has also become an important method to study learners' atten...
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