Research Article
A Hybrid EMD-Wavelet EEG Feature Extraction Method for the Classification of Students’ Interest in the Mathematics Classroom
Table 3
MANOVA result of the features of high and low SI students.
| | Method | Independent variables | MANOVA |
| | EMD-energy | Interest | F (16, 1) = 9.024, , Wilks’ ∧ = 0.007 | | Lecture | F (16, 1) = 0.229, , Wilks’ ∧ = 0.214; interaction | | DWT-energy | Interest | F (16, 1) = 2.063, , Wilks’ ∧ = 0.029 | | Lecture | F (16, 1) = 6.376 , Wilks’ ∧ = 0.010; interaction | | Proposed method | Interest | F (10, 7) = 7.275, , Wilks’ ∧ = 0.088 | | Lecture | F (10, 7) = 12.818, , Wilks’ ∧ = 0.052; interaction |
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