Siamese Network-Based Feature Transformation for Improved Automated Epileptic Seizure Detection

Table 4

30 high-ranked features selected by ANOVA.

Rank	Feature/N. S^1	Rank	Feature/N. S	Rank	Feature/N. S
1	Spectral En/5	2	Spectral En/6	3	Samp En/10
4	Complexity/10	5	SD/0^2	6	NLE/9
7	Spectral En/9	8	SampEn/2	9	N. ZC^4/5
10	NLE/3	11	N. LE^3/1	12	Kurtosis/0
13	Mobility/4	14	Skewness/6	15	N. LE/5
16	SampEn/9	17	Perm. En./10	18	Skewness/5
19	Line length/8	20	NLE/7	21	Spectral En/4
22	Shannon En/8	23	Skewness/2	24	Mobility/1
25	SD/1	26	Line length/4	27	N. ZC/3
28	Sample En/5	29	Mobility/7	30	Complexity/2

¹Number of sub-band features extracted. ²Sub-band “0” means raw EEG signal. ³Number of local extrema. ⁴Number of zero crossing.