Table 2.

Classification results of SVM classifier.

Subject	CA	SP	SE	AUC
1	0.893	0.857	0.929	0.952
2	0.893	0.929	0.857	0.967
3	0.833	0.800	0.867	0.804
4	0.889	0.833	0.944	0.965
5	0.933	0.933	0.933	0.931
6	0.882	0.941	0.824	0.891
7	0.921	0.895	0.947	0.922
8	0.906	0.938	0.875	0.972
9	0.969	0.941	0.987	0.981
10	0.933	0.892	0.975	0.998
11	0.900	0.933	0.867	0.929
12	0.893	0.857	0.929	0.965
13	0.886	0.909	0.864	0.934
14	0.857	0.809	0.905	0.981
15	0.923	0.896	0.950	0.884
16	0.821	0.857	0.786	0.996
17	0.933	0.980	0.887	0.998
18	0.885	0.923	0.846	0.846
19	0.923	0.932	0.914	0.953
20	0.864	0.864	0.864	0.935
Mean	0.897	0.896	0.898	0.940

Note: CA represents classification accuracy, SP represents specificity, SE represents sensitivity and AUC represents area under ROC curve.