Classification of Electroencephalogram Signal for Developing Brain-Computer Interface Using Bioinspired Machine Learning Approach

Table 2

Performances of subjects of the age group 29–40 using the AR Yule-Walker features with FFNNCSA.

Subjects	Average training time for ten trials (sec)	Average testing time for ten trials (sec)	Average classification performance (%)
			Sd	Max	Min	Mean
S11	19.65	0.79	1.73	94.16	88.58	93.90
S12	19.74	0.78	1.70	93.51	87.65	93.16
S13	19.58	0.76	1.75	94.89	89.82	93.32
S14	19.42	0.77	1.77	94.69	88.94	93.62
S15	19.68	0.72	1.66	94.22	89.24	93.21
S16	19.36	0.73	1.69	94.30	88.74	93.48
S17	19.47	0.75	1.68	95.10	88.56	93.77
S18	19.74	0.81	1.73	94.68	88.80	93.60
S19	19.78	0.80	1.72	94.56	89.25	93.95
S20	19.12	0.74	1.62	95.78	90.18	95.00