Evaluating a Semiautonomous Brain-Computer Interface Based on Conformal Geometric Algebra and Artificial Vision

Table 3

Features: EEG channels and frequency range (in Hz) and mean accuracy of LDA classifiers for all subjects and training sessions.

Subject	Session	Features	Accuracy (%)
	1	C4 (11–15), P3 (11–15), C3 (7–11), Fp2 (13–17)	65
	2	C3 (7–13), P3 (9–13), P4 (9–13), P4 (13–17), Cz (9–13)	64
	3	C4 (9–15), C3 (13–17), P3 (23–27), P4 (25–29)	63
	1	C4 (9–13), P4 (11–15), F4 (17–21), F4 (11–15), Cz (11–15)	65
	2	C4 (15–19), C3 (19–23), P4 (21–25), Cz (19–23), FP1 (25–29)	62
	3	C4 (19–23), C4 (17–21), Cz (19–23), P3 (21–25), F3 (19–23)	60
	1	F4 (15–21), F3 (9–11), P4 (9–13), F4 (15–21)	56
	2	C3 (11–15), C4 (7–11), P3 (15–19), P4 (11–15)	61
	3	C3 (9–15), C4 (11–15), P3 (11–15)	78
	1	C4 (9–13), C3 (9–13), P4 (17–21), F4 (19–23), F3 (19–23)	73
	2	F3 (11–15), C4 (7–13), P4 (17–21), P3 (17–21), F4 (19–23)	72
	3	C4 (7–11), C3 (13–17), F4 (17–21), C4 (11–15)	60