Improving EEG-Based Motor Imagery Classification for Real-Time Applications Using the QSA Method

Table 7

Comparison of performance measures for the decision tree classifier using 64 samples.

Subject	ER	RT				Sp0	Sp1	Sp2
	0.17667	0.82333	0.83000	0.81500	0.82500	0.82000	0.82750	0.82250
	0.18625	0.81375	0.81375	0.79500	0.83250	0.81375	0.82312	0.80437
	0.17542	0.82458	0.85125	0.79000	0.83250	0.81125	0.84188	0.82063
	0.19145	0.80855	0.81923	0.81410	0.79231	0.80321	0.80577	0.81667
	0.20875	0.79125	0.77750	0.79125	0.80500	0.79812	0.79125	0.78437
	0.15792	0.84208	0.86500	0.81875	0.84250	0.83063	0.85375	0.84187
	0.18417	0.81583	0.83500	0.79875	0.81375	0.80625	0.82438	0.81687
	0.18333	0.81667	0.82125	0.80625	0.82250	0.81437	0.82188	0.81375
	0.17125	0.82875	0.82875	0.83625	0.82125	0.82875	0.82500	0.83250
	0.16458	0.83542	0.86375	0.84375	0.79875	0.82125	0.83125	0.85375
	0.18803	0.81197	0.80641	0.81154	0.81795	0.81474	0.81218	0.80897
	0.15500	0.84500	0.83125	0.84000	0.86375	0.85187	0.84750	0.83562
	0.19542	0.80458	0.83125	0.78250	0.80000	0.79125	0.81563	0.80688
	0.15792	0.84208	0.85000	0.82625	0.85000	0.83813	0.85000	0.83813
	0.19167	0.80833	0.80625	0.79875	0.82000	0.80937	0.81312	0.80250
	0.19458	0.80542	0.82500	0.76875	0.82250	0.79563	0.82375	0.79688
	0.16292	0.83708	0.85000	0.83500	0.82625	0.83063	0.83813	0.84250
	0.17137	0.82863	0.84615	0.81154	0.82821	0.81987	0.83718	0.82885
	0.15875	0.84125	0.84000	0.83250	0.85125	0.84187	0.84562	0.83625
	0.18250	0.81750	0.81500	0.80375	0.83375	0.81875	0.82438	0.80937
	0.31250	0.68750	0.65625	0.68625	0.72000	0.70312	0.68812	0.67125
	0.16708	0.83292	0.86250	0.82125	0.81500	0.81812	0.83875	0.84188
	0.18917	0.81083	0.82375	0.81625	0.79250	0.80437	0.80813	0.82000
	0.16958	0.83042	0.84250	0.81500	0.83375	0.82438	0.83813	0.82875
	0.17500	0.82500	0.84079	0.83947	0.79474	0.81711	0.81776	0.84013
	0.19583	0.80417	0.80750	0.80250	0.80250	0.80250	0.80500	0.80500
	0.16500	0.83500	0.83000	0.82750	0.84750	0.83750	0.83875	0.82875
	0.20083	0.79917	0.78500	0.79625	0.81625	0.80625	0.80063	0.79062
	0.18947	0.81053	0.83421	0.79474	0.80263	0.79868	0.81842	0.81447
	0.16083	0.83917	0.85875	0.83250	0.82625	0.82937	0.84250	0.84563
	0.17875	0.82125	0.83375	0.80625	0.82375	0.81500	0.82875	0.82000
	0.19083	0.80917	0.82125	0.81125	0.79500	0.80312	0.80812	0.81625
	0.19333	0.80667	0.82125	0.79750	0.80125	0.79937	0.81125	0.80937
	0.18917	0.81083	0.80250	0.82000	0.81000	0.81500	0.80625	0.81125
	0.16333	0.83667	0.86500	0.82750	0.81750	0.82250	0.84125	0.84625
	0.16833	0.83167	0.83250	0.82250	0.84000	0.83125	0.83625	0.82750
	0.18833	0.81167	0.83125	0.81000	0.79375	0.80188	0.81250	0.82063
	0.17000	0.83000	0.81125	0.86750	0.81125	0.83937	0.81125	0.83938
	0.19083	0.80917	0.82125	0.80375	0.80250	0.80313	0.81187	0.81250
Mean	0.18247	0.81753	0.82533	0.81071	0.81656	0.81363	0.82095	0.81802
STD	0.02544	0.02544	0.03451	0.02796	0.02404	0.02315	0.02667	0.0291