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Table 3 Pseudo-online results for each subject with features extracted at optimal time intervals

From: Analyzing EEG signals to detect unexpected obstacles during walking

C S P
Subject Time recording [s] No. Obstacles True reaction detection False detection/min
    k =2 k =3 k =4 k =2 k =3 k =4
S1 186.0 14 4 3 2 18.88 13.63 9.01
S2 184.5 14 13 9 3 13.38 6.70 3.16
S3 184.0 14 2 2 1 5.65 1.77 0.71
S4 198.5 14 7 7 6 12.90 6.46 2.41
S5 115.5 6 4 3 2 19.70 15.06 8.80
P O W E R
Subject Time recording [s] No. Obstacles True reaction detection False detection/min
    k =2 k =3 k =4 k =2 k =3 k =4
S1 186.0 14 4 4 3 15.03 13.63 11.88
S2 184.5 14 12 12 12 19.36 17.25 15.85
S3 184.0 14 3 2 2 4.24 4.24 2.12
S4 198.5 14 6 4 4 9.96 9.06 6.64
S5 115.5 6 2 2 0 11.42 9.35 7.27
S L O P E
Subject Time recording [s] No. Obstacles True reaction detection False detection/min
    k =2 k =3 k =4 k =2 k =3 k =4
S1 186.0 14 6 4 4 22.73 12.94 8.04
S2 184.5 14 12 11 10 13.29 9.09 4.55
S3 184.0 14 4 3 2 3.88 3.53 2.12
S4 198.5 14 2 0 0 2.41 0.60 0.30
S5 115.5 6 2 2 0 4.15 1.55 1.02
P O L Y N O M I A L
Subject Time recording [s] No. Obstacles True obstacle detection False detection/min
    k =2 k =3 k =4 k =2 k =3 k =4
S1 186.0 14 5 4 4 12.94 10.48 8.04
S2 184.5 14 14 10 6 12.68 6.34 2.11
S3 184.0 14 6 1 0 8.48 4.94 1.77
S4 198.5 14 1 0 0 2.71 0.00 0.00
S5 115.5 6 4 1 1 11.94 3.63 1.55