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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