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Table 2 Accuracy of the trajectories predicted with EEG

From: A study on a robot arm driven by three-dimensional trajectories predicted from non-invasive neural signals

Subject

Session

Correlation

RMSE (cm)

TPE (cm)

1

1

0.777 (0.204)

19.606 (58.826)

4.539 (2.771)

2

0.745 (0.209)

11.569 (13.751)

11.915 (4.293)

2

1

0.743 (0.333)

14.908 (8.867)

12.007 (4.061)

2

0.592 (0.255)

19.262 (37.090)

14.923 (4.700)

3

1

0.743 (0.202)

12.694 (17.501)

10.547 (4.033)

2

0.756 (0.224)

11.065 (6.688)

9.923 (3.766)

4

1

0.587 (0.197)

15.007 (3.204)

13.643 (4.747)

2

0.729 (0.205)

12.267 (2.833)

9.369 (3.005)

5

1

0.437 (0.459)

17.402 (10.729)

7.726 (5.526)

2

0.439 (0.539)

17.590 (7.753)

8.854 (7.744)

6

1

0.635 (0.271)

14.435 (3.482)

8.486 (5.152)

2

0.569 (0.308)

15.037 (3.454)

10.115 (4.403)

7

1

0.592 (0.277)

12.385 (3.259)

17.309 (4.899)

2

0.820 (0.175)

11.011 (2.415)

13.828 (3.380)

8

1

0.787 (0.186)

12.225 (3.719)

14.689 (3.600)

2

0.798 (0.129)

10.773 (3.181)

12.563 (3.875)

9

1

0.800 (0.155)

10.158 (2.485)

12.852 (4.224)

2

0.765 (0.198)

9.638 (2.846)

12.482 (4.333)

Average

 

0.684 (0.309)

13.724 (5.370)

11.432 (4.749)

  1. Values in brackets represent standard deviations
  2. RMSE root mean square error, TPE terminal point error