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Table 1 Accuracy of the trajectories predicted with MEG

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

0.726 (0.224)

10.041 (3.584)

11.040 (4.334)

2

0.706 (0.216)

10.165 (3.458)

11.068 (4.490)

2

1

0.513 (0.381)

17.418 (7.194)

16.086 (6.086)

2

0.569 (0.321)

16.953 (9.258)

4.027 (2.205)

3

1

0.812 (0.166)

13.383 (6.544)

6.499 (4.175)

2

0.820 (0.188)

20.006 (70.367)

7.595 (4.786)

4

1

0.762 (0.219)

7.935 (3.147)

8.239 (3.241)

2

0.800 (0.233)

6.919 (3.108)

6.787 (3.537)

5

1

0.754 (0.210)

8.560 (3.080)

8.086 (3.483)

2

0.657 (0.269)

11.038 (4.098)

10.351 (4.849)

6

1

0.654 (0.265)

8.401 (3.299)

9.004 (4.372)

2

0.770 (0.233)

6.811 (1.880)

8.391 (3.118)

7

1

0.728 (0.196)

10.304 (3.656)

10.564 (4.397)

2

0.750 (0.210)

8.745 (3.098)

8.395 (4.076)

8

1

0.699 (0.274)

11.379 (6.137)

12.190 (5.771)

2

0.762 (0.209)

10.522 (8.859)

11.621 (4.163)

9

1

0.620 (0.277)

11.022 (4.401)

11.346 (6.023)

2

0.584 (0.246)

11.169 (3.924)

12.850 (6.033)

Average

 

0.705 (0.292)

11.154 (5.399)

9.714 (4.789)

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