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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