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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