Research Article
Estimation of Continuous Joint Angles of Upper Limb Based on sEMG by Using GA-Elman Neural Network
Table 2
and
estimated by subjects using three NNs.
| ā | GA-Elman | GA-BP | Elman |
| Subject A | Shoulder | | 4.1417 | 7.3099 | 10.2045 | | 0.7833 | 0.5918 | 0.4514 | Elbow | | 5.1253 | 8.3085 | 9.3042 | | 0.8222 | 0.5041 | 0.6763 | Subject B | Shoulder | | 3.0728 | 6.3099 | 10.1078 | | 0.8142 | 0.7015 | 0.5912 | Elbow | | 7.1421 | 4.8686 | 8.5155 | | 0.7723 | 0.8203 | 0.6565 | Subject C | Shoulder | | 6.1708 | 10.1952 | 8.1873 | | 0.7841 | 0.5480 | 0.6521 | Elbow | | 1.1358 | 7.2054 | 9.2116 | | 0.8556 | 0.7489 | 0.4302 | Subject D | Shoulder | | 3.1324 | 6.1982 | 6.1745 | | 0.8764 | 0.6102 | 0.6975 | Elbow | | 3.0988 | 10.2543 | 10.1865 | | 0.7874 | 0.4972 | 0.6153 | Subject E | Shoulder | | 4.1053 | 9.2633 | 9.1954 | | 0.7954 | 0.6645 | 0.6253 | Elbow | | 5.1623 | 8.2845 | 10.2064 | | 0.8133 | 0.6572 | 0.5382 | Subject F | Shoulder | | 3.2588 | 8.0483 | 8.4527 | | 0.8253 | 0.7235 | 0.6348 | Elbow | | 4.3527 | 7.6523 | 7.2594 | | 0.8075 | 0.7838 | 0.6972 |
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