Table 6 The result of the algorithm using five wrist positions in the training dataset, one-step regression
From: Regressing grasping using force myography: an exploratory study
Included wrist position in training dataset | \(\theta _{TI}\) | \(\theta _{TM}\) | ||
|---|---|---|---|---|
\(R^2\) | \(RMSE\%\) | \(R^2\) | \(RMSE\%\) | |
Extension, Flexion, Neutral, Pronation, Radial, Ulnar | 0.872 ± 0.034 | 9.402 ± 1.052 | 0.941 ± 0.021 | 6.133 ± 0.843 |
Flexion, Neutral, Pronation, Radial, Ulnar | 0.821 ± 0.056 | 11.072 ± 1.375 | 0.901 ± 0.051 | 7.810 ± 1.575 |
Extension, Flexion, Neutral, Radial, Ulnar | 0.842 ± 0.046 | 10.432 ± 1.362 | 0.927 ± 0.034 | 6.748 ± 1.221 |
Extension, Flexion, Neutral, Pronation, Ulnar | 0.845 ± 0.046 | 10.320 ± 1.343 | 0.925 ± 0.039 | 6.797 ± 1.187 |
Extension, Flexion, Neutral, Pronation, Radial | 0.832 ± 0.051 | 10.722 ±1.238 | 0.919 ± 0.039 | 7.239 ± 1.070 |