Force Estimation in Multiple Degrees of Freedom From Intramuscular Emg Via Muscle Synergies
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Bibliographic record
Abstract
Force estimation is an important factor in proportional control of prosthetic arms. Muscle synergies seem to be relevant for force estimation since they are patterns of co- activations of muscles during actions. This study investigates the use of muscle synergies extracted from intramuscular electromyography (EMG) for estimating force during multiple degrees of freedom (DOF) voluntary contraction. For this purpose, muscle synergies of the contractions were extracted from six superficial forearm muscles from four able- bodied subjects. Also, the isometric force produced by the wrist during these contractions were recorded along multiple axes each responsible for one DOF. The neural inputs were then fed to an Artificial Neural Network (ANN) to estimate the force. The results show a significant correlation between the estimated and measured force.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it