Improving Wrist Force Estimation With Surface EMG During Isometric Contractions
Bibliographic record
Abstract
In this paper, methods for selecting channels to improve estimated force using fast orthogonal search (FOS) have been investigated and a new method is proposed. The surface electromyogram (sEMG) signal acquired from linear surface electrode arrays, placed on the long head and short head of biceps brachii and brachioradialis during isometric contractions are used to estimate force induced at wrist using the FOS algorithm. In this paper, the effects of the sEMG signal characteristics obtained from the arrays and channels’ locations on the estimated force are investigated to find channels resulting in force estimation improvement compared to using all available channels. Several methods for channel selection have been studied, showing that the sensitivity of the estimated force to the location of the channels is subject-dependent. The proposed method uses only the channels with highest mean of power spectrum density (PSD) and low cross correlations. The channels selected by this method have improved FOS force estimate compared to using all the available channels.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".