Detecting muscle contractions using strain gauges
Bibliographic record
Abstract
Myoelectric prostheses aim to help amputees to experience partial function of the absent organ. The sensors usually used to control the prostheses are surface electromyography (sEMG) electrodes, of which the number tends to increase with the increase of the number of degrees of freedom in the recent prostheses, i.e. dozens of sensors today. However, sEMG requires a high sampling frequency, traditionally about 1000 Hz, which drastically limits the number of sensors that the processors can manage. The objective is to develop a device enabling to measure muscle contractions (MCs) with a sampling frequency compared with the movement frequencies. Strain gauges are known for their accuracy, so using them to detect MCs could help to predict the movement intentions of the amputee. The designed devise includes the integration of four strain gauges in silicone rubber that is similar to human skin. The reliability of the sensor results is demonstrated by a comparison with Ag/AgCl electrodes of an electromyography system. The correlation coefficient is very high (0.89) between the tensions measured by the sEMG and the strain gauges. So the advantage of a low sampling frequency compared with sEMG is the potential development of matrices with many strain gauges.
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How this classification was reachedexpand
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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".