Non-Invasive and Flexible Electrodes Based on Multimaterial Fiber for sEMG Signal Detection
Bibliographic record
Abstract
A novel sensor made of a multimaterial metal-polymer-glass hollow-core fiber connected to a smart wearable sensing device, for surface electromyography (sEMG) measurement, is proposed. The high flexibility of the fibers allows their easy integration into stretchable garments and textiles, without compromising the comfort of the users. The multimaterial fiber electrodes were first optimized in length and inter-electrode distance by recording different sEMG signals. With the first prototype achieved, sEMG signals from the forearm flexor, and the biceps muscles were recorded. The collected data were compared to a commercial grade sensor and the use of Ag/AgCl electrodes. Frequency and time domain content analysis show that the new flexible sensor enables the recording of comparable sEMG signals, in addition to being suitable for use on muscle zones on which rigid electrode type or wearable sensor cannot be used. This opens up a wide range of applications, in particular for assistive technology devices, and telemedicine.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".