A dry polymer nanocomposite transcutaneous electrode for functional electrical stimulation
Bibliographic record
Abstract
BACKGROUND: Functional electrical stimulation (FES) can be used in rehabilitation to aid or improve function in people with paralysis. In clinical settings, it is common practice to use transcutaneous electrodes to apply the electrical stimulation, since they are non-invasive, and can be easily applied and repositioned as necessary. However, the current electrode options available for transcutaneous FES are limited and can have practical disadvantages, such as the need for a wet interface with the skin for better comfort and performance. Hence, we were motivated to develop a dry stimulation electrode which could perform equivalently or better than existing commercially available options. METHODS: We manufactured a thin-film dry polymer nanocomposite electrode, characterized it, and tested its performance for stimulation purposes with thirteen healthy individuals. We compared its functionality in terms of stimulation-induced muscle torque and comfort level against two other types of transcutaneous electrodes: self-adhesive hydrogel and carbon rubber. Each electrode type was also tested using three different stimulators and different intensity levels of stimulation. RESULTS: We found the proposed dry polymer nanocomposite electrode to be functional for stimulation, as there was no statistically significant difference between its performance to the other standard electrodes. Namely, the proposed dry electrode had comparable muscle torque generated and comfort level as the self-adhesive hydrogel and carbon rubber electrodes. From all combinations of electrode type and stimulators tested, the dry polymer nanocomposite electrode with the MyndSearch stimulator had the most comfortable average rating. CONCLUSIONS: The dry polymer nanocomposite electrode is a durable and flexible alternative to existing self-adhesive hydrogel and carbon rubber electrodes, which can be used without the addition of a wet interfacing agent (i.e., water or gel) to perform as well as the current electrodes used for stimulation purposes.
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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) | 0.000 | 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) | 0.001 | 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".