Garments for functional electrical stimulation: Design and proofs of concept
Bibliographic record
Abstract
INTRODUCTION: Repeated use of functional electrical stimulation can promote functional recovery in individuals with neurological paralysis. We designed garments able to deliver functional electrical stimulation. METHODS: Shirts and pants containing electrodes knitted with a conductive yarn were produced. Electrodes were moistened with water before use. Stimulation intensity at four thresholds levels (sensory, movement, full range of motion, and maximal), stimulation comfort, and electrical properties of the interface were tested in one able-bodied subject with garment electrodes and size-matched conventional gel electrodes. The pants and shirt were then used to explore usability and design limitations. RESULTS: Compared to gel electrodes, fabric electrodes had a lower sensory threshold (on forearm muscles) but they had a higher maximal stimulation threshold (for all tested muscles). The stimulation delivery was comfortable when the garment electrodes were recently moistened; however, as the electrodes dried (within 9 to 18 min) stimulation became unpleasant. Inconsistent water content in the fabric electrodes caused inconsistent intensity thresholds and inconsistent voltage necessary to apply a desired stimulation current. Garments' tightness and impracticality of electrode lead necessitate further design improvement. CONCLUSIONS: Fabric electrodes offer a promising alternative to gel electrodes. Further work involving people with paralysis is required to overcome the identified challenges.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".