Minimizing Discomfort with Surface Neuromuscular Stimulation
Bibliographic record
Abstract
The purpose of this study was to evaluate the effects of stimulus parameters, electrode types, and electrode positions on the perception of discomfort during lower extremity surface neuromuscular stimulation. Ten normal and eight neurologically impaired (four incomplete spinal cord and four stroke) subjects were enrolled. Neurologically impaired subjects had some sensation, although it was often reduced. Parameters of the stimulation were varied in a way that produced the same level of ankle dorsiflexion, as measured with a goniometer. Discomfort was assessed after each stimulation with a 0-10 verbal scale (0, no discomfort; 10, worst pain). Increasing the pulse frequency was associated with increased discomfort for subjects in both groups (p > 0.05). Increasing the pulse duration was associated with increased discomfort in the neurologically impaired subjects (p > 0.05), but not in the normal subjects (p > 0.05). The electrode size and type had no effects on discomfort (p > 0.05). Stimulation of the peroneal nerve over the fibular head was better tolerated than the direct motor point stimulation of the tibialis anterior motor point (p < 0.05). The data suggest that to minimize discomfort, surface stimulation should be applied over nerves rather than motor points, and frequency and pulse duration should be set as low as possible for a given degree of contraction.
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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 | 0.003 |
| 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) | 0.002 | 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".