Wide-pulse-width, high-frequency neuromuscular stimulation: implications for functional electrical stimulation
Bibliographic record
Abstract
Electrical stimulation (1-ms pulses, 100 Hz) produces more torque than expected from motor axon activation (extra contractions). This experiment investigates the most effective method of delivering this stimulation for neuromuscular electrical stimulation. Surface stimulation (1-ms pulses; 20 Hz for 2 s, 100 Hz for 2 s, 20 Hz for 3 s) was delivered to triceps surae and wrist flexors (muscle stimulation) and to median and tibial nerves (nerve stimulation) at two intensities. Contractions were evaluated for amplitude, consistency, and stability. Surface electromyograph was collected to assess how H-reflexes and M-waves contribute. In the triceps surae, muscle stimulation produced the largest absolute contractions (23% maximal voluntary contraction), evoked the largest extra contractions as torque increased by 412% after the 100-Hz stimulation, and was more consistent and stable compared with tibial nerve stimulation. Absolute and extra contraction amplitude, consistency, and stability of evoked wrist flexor torques were similar between stimulation types: torques reached 11% maximal voluntary contraction, and extra contractions increased torque by 161%. Extra contractions were 10 times larger in plantar flexors compared with wrist flexors with muscle stimulation but were similar with nerve stimulation. For triceps surae, H reflexes were 3.4 times larger than M waves during nerve stimulation, yet M waves were 15 times larger than H reflexes during muscle stimulation. M waves in the wrist flexors were larger than H reflexes during nerve (8.5 times) and muscle (18.5 times) stimulation. This is an initial step toward utilizing extra contractions for neuromuscular electrical stimulation and the first to demonstrate their presence in the wrist flexors.
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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".