Influence of phase duration and waveform on the relative recruitment of motor and sensory axons in a human peripheral nerve
Bibliographic record
Abstract
Electrical stimulation can be used to stimulate human peripheral nerves, for some applications sensory axons are the targets, for others the targets are motor axons. Presently, we assessed the influence of two stimulus parameters, phase duration and waveform, on the relative recruitment of sensory versus motor axons. Four monophasic pulses (0.1, 0.5, 1.0, and 2.0 ms phase durations), two square biphasic pulses (0.125 and 0.5 ms phase durations) and two sinusoidal biphasic kilohertz frequency alternating current pulses (KFAC: 0.1, 0.5 ms phase durations), were tested in twenty participants. Pulses were delivered to generate soleus M-wave versus H-reflex recruitment curves ( n = 40 stimuli) and, in separate trials, to produce M-waves that were ∼5% of the maximal M-wave ( n = 20 stimuli). Changes in the amplitude of H-reflexes, relative to M-waves, between pulses provided measures of the relative recruitment of sensory versus motor axons. There was a significant effect of phase duration, but not waveform, on most of outcome measures that was consistent with a preferential recruitment of sensory over motor axons when using pulses with longer phase durations. The phase duration of a stimulus pulse, but not its waveform, influenced the relative recruitment of sensory and motor axons in the human tibial nerve. For monophasic, biphasic, and sinusoidal KFAC waveforms, short phase durations preferentially target motor axons, and longer phase durations target sensory axons. Our findings may help clinicians to better understand the impact of phase duration and waveforms on ES and to design more rational stimulation strategies.
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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 | 0.005 |
| 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".