Torque, Current, and Discomfort During 3 Types of Neuromuscular Electrical Stimulation of Tibialis Anterior
Bibliographic record
Abstract
BACKGROUND: The benefits of neuromuscular electrical stimulation (NMES) for rehabilitation depend on the capacity to generate functionally relevant torque with minimal fatigability and discomfort. Traditionally, NMES is delivered either over a muscle belly (mNMES) or a nerve trunk (nNMES). Recently, a technique that minimizes contraction fatigability by alternating pulses between the mNMES and nNMES sites, termed "interleaved" NMES (iNMES), was developed. However, discomfort and the ability to generate large torque during iNMES have not been explored adequately. OBJECTIVE: The study objective was to compare discomfort and maximal torque between mNMES, nNMES, and iNMES. METHODS: Stimulation trains (12 pulses at 40 Hz) were delivered to produce dorsiflexion torque using mNMES, nNMES, and iNMES. Discomfort was assessed using a visual analogue scale for contractions that generated 5-30% of a maximal voluntary isometric contraction (MVIC), and for the maximal tolerable torque. RESULTS: Discomfort scores were not different between NMES types when torque was ≤20% MVIC. At 30% MVIC, mNMES produced more discomfort than nNMES and iNMES. nNMES produced the most torque (65% MVIC), followed by iNMES (49% MVIC) and mNMES (33% MVIC); in these trials, mNMES produced more discomfort than nNMES, but not iNMES. LIMITATIONS: The present results may be limited to individuals with no history of neuromusculoskeletal impairment. CONCLUSIONS: In terms of discomfort, there were no differences between mNMES, nNMES, or iNMES for contractions between 5-20% MVIC. However, mNMES produced more discomfort than nNMES and iNMES for contractions of 30% MVIC, while for larger contractions, mNMES only produced more discomfort than nNMES. The advantages and disadvantages of each NMES type should be considered prior to implementation in rehabilitation programs.
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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".