Enhanced transcutaneous electrical nerve stimulation achieved by a localized virtual bipole: a computational study of human tibial nerve stimulation
Bibliographic record
Abstract
OBJECTIVE: Electrical neuromodulation is a clinically effective therapeutic instrument, currently expanding into newer indications and larger patient populations. Neuromodulation technologies are also moving towards less invasive approaches to nerve stimulation. In this study, we investigated an enhanced transcutaneous electrical nerve stimulation (eTENS) system that electrically couples a conductive nerve cuff with a conventional TENS electrode. The objectives were to better understand how eTENS achieves lower nerve activation thresholds, and to test the feasibility of applying eTENS in a human model of peripheral nerve stimulation. APPROACH: A finite element model (FEM) of the human lower leg was constructed to simulate electrical stimulation of the tibial nerve, comparing TENS and eTENS. Key variables included surface electrode diameter, nerve cuff properties (conductivity, length, thickness), and cuff location. Enhanced neural excitability was predicted by relative excitability (RE > 1), derived using either the activating function (AF) or the nerve activation threshold (MRG model). MAIN RESULTS: ), and cuff position relative to the cathodic surface electrode. SIGNIFICANCE: This study provides a theoretical basis for designing and testing eTENS applied to various neural targets and data suggesting function of eTENS in large models of nerve stimulation. Although eTENS carries key advantages over existing technologies, further work is needed to translate this approach into effective clinical applications.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".