Effect of Modulated TENS on Muscle Activation, Oxygenation, and Pain: Searching for a Physiological Mechanism
Bibliographic record
Abstract
Objectives: To understand the possible physiological mechanisms of a modulated transcutaneous electrical nerve stimulation [TENS] device on the reported reductions in pain using quantitative electromyography to measure muscle activation and near-infrared spectroscopy to estimate muscular oxygenation levels.Methods: All subjects self-selected the intensity of the TENS stimulation current. Electromyography, near-infrared spectroscopy and a color analog scale of pain intensity to measure reported pain levels were collected both pre- and post-treatment. For Studies 1 and 2, measures of muscle activity and self-perceived pain were taken from 51 male and female subjects. For study 3, measures of muscle oxygenation and pain scores were taken from 12 different subjects.Results: Myoelectric activation level and pain scores of painful muscles were reduced after treatment [P < 0.001] with no change in activation or pain in the control muscles. The follow-up study revealed that muscle oxygenation was significantly increased in the treatment trials when compared to the control trials [P = 0.013], while the color analog scale of pain intensity pain scores decreased [P <. 05].Conclusions: Pain reduction following TENS treatment has been reported before. The documented reduction in muscle activation suggests less vasoconstriction from prolonged contraction. Simultaneous documentation of increases in available oxygen suggests a tenable mechanism; reduced contraction level and less oxygen consumption, and/or more blood flow suggests an increased capacity to flush metabolites known to cause pain.
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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 | 0.000 | 0.001 |
| 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".