Investigation of Interelectrode Distance for Surface Recording of Electrical Responses From a Single Motor Unit: A Simulation Study
Bibliographic record
Abstract
Computer simulation studies of physiologically informed mathematical models have successfully revealed the dependence of the surface electromyogram (sEMG) on the functional and structural properties of the neuromuscular system. The surface recording of the propagating motor unit action potential (MUAP) is influenced by the montage of the recording electrode placed on the skin during differential sEMG recording. In this context, along with several other topographical factors of the motor units (MU), the appropriate inter-electrode distance (IED) along the directions of the muscle fiber is of vital importance. Here, we have proposed and implemented a physiologically relevant three-dimensional in-silico model of activated muscle fibers associated with a single motor unit to investigate the effect of the IED exclusively under several conditions. Based on the model output, we found the optimal IED (OIED) that records the maximum peak-to-peak (P-P) amplitude of sEMG signals. The OIEDs were found to vary from 6 to 13 mm according to the selected muscle fiber parameters (i.e., fiber length, fiber density, distribution of innervation zone, fiber distribution, fiber alignment etc.). We have reported that the OIED values are positively correlated with fiber depth, while a millimeter increase in MU territory results in 8% reduction of the OIED (p < 0.01). The concentrically distributed fiber density resulted 14% lower (p < 0.05) OIEDs compared to the randomly distributed fibers. Finally, this paper provides a method of IED optimization to potentially improve the EMG signal that may be usefully combined with more complex models in future studies.
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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".