Development of a multichannel current-EMG system for coherence modulation with visual biofeedback
Bibliographic record
Abstract
By means of biofeedback, neuromotor control can be modified. Recent biofeedback experiments have used the power of the electromyogram of one muscle in different frequency bands to control a two-dimensional cursor. However, the human body usually requires coherent activation of multiple muscles to achieve daily life tasks. Additionally, electromyography (EMG) instrumentation has remained the same for decades, and might not be the most suitable to measure coherent activations from pennated muscles according to recent experiments by von Tscharner and colleagues. In this study, we propose the development of a multichannel current-based EMG amplifier to use intermuscular coherence as the control feature of a visual biofeedback system. The system was used in a leg extension protocol to voluntarily increase intermuscular coherence between the vastii muscles. Results from ten subjects show that it is possible to increase intermuscular coherence through visual biofeedback. Such a system can have applications in endurance training and rehabilitation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".