Perception of effort during an isometric contraction is influenced by prior muscle lengthening or shortening
Bibliographic record
Abstract
Abstract Purpose Following a shortening or lengthening muscle contraction, the torque produced in the isometric steady state is distinctly lower (residual torque depression; rTD) or higher (residual torque enhancement; rTE), respectively, compared to a purely isometric contraction at the same final muscle length and level of activation. This is referred to as the history dependence of force. When matching a given torque level, there is greater muscle activation (electromyography; EMG) following shortening and less activation following lengthening. Owing to these differences in neuromuscular activation, it is unclear whether perception of effort is altered by the history dependence of force. Methods Experiment 1 tested whether perception of effort differed between the rTD and rTE state when torque was matched. Experiment 2 tested whether perception of effort differed between the rTD and rTE state when EMG was matched. Finally, experiment 3 tested whether EMG differed between the rTD and rTE state when perception of effort was matched. Results When torque was matched, both EMG and perception of effort were higher in the rTD compared to rTE state. When EMG was matched, torque was lower in the rTD compared to rTE state while perception of effort did not differ between the two states. When perception of effort was matched, torque was lower in the rTD compared to rTE state and EMG did not differ between the two states. Conclusion The combined results from these experiments indicate that the history dependence of force alters one’s perception of effort, dependent on the level of motor command.
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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 | 0.004 |
| 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 | 0.001 | 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".