Neck and Inspiratory Muscle Recruitment during Inspiratory Loading and Neck Flexion
Bibliographic record
Abstract
PURPOSE: This study aimed to compare muscle activation of the diaphragm (DIA), scalenes (SA), parasternal intercostals (PS), and sternomastoid (SM) during submaximal intermittent neck flexion (INF) versus submaximal inspiratory threshold loading (ITL) until task failure in healthy adults. METHODS: Twelve healthy adults performed submaximal ITL or INF tests in random order for 2 d. Surface electromyography was monitored to acquire root mean square (RMS) and median power frequency (MPF) from the SA, PS, SM, and DIA. Maximal inspiratory pressures and maximal voluntary contraction for neck flexion were determined. Next, participants performed the first submaximal test-ITL or INF-targeting 50% ± 5% of the maximal inspiratory pressure or maximal voluntary contraction, respectively, until task failure. After a rest, they performed the other test until task failure. Two days later, they performed ITL and INF but in the opposite order. The Borg scale assessed breathlessness and perceived exertion. RESULTS: Endurance times for ITL and INF were 38.1 and 26.3 min, respectively. INF activated three of four inspiratory muscles at higher average RMS (PS, SM, and SA) and at different MPF (PS, SM, and DIA but not SA) compared with ITL. During ITL, RMS did not change in the four inspiratory muscles over time, but MPF decreased in PS, SM, and SA (P < 0.04). In contrast, RMS increased in three of four inspiratory muscles (SM, PS, and SA) during INF, but MPF did not change throughout its duration. Borg rating was 3.9-fold greater than ITL compared with INF. CONCLUSION: At a similar percentage of maximal load, INF evokes greater activation of primary muscles of inspiration (PS and SA) and a major accessory muscle of inspiration (SM) compared with ITL during a prolonged submaximal protocol.
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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) | 0.001 | 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".