Effects of Inspiratory Muscle Training on Whole Body Exercise Performance in Males
Bibliographic record
Abstract
It has been shown in humans that following a bout of whole body endurance exercise at intensity level greater than 85% VO2 max the diaphragm response to supramaximal electrical stimulation was substantially lower compared to the pre-exercise response. This fatigue of the major inspiratory muscle could potentially be limiting to intense whole body exercise performance. PURPOSE: To examine the effects of inspiratory muscle training (IMT) on whole body exercise performance time. METHODS: Forty male subjects Gave informed consent and were randomly placed in four groups; a control group (N=10, CON), an inspiratory muscle training group (N=10, IMT), a whole body exercise group (N=10, WB), and a group doing whole body training followed by inspiratory muscle training (N=10, WB+IMT). WB training consisted of 10–20 minute on a cycle ergometer working at 90% VO2max. IMT required the subject to inspire against a resistive load set at 50% of the subjects measured maximal inspiratory pressure (MIP). The subject performed 30 maximal efforts at this load followed by a 10 minute break and then performed 30 more maximal efforts. The training sessions were done three times per week for six weeks. Pre and post training testing consisted of an incremental cycle ergometer test to determine VO2max and two 10 kilometer time trials (10 KmTT) on a cycle ergometer. The time to complete the 10 Km TT was used as the indication of performance. Comparisons of performance time were made between pre vs. post -training within a group and between groups. RESULTS: The post-training performance times were significantly reduced for the IMT(97% of pre-training time), WB (96% of pre-training time) and WB+IMT(92% of pre-training time) groups versus pre-training times (p<0.05). The largest decrease in performance time was found in the WB+IMT group (8% lower vs. pre-training) and was substantially different vs. WB (4% lower) and IMT groups (3% lower) (p<0.05). CONCLUSION: Improvements in whole body exercise performance due to IMT program may be enhanced by preceding the IMT training session with a short bout of intense whole body exercise.
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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 | 0.000 |
| 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) | 0.003 | 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".