Exercise in space: the European Space Agency approach to in-flight exercise countermeasures for long-duration missions on ISS
Bibliographic record
Abstract
BACKGROUND: To counteract microgravity (µG)-induced adaptation, European Space Agency (ESA) astronauts on long-duration missions (LDMs) to the International Space Station (ISS) perform a daily physical exercise countermeasure program. Since the first ESA crewmember completed an LDM in 2006, the ESA countermeasure program has strived to provide efficient protection against decreases in body mass, muscle strength, bone mass, and aerobic capacity within the operational constraints of the ISS environment and the changing availability of on-board exercise devices. The purpose of this paper is to provide a description of ESA's individualised approach to in-flight exercise countermeasures and an up-to-date picture of how exercise is used to counteract physiological changes resulting from µG-induced adaptation. Changes in the absolute workload for resistive exercise, treadmill running and cycle ergometry throughout ESA's eight LDMs are also presented, and aspects of pre-flight physical preparation and post-flight reconditioning outlined. RESULTS: With the introduction of the advanced resistive exercise device (ARED) in 2009, the relative contribution of resistance exercise to total in-flight exercise increased (33-46 %), whilst treadmill running (42-33 %) and cycle ergometry (26-20 %) decreased. All eight ESA crewmembers increased their in-flight absolute workload during their LDMs for resistance exercise and treadmill running (running speed and vertical loading through the harness), while cycle ergometer workload was unchanged across missions. CONCLUSION: Increased or unchanged absolute exercise workloads in-flight would appear contradictory to typical post-flight reductions in muscle mass and strength, and cardiovascular capacity following LDMs. However, increased absolute in-flight workloads are not directly linked to changes in exercise capacity as they likely also reflect the planned, conservative loading early in the mission to allow adaption to µG exercise, including personal comfort issues with novel exercise hardware (e.g. the treadmill harness). Inconsistency in hardware and individualised support concepts across time limit the comparability of results from different crewmembers, and questions regarding the difference between cycling and running in µG versus identical exercise here on Earth, and other factors that might influence in-flight exercise performance, still require further investigation.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".