Physiological interdependence of the cardiovascular and postural control systems under orthostatic stress
Bibliographic record
Abstract
The cardiovascular system has been observed to respond to changes in human posture and the environment. On the same lines, frequent fallers have been observed to suffer from cardiovascular deficits. The present article aims to demonstrate the existence of interactions between the cardiovascular and postural control systems. The behavior of the two systems under orthostatic challenge was studied through novel adaptations of signal processing techniques. To this effect, the interactions between the two systems were assessed with two metrics, coherence and phase lock value, based on the wavelet transform. Measurements from the cardiovascular system (blood pressure), lower limb muscles (surface electromyography), and postural sway (center of pressure) were acquired from young healthy adults (n = 28, men = 12, age = 20-28 yr) during quiet stance. The continuous wavelet transform was applied to decompose the representative signals on a time-scale basis in a frequency region of 0.01 to 0.1 Hz. Their linear coupling was quantified through a coherence metric, and the synchrony was characterized via the phase information. The outcomes of this study present evidence that the cardiovascular and postural control systems work together to maintain homeostasis under orthostatic challenge. The inferences open a new direction of study for effects under abnormalities and extreme environmental conditions.
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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".