Modeling Perceived Exertion during Graded Arm Cycling Exercise in Spinal Cord Injury
Bibliographic record
Abstract
PURPOSE: RPE may be useful for exercise testing and prescription in individuals with spinal cord injury (SCI), although the roles of differentiated central and peripheral fatigue during exercise are not clear. We aimed to model differentiated RPE responses during graded arm cycling in individuals with SCI and to describe their relationship to cardiorespiratory outcomes. METHODS: Thirty-six individuals with SCI (13 paraplegia and 23 tetraplegia) completed a maximal graded arm cycling exercise test to volitional exhaustion (5 W·min paraplegia; 10 W·min tetraplegia). Participants were asked to report central RPE (CRPE) and peripheral RPE (PRPE) every minute using the Borg category ratio (CR10) scale until termination of exercise. Heart rate and breath-by-breath respiratory outcomes were collected throughout the exercise test. Ventilatory threshold (VT) was assessed using the ventilatory equivalents method. RESULTS: Cardiorespiratory indices increased linearly during graded arm exercise. By contrast, both CRPE and PRPE responses were best fit to a quadratic model with positively accelerating growth in individuals with paraplegia (P < 0.01) and tetraplegia (P < 0.05). PRPE developed faster than CRPE in individuals with tetraplegia (P < 0.01). Individuals with paraplegia had accelerated CRPE (P < 0.05) and PRPE (P < 0.05) responses compared with tetraplegia, but not when considering only individuals who reached VT. PRPE was higher than CPRE only in the late stages (80%-100% test duration; P < 0.05) in both groups when only considering individuals who reached VT. CONCLUSIONS: PRPE develops faster than CRPE in individuals with tetraplegia in a nonlinear fashion, despite linear increases in cardiorespiratory responses during graded arm cycling. Although there is promise to use differentiated RPE for exercise testing and prescription within the SCI population, our results indicate that there are differences in how individuals with tetraplegia perceive peripheral versus central exertion.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 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) | 0.000 | 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".