Comparing the Finapres and Caretaker Systems for Measuring Pulse Transit Time Before and After Exercise
Bibliographic record
Abstract
We aimed to compare the Finapres system, which is designed for accurate intra-arterial amplitude measurement, to the Caretaker system, which is designed for temporal accuracy of intra-arterial measurement, in regard to measurement of pulse transit time (PTT) at baseline and following an endurance exercise session. Pulse transit time was evaluated between the R-wave of the ECG and the foot of the arterial waveform using either the Finapres (fpPTT) or Caretaker (ctPTT). 23 participants were measured before and after completion of endurance exercise. When comparing PTT values before and after an exercise intervention within devices, ctPTT was significantly different following exercise (P=0.03); however, the Finapres obtained values did not differ significantly. Before exercise, there was no significant relationship between devices, however, after exercise a significant moderate correlation was observed (r=0.45, P=0.02). Significant differences existed between ctPTT and fpPTT (P< 0.001). The Caretaker system appears to be more accurate at detecting changes in PTT occurring as a result of a single aerobic exercise session. This may be due to the servo-controller feedback loop in the waveform contour predicting algorithm within the Finapres system, which is not present in the Caretaker unit. The Finapres system also appears to have an inherent delay in pulse contour reporting.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".