Remote physiological monitoring of neck blood vessels
Bibliographic record
Abstract
Cardiovascular disease (CVD) is a leading cause of death globally. Current CVD diagnostic tests fail to predict early cardiovascular events and assess the risk of developing early CVD. Researchers are actively looking for biomarkers for CVD prediction, such as blood pressure, arterial stiffness, and pulse wave velocity (PWV). Several population-based clinical studies suggest increased PWV is associated with increased CVD mortality. In this study, we propose using a high-speed camera to study PWV as a biomarker of CVD with remote photoplethysmography (rPPG). We selected a reference signal based on distinct features, including peak and modulation depth variations, and used correlation to find the relationship between the local signals and the reference signal. The results revealed areas on the neck that positively and negatively correlated with selected reference signals, possibly representing the distribution of the significant neck vessels: carotid artery and jugular vein, which implies the feasibility of the remote estimation of local PWV using a high-speed camera, thereby expanding the potential applications of rPPG used for PWV estimation and assisted the CVD diagnosis.
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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 | 0.001 | 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".