Non-contact imaging of the neck for monitoring cardiopulmonary clinic patients
Bibliographic record
Abstract
Non-contact neck imaging using a standard smartphone camera and ambient lighting with accurate estimates of heart rate (HR) and respiratory rate (RR) provides superior access to care in resource constrained health care systems. While most existing techniques for non-contact imaging focus on detecting HR from facial regions, limited work has explored HR and RR detection from the neck. Prior studies involve healthy volunteers while relying on specialized cameras or controlled lighting conditions. Data acquired for the study were collected in a cardiology clinic under regular fluorescent lighting, with the participants being assessed for cardiac pathology. The proposed approach uses 15 to 30-second videos to analyze the skin displacement motion of neck pixels. The results demonstrate superior performance with R-values of 0.98 and 0.85 for HR and RR respectively compared to existing imaging photoplethysmography (iPPG) algorithms, highlighting the robustness of this method. The outcomes of this work could facilitate the detection of carotid artery and jugular venous pulsation, providing a more comprehensive assessment of cardiovascular and respiratory health, particularly for patient monitoring.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".