Continuous Artery Monitoring Based on Decomposition of Ultrasound Radiofrequency Signals
Bibliographic record
Abstract
Ultrasound can noninvasively monitor the mechanical and dynamical properties of the artery.Scattering and overlap of adjacent tissue boundary echoes with those from the artery wall affect the estimation accuracy of the artery properties and impede continuous and automatic monitoring.Decomposition of the ultrasound radiofrequency (RF) signals using matching pursuit with particle swarm optimization is proposed to isolate the echoes arising from the tissue boundaries of the carotid artery wall for subsequent estimation of the wall thickness and diameter changes during the cardiac cycle.The proposed method exhibited less variance in the estimation of artery wall thickness when compared to manual estimation by a clinical method.Artery wall motion tracking by the proposed method was more robust compared to tracking achieved through the conventional cross-correlation technique when applied to the ultrasound RF signals from a wearable ultrasound sensor that contain a high volume of scattering echoes.i 6.1 Conclusions . . . . . . . . . . .
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".