Ultrasound sensors and its application in human heart rate monitoring
Bibliographic record
Abstract
Noninvasive wearable human health monitoring devices are developed to improve the comfort, convenience, and security of humans in their life. Ultrasound technology has been used for imaging the human body for over half a century. In this study, the use of ultrasound as a wearable device for human health monitoring is introduced. This work investigates analysis of the heart motions for heart rate extraction. Experimental results showed promising performance of the proposed method in reference to an electrocardiogram device. A low power and low complexity hardware prototype is designed to measure the Time Of Flight (TOF) and amplitude of reflected ultrasound signals generated by piezo sensors at 1 MHz (nominally), under design considerations for safety issues of intensity exposure defined by FDA. This type of a wearable human-interactive device represents a promising platform not only for heart rate measurement but also for more feasible features such as respiration rate. A new technique is applied to minimize the signal processing time and ensure the device response correctness.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".