Neckband-type Self-powered Pulsewave Sensor for Continuous Blood Pressure Monitoring
Bibliographic record
Abstract
For effective continuous blood pressure (BP) monitoring at home, the system should be portable, user-friendly, and comfortable for the patient, ensuring convenience during continuous data collection. In this paper, we report a wearable neckband-type earphone designed for continuous monitoring of cardiovascular symptoms and BP in a non-invasive and wireless manner via a self-powered pulse wave (SPP) sensor. The SPP exhibits a sensitivity of 19.88 mV/Pa, allowing for the measurement of human pulse waves directly on the skin. Additionally, its low energy consumption, achieved through a triboelectric mechanism, enables the development of user-friendly auxiliary care systems, such as continuous BP monitoring integrated with seamless patient-doctor remote communication systems. This work provides an efficient and cost-effective approach toward active and personalized health condition monitoring.Clinical Relevance- Currently, the ratio of medical doctors to patients in hospitals in British Columbia, Canada, is approximately 2.47 per 1,000 individuals . [1] This research, which focuses on out-of-clinic care services for cardiovascular symptoms, aims to reduce the burden on clinicians by enabling continuous remote monitoring and management.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".