Metasurface-Enhanced Bio-Sensing Radar for Advanced Health Monitoring
Bibliographic record
Abstract
Introducing a metasurface-enhanced radar system for advanced bio-sensing applications, this paper underscores its potential for non-invasive, real-time wearable health monitoring and precision in detecting physiological parameters. The system utilizes a transmissive metasurface to dynamically shape the near- field radiation of a millimeter-wave radar transmitter antenna, focusing within the human body's skin. Comprising two layers of phase-synthesized unit cells, the metasurface acts as a low-profile near-field impedance matching network, seamlessly integrating with radar operating within the 58 to 63 GHz frequency band and establishing direct contact with the human body skin. Simulations and measurements within a customized phantom closely resembling human skin demonstrate that integrating the metasurface increases the near-field absorbed power density by over 11 dB. This improvement is accompanied by a significant increase of over 11 dB in the received power level reflected from the skin to the radar receiver antenna, enhancing the overall radar signal-to-noise ratio.
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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 | 0.000 |
| 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 | 0.001 |
| 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".