A Transmission Line Modeling for IR-UWB Radars in Human Body Sensing and Detection
Bibliographic record
Abstract
For the applications of IR-UWB in human body’s sensing and detection, researchers and industries concentrate on the circuit design of the UWB transceiver and antenna. Very few work focuses on the significant part, the human body’s physical dimension through which the UWB signal propagate. This paper presents an approach to model the multi-tissue layer from the skin to the heart of a human body in a wideband of spectrum. The tissues act as a two-wire transmission line carrying a high frequency signal. Some of critical transmission line parameters such as characteristic impedance, propagation constant as well as its resistance, inductance, conductance, and capacitance per unit length are derived based on the transmission line theory and the human body featured from a cellular view. The distributed circuit of this transmission line model is implemented and simulated in a CAD tool. Simulation results provide the reflection and transmission factors at the boundary between two neighbor tissues (for example, between the lung and the heart) along with S-parameter analysis and attenuation in the tissues. The “body channel” model is very useful in the design of IR-UWB human sensing devices.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".