PCA-Assisted Blood Glucose Monitoring Using Metamaterial-Inspired Sensor
Bibliographic record
Abstract
A metamaterial-inspired sensor is developed for noninvasive blood glucose monitoring. The sensor operating between 3–4 GHz integrates three resonant cells of single split rings with a microstrip line on a 66 × 20 mm2dielectric substrate.The proposed design exploits the inter-resonator coupling between adjacent cells to enlarge the sensing zone for more intensive interaction with the glucose tissue. The sensitivity performance for glucose detection is numerically analyzed at different geometrical parameters using a single-pole Debye model to approximate the dispersing behavior of the varying glucose on top of a skin layer. The resulting scattering responses to glucose variations are projected into a low-dimensional space using the principal component analysis algorithm to epitomize the data variances near resonance in fewer variables with a higher spatial resolution.The desired performance of the prototyped sensor is practically validated by measuring synthetic types of blood of 100–300 mg/dL inside a 3-D printed ear phantom using a vector network analyzer with higher sensitivity (∼0.0125 dB/[mg/dL]) than that of a single-cell double split-ring type.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".