Non-invasive blood glucose sensors based on electromagnetic wave
Bibliographic record
Abstract
Low-cost, reusable, highly compliant and non-invasive blood glucose sensors (NIBGS) are necessary for current and future medical systems. This review aims to introduce various NIBGS with wide application prospect and focus on electromagnetic wave-based NIBGS. The main introduction is based on Near-infrared spectroscopy-based, Raman spectroscopy-based and microwave-based sensors. The basic working principle of each type of sensor is explained, and their structure, detection accuracy, detection range and detection site are also summarized. The improvements and impacts made by various types of non-invasive testing applications are also analyzed. Several commonly used performance evaluation methods of non-invasive blood glucose monitoring (NIBGM) are introduced. With the development of electronic device and intelligent algorithms, NIBGM will continue to expand its advantages, and the creation of new practical applications will greatly improve the healthcare environment and bring great convenience to the lifestyle of patients with diabetes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".