Realizing the Potential of Commercial E-Textiles for Wearable Glucose Biosensing Application
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Advancements in wearable technology have enabled noninvasive health monitoring using biosensors. This research focuses on developing a textile-based sweat glucose sensor using commercially available conductive textiles, evading the complexity of traditional fabrication methods. A comparative analysis of three low-cost conductive textiles, Adafruit 1364, 1167, and 4762, has been conducted for electrochemical glucose detection with glucose-specific enzymes such as glucose oxidase (GOx) and glucose dehydrogenase (GDH). Adafruit 1364 outperformed others in morphological, electrochemical, and wearable properties. Cyclic voltammetry shows that Adafruit 1364 and 4762 effectively detect glucose at the potential of 0.23 and 0.08 V using glucose oxidase and 0.1 and 0.08 V using glucose dehydrogenase enzymes, respectively. Furthermore, chronoamperometry has been conducted to confirm the presence of glucose at 1 μM concentration. Differential pulse voltammetry was conducted to assess the sensitivity of the Adafruit 1364 fabric electrode using glucose solutions with concentrations of 0.05, 0.15, 0.25, and 0.5 mM. The electrode immobilized with GOx showed a sensitivity of 0.005 μA μM −1 and a limit of detection (LOD) of 41.3 μM, while the electrode immobilized with GDH exhibited a sensitivity of 0.0019 μA μM −1 and an LOD of 63.1 μM. The study also highlighted the reproducibility, effect of interferents, and advantageous wearable properties of these sensors.
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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".