An electrochemically actuated drug delivery device with <i>in-situ</i> dosage sensing
Bibliographic record
Abstract
Abstract Very few conventional micro-electro-mechanical systems as drug delivery devices have in-situ dosage monitoring sensors, this thus brings inaccurate released dose, which results in either inefficient pharmaceutical effects or over-dose induced side effects. In this work, we integrate a low-cost piezoresistive sensor with an electrochemically actuated drug delivery device, and investigate its dosage monitoring performance. Different from the conventional sensor fabrication based on mixing conductive particles into liquid polymer, our proposed sensor is constructed from solidified carbon ink film embedded in a polydimethylsiloxane (PDMS) membrane, which can obtain an optimum tradeoff between the gauge factor and maximum achievable displacement. An electrolytic reaction induces the electrolysis-bubble in the actuator chamber with an increase in pressure, which causes displacement of the PDMS sealing membrane. This provides the actuation force to deliver the drug solution. The displacement of the PDMS membrane that determines the pumped volume of the drug solution is quantified through a resistance change of the embedded piezoresistive sensor. We report a single pumping volume of up to 7 μ l, which is monitored by the resistance change ratio (Δ R / R ), ranging from 2% to 12% with a dosage sensing accuracy of ±6.5%.
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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 | 0.001 | 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".