Mechatronics Application for a Smart Inhaler
Bibliographic record
Abstract
Metered dose inhalers (MDI) are used to manage or to provide quick relief to asthmatics. The improper use of an inhaler can result in the administration of an incorrect medication dosage, reducing the effectiveness of the device and resulting in higher treatment costs for the patient. The design process of an inhaler sleeve is outlined, intended to assist in the use of a standard MDI. The purpose of the sleeve is to monitor the user's technique during the four most critical steps of their inhaler use. These steps include shaking the device before use, coordinating the canister actuation with their inhalation, inhaling at the correct rate, and holding their breathing for the correct amount of time. The final design consists of a 3-D printed sleeve and a mobile application that guide the patient through the process. Lights are integrated into the sleeve indicating to the user which step they are on and for how long. Sensors are able to monitor the inhaler throughout its use and provide feedback by sharing the data collected to a mobile app. From there, users are shown what steps they are preforming correctly, and which ones need further improvement. A prototype printed in polylactic acid (PLA) acts as a reference for the accuracy of the 3-D model created. A finite element analysis conducted on the model indicates that the PLA material has sufficient strength for the product; however, opting to print in polyethylene terephthalate glycol (PETG) will allow the inhaler to fit into the sleeve more easily and will reduce the concentrated stresses and deformations seen on the sleeve.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| 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 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".