Smart apparel design for urinary incontinence detection
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract A wide range of wearable devices are now used to help people with various health conditions. While approximately 10% of the Canadian population is affected by some form of urinary incontinence, there is a significant need for devices addressing this condition. This paper presents an ongoing research project for the design and development of an underwear fitted with urinary detection capacities. The paper focuses on the testing and comparison of three different solutions identified from scientific literature for detecting urinary leakage, namely by measuring conductivity, temperature, and humidity. These three detection modules have been integrated into a single prototype to ensure that they are tested under the same conditions. Our results point out that conductivity and humidity measurements appear to be viable for urine leakage detection in an absorbent pad, whereas temperature measurement has proven to be unsuccessful due to the rapid drop of the solution temperature and the time required for the liquid to reach the sensor. The temperature method is hence excluded from the next development stages. Finally, further tests on participants are still required to evaluate how body fluids other than urine might impact conductivity and humidity measurements.
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.
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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 it