Detecting hypoxia through the non-invasive monitoring of sweat lactate and tissue oxygenation
Bibliographic record
Abstract
Hypoxia is the state of insufficient tissue blood oxygenation that causes tissue damage and even organ failure. Accurate and timely methods for detecting hypoxia are critically needed. To address this need, a wearable device for the non-invasive and simultaneous detection of sweat lactate and tissue oxygenation levels is developed. The integrated device consists of a hydrogel for colourimetric sweat lactate sensing and optical electronics. Both tissue oxygenation and the colourimetric changes of the hydrogel were optically read out quantitatively and concurrently over the same skin area. Prototype devices were tested on an optical phantom with artificial and real sweat samples, validating its capability to measure these two indicators independently and without interference. Finally, the device was demonstrated to be capable of real-time “on-body” simultaneous monitoring of sweat lactate spikes and tissue oxygenation drops (StO2), which showed strong correlation during a hypoxia protocol.The novel device can be applied in broad clinical and non-clinical settings including post-operative care and measuring athlete endurance in a cost-effective manner.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".