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Record W4392639866 · doi:10.1117/12.2692676

Detecting hypoxia through the non-invasive monitoring of sweat lactate and tissue oxygenation

2024· article· en· W4392639866 on OpenAlexaff
Cindy Cheng, Shirley Tang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMedicine
TopicCardiovascular and Diving-Related Complications
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsOxygenationBiomedical engineeringBlood oxygenationSWEATHypoxia (environmental)Tissue hypoxiaOxygenMedicineChemistryInternal medicineRadiology

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.192
Threshold uncertainty score0.180

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.020
GPT teacher head0.288
Teacher spread0.268 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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