Continuous measurements of respiratory muscle blood flow and oxygen consumption using non-invasive frequency domain near-infrared spectroscopy and diffuse correlation spectroscopy
Bibliographic record
Abstract
Prior studies of muscle blood flow and muscle specific oxygen consumption have required invasive injection of dye and Magnetic Resonance Imaging, respectively. Such measures have limited utility for continuous monitoring of the respiratory muscles in patients. Frequency domain near-infrared spectroscopy and diffuse correlation spectroscopy (FD-NIRS & DCS) can provide continuous surrogate measures of blood flow index (BFi) and metabolic rate of oxygen consumption (MRO2). This study aimed to validate sternocleidomastoid (SCM) FD-NIRS & DCS outcomes against electromyography (EMG) and mouth pressure (Pm) during incremental inspiratory threshold loading (ITL). Six females and six male healthy adults (30±7 years, maximum inspiratory pressure 118±61 cmH2O) performed ITL with 50g increments every two minutes until task failure. FD-NIRS & DCS continuously measured SCM oxygenated and deoxygenated hemoglobin+myoglobin (oxy/deoxy[Hb+Mb]), tissue saturation of oxygen (StO2), BFi and MRO2. Ventilatory parameters (e.g., Pm) were also evaluated. Pm increased during incremental ITL (P<0.05), reaching -47[−74, -34] cmH2O at task failure. Ventilatory parameters were constant throughout ITL (P>0.05). SCM BFi and MRO2 increased from the start of the ITL (P<0.05). Deoxy[Hb+Mb] increased close to task failure, concomitantly with a plateau in BFi, a constant increase in MRO2, and decreased StO2. SCM deoxy[Hb+Mb], BFi, StO2 and MRO2 correlated with sternocleidomastoid EMG (P<0.05 for all). Increasing SCM oxygen consumption near task failure was associated with increased oxygen extraction while delivery plateaued and reduced StO2
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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 | 0.000 | 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 | 0.000 |
| 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 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".