“Smart Clothing” Technology for Heart Function Monitoring During a Session of “Dry” Immersion
Bibliographic record
Abstract
The study aimed at obtaining a precise view of the modification of heart rate variability (HRV) and respiratory rate with the help of “smart clothes” (the Hexoskin Smart Shirt, Hexoskin Smart Sensors & AI, Montreal, QC, Canada) during a 45 min session of “dry” immersion (DI), which is considered a model of Earth-based weightlessness. Eight healthy subjects aged 19 to 21 years participated in the study. Hexoskin Smart Shirt provided a .wav sound file. For analysis, the ecg_peaks function of the neurokit2 library was applied. HRV parameters were calculated within 5 min segments with the help of the pyHRV toolbox. Time-domain (HR and SDNN) and frequency-domain (HF, LF, and VLF) HRV parameters, sample, and approximate entropy were calculated. Thus, the “smart cloth” technology appears as a reliable telemetric instrument to monitor cardiac and respiratory regulation during the DI session.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".