Physiological Data Validation of the Hexoskin Smart Textile
Bibliographic record
Abstract
Keywords: Concordance Correlation Coefficient, Intraclass Correlation Coefficient, Bland-Altman, Agreement Analysis, Cardiorespiratory. \nAbstract: The aim of this study is to validate cardiorespiratory function measurement of a healthy population provided by a wearable textile during a progressive maximal exercise test. The following measurements were collected using embedded sensors to assess three variables: heart rate (HR), breathing rate (BR) and ventilation (Ve). These variables were recorded simultaneously by the wearable textile and using as a reference system for a comparison purpose. The validation was performed based on the two systems agreement estimation by calculating the intraclass correlation coefficient (ICC), the concordance correlation coefficient (CCC) and the Bland-Altman plot for each variable. Twenty-eight healthy volunteers participated in this study. Analysis of each participant under exercise condition by the two measurement systems revealed high CCC values (rc between 0.91 and 0.99), no deviation from the 45� line (Cb between 0.96 and 0.99) and significant ICC values (r between 0.91 and 0.99, p < 0.05) for HR and BR. The Bland Altman plot for HR and BR indicated no deviation of the mean difference from zero and a small variability with tight agreement limits. However, the analysis of the estimated ventilation Ve of each participant revealed doubtful values for the CCC (rc between 0.2 and 0.99) and ICC (r between 0.11 and 0.99). In summary, the Hexoskin presented good agreement for HR and BR. However, for ventilation, it is difficult to conclude from the results due to variability
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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) | 0.001 | 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 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".