Validation of the Hexoskin wearable vest during lying, sitting, standing, and walking activities
Bibliographic record
Abstract
We tested the validity of the Hexoskin wearable vest to monitor heart rate (HR), breathing rate (BR), tidal volume (VT), minute ventilation, and hip motion intensity (HMI) in comparison with laboratory standard devices during lying, sitting, standing, and walking. Twenty healthy young volunteers participated in this study. First, participants walked 6 min on a treadmill at speeds of 1, 3, and 4.5 km/h followed by increasing treadmill grades until 80% of their predicted maximal heart rate. Second, lying, sitting, and standing tasks were performed (5 min each) followed by 6 min of treadmill walking at 80% of their ventilatory threshold. Analysis of each individual's mean values under each resting or exercise condition by the 2 measurement systems revealed low coefficient of variation and high intraclass correlation values for HR, BR, and HMI. The Bland-Altman results from HR, BR, and HMI indicated no deviation of the mean value from zero and relatively small variability about the mean. VT and minute ventilation were provided in arbitrary units by the Hexoskin device; however, relative magnitude of change from Hexoskin closely tracked the laboratory standard method. Hexoskin presented low variability, good agreement, and consistency. The Hexoskin wearable vest was a valid and consistent tool to monitor activities typical of daily living such as different body positions (lying, sitting, and standing) and various walking speeds.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".