Validation of a smart textile device for long-duration heart rate variability and detection of physiological arrhythmias in resting horses
Bibliographic record
Abstract
BACKGROUND: A smart textile device has been developed for the recording of electrocardiograms (ECGs) in horses; however, the utility of this device for long-duration heart rate variability (HRV) monitoring and detection of physiological arrhythmias is unknown. Therefore, the objective of this study was to validate a smart textile device for HRV over long durations (6 h) in resting horses. ECGs were recorded simultaneously via the Myant Skiin Equine textile device and a reference device (Televet 100) in 12 horses. ECGs were evaluated by a blinded observer for arrhythmias, and HRV metrics were calculated. Agreement between the two devices was assessed via Bland‒Altman analysis and Lin's concordance correlation coefficient. RESULTS: Substantial to perfect agreement was found for all the HRV metrics. Physiological arrhythmias were detected in all the recordings from the twelve horses. Small biases and substantial to perfect agreement were found between the two devices for sinoatrial blocks (ρc = 0.99), sinus pauses (ρc = 0.96), sinus arrhythmias (ρc = 0.96), sinus tachycardia (ρc = 0.99), and 2nd degree atrioventricular blocks (ρc = 1.0). CONCLUSIONS: This study demonstrates that a smart textile system is a practical alternative to the standard telemetric device for long-duration assessment of HRV and the detection of physiological arrhythmias in healthy, resting horses.
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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 | 0.005 | 0.005 |
| 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".