Accuracy of smartwatches for measuring heart rate and oxygen saturation in cynomolgus macaques compared to clinical standards
Bibliographic record
Abstract
Continuous monitoring of physiological parameters in non-human primates (NHPs) necessitates a precise, non-invasive, and convenient method. This study aimed to validate the use of smartwatches with integrated pulse oximetry and heart rate (HR) monitoring capabilities for use in NHPs. Currently, the clinical standard for non-invasive continuous monitoring of peripheral oxygen saturation (SpO 2 ) in NHPs has been the use of a transmittance pulse oximeter (TPO) affixed to a location of highly vascularized tissue. In a clinical setting, HR is monitored through electrocardiogram (ECG) or associated with SpO 2 measurement from a TPO probe utilizing photoplethysmography technology. Challenges in obtaining precise readings with TPOs stem from technological limitations and probe placement restrictions. To address these limitations, simultaneous HR and SpO 2 measurements were obtained from 15 cynomolgus macaques ( Macaca fascicularis ) using the Apple Watch 7 (AW 7), Apple Watch 9 (AW 9), and a clinical-grade TPO probe with integrated optical HR measurement technology (iM70, ELAN). Arterial blood gas (ABG) analysis was used as a reference method for SpO 2 . We found that a TPO device significantly underestimated SpO 2 compared to the AW 7 and AW 9 when referenced against ABG values. Smartwatch-derived HR and SpO 2 measurements demonstrated good agreement and minimal bias compared to the gold standard method. Overall, the AW 7 and AW 9 exhibited good agreement with clinical reference standards for HR and good agreement with the gold standard for SaO 2 in sedated cynomolgus macaques.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".