Validity of the Polar S810 Heart Rate Monitor to Measure R-R Intervals at Rest
Bibliographic record
Abstract
PURPOSE: This study was conducted to compare R-R intervals and the subsequent analysis of heart rate variability (HRV) obtained from the Polar S810 heart rate monitor (HRM) (Polar Electro Oy) with an electrocardiogram (ECG) (Physiotrace, Estaris, Lille, France) during an orthostatic test. METHODS: A total of 18 healthy men (age: 27.1 +/- 1.9 yr; height: 1.82 +/- 0.06 m; mass 77.1 +/- 7.7 kg) performed an active orthostatic test during which R-R intervals were simultaneously recorded with the HRM and the ECG recorder The two signals were synchronized and corrected before a time domain analysis, the fast Fourier transform (FFT) and a Poincaré plot analysis. Bias and limits of agreement (LoA), effect size (ES), and correlation coefficients were calculated. RESULTS: R-R intervals were significantly different in the supine and standing position between the ECG and the HRM uncorrected and corrected signal (P < 0.05, ES = 0.000 and 0.006, respectively). The bias +/- LoA, however, were 0.9 +/- 12 ms. HRV parameters derived from both signals in both positions were not different (P > 0.05) and well correlated (r > 0.97, P < 0.05), except root mean square of difference (RMSSD) and SD1 in standing position (P < 0.05, ES = 0.052 and 0.057; r = 0.99 and 0.98, respectively). CONCLUSION: Narrow LoA, good correlations, and small effect sizes support the validity of the Polar S810 HRM to measure R-R intervals and make the subsequent HRV analysis in supine position. Caution must be taken in standing position for the parameters sensitive to the short-term variability (i.e., RMSSD and SD1).
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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 | 0.004 | 0.017 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".