Bibliographic record
Abstract
The heart rate variability (HRV) signal has been employed as a measure of sympathovagal balance in the human autonomic nervous system (ANS). It is known that aging affects the functional characteristics of the ANS. It has been suggested that complexity as measured by nonlinear dynamical indices, decays with age. We developed several algorithms and test protocols to characterize nonlinear dynamics in the HRV signal and to test the hypothesis that aging reduces the complexity within the HRV signal. Continuous HRV signal was obtained from 93 healthy subjects (41 males and 52 females) ranging in age between 5 and 78 years under controlled laboratory conditions in supine state. Subjects were from pediatric (PED, 5-12 years, n=15, 9 male, 6 female), adolescent (ADO, 13-17 years, n=16, 6 male, 10 female), adult (ADL, 18-30 years, n=22, 12 male, 10 female), middle aged (MDA, 31-60 years, n=21, 8 male, 13 female) and elderly (ELD, 61+ years, n=19, 6 male, 13 female) age groups. The length of data was 1000 or more R-R intervals for adequate computation. Stationary Holter HRV data from these controls were also used for the present study. Our results are as follows: There is a continuous systematic decay in the power-law scaling (beta), which decreases from -1.162 ± 0.388 for the PED group to -1.95 ± 0.6 for the ELD group (F = 6.649, p < 0.001; R = 0.475, p < 0.001. Approximate entropy (ApEn) decreases with age from 1.456 ± 0.093 for the PED group to 1.272 ± 0.135 for the ELD group (F = 7.82, p < 0.001; R = 0.519, p < 0.001. The detrended fluctuation analysis (DFA) of short-term data yielded an increase in short-range DFA scaling exponent (alpha)1 from 0.774 ± 0.204 for the PED group to 1.138 ± 0.289 for the ELD group (F = 7.535, p < 0.001), and in long-range DFA scaling exponent (alpha)2 increased from 0.667 ± 0.082 for the PED group to 0.86 ± 0.172 for the ELD group (F= 4.841,p < 0.001). The detrended fluctuation analysis (DFA) of long-term data yielded an increase in short-range DFA scaling exponent (alpha)1 from 1.052 ± 0.218 for the PED group to 1.204 ± 0.205 for the ELD group (F = 1.922), and in long-range DFA scaling exponent (alpha)2 increased from 0.961 ± 0.081 for the PED group to 1.076 ± 0.102 for the ELD group (F = 4.06, p < 0.01). Surrogate data analysis demonstrated that the hypothesis that the HRV signal is generated by a linear stochastic process is not always rejected. In summary, the HRV signal lends itself to an analysis using nonlinear dynamical methods and studies in patients may yield useful clinical information in the future.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.061 | 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".