Effect of Various Lengths of Respiration on Heart Rate Variability during Simple Bhramari (Humming)
Bibliographic record
Abstract
Background: Heart rate varies during breathing and the heart rate variability (HRV) facilitates the autonomic homeostatic capacity. The maximum HRV was observed at around 10 s of prolonged respiration as per HRV biofeedback literature. However, there is a gap in understanding the variations in HRV by different respiration lengths during simple Bhramari practice. Objective: To assess the effect of various respiration lengths (8, 10, 12, and 14 s) on HRV during the simple Bhramari (humming) practice. Methodology: A total of 118 individuals (67 males, 51 females) signed up for the study based on convenience sampling at a wellness center. A randomized (simple permutation) within-subject crossover design with repeated measures was used to measure their HRV during the simple Bhramari practice. The results were analyzed with one-way ANOVA and paired samples t -test. Results: The results indicate that, unlike the 10 s of respiration during HRV biofeedback breathing, maximum HRV during humming happens between 12 and 14 s of long breathing. Conclusions: The unique findings of the study demonstrate the maximization of HRV between the respiration lengths of 12 and 14 s. Future work should explore expanding the research to a broader group of participants, including individuals with chronic conditions and other demographic variables and mantra chanting.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.003 |
| 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".