References

The HRV knowledge base

The bibliography behind these docs (docs/references.bib, 543 entries) was built in three passes. First, every zoo entry was tied to the source that introduced the measure, plus the curated applications literature behind its Applications by area section, with metadata verified against PubMed, publisher pages, and Semantic Scholar. Second, this set was merged with the project's RR-forecasting and real-world driving bibliographies. Third, every confirmed DOI was resolved on OpenAlex and the HRV-related papers cited by two or more confirmed papers were added. The expansion is capped at the roughly 400 most cross-cited external works, a foundations sample rather than an exhaustive sweep.

The result spans 1948 to 2026, from Shannon, Hurst, Welch, Lomb, and Scargle through the Task Force standard to current work. It is one field, not many: in the citation graph behind the KB (554 papers, 3 841 citation edges), 89 % of papers form a single connected component. An earlier fragmented picture came from drawing co-authorship edges only. Each paper carries one or more field labels (multi-label, over the 554-paper graph):

Field	papers
methods & foundations	285
clinical	253
sports & peak-performance	125
contemplative practice	44

These are the four fields each zoo entry references: the three Applications by area sections and the seminal Citation section (methods & foundations), summarized per feature in the C S P M column on the zoo index.

Cited works

The list below renders the entries cited on the documentation pages. The full knowledge base lives in docs/references.bib.

Akselrod, S.; Gordon, D.; Ubel, F. A.; Shannon, D. C.; Barger, A. C. and Cohen, R. J. (1981). Power spectrum analysis of heart rate fluctuation: a quantitative probe of beat-to-beat cardiovascular control. Science 213, 220–222.
Aune, D.; Sen, A.; Ó'Hartaigh, B.; Janszky, I.; Romundstad, P. R.; Tonstad, S. and Vatten, L. J. (2017). Resting heart rate and the risk of cardiovascular disease, total cancer, and all-cause mortality – a systematic review and dose-response meta-analysis of prospective studies. Nutrition, Metabolism and Cardiovascular Diseases 27, 504–517.
Bandt, C. and Pompe, B. (2002). Permutation entropy: a natural complexity measure for time series. Physical Review Letters 88, 174102.
Bellenger, C. R.; Fuller, J. T.; Thomson, R. L.; Davison, K.; Robertson, E. Y. and Buckley, J. D. (2016). Monitoring athletic training status through autonomic heart rate regulation: a systematic review and meta-analysis. Sports Medicine 46, 1461–1486.
Bigger, J. T.; Steinman, R. C.; Rolnitzky, L. M.; Fleiss, J. L.; Albrecht, P. and Cohen, R. J. (1996). Power law behavior of RR-interval variability in healthy middle-aged persons, patients with recent acute myocardial infarction, and patients with heart transplants. Circulation 93, 2142–2151.
Billman, G. E. (2013). The LF/HF ratio does not accurately measure cardiac sympatho-vagal balance. Frontiers in Physiology 4, 26.
Brennan, M.; Palaniswami, M. and Kamen, P. (2001). Do existing measures of Poincaré plot geometry reflect nonlinear features of heart rate variability? IEEE Transactions on Biomedical Engineering 48, 1342–1347.
Brown, L.; Rando, A. A.; Eichel, K.; Van Dam, N. T.; Celano, C. M.; Huffman, J. C. and Morris, M. E. (2021). The effects of mindfulness and meditation on vagally mediated heart rate variability: a meta-analysis. Psychosomatic Medicine 83, 631–640.
Cassirame, J.; Eustache, E.; Garbellotto, L.; Chevrolat, S.; Gimenez, P. and Leprêtre, P.-M. (2025). Detrended fluctuation analysis to determine physiologic thresholds, investigation and evidence from incremental cycling test. European Journal of Applied Physiology 125, 523–533.
Chalmers, J. A.; Quintana, D. S.; Abbott, M. J.-A. and Kemp, A. H. (2014). Anxiety disorders are associated with reduced heart rate variability: a meta-analysis. Frontiers in Psychiatry 5, 80.
Chen, W.; Wang, Z.; Xie, H. and Yu, W. (2007). Characterization of surface EMG signal based on fuzzy entropy. IEEE Transactions on Neural Systems and Rehabilitation Engineering 15, 266–272.
Ciccone, A. B.; Siedlik, J. A.; Wecht, J. M.; Deckert, J. A.; Nguyen, N. D. and Weir, J. P. (2017). Reminder: RMSSD and SD1 are identical heart rate variability metrics. Muscle & Nerve 56, 674–678.
Costa, M.; Goldberger, A. L. and Peng, C.-K. (2002). Multiscale entropy analysis of complex physiologic time series. Physical Review Letters 89, 068102.
Deka, B. and Deka, D. (2023). Nonlinear analysis of heart rate variability signals in meditative state: a review and perspective. BioMedical Engineering OnLine 22, 35.
Ewing, D. J.; Neilson, J. M. and Travis, P. (1984). New method for assessing cardiac parasympathetic activity using 24 hour electrocardiograms. British Heart Journal 52, 396–402.
Francis, D. P.; Willson, K.; Georgiadou, P.; Wensel, R.; Davies, L. C.; Coats, A. and Piepoli, M. (2002). Physiological basis of fractal complexity properties of heart rate variability in man. The Journal of Physiology 542, 619–629.
Goldstein, D. S.; Bentho, O.; Park, M. Y. and Sharabi, Y. (2011). Low-frequency power of heart rate variability is not a measure of cardiac sympathetic tone but may be a measure of modulation of cardiac autonomic outflows by baroreflexes. Experimental Physiology 96, 1255–1261.
Gronwald, T. and Hoos, O. (2020). Correlation properties of heart rate variability during endurance exercise: a systematic review. Annals of Noninvasive Electrocardiology 25, e12697.
Hillebrand, S.; Gast, K. B.; de Mutsert, R.; Swenne, C. A.; Jukema, J. W.; Middeldorp, S.; Rosendaal, F. R. and Dekkers, O. M. (2013). Heart rate variability and first cardiovascular event in populations without known cardiovascular disease: meta-analysis and dose-response meta-regression. Europace 15, 742–749.
Hoos, O. and Gronwald, T. (2025). Detrended fluctuation analysis of heart rate variability during exercise: time to reconsider the theoretical and methodological background. Comment on Cassirame et al. (2025). European Journal of Applied Physiology 125, 2637–2639.
Hurst, H. E. (1951). Long-term storage capacity of reservoirs. Transactions of the American Society of Civil Engineers 116, 770–799.
Inouye, T.; Shinosaki, K.; Sakamoto, H.; Toi, S.; Ukai, S.; Iyama, A.; Katsuda, Y. and Hirano, M. (1991). Quantification of EEG irregularity by use of the entropy of the power spectrum. Electroencephalography and Clinical Neurophysiology 79, 204–210.
Iyengar, N.; Peng, C. K.; Morin, R.; Goldberger, A. L. and Lipsitz, L. A. (1996). Age-related alterations in the fractal scaling of cardiac interbeat interval dynamics. American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 271, R1078–R1084.
Jeppesen, J.; Beniczky, S.; Johansen, P.; Sidenius, P. and Fuglsang-Frederiksen, A. (2014). Using Lorenz plot and Cardiac Sympathetic Index of heart rate variability for detecting seizures for patients with epilepsy. In: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (IEEE); pp. 4563–4566.
Jeppesen, J.; Beniczky, S.; Johansen, P.; Sidenius, P. and Fuglsang-Frederiksen, A. (2016). Comparing maximum autonomic activity of psychogenic non-epileptic seizures and epileptic seizures using heart rate variability. Seizure 37, 13–19.
Kleiger, R. E.; Miller, J. P.; Bigger, J. T. and Moss, A. J. (1987). Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. The American Journal of Cardiology 59, 256–262.
Koch, C.; Wilhelm, M.; Salzmann, S.; Rief, W. and Euteneuer, F. (2019). A meta-analysis of heart rate variability in major depression. Psychological Medicine 49, 1948–1957.
Lomb, N. R. (1976). Least-squares frequency analysis of unequally spaced data. Astrophysics and Space Science 39, 447–462.
Malik, M.; Farrell, T.; Cripps, T. and Camm, A. J. (1989). Heart rate variability in relation to prognosis after myocardial infarction: selection of optimal processing techniques. European Heart Journal 10, 1060–1074.
Mietus, J. E.; Peng, C.-K.; Henry, I.; Goldsmith, R. L. and Goldberger, A. L. (2002). The pNNx files: re-examining a widely used heart rate variability measure. Heart 88, 378–380.
Moody, G. B. (1993). Spectral analysis of heart rate without resampling. In: Proceedings of Computers in Cardiology (IEEE); pp. 715–718.
Natarajan, A. (2023). Heart rate variability during mindful breathing meditation. Frontiers in Physiology 13, 1017350.
Pagani, M.; Lombardi, F.; Guzzetti, S.; Rimoldi, O.; Furlan, R.; Pizzinelli, P.; Sandrone, G.; Malfatto, G.; Dell'Orto, S.; Piccaluga, E.; Turiel, M.; Baselli, G.; Cerutti, S. and Malliani, A. (1986). Power spectral analysis of heart rate and arterial pressure variabilities as a marker of sympatho-vagal interaction in man and conscious dog. Circulation Research 59, 178–193.
Pascoe, M. C.; Thompson, D. R.; Jenkins, Z. M. and Ski, C. F. (2017). Mindfulness mediates the physiological markers of stress: systematic review and meta-analysis. Journal of Psychiatric Research 95, 156–178.
Peng, C.-K.; Buldyrev, S. V.; Havlin, S.; Simons, M.; Stanley, H. E. and Goldberger, A. L. (1994). Mosaic organization of DNA nucleotides. Physical Review E 49, 1685–1689.
Peng, C.-K.; Havlin, S.; Stanley, H. E. and Goldberger, A. L. (1995). Quantification of scaling exponents and crossover phenomena in nonstationary heartbeat time series. Chaos: An Interdisciplinary Journal of Nonlinear Science 5, 82–87.
Peng, C.-K.; Mietus, J. E.; Liu, Y.; Khalsa, G.; Douglas, P. S.; Benson, H. and Goldberger, A. L. (1999). Exaggerated heart rate oscillations during two meditation techniques. International Journal of Cardiology 70, 101–107.
Pincus, S. M. (1991). Approximate entropy as a measure of system complexity. Proceedings of the National Academy of Sciences 88, 2297–2301.
Rahman, S.; Habel, M. and Contrada, R. J. (2018). Poincaré plot indices as measures of sympathetic cardiac regulation: responses to psychological stress and associations with pre-ejection period. International Journal of Psychophysiology 133, 79–90.
Richman, J. S. and Moorman, J. R. (2000). Physiological time-series analysis using approximate entropy and sample entropy. American Journal of Physiology-Heart and Circulatory Physiology 278, H2039–H2049.
Roberts, S. J.; Penny, W. and Rezek, I. (1999). Temporal and spatial complexity measures for electroencephalogram based brain-computer interfacing. Medical & Biological Engineering & Computing 37, 93–98.
Rueda-Ochoa, O. L.; Osorio-Romero, L. F. and Sanchez-Mendez, L. D. (2024). Which indices of heart rate variability are the best predictors of mortality after acute myocardial infarction? Meta-analysis of observational studies. Journal of Electrocardiology 84, 42–48.
Rényi, A. (1961). On measures of entropy and information. In: Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, Volume 1: Contributions to the Theory of Statistics (University of California Press); pp. 547–561.
Rådmark, L.; Sidorchuk, A.; Osika, W. and Niemi, M. (2019). A systematic review and meta-analysis of the impact of mindfulness based interventions on heart rate variability and inflammatory markers. Journal of Clinical Medicine 8, 1638.
Scargle, J. D. (1982). Studies in astronomical time series analysis. II. Statistical aspects of spectral analysis of unevenly spaced data. The Astrophysical Journal 263, 835–853.
Schmid, P. J. (2010). Dynamic mode decomposition of numerical and experimental data. Journal of Fluid Mechanics 656, 5–28.
Sen, J. and McGill, D. (2018). Fractal analysis of heart rate variability as a predictor of mortality: a systematic review and meta-analysis. Chaos: An Interdisciplinary Journal of Nonlinear Science 28, 072101.
Shaffer, F. and Ginsberg, J. P. (2017). An overview of heart rate variability metrics and norms. Frontiers in Public Health 5, 258.
Shannon, C. E. (1948). A mathematical theory of communication. The Bell System Technical Journal 27, 379–423.
Stuckey, M. I.; Tulppo, M. P.; Kiviniemi, A. M. and Petrella, R. J. (2014). Heart rate variability and the metabolic syndrome: a systematic review of the literature. Diabetes/Metabolism Research and Reviews 30, 784–793.
Tanaka, H.; Monahan, K. D. and Seals, D. R. (2001). Age-predicted maximal heart rate revisited. Journal of the American College of Cardiology 37, 153–156.
Toichi, M.; Sugiura, T.; Murai, T. and Sengoku, A. (1997). A new method of assessing cardiac autonomic function and its comparison with spectral analysis and coefficient of variation of R-R interval. Journal of the Autonomic Nervous System 62, 79–84.
Tulppo, M. P.; Mäkikallio, T. H.; Takala, T. E.; Seppänen, T. and Huikuri, H. V. (1996). Quantitative beat-to-beat analysis of heart rate dynamics during exercise. American Journal of Physiology-Heart and Circulatory Physiology 271, H244–H252.
Vollmer, M. (2015). A robust, simple and reliable measure of heart rate variability using relative RR intervals. 2015 Computing in Cardiology Conference (CinC), 609–612.
Welch, P. D. (1967). The use of fast Fourier transform for the estimation of power spectra: a method based on time averaging over short, modified periodograms. IEEE Transactions on Audio and Electroacoustics 15, 70–73.
Wolf, M. M.; Varigos, G. A.; Hunt, D. and Sloman, J. G. (1978). Sinus arrhythmia in acute myocardial infarction. Medical Journal of Australia 2, 52–53.
Wu, Q.; Miao, X.; Cao, Y.; Chi, A. and Xiao, T. (2023). Heart rate variability status at rest in adult depressed patients: a systematic review and meta-analysis. Frontiers in Public Health 11, 1243213.
Yang, S.; Wu, H.; Liao, X.; Lin, Y. and Liou, J.-J. (2026). Advancing entropy analysis for heart rate variability: clinical insights for aging and diabetes. Frontiers in Physiology 17, 1795118.
Yuda, E.; Ueda, N.; Kisohara, M. and Hayano, J. (2021). Redundancy among risk predictors derived from heart rate variability and dynamics: ALLSTAR big data analysis. Annals of Noninvasive Electrocardiology 26, e12790.
Zhang, D.; Shen, X. and Qi, X. (2016). Resting heart rate and all-cause and cardiovascular mortality in the general population: a meta-analysis. CMAJ 188, E53–E63.
Task Force, European Society of Cardiology / North American Society of Pacing & Electrophysiology (1996). Heart rate variability: Standards of measurement, physiological interpretation, and clinical use. Circulation 93, 1043–1065.