Advances in heart rate variability signal analysis: Joint position statement by the e-Cardiology ESC Working Group and the European Heart Rhythm Association co-endorsed by the Asia Pacific Heart Rhythm Society
Open accessAbstract
Following the publication of the Task Force document on heart rate variability (HRV) in 1996, a number of articles have been published to describe new HRV methodologies and their application in different physiological and clinical studies. This document presents a critical review of the new methods. A particular attention has been paid to methodologies that have not been reported in the 1996 standardization document but have been more recently tested in sufficiently sized populations. The following methods were considered: Long-range correlation and fractal analysis; Short-term complexity; Entropy and regularity; and Nonlinear dynamical systems and chaotic behaviour. For each of these methods, technical aspects, clinical achievements, and suggestions for clinical application were reviewed. While the novel approaches have contributed in the technical understanding of the signal character of HRV, their success in developing new clinical tools, such as those for the identification of high-risk patients, has been rather limited. Available results obtained in selected populations of patients by specialized laboratories are nevertheless of interest but new prospective studies are needed. The investigation of new parameters, descriptive of the complex regulation mechanisms of heart rate, has to be encouraged because not all information in the HRV signal is captured by traditional methods. The new technologies thus could provide after proper validation, additional physiological, and clinical meaning. Multidisciplinary dialogue and specialized courses in the combination of clinical cardiology and complex signal processing methods seem warranted for further advances in studies of cardiac oscillations and in the understanding normal and abnormal cardiac control processes.
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The new HRV analyses methods that emerged since the Task Force did not bring any additional information regarding physiological underpinnings of HRV, and therefore no additional information for vagal tone.
“Finally, a critical review of the new HRV analyses methods that emerged since the Task Force regarding HRV (Malik, 1996) was realized by Sassi et al. (2015), and the conclusion was that the new methods did not bring any additional information regarding physiological underpinnings of HRV, and therefore no additional information for vagal tone.”
From Heart Rate Variability and Cardiac Vagal Tone in Psychophysiological Research – Recommendations for Experiment Planning, Data Analysis, and Data Reporting (2017) · cites this paper as Sassi et al., 2015
The Conclusions (p. 9) say that new parameters can provide different information about the complexity of physiological mechanisms underlying HRV, contrary to the claim that they brought no additional physiological information. Suggestions for clinical use (p. 9) say the methods have provided more information about signal complexity than about parasympathetic control; they do not conclude that the methods provide no information about vagal control. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredStudies have demonstrated the correlation of depressed HRV with risk of mortality including cardiovascular death but not with SCD.
“Studies have demonstrated the correlation of depressed HRV with risk of mortality including cardiovascular death but not with SCD (Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology, 1996;Sassi et al., 2015;Wellens et al., 2014).”
From 2017 ISHNE-HRS expert consensus statement on ambulatory ECG and external cardiac monitoring/telemetry (2017) · cites this paper as Sassi et al., 2015
The paper reports associations with all-cause and cardiovascular mortality, but it contradicts the claim’s exclusion of sudden cardiac death. In “Subjects without evidence of heart disease” (p. 9), it reports that a DFA HRV measure was an independent predictor of sudden cardiac death. (LLM, conf=0.90)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredThe utility of non-linear indices has still to be demonstrated to predict psychophysiological phenomena.
“However, some caution is still required regarding non-linear indices and their utility has still to be demonstrated to predict psychophysiological phenomena (Sassi et al., 2015).”
From Heart Rate Variability and Cardiac Vagal Tone in Psychophysiological Research – Recommendations for Experiment Planning, Data Analysis, and Data Reporting (2017) · cites this paper as Sassi et al., 2015
The Conclusions (p. 9) call for further validation to establish the clinical predictive value of novel HRV methods, and Suggestions for clinical use (p. 9) favor traditional measures for assessing autonomic physiology. These passages support caution about nonlinear indices, but they do not specifically assess their ability to predict psychophysiological phenomena. (LLM, conf=0.84)
Experimental — accuracy not yet measuredIf novel HRV methods are used, researchers should follow recent recommendations and always present the new HRV measures together with more traditional measures of HRV.
“In addition, if novel HRV methods are used, researchers should follow recent recommendations and always present the new HRV measures together to more traditional measures of HRV (Sassi et al., 2015).”
From Heart Rate Variability and Cardiac Vagal Tone in Psychophysiological Research – Recommendations for Experiment Planning, Data Analysis, and Data Reporting (2017) · cites this paper as Sassi et al., 2015
In “Suggestions for clinical use” (p. 9), the paper suggests using novel HRV techniques in conjunction with traditional ones. That supports presenting both kinds of measures, but the paper frames this as a suggestion, not an instruction to always do so. (LLM, conf=0.84)
Experimental — accuracy not yet measured
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- Authors
- Sassi, R., Cerutti, S., Lombardi, F., Malik, M., Huikuri, H. V., Peng, C.-K., Schmidt, G., Yamamoto, Y., Reviewers:, D., Gorenek, B., Lip, G. Y. H., Grassi, G., Kudaiberdieva, G., Fisher, J. P., Zabel, M., & Macfadyen, R.
- Affiliations
- University of Milan (IT)
- Politecnico di Milano (IT)
- University of London (GB)
- Beth Israel Deaconess Medical Center (US)
- TUM Klinikum (DE)
- The University of Tokyo (JP)
- ORCID
- Venue
- Europace
- Publisher
- Oxford University Press (OUP)
- Published
- 2015-07-14
- Volume
- 17
- Issue
- 9
- Pages
- 1341-1353
- ISSN
- 1099-5129 (ISSN-L)
- 1532-2092
- OpenAlex
- W1929108078
- Cited by
- 727
- References
- 76
- Citations by year
- 2026: 39 · 2025: 56 · 2024: 70 · 2023: 72 · 2022: 74 · 2021: 75 · 2020: 74 · 2019: 84 · 2018: 82 · 2017: 66 · 2016: 31 · 2015: 4
- FWCI
- 44.40
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- EP Europace (publishedVersion)
- PubMed (publishedVersion)
- Virtual Community of Pathological Anatomy (University of Castilla La Mancha) (submittedVersion, other-oa)
- University of Birmingham Research Portal (University of Birmingham) (submittedVersion)
- Funders
- British Heart Foundation (PG/13/54/30358, PG/12/77/29857)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac electrophysiology and arrhythmias
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › ECG Monitoring and Analysis
- Keywords
- heart rate variability, long-range correlations, fractal analysis, entropy (information theory), nonlinear dynamical systems, chaotic dynamics, heart rate regulation, cardiac oscillations, high-risk patient identification
- MeSH terms
- Asia, Autonomic Nervous System, Cardiology, Electrocardiography, Europe, Heart Rate, Humans, Signal Processing, Computer-Assisted, Societies, Medical, Practice Guidelines as Topic, Nonlinear Dynamics
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