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Considerations in the assessment of heart rate variability in biobehavioral research
Open accessAbstract
Heart rate variability (HRV) refers to various methods of assessing the beat-to-beat variation in the heart over time, in order to draw inference on the outflow of the autonomic nervous system. Easy access to measuring HRV has led to a plethora of studies within emotion science and psychology assessing autonomic regulation, but significant caveats exist due to the complicated nature of HRV. Firstly, both breathing and blood pressure regulation have their own relationship to social, emotional, and cognitive experiments - if this is the case are we observing heart rate (HR) changes as a consequence of breathing changes? Secondly, experiments often have poor internal and external controls. In this review we highlight the interrelationships between HR and respiration, as well as presenting recommendations for researchers to use when collecting data for HRV assessment. Namely, we highlight the superior utility of within-subjects designs along with the importance of establishing an appropriate baseline and monitoring respiration.
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“Within-subject designs offer optimal experimental control, contribute to the elimination of individual differences in respiratory rates (though there is still a need to control for them, which will be covered later), require less participants given they offer an increased statistical power, and reduce the impact of external factors such as medication, alcohol, smoking, etc. (Quintana and Heathers,”
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 Quintana and Heathers, 2014
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In the citing paper
“Within-subject designs offer optimal experimental control”
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 Quintana and Heathers, 2014
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In the citing paper
“reduce the impact of external factors such as medication, alcohol, smoking, etc.”
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 Quintana and Heathers, 2014
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“contribute to the elimination of individual differences in respiratory rates”
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 Quintana and Heathers, 2014
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“Respiratory depth is linked to tidal volume and controlling for tidal volume can be done with pneumotachography (Quintana and Heathers, 2014).”
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 Quintana and Heathers, 2014
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“This might then conflict the difference between passive rest in regards to paying attention to the experimental task, with the difference between passive rest in regards to the specific experimental task demands (Quintana and Heathers, 2014).”
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 Quintana and Heathers, 2014
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“The recording of an accurate baseline is crucial (Quintana and Heathers, 2014), for several reasons.”
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 Quintana and Heathers, 2014
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“Moreover, the breathing exercise used in the present study was not individually adapted based on the spontaneous respiration of each participant81.”
From Benefits from one session of deep and slow breathing on vagal tone and anxiety in young and older adults (2021) · cites this paper as [81]
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Metadata
- Authors
- Quintana, D. S., & Heathers, J. A. J.
- Affiliations
- Oslo University Hospital (NO)
- The University of Sydney (AU)
- Corresponding author
- Quintana, Daniel S.
- Venue
- Frontiers in Psychology
- Publisher
- Frontiers Media SA
- Published
- 2014-07-22
- Volume
- 5
- Pages
- 805-805
- ISSN
- 1664-1078 (ISSN-L)
- PMC
- PMC4106423
- OpenAlex
- W2137440205
- Cited by
- 395
- References
- 149
- Citations by year
- 2026: 31 · 2025: 37 · 2024: 38 · 2023: 41 · 2022: 41 · 2021: 45 · 2020: 38 · 2019: 34 · 2018: 28 · 2017: 22 · 2016: 24 · 2015: 15 · 2014: 1
- FWCI
- 3.33
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- Frontiers in Psychology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- NORA - Norwegian Open Research Archives (submittedVersion, cc-by)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Heart Rate Variability and Autonomic Control
- Physical Sciences › Engineering › Biomedical Engineering › Non-Invasive Vital Sign Monitoring
- Physical Sciences › Computer Science › Artificial Intelligence › Emotion and Mood Recognition
- Keywords
- heart rate variability, autonomic nervous system, heart rate, respiration, breathing, blood pressure, within-subjects design, baseline establishment, respiratory monitoring, emotion regulation, biobehavioral research
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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