Definition and research guide
This page combines a MeSH definition, publication statistics and selected research abstracts. It is a starting point for reading the literature, not a medical textbook or a systematic evidence review.
Content available: 3 complete abstracts (661 words), 9 references. Full article text is not stored or reproduced here; follow the PMID, DOI or PMC links to read the original sources and their access terms.
Definition
The number of times the heart ventricles contract per unit of time, usually per minute.
Definition: NLM Medical Subject Headings (MeSH) scope note (Public domain (U.S. National Library of Medicine); attribution requested). View the MeSH record.
Also known as: Heart Rates; Rate, Heart; Cardiac Rate; Cardiac Rates; Rate, Cardiac; Pulse Rate; Pulse Rates; Rate, Pulse.
Where it fits in the MeSH classification
- Broader topics
- Vital Signs; Hemodynamics
- Narrower topics
- Heart Rate, Fetal; Respiratory Sinus Arrhythmia
- See also
- Pulse
Related concepts
- Heart Ventricles
Research landscape
PubMed indexes 193,068 records tagged with the MeSH heading “Heart Rate” (counts retrieved 2026-10-29). 23,471 of them (12.2%) were published from 2020 onward, and the busiest period so far is through 1999 with 93,434 records.
Reviews account for 8,380 records (4.3%) and meta-analyses for 960. Randomized controlled trials number 18,581 (9.6%) as a share of all records on the topic. Randomized trials make up a comparatively large share of this literature, which means many treatment questions have been tested directly.
Show the data
| Period | Records |
|---|---|
| through 1999 | 93,434 |
| 2000-2009 | 35,173 |
| 2010-2019 | 40,990 |
| 2020 onward | 23,471 |
Publication-type chart data
| Type | Records | Share |
|---|---|---|
| Reviews | 8,380 | 4.3% |
| Meta-analyses | 960 | 0.5% |
| Randomized controlled trials | 18,581 | 9.6% |
Method: PubMed query "Heart Rate"[MeSH Terms] with publication-type and date filters, retrieved 2026-10-29.
Reading the evidence in cardiovascular medicine
Cardiovascular medicine has an unusually large body of randomized trials, so the type of outcome matters: hard clinical events such as death, heart attack and stroke carry more weight than changes in blood pressure, cholesterol or imaging markers that only predict risk. Observational studies can show associations but are confounded by age, lifestyle and other illness. Check whether a result is about prevention or treatment, the baseline risk of participants, and the absolute rather than only the relative size of any benefit.
Evidence from open-access studies
These open-access studies come from PubMed’s best-match results for this heading (papers whose main topic it is), ranked here by citation count, with one recent addition. Each abstract is reproduced in full under its recorded open licence so that you can read the authors’ own words. They illustrate the literature; they are not a systematic summary of it. Citation counts measure attention, not reliability or clinical benefit.
| Study / authors | Year | Source label / design | Europe PMC citations | Licence / source |
|---|---|---|---|---|
| Heartbeat-Evoked Responses in M/EEG: A Systematic Review of Methods With Suggestions for Analysis and Reporting | 2026 | Systematic review Design not recorded in structured metadata | 6 | cc by PMID 41943417 · DOI · PMC13053922 |
| Wearable-measured heart rate variability and premenstrual disorder symptoms across menstrual cycle | 2026 | Research article Design not recorded in structured metadata | 5 | cc by PMID 42412242 · DOI · PMC13342218 |
| Review of methods to derive the heartbeat-evoked potential: past practices and future directions | 2026 | Review article Design not recorded in structured metadata | 3 | cc by PMID 42464026 · DOI · PMC13585452 |
Heartbeat-Evoked Responses in M/EEG: A Systematic Review of Methods With Suggestions for Analysis and Reporting [1]
Abstract reading summary — source excerpts
- Opening excerpt
- Heartbeat-evoked responses (HER), as measured by electroencephalography (EEG) or magnetoencephalography (MEG), represent neural activity time-locked to heartbeats and are widely used as a marker of cardiac interoception in the study of brain-body interactions.
- Closing excerpt
- We hope that these resources will improve the robustness, reproducibility, and transparency of research in the growing HER field.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (231 words)
Heartbeat-evoked responses (HER), as measured by electroencephalography (EEG) or magnetoencephalography (MEG), represent neural activity time-locked to heartbeats and are widely used as a marker of cardiac interoception in the study of brain-body interactions. However, HER studies report largely variable findings, at least partially due to methodological variability. To achieve consensus on HER processing and improve the reproducibility of findings, the field urgently requires a structured summary of the methods employed so far. To this end, we conducted a systematic review of 132 HER studies using non-invasive M/EEG recordings in humans. Our results reveal substantial heterogeneity across most steps of HER analysis, ranging from data acquisition and preprocessing to HER estimation and statistical approaches. The large diversity in the processing choices is accompanied by considerable proportions of unreported methodological information across reviewed studies, reaching up to 80% for key processing steps. In addition, less than 33% of studies had enough statistical power to reliably detect meta-level HER effects, while their reported spatiotemporal locations varied substantially. We provide a comprehensive reporting and quality control checklist to aid in the development of more standardized procedures, highlighting critical steps for robust HER investigations. Additionally, we share the full extracted dataset, including an interactive version, to support other researchers in answering additional specific questions they may have. We hope that these resources will improve the robustness, reproducibility, and transparency of research in the growing HER field.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 41943417 · DOI · PMC13053922
Wearable-measured heart rate variability and premenstrual disorder symptoms across menstrual cycle [2]
Abstract reading summary — source excerpts
- Opening excerpt
- BackgroundScreening premenstrual disorders (PMDs) is time-consuming and challenging, resulting in delays in detection and treatment.
- Closing excerpt
- , rMSSD, postmenstrual week, β = -0·036 per SD, 95% CI: -0·065 to -0·048), whereas null association was noted for those without PMDs (β = -0·001, 95% CI -0·011 to 0·009; P-for-difference ConclusionsWearable device-estimated HRV fluctuate across menstrual cycles, with varying strengths of association with PMDs symptoms between individuals with and without PMDs, which may facilitate the development of digital biomarkers for future PMDs diagnostics.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (257 words)
BackgroundScreening premenstrual disorders (PMDs) is time-consuming and challenging, resulting in delays in detection and treatment. To characterize the temporal dynamics of portable digital-marker across the menstrual cycle and its biological basis in PMDs, we investigated the menstrual fluctuation of wearable device-based real-time heart rate variability (HRV) through menstrual cycles and its associations with premenstrual disorders (PMDs) symptoms.MethodsA prospective study of female participants nested from the Care of Premenstrual Emotion Cohort was conducted. Daily HRV metrics were collected by the Huawei Fitness Tracker over 1-2 menstrual cycles. PMDs symptoms were assessed with the Daily Record of Severity of Problems on a daily basis. HRV variability across cycles was described using descriptive statistics and splines, while associations between HRV metrics and PMDs symptoms were estimated using a mixed-effect model.ResultsIn total, 193 participants (with 68 prospectively confirmed PMDs) were included, with measures from 293 menstrual cycles. In both women with and without PMDs, SDNN, rMSSD, and HF decreased before menses and increased afterwards; the increase trends were more pronounced in women without PMDs. During the week before or after menses, levels of these HRV metrics were inversely associated with PMDs symptoms among women with PMDs (e.g., rMSSD, postmenstrual week, β = -0·036 per SD, 95% CI: -0·065 to -0·048), whereas null association was noted for those without PMDs (β = -0·001, 95% CI -0·011 to 0·009; P-for-difference ConclusionsWearable device-estimated HRV fluctuate across menstrual cycles, with varying strengths of association with PMDs symptoms between individuals with and without PMDs, which may facilitate the development of digital biomarkers for future PMDs diagnostics.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42412242 · DOI · PMC13342218
Review of methods to derive the heartbeat-evoked potential: past practices and future directions [3]
Abstract reading summary — source excerpts
- Opening excerpt
- The heartbeat-evoked potential (HEP) is an implicit, electrophysiological marker of cortical heartbeat processing and interoception, with increasing clinical relevance.
- Closing excerpt
- In order to ensure reproducibility and transparency, publications should report critical values for reliable HEP extraction, emphasizing the need for standardized methods to enhance study comparability and reproducibility.
- Interpretation limits
- Verbatim excerpts from the authors’ abstract; the closing excerpt may describe a finding, limitation or recommendation. Design, population, effect size and uncertainty have not been independently extracted or appraised. Read the complete abstract and linked paper before interpreting the findings.
Read complete abstract (173 words)
The heartbeat-evoked potential (HEP) is an implicit, electrophysiological marker of cortical heartbeat processing and interoception, with increasing clinical relevance. However, on the scalp, HEP are low-amplitude signals mixed with cardiac field artefacts (CFA), requiring signal processing pipelines to separate HEP from CFA. This review evaluates current analytical approaches and addresses methodological gaps in HEP pipelines. A scoping review of the literature was conducted focusing on previously published HEP studies. This was to extract HEP processing methods and parameters used in EEG (199 included papers) and MEG (8 included papers). Parameters investigated included the HEP window, filters, baseline correction window, epoch timeframes, minimum RR intervals, epoch amplitude rejection threshold, and CFA removal. EEG and MEG studies revealed clear heterogeneity and variability in the methods used to derive HEP. These clear inconsistencies in HEP parameter use and reporting would appear to challenge the level replicability between studies. In order to ensure reproducibility and transparency, publications should report critical values for reliable HEP extraction, emphasizing the need for standardized methods to enhance study comparability and reproducibility.
Abstract reproduced from the open-access article under the recorded cc by licence; © the authors. PMID 42464026 · DOI · PMC13585452
Key reviews and meta-analyses
The most cited review-type papers among PubMed’s best-match results for this heading, listed with bibliographic details only. Follow the links for the full text and access terms.
- Research article Age-predicted maximal heart rate revisited [4]
- Research article A meta-analysis of heart rate variability and neuroimaging studies: implications for heart rate variability as a marker of stress and health [5]
- Research article Impact of depression and antidepressant treatment on heart rate variability: a review and meta-analysis [6]
- Research article Sex differences in healthy human heart rate variability: A meta-analysis [7]
- Research article The effect of heart rate variability biofeedback training on stress and anxiety: a meta-analysis [8]
- Research article A meta-analysis of heart rate variability in major depression [9]
References
- Steinfath P, Azanova M, Kapralov N, Loesche T, Enk L, Nikulin V, et al.. Heartbeat-Evoked Responses in M/EEG: A Systematic Review of Methods With Suggestions for Analysis and Reporting. . 2026. PMID 41943417 · DOI · PMC13053922
- Pan Q, Zhou J, Chen M, Zhang P, Shi X, Lin Y, et al.. Wearable-measured heart rate variability and premenstrual disorder symptoms across menstrual cycle. . 2026. PMID 42412242 · DOI · PMC13342218
- Virjee RI, Kandasamy R, Garfinkel SN, Carmichael DW, Yogarajah M. Review of methods to derive the heartbeat-evoked potential: past practices and future directions. . 2026. PMID 42464026 · DOI · PMC13585452
- Tanaka H, Monahan KD, Seals DR. Age-predicted maximal heart rate revisited. J Am Coll Cardiol. 2001. PMID 11153730 · DOI
- Thayer JF, Ahs F, Fredrikson M, Sollers JJ, Wager TD. A meta-analysis of heart rate variability and neuroimaging studies: implications for heart rate variability as a marker of stress and health. Neurosci Biobehav Rev. 2012. PMID 22178086 · DOI
- Kemp AH, Quintana DS, Gray MA, Felmingham KL, Brown K, Gatt JM. Impact of depression and antidepressant treatment on heart rate variability: a review and meta-analysis. Biol Psychiatry. 2010. PMID 20138254 · DOI
- Koenig J, Thayer JF. Sex differences in healthy human heart rate variability: A meta-analysis. Neurosci Biobehav Rev. 2016. PMID 26964804 · DOI
- Goessl VC, Curtiss JE, Hofmann SG. The effect of heart rate variability biofeedback training on stress and anxiety: a meta-analysis. Psychol Med. 2017. PMID 28478782 · DOI
- Koch C, Wilhelm M, Salzmann S, Rief W, Euteneuer F. A meta-analysis of heart rate variability in major depression. Psychol Med. 2019. PMID 31239003 · DOI
About this article
- Sources
- NLM Medical Subject Headings (definition, synonyms); NCBI PubMed (counts, identifiers); Europe PMC (open-access abstracts and citation counts).
- Verification
- Every reference was resolved against PubMed on 2026-10-31; title, year and DOI matched.
- Review state
- automated source verified; no human expert review has been recorded yet.
- Version
- 1, last updated 2026-10-29.
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Evidence strength
EvidenceHelix's computed view of the study designs behind this topic: how common meta-analyses, randomized trials and reviews are, how recent the literature is, and a plain-language reading. It describes the design mix of the literature. It is not a quality appraisal of any study, and it is not medical advice.