Evidence map›Paper›PMID 39863733›Full record

ArticleScientific reports2025

Heart rate variability biofeedback in a global study of the most common coherence frequencies and the impact of emotional states.

Sai Balaji, Nachum Plonka, Mike Atkinson, Malathy Muthu, Minvydas Ragulskis, Alfonsas Vainoras, Rollin McCraty

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In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

9 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sai BalajiHeartMath Institute, Boulder Creek, CA, 95006, USA.
Nachum PlonkaHeartMath Institute, Boulder Creek, CA, 95006, USA.
Mike AtkinsonHeartMath Institute, Boulder Creek, CA, 95006, USA.
Malathy MuthuCapitol Technology University, Laurel, MD, 20708, USA.
Minvydas RagulskisFaculty of Mathematics and Natural Sciences, Kaunas University of Technology, LT-51368, Kaunas, Lithuania.
Alfonsas VainorasInstitute of Cardiology, Lithuanian University of Health Sciences, LT-50162, Kaunas, Lithuania.
Rollin McCratyHeartMath Institute, Boulder Creek, CA, 95006, USA. Rollin@heartmath.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This global study analyzed data from the largest dataset ever studied in the Heart Rate Variability (HRV) biofeedback field, comprising 1.8 million user sessions collected from users of a mobile app during 2019 and 2020. We focused on HRV Coherence, which is linked to improved emotional stability and cognitive function. Positive emotions reported by users were associated with higher Coherence scores and more stable HRV frequencies. In contrast, negative emotions exhibited lower scores and more dispersed frequency distributions. The most common frequency associated with Coherence was identified at 0.10 Hz. However, many users with the highest levels of Coherence fell within a lower range from 0.04 to 0.10 Hz. Most users exhibited high stability (standard deviation < 0.012 Hz) in their coherence frequencies from session to session, and their stability within a given session increased with increasing Coherence. The insights gained from this extensive dataset suggest that by instructing users to breathe deeper and slower and find a rhythm that's comfortable, they naturally find their unique resonant frequency. The findings provide a strong foundation for future research and the development of targeted interventions aimed at enhancing emotional and physiological well-being through HRV biofeedback and coherence practices.

Indexed as

Biofeedback, PsychologyEmotionsHeart RateAdultFemaleHumansMaleMiddle AgedMobile ApplicationsYoung AdultAutonomic nervous system (ANS)BiofeedbackEmotional statesHeart rate variability (HRV)Heart-rhythm coherenceResonant frequency breathing

Identifiers

PMID39863733
PMCPMC11762750

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.