Reduced heart rate variability and vagal tone in anxiety: Trait versus state, and the effects of autogenic training

Miu, Andrei C.; Heilman, Renata M.; Miclea, Mircea

doi:10.1016/j.autneu.2008.11.010

Cited by 188 publications

(121 citation statements)

References 54 publications

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“…Exclusion criteria included a history or current diagnosis of any anxiety disorder and/or major depressive disorder and cardiovascular disease (hypertension, coronary artery disease, and arrhythmias) as these conditions are known to involve ANS dysfunction (Chalmers et al, 2014;Haensel et al, 2008;Kemp et al, 2012;Marano et al, 2009;Miu et al, 2009). Participants were excluded if they had a history of practicing mindfulness meditation or even minimal exposure to the practice (N60 min).…”

Section: Participantsmentioning

confidence: 99%

Heart rate variability is enhanced in controls but not maladaptive perfectionists during brief mindfulness meditation following stress-induction: A stratified-randomized trial

Azam

Katz

Fashler

et al. 2015

International Journal of Psychophysiology

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Heart rate variability (HRV) is a vagal nerve-mediated biomarker of cardiac function used to investigate chronic illness, psychopathology, stress and, more recently, attention-regulation processes such as meditation. This study investigated HRV in relation to maladaptive perfectionism, a stress-related personality factor, and mindfulness meditation, a stress coping practice expected to elevate HRV, and thereby promote relaxation. Maladaptive perfectionists (n = 21) and Controls (n = 39) were exposed to a lab-based assessment in which HRV was measured during (1) a 5-minute baseline resting phase, (2) a 5-minute cognitive stress-induction phase, and (3) a post-stress phase. In the post-stress phase, participants were randomly assigned to a 10-minute audioinstructed mindfulness meditation condition or a 10-minute rest condition with audio-description of mindfulness meditation. Analyses revealed a significant elevation in HRV during meditation for Controls but not for Perfectionists. These results suggest that mindfulness meditation promotes relaxation following cognitive stress and that the perfectionist personality hinders relaxation possibly because of decreased cardiac vagal tone. The results are discussed in the context of developing psychophysiological models to advance therapeutic interventions for distressed populations.

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Section: Participantsmentioning

confidence: 99%

Heart rate variability is enhanced in controls but not maladaptive perfectionists during brief mindfulness meditation following stress-induction: A stratified-randomized trial

Azam

Katz

Fashler

et al. 2015

International Journal of Psychophysiology

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“…While findings in pathological anxiety are quite consistent across various studies (for review, see 11), HRV changes in subclinical anxiety are not so univocal. The assumption that chronic anxiety may be associated with trait-like lowered vagal tone (9) was supported by some studies, which found lowered HRV in highly anxious people (12,13). However, there has been a problem with replication of these results on other data, with small effects attributable to anxiety, while acute stress related reductions of HRV were reliably observed (14).…”

Section: Data Collectionmentioning

confidence: 60%

Allergy and high trait anxiety are related to increases in heart rate variability: results of naturalistic long-term design study

Rajčáni

Soláriková

Brezina

2018

Eur Ann Allergy Clin Immunol

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“…Investigations also have been made on HRV in healthy volunteers that were selected for extreme scores of TA and found that HTA was associated with reduced R-R intervals and high frequency power across conditions. [36] Moreover, a number of neuroscientific studies have employed scales to detect anxiety levels and have associated the scores obtained with hormonal, behavioral, neurophysiological and cardiac parameters. [13,32] Mocaiber and colleagues (2009) showed that HTA individuals are susceptible to modifications in affective contexts.…”

Section: Discussionmentioning

confidence: 99%

Applying learning algorithms to extract anxiety levels using the heart rate variability measure

Magini

Mocaiber

Calembo

et al. 2015

JBGC

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The classification problems in biological measures have been studied since mathematical methods and statistical tools were created to determine difference between two distinct samples. In this paper we present a mathematical methodology capable of differing 29 non-clinical volunteers with distinct degrees of trait anxiety (high or low) according to the State and Trait Anxiety Inventory (STAI-T) using an electrocardiogram (ECG) data as starting point. Specifically, the wavelet transforms and its statistical measures were used to extract simple patterns from the resting ECG and classify the group as low or high trait anxiety. The Daubechies, Haar and Symlet mother function were used to filter the original ECG data. Then, by means of the Weka Learning Algorithm and using only 5 attributes (Pearson Coefficient from Haar and Symlet, Median from Haar and Mode of Haar and Daubechies) we achieved a higher level of reliability, 96.90% (p < .05), with low training percentages. The results showed the efficiency of this methodology to classify volunteers according to their anxiety levels through an ECG data collection.

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Reduced heart rate variability and vagal tone in anxiety: Trait versus state, and the effects of autogenic training

Cited by 188 publications

References 54 publications

Heart rate variability is enhanced in controls but not maladaptive perfectionists during brief mindfulness meditation following stress-induction: A stratified-randomized trial

Heart rate variability is enhanced in controls but not maladaptive perfectionists during brief mindfulness meditation following stress-induction: A stratified-randomized trial

Allergy and high trait anxiety are related to increases in heart rate variability: results of naturalistic long-term design study

Applying learning algorithms to extract anxiety levels using the heart rate variability measure

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