Back to Journals » Neuropsychiatric Disease and Treatment » Volume 15

Cardiac dysautonomia in depression – heart rate variability biofeedback as a potential add-on therapy

Authors Pinter A, Szatmari S Jr, Horvath T, Penzlin AI, Barlinn K, Siepmann M, Siepmann T

Received 4 January 2019

Accepted for publication 21 March 2019

Published 17 May 2019 Volume 2019:15 Pages 1287—1310


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Dr Roger Pinder

Download Article [PDF] 

Alexandra Pinter,1,2 Szabolcs Szatmari Jr,1,3–4 Tamas Horvath,5 Ana Isabel Penzlin,6 Kristian Barlinn,7 Martin Siepmann,8 Timo Siepmann1,7

1Division of Health Care Sciences, Dresden International University, Dresden, Germany; 2Department of Family Medicine, Semmelweis University, Budapest, Hungary; 3Department of Neurology, Semmelweis University, Budapest, Hungary; 4Janos Szentagothai Doctoral School of Neurosciences, Semmelweis University, Budapest, Hungary; 5Department of Hydrodynamic Systems, Budapest University of Technology and Economics, Budapest, Hungary; 6Department of Neurology, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA; 7Department of Neurology, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany; 8Department of Psychosomatic Medicine and Psychotherapy, Carl Gustav Carus University Hospital, Technische Universität Dresden, Dresden, Germany

Abstract: Depressive disorders are among the most important health problems and are predicted to constitute the leading cause of disease burden by the year 2030. Aside significant impact on quality of life, psychosocial well-being and socioeconomic status of affected patients, depression is associated with impaired cardiovascular health and increased mortality. The link between affective and cardiovascular disease has largely been attributed to dysregulation of the autonomic nervous system resulting in a chronic shift toward increased sympathetic and decreased parasympathetic activity and, consecutively, cardiac dysautonomia. Among proposed surrogate parameters to capture and quantitatively analyze this shift, heart rate variability (HRV) and baroreflex sensitivity have emerged as reliable tools. Attenuation of these parameters is frequently seen in patients suffering from depression and is closely linked to cardiovascular morbidity and mortality. Therefore, diagnostic and therapeutic strategies were designed to assess and counteract cardiac dysautonomia. While psychopharmacological treatment can effectively improve affective symptoms of depression, its effect on cardiac dysautonomia is limited. HRV biofeedback is a non-invasive technique which is based on a metronomic breathing technique to increase parasympathetic tone. While some small studies observed beneficial effects of HRV biofeedback on dysautonomia in patients with depressive disorders, larger confirmatory trials are lacking. We reviewed the current literature on cardiac dysautonomia in patients suffering from depression with a focus on the underlying pathophysiology as well as diagnostic workup and treatment.

Keywords: mood disorder, autonomic dysfunction, cardiovascular disease, brain-heart axis, biofeedback


The burden of depression is high and on the rise globally: according to the World Health Organization, unipolar depressive disorder is predicted to be the leading cause of disease burden by 2030.1 Affective disorders can cause people to bear daily activities as an enormous challenge and function poorly at work, at school and in their families. At its worst, it may culminate into suicide. It has been estimated that the prevalence of suicide among patients with affective disorders varies between 2.2% and 8.6%.2

According to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-V), the diagnosis of a Major Depression (MD) Episode requires five or more symptoms to be present within a 2-week period.3 One of the symptoms should, at least, be either a depressed mood or anhedonia. The secondary symptoms are appetite or weight changes, sleep difficulties psychomotor agitation or retardation, fatigue or loss of energy, diminished ability to think or concentrate, feelings of worthlessness or excessive guilt and suicidality. These symptoms are rated in an all or none (0 or 1) fashion.4 Beyond the human costs, mental diseases are placing an increasing load on the global economy.5 Medical expenditures on depression scale similar to those on stroke and absenteeism its costs are higher than type 2 diabetes in the US.6 The financial burden of major depressive disorder showed an increment of 21.5% from 2005 to 2010.7 Depression represents a major economic challenge for Europe, as well. It was found the most costly brain disorder consuming up to 1% of the European overall GDP.8 Since depression and cardiovascular disease were prognosed to be two of the three leading causes of global disease burden worldwide,911 medical and socioeconomic concerns are assigned to their concurrence. In fact, patients with depression display impaired cardiovascular health which has been partially attributed to chronic dysregulation of the autonomic nervous system.

We aimed to review the current literature on cardiac autonomic failure in patients suffering from depression with a focus on the underlying pathophysiological mechanisms as well as diagnosis and treatment. We paid particular attention to cardiac autonomic function assessment via analysis of heart rate variability (HRV) and applied quality measures on the landscape of HRV studies based on the checklist of the recently published guidelines for HRV measurements in psychiatric investigations (GRAPH).12 Lastly, we aimed to summarize current treatment options for impaired cardiac autonomic function in patients with depressive disorders with a focus on non-invasive biofeedback.

Search strategy

This is a narrative review. Literature research was undertaken using the Web of Science database, Medline via the PubMed and Ovid interface. The keywords “depressive symptoms”, “depression”, “major depressive disorder”, “mood disorder” and “autonomic dysfunction”, “heart rate variability”, “baroreflex sensitivity”, “heart rate variability biofeedback” with the use of the Boolean operators “AND” or “OR” were used to identify relevant studies and reports that examined the association between cardiac dysautonomia, depression and the effects of heart rate variability biofeedback (HRVB) in health and diseased states. In the initial literature search, we exclusively chose these keywords. In addition, we performed a second literature search using the same electronic database with more specific terms to ensure coverage of all aspects that our review focused on. For this purpose, we established a search strategy using the following terms and their combinations:

“economical burden”, “brain-heart axis”, “neurocardiac axis”, “cardiovascular disease”, “cardiovascular risk”, “neuroimaging technique” AND “drug naive” OR “treated” AND “depression” OR “heart rate variability”, “anxiety”, “dysthymia”, “impulse control disorder”, “substance use disorder”, “psychosis”, “depression” AND “heart rate variability biofeedback”

We added every study that was relevant to our topic, which contained various study designs: randomized controlled studies, observational studies, meta-analyses, systematic reviews, and case reports published between 1969 and 2018. The relevance of the papers was assessed in light of our five core principles of this narrative review: 1) depression, 2) cardiovascular disease (CVD), 3) heart rate variability, 4) baroreflex sensitivity (BRS) and 5) heart rate variability biofeedback (HRVB). The included articles were all written in English. We reviewed the existing information on possible mechanisms linking depression and CVD and HRV as a measure for neurocardiac integrity. We summarized the results reported in depressive disorder on reduced HRV and BRS and excluded papers from our analysis if 4 or more recommendations of GRAPH were not fulfilled in them. Finally, HRVB as a treatment option was reviewed in psychiatric diseases, especially in depression aiming the restoration of physiological neurocardiac conditions.

Autonomic cardiac failure in depression

Depression and cardiovascular disease

Clinical depressive disorder is more than a substantial negative impact on mood and productivity. Pathophysiological connections were shown to exist between depression and somatic diseases, which is supported by observational and prospective clinical data.1317 The group of medical conditions that probably carries the highest overall health risk in this context are CVDs. Depressive disorder is an established risk factor for cardiovascular mortality and morbidity,1820 this entails coronary artery disease,21,22 myocardial infarction,23,24 congestive heart failure25 and hypertension.26 Primary and secondary associations have been described between depression and increased cardiovascular risk.22,27 A growing body of evidence shows that the brain-heart axis – including the autonomic nervous control of the heart – is disrupted by the functional and organic neural changes in depressive disorders. As for secondary causes, the behavioral constellation of the depressed person carries a complex obstacle in the way of primary and secondary prevention (lifestyle changes, compliance problems, poor adherence to medication).2830 The association between mood disorders and CVD was found to be independent of “classical” cardiovascular risk factors such as body mass index, physical activity, hypertension and hypercholesterolemia,18,22,31,32 supporting a genuine disease-specific mechanism whereby depression compromises cardiovascular health. In line with this hypothesis, an independent association between depression and increased risk of developing coronary artery disease has been shown.33 Based on cumulative data the American Heart Association has recommended that depression should be recognized as a risk factor for poor prognosis in patients with an acute coronary syndrome (ACS). The authors concluded that the preponderance of evidence had indicated that depression was associated with adverse medical outcomes after ACS.13 Having this clinical perspective in mind, understanding underlying mechanisms mediating these comorbid disorders might help identify therapeutic targets.

Brain–heart axis – the site of autonomic disruption, linking depression and cardiovascular disease

The underlying pathological processes of the association of depression and CVD have been in the limelight of scientific research. Apart from numerous behavioral and lifestyle factors, the central mechanisms connecting mood and cardiovascular disorders appears to stem from a generalized autonomic dysregulation with hypothalamic-pituitary-adrenal activation.27,34 This, in turn, has deleterious downstream effects, including the development of hypertension,35 endothelial dysfunction,36 inflammatory processes,37 platelet activation38 – which all have been hypothesized to contribute to impaired cardiovascular health in patients suffering from depression and thus lead to manifest CVD.

Central involvement of the brain-heart axis

Various studies have investigated the structures involved in modulating biobehavioral resources in emotion by flexibly adjusting physiological arousal in concert with changing situational demands.3941 To better understand this complexity, a model of interconnected neural elements has been introduced which is referred to as central autonomic network (CAN). In this model, autonomic, attentional and affective systems are integrated into a structural and functional network to interpret emotional regulation. The neural structures involved in the built-up of the CAN are the prefrontal cortex, insular cortex, the amygdala, hypothalamus, periaqueductal gray matter, parabrachial complex, nucleus tractus solitarii (NTS) and ventrolateral medulla, as well as the peripheral autonomic nervous system. The elements of this network were shown to be associated with various aspects of emotional and autonomic responses. Ventromedial prefrontal cortex is a key neural substrate of human social and affective function, central to the pathophysiology of mood and anxiety disorders. Neuroimaging studies in depression and anxiety suggest that it serves to regulate negative affect by top-down inhibition of brain regions involved in processing negative emotions – particularly the amygdala. Pathologically elevated negative affect in depression result from deficient prefrontal cortex-mediated inhibition of amygdala activity.42,43 Prefrontal, orbitofrontal and insular areas of the cortex were found to gate emotionally entrained responses. Threat results in their withdrawn activity which involuntary, defensive behaviors of short latency. Long-term prefrontal cortex hypoactivity can manifest as poor habituation to novel stimuli, failure to recognize safety signals and poor affective information processing. In line with these data, reduced prefrontal activity can lead to hypervigilance and social isolation.44 Beyond emotional regulation, patients with prefrontal cortex lesions also exhibited impaired cardiac autonomic responses.45 Amygdala was described as a critical brain region for emotional fear.46 Volume changes and increased metabolism of the amygdala was found in major depressive disorder.47,48 The amygdala plays a pivotal role in integrating emotional content into appropriate cardiovascular responses that match the environmental challenges. Insular cortex is a site of multimodal integration, provides emotional related functions, conscious interoceptive awareness and mediates arousal-states in the autonomic divisions.49 Neuroimaging studies revealed alterations in insular cortex activity in major depressive disorder.50 Moreover, a positive correlation was found between dysfunction of the insular cortex and severity of depression.51 Insular cortex lesions and impaired interconnection between insular cortex, amygdala and hypothalamus were reported to induce arrhythmias.52 In the CAN model, supramedullar structures converge to the NTS, as the final common pathway, through numerous feed-forward and feedback loops. The medullar segment of the brain stem receives and integrates afferent and efferent information crucial for autonomic regulation of the cardiorespiratory system. Cardiac and respiratory centers in the medulla are directly connected both physically and functionally. This allows them to elaborate complex afferentation and produce highly integrated efferent output.

Peripheral output and feedback of the brain–heart axis

Efferent parasympathetic and sympathetic fibers descend from the central nervous system to innervate – among others – the sinoatrial node and the vasculature in the cardiovascular system. Physiologically, sinoatrial node activity is under parasympathetic dominance, fluctuations in vagal efferent activity induce beat-to-beat changes in heart rate. Sympathetic innervation of the sinoatrial node affects heart rate to a lesser degree. However, the variation of elapsed time between two consecutive heartbeats is determined by the balance between the two antagonistic branches of the autonomic nervous system. Efferent autonomic activity mediates changes in heart rate and also total peripheral resistance. The resulting blood pressure alterations elicit cardiovascular feedback mechanisms such as the arterial baroreflex. The baroreflex includes conduction of sensory information from baroreceptor vessel walls (the aortic arch and carotid artery sinus) to the NTS. This information is further processed and integrated by the CAN with information from the cortical areas on the adequateness of the circulatory arousal. Eventually, the refined information propagates back to the cardiovascular system. According to human studies, the arterial baroreflex is responsible in 70% for the development of the cardiovagal tone.53 Thus, the arterial baroreflex has a crucial role in the maintenance of the blood pressure regulation: acute increases in BP lead to a decrease in heart rate and a lowering of vessel tone via increased vagal and reduced sympathetic efferent activity whereas decreased blood pressure results in opposite changes.

HRV as a marker of neurocardiac function

HRV is considered a measure of neurocardiac function that reflects heart–brain interactions and autonomic nervous system dynamics. From this psychophysiological point of view, HRV may provide an insight into complex regulatory processes with an affective tincture.54,55 The healthy heart is not a metronome, heart rate is varying slightly around a resting value within an interval due to autonomic, dominantly cardiovagal activity. Analysis of the HRV is suitable for assessing the magnitude of the cardiac efferent activity, mainly the parasympathetic activity.56,57 An optimal level of HRV within an organism was found to reflect healthy function and an inherent self-regulatory capacity,58 adaptability,44 or emotional and stress resilience.59,60 By contrast, reduced HRV has been linked to stress vulnerability. Higher resting HRV was shown to be associated with i) smaller negativity bias and ii) greater willingness to approach positive novel objectives. Moreover, the arterial baroreflex integrates cognitive and physiological aspects of emotion regulation. Afferent input from baroreceptors in the heart and the carotid-aortic arch contributes to visceroaffective integration, further highlighting the bidirectional link between autonomic and affective neural systems.61,62 Conversely, functional magnetic resonance imaging (fMRI) studies have revealed that baroreceptor afferentation contributes to psychological factors, such as attention level, perception and the processing of certain emotions. At the time of baroreceptor activation, attenuation of pain evoked potentials, nociceptive motor and autonomic reflexes and perception of pain were present.63,64 Periaqueductal grey matter activity mirrored negative emotional intensity ratings in concert with baroreceptor activity.65 Baroreceptor activity also enhanced detection of threat signals and is associated with facilitation of “attentional blink” for fear. With other words, baroreceptor afferent signaling augmented the attribution of emotional salience to fear.66

Heart rate variability and baroreflex sensitivity

Each medical specialty selects a set of autonomic tests to characterize the most relevant aspects of autonomic function in the specific field. In human psychological and psychiatric research, the HRV is a widely used methodology for autonomic assessments. The range of available autonomic tests is listed in detail in Table 1.

Table 1 Testing possibilities for autonomic function

Analysis of HRV is mostly based on ECG-recordings, from which the distance between two successive R-waves can be calculated. Based on time-RR-interval (RRI), series HRV parameters of time and frequency domain are calculated. Usually, the following time domain measures are determined: standard deviation of normal RRIs (SDNN), root mean square of normal to normal interval differences, and the percentage of successive RRIs that differ by >50 ms (pNN50). The latter two parameters are indicative of the parasympathetic nervous system activity. In the frequency band, the most widely used indices are the very low (0.03–0.04 Hz), low (0.04–0.15 Hz) and high (0.15–0.4 Hz) power bands (LF and HF). Very low frequency power (VLF) describes sympathovagal balance and has unique characteristics that gained attention recently.67 Normally, the respiration-related variability presents itself around 0.25 Hz frequency (15/min respiratory rate) and reflects parasympathetic nervous system effects (HF). The slower (6 cycles/min) fluctuations, observed in RRI, are presumably mediated by sympathetic and to a certain extent, parasympathetic nervous system activity (LF). By simultaneously assessing high and low-frequency HRV, information on the relative changes in sympathovagal balance can be gained (LF/HF). High variability of the heart rate indicates well-functioning parasympathetic nervous system regulation, reduced HRV is a consequence of deteriorated vagal and simultaneously increased sympathetic activity. Beyond that, HRV is a property of interdependent regulatory systems that operate on different time scales to help us adapt to environmental challenges. It is generated by heart–brain interactions and dynamic non-linear autonomic nervous system processes. Therefore, nonlinear HRV parameters represent a promising but not yet well-defined area of research. Due to the physiological and clinical importance of cardiovagal activity, numerous studies investigated the determining factors of the cardiovagal activity. The cardiac vagal motoneuron activity is largely influenced by the arterial baroreflex.68 As a negative feedback loop, arterial baroreflex can minimize blood pressure fluctuations by influencing cardiac output and total peripheral resistance. From the complex efferentation, the cardiovagal branch of the reflex-the changes in blood pressure and heart rate can be well examined.69 Cardiovagal BRS is a measure of the gain of the baroreflex and is defined as the change in RRI in milliseconds per unit change in blood pressure. To study the baroreflex function in humans, two approaches are widespread. The two methods investigate the reflectoric changes in RRI in response to i) pharmacologically induced blood pressure changes and ii) spontaneous fluctuations in blood pressure. The HRV and BRS methodologies are challenged to yield precise assessments in patient groups with low values; therefore, it is important to implement high-quality standards for such studies.70

Reduced heart rate variability and impaired baroreflex sensitivity in cardiovascular disease

Shifted sympathovagal balance toward the sympathetic branch leads to electric instability of the heart. Low HRV was associated with ventricular fibrillation after myocardial ischemia and infarction.71,72 Reduced HRV was shown to be an independent risk factor for sudden cardiac death, while increased HRV was associated with reduced cardiac mortality.72 Moreover, attenuation of HRV has been described in patients with chronic congestive heart failure and in those with hypertension and with dilatative cardiomyopathy.7375 Clinical significance of cardiac dysautonomia is, however, not limited to changes in HRV. A reduction in BRS was shown to be an independent risk factor for cardiovascular morbidity.76 Impaired BRS has been linked to increase the risk for arrhythmias, hypertension,77 heart failure,78 myocardial infarction79 and stroke.80

Combined reductions in HRV and BRS parameters were described in numerous diseased states. However, often there is no detectable, close relation between the indices of BRS and HRV, which can be probably explained by differences in their physiology. Therefore, it would be recommended to perform both HRV and BRS measurements simultaneously.79

Impairment of heart rate variability and impaired baroreflex sensitivity in depressive disorders

It appears from previous studies that autonomic disturbances in depressive disorders are present.8183 However, there is a considerable heterogeneity among studies concerning methods and ANS function testing. Based on our inclusion criteria (GRAPH), we have analyzed 21 studies in total, all presenting high methodological quality (Table 2). They were published between 2002 and 2017. In total, 967 patients with MD, 228 patients with history of depression, 591 patients with unipolar depression, 116 patients with bipolar disorder and 24 patients with posttraumatic stress disorder and MD were enrolled in these studies. Their results were compared to 1,050 healthy controls. Eighteen studies investigated autonomic nervous system function measured by HRV in depression, 14 (78%) studies have reported reduced variability of the heart rate. Seven studies determining BRS have described reduction in BRS in depressed patients compared to controls, however, one study showed only a tendency for BRS to be lower.

Table 2 Studies in which HRV measures were calculated on a least one cohort with depression diagnoses

Attention has to be paid to the evaluation of this apparently convincing result. When relating autonomic dysfunction with depressive disorders many possible confounding factors have to be taken into account. Out of these, CVD/risk factors and (non-)pharmacological treatment are noteworthy. Only nine studies have reported CVD/risk profiles or exclusion criteria of this patient population. It is established that CVD is associated with autonomic disturbances, and in depressed patient populations, this prevalent comorbidity has to be accounted for when analyzing ANS function. There is an ongoing debate, if depression alone, antidepressive treatment or their combination result in autonomic abnormalities and reduced HRV. Out of investigations included in our review, eight studies enrolled medication-free patients. Seven of these studies (88%) published autonomic distortions in depressed patients compared to controls. This finding is in line with a meta-analysis,82 which analyzed CVD-free, unmedicated depressed patients and found attenuated HRV which seemed to decrease with increasing depression severity. In contrast, two studies found that HRV parameters of depressed patients were not statistically significant from the values of healthy controls. Voss et al indicated, however, that BRS is reduced in depressed patients and concluded that BRS would mirror depression-related autonomic dysfunction more sensitively than HRV.

The effect of treatment on autonomic function in depression remains controversial. Treatment did not change HRV indices in the study of Brunoni et al and the authors concluded that reduced HRV could be a trait marker for depression. In three studies, however, treatment modified autonomic nervous system parameters, mostly worsened autonomic function was found. A prospective comparison indicated that the type of treatment may have different impacts on autonomic parameters (ie, tricyclic antidepressants reduced, SSRI did not change, repetitive transcranial magnetic stimulation increased them). It cannot be excluded that pharmacological treatment contributes to ANS dysfunction and indirectly to CVD risk in depression. However, it is also possible that sympathovagal imbalance is caused by depression severity, indexed by antidepressant use. In summary, since CVD is often associated with depression and autonomic parameters are largely influenced by CVD, in clinical assessment detailed CVD phenotyping and risk assessment should be performed and taken into account when autonomic functions are evaluated in patients suffering from depressive disorders.27 It seems recommendable to involve CVD in the exclusion criteria or account for them statistically. Ideally, treatment-naïve populations should be targeted or each treatment modality must be adequately discussed and controlled for. Finally, BRS may represent a more sensitive marker of ANS dysfunction in depression. Therefore, it would be recommended to involve the measurement of this index when assessing ANS dysfunction in depression.

Understanding the brain–heart axis can imply therapeutic interventions in depressive disorders

Knowledge of psychophysiological mechanisms interconnecting affective, autonomic and cardiovascular regulation may also imply treatment possibilities when evidence of dysregulation is present. Currently, pharmacological interventions are considered effective, when a reduction of ≥50% on the Hamilton Depression Rating Scale (HAM-D) is achieved.84 Below this ratio, the patients are held refractory to the specific treatment. Even the patients, who manage to respond adequately and fulfill the criterion, often continue to experience symptoms. Beyond this, the antidepressants are known to cause unpleasant side effects such as weight gain, which may also worsen the cardiovascular prognosis.85 Moreover, when pharmacological therapy is discontinued, the patients frequently relapse. Non-pharmacological treatment options carry clinical significance and are favored directions of psychiatric research. Neurocardiological interventions are likely to alleviate depressive symptoms, as well. Vagal stimulation, eg, was found to help patients with refractory depressive symptoms, however, its invasive nature and costliness mean significant limitation for its usability.86 Deep brain stimulation of cingular areas has also been found to be effective in treatment severe resistant depression.87,88 Further interventions targeting psychophysiological pathways are transcranial magnetic stimulation, psychotherapy and different biofeedback approaches with various evidence levels and grades.8991 Psychotherapy is, eg, well established and recommended as a treatment regimen in depressed patients in various national guidelines. Recently, it has been demonstrated that transcranial magnetic stimulation may be considered as a promising enhancement in treatment-resistant depression.92 Whereas, HRVB represents a novel, experimental, non-pharmacological intervention to improve complex biobehavioral mechanisms that result in improvements in mood regulation, autonomic function and have possible positive impact on cardiovascular complications.

Heart rate variability biofeedback

Physiological background

HRVB is a biobehavioral clinical intervention that has been used in research studies in both psychological and somatic disorders. The technique has been shown to enhance vagal control of heart rate and affect the networks involved in neurocardiac regulations: the autonomic nervous system, the cardiovascular system, the respiratory system and biological substrates of emotion regulation.

At its discovery, it was observed that maximal oscillations in heart rate (up to 60/min!) were provoked by low respiratory rates.93,94 The effects are based on resonance properties of the cardiovascular system. To be specific, breathing at the resonant frequency augments the earlier described respiratory sinus arrhythmia (RSA) and stimulates rhythmically the baroreflex that triggers large-amplitude reflectoric heart rate oscillations.95 Thus, greatly amplified HRV develops at least partially due to increased baroreflex gain. This appears as augmented LF and LF/HF ratio in terms of HRV spectral parameters. The optimal breathing frequency individually varies (4.5–6.5/min) and averages around 5.5–6/min. Male gender and bigger height appear to be associated with lower resonant respiratory rate, the common physiological factor would be larger blood volume.96 The higher the blood volume, the bigger is its inertia, which leads to longer delay between baroreflex-elicited heart rate and blood pressure-and longer periodic time of resonant breathing.

Effects of heart rate variability biofeedback on autonomic cardiovascular regulation

The regular application of HRVB is thought to ameliorate autonomic functioning and restore autonomic homeostasis, important for cardiovascular health. Precise resonant frequency breathing plays a pivotal role in the beneficial effects of HRVB such as augmenting HRV parameters and reducing blood pressure in health.97 HRVB has been found to reduce blood pressure in prehypertensive individuals and proved to be superior to slow abdominal breathing.98 In another group of prehypertensive patients, beneficial effects on blood pressure and HRV parameters of HRVB were maintained when stressors were applied.99 However, in an early study in mildly hypertensive patients, the HRVB has been found to be ineffective in reducing blood pressure values.100 Larger, controlled studies are needed to detangle HRVB effects in hypertension. It seems reasonable to target subgroups within hypertensive patients, such as individuals with white coat hypertension or essential hypertension where stress is believed to be an important component of the pathology. HRVB seems a promising therapeutic add-on in patients with cardiac diseases, by reducing symptoms and increasing quality of life.101 Del Pozo et al enrolled 63 patients with CAD and performed six sessions of HRVB with them coupled with daily practices at home.102 A significant increment was observed in HRV parameters in this group of patients. In end-stage heart failure patients, HRVB has been shown to change the remodeling biology of the myocardium favorably.103 Still, in heart failure patients, “6 mins walk test” performance was improved and perceived stress level was reduced by HRVB intervention.104

Another effect of HRVB mechanism is probably by influencing visceral afferent activity, which has complex upstream effects. This fits into a timely area of research regarding “peripheral emotion theories”. It postulates that a feedback of bodily response is proposed to be the basis for emotional feelings and physiological change. Among these, there appears to be a primacy of cardiovascular feedback on the generation of biobehavioral phenomena. HRVB and the slow abdominal breathing during the intervention trigger central responses, primarily by increased baroreflex afferent (vagal) activity but also by subdiaphragmal vagal afferent stimulation.

HRVB increases the signal input intensity conveyed by vagal afferents. This effect is similar to the course of action of vagal nerve stimulation. Enhanced activity of vagal afferents conveyed via NTS and projected to cortical, paralimbic and limbic structures, known to be involved in emotion regulation and implicated in depression. The data originating from neuroimaging studies in vagal nerve stimulation, described substantial ipsi- or bilateral modifications of medial temporal regions such as hippocampus, parahippocampus or amygdala as well as orbito- and prefrontal cortical areas, all known to be involved in emotional processes.86

Deep brain stimulation of cortical areas, where vagal nerve projects, have been found also effective in treatment-resistant depression.87,88

Further evidence on these central effects come from Heartbeat Evoked Potential (HEP) studies. HEP in EEG recordings has been described to be altered by resonant breathing and attenuated by negative emotional stimuli.105 HEP has also been found to be a marker of altered bodily awareness in depressed patients. Decreased interoceptive involvement of the insular cortex detected by fMRI was related to depression and somatic symptom severity in major depressive disorder.106 It can be hypothesized that HRVB by altering cardiac afferent activity, improves interoceptive representation of the insular cortex, therefore reduces alexithymia and ameliorates decision-making in depression.107

Heart rate variability biofeedback assessment: conduction and practical aspects

In general, ECG or plethysmograph recording equipment is necessary for the application of HRVB. There are standardized, easily available HRV biofeedback systems for clinicians who wish to deliver HRVB (Stressball BioSign, Ottenhofen, Germany Mück-Weyman 1996, J&J Engineering, Poulsbo, WA, Stress Pilot, Biosoft, Germany). Ideally, the instrumentation provides real-time information on heart rate, respiration, low-frequency HRV power band and a running spectral chart to display average amplitude of heart rate fluctuations at each frequency. The original HRVB training protocol used to be 10-session long.108 However, based on research data of the authors, it has been shortened and currently involves five visits with durations of 30–45 mins (Table 3.).109

Table 3 Shortened protocol for heart rate variability biofeedback training

Utility of heart rate variability biofeedback in clinical practice

HRVB has been shown to enhance psychophysiological functioning in both health and disease. In healthy individuals, HRVB practicing has been shown to improve control over autonomic responses when encountering negative stimuli.110 Furthermore, merely the acquired skill of HRVB enabled the participants to better reduce heart rate in emotionally challenging situations.111 HRVB appears to reduce anxiety and improve coping with stressors,112 although large randomized-controlled trials are lacking to confirm these findings. Highly anxious college113 students have achieved decreases in anxiety and negative mood with the help of a HRVB protocol. Profession-associated stress was addressed by a study with quasi-experimental research design, who investigated HRVB effects on psychophysiological stress markers in correctional officers.114 They have found improvements of laboratory stress marker levels and reduced psychological distress which would mean a health-care cost difference of 1,179 USD/year/person. A recent review has concluded that HRVB is a safe, easy-to-learn method for athletes and coaches to apply in order to increase sports performance.115 Competitional stress and recital excitement is often a profound source of anxiety in dancers and musicians, which may undermine their performance. HRVB has benefitted the both the dance and musical performance.116,117 In a systematic review HRVB has been also described as a feasible, adjuvant, health-promoting stress management tool for peripartum women.118 According to the two studies119,120 analyzed in this review, stress levels of peripartum women with HRVB intervention were reduced compared with participants who did not receive HRVB. Furthermore, HRVB has also been shown to decrease depressive symptoms (measured by a significant decrease in total Edinburgh Postnatal Depression Scale score) by reducing anxiety or difficulties in sleeping in postpartum women.119 To our knowledge, there is no information on the effectiveness of HRVBF on psychological stress in the first and early second trimester of pregnancy. It is also unclear, whether stress reduction via HRVB has beneficial effect on preterm labor. Recently, a study with open trial design has found significant decrease in impaired ability to tolerate normal stressors and dysphoric mood by a 4-week HRVB treatment in young individuals with clinically high risk for developing psychosis.121 Promising trends in reducing self-reported anxiety were also reported. However, randomized-controlled trial would be necessary to assess the efficacy of HRVB in this group of individuals.

Beneficial effects of HRVB have been shown in somatic and psychiatric diseases, as well. It is known that HRV correlates negatively with age in adults and biofeedback effects on cardiovascular variability attenuate with declining age.122,123 In contrast with this observation, Lehrer et al have shown that age-related attenuation effect of biofeedback does not affect significantly the usability of HRVB for treating asthma in older patients.124 HRVB has been found a useful add-on therapy in chronic obstructive pulmonary disease, improving quality of life and 6 min walk test.125 Another study has investigated the effects of HRVB on subjects with chronic neck-shoulder pain, who experienced after a 10-week session improvements in perceived health and showed ameliorated HRV profile.126 Patients with unexplained medical symptoms can represent unique challenge to physicians, HRVB may represent a useful method to alleviate their somatic symptoms and improve their functional status.127

Furthermore, potential efficacy of HRVB is indicated by a growing number of studies in mental disorders. In a pilot study in patients with posttraumatic stress disorder in veterans, HRVB together with conventional therapy has elevated diminished HRV and reduced their symptoms, whereas conventional therapy alone had no significant effect on either HRV or symptom profile.128 HRVB was also found to attenuate dysfunctional eating behaviors and reduce food craving, eating and weight concerns food craving. Interestingly, the intervention was not accompanied by long-term increase in HRV parameters.129 By reducing craving and anxiety accompanying abstinence HRVB represents a useful adjunct therapeutic option in substance use disorders.130 In a mixed group of alcohol or drug addict men, HRVB proved to be an efficient add-on therapy for reducing craving.131 Reduced HRV parameters in this group of patients appeared to predict increases in craving by the end of the conventional treatment. Improved HRV, vasomotor function and reduced anxiety in response to HRVB intervention was also seen in alcohol-dependent patients.132 After 1-year follow-up, the rate of abstinence tended to be higher in patients who underwent HRVB intervention.133

However, while these findings are quite promising, large well-designed confirmatory studies are needed to form a basis for potential translation of the technique into standard clinical care. Moreover, a publication bias with non-reporting of negative studies is to be anticipated, particularly as the majority of available studies have small sample sizes.

Studies of heart rate variability biofeedback as add-on therapy in depression

To our best knowledge, there have been four studies enrolling patients diseased by depression disorders alone.134137 Details of these studies are found in Table 4 and they are discussed below in chronological order.

Table 4 Details of the studies investigating HRV biofeedback intervention in major depressive disorders

First, an open-label study with 11 patients with major depressive disorder.134 The middle-aged patients were dominantly females, similar to the other three studies, discussed later. There was no control arm in this investigation. All subjects were diagnosed in accordance with DSM-IV. Depression severity was assessed by HAM-D and Beck Depression Inventory (BDI)-II. Anxiety and dysthymic disorders as comorbidities were allowed as long as the primary diagnosis was MD. Detailed exclusion criteria were applied which also included CVDs. The training manual of Lehrer et al was followed when performing HRVB. They have implemented home-practice as part of the training routine. This is an essential component of the method, since HRV biofeedback relies on self-management that is not controlled by therapeutic supervision following few initial supervised training sessions. However, the lack of control over this might impair the evaluation of efficacy. The determined HRV parameters were in line with international guidelines. It was observed that depressive symptoms were improved during HRVB treatment and there were also increases in SDNN, pNN50, LF and HF. However, no correlation was detected between the two findings. Improved HRV indices tended to return back to baseline by the end of the protocol. Complete and partial clinical remissions were reported in 6 and 3 patients, respectively. The authors have emphasized that especially the neurovegetative components of the disorder (sleep hygiene, fatigue, concentration) showed partial recovery. The study was a preliminary, uncontrolled investigation, which does not lead to definitive conclusions. Further limitation that the sample was Caucasian, dominantly female and the home-practice was not standardized.

Shortly after, another open-label trial was performed and recruited 14 patients with MD and 24 healthy controls.135 Half of the controls received HRVB intervention. The participants were young adults; the majority of them were female. Anxiety and depression severity was assessed by BDI and state-trait anxiety inventory. Patients already receiving antidepressant and/or anxiolytic medication and/or psychotherapy were included. Exclusion criteria were elaborated in detail and they have controlled for CVD, similarly to the first study. HRVB protocol and the calculated HRV parameters were in line with protocols. Additionally, the authors have also assessed vasoconstrictory response of cutaneous blood vessels (VR). The depressive symptoms were improved during HRVB treatment, at the end of the intervention and at 2 weeks follow-up. The latter highlights the possible long-term efficacy of the intervention, as well as the fact that a chronic disease requires constant care. Reduced heart rate and pNN50 was described at follow-up. By contrast, there was no change noted in healthy controls receiving biofeedback. VR was unchanged. However, vasomotor tone is influenced by the baroreflex, that is known to be triggered by HRVB technique.138 The authors concluded that HRVB appears to be a useful adjunct for the treatment of depression, associated with increases in HRV. Major limitation of the study was the small sample size, the absence of an active control group in depressed patients. Longer follow-up period also would have been recommended.

The third study was conducted with a replicated single-subject study.136 Seven participants with MD completed the full protocol, there were no healthy controls. The patients were middle-aged, mostly (6) women. CVD did not form a part of the exclusion criteria. Diagnosis of MD was based on DSM-IV. Avoidant and dependent personality traits were allowed, three patients were on medication. Psychological measures included BDI-II, happiness index and positive outcome list. The authors applied a conceptually different technique, the Stress Relieving Program which included HRVB. HRVB sessions were extended by induction, remembrance of positive emotions and turning negative feelings into positive. The authors have also not reported conventional HRV variables, but assessed heart coherence. It was described as a harmonious ordered heart rhythm pattern and reflects a regular, sine-wavelike pattern in HRV. This study did not show significant reduction of the depressive symptoms and increases in heart coherence as the effect of their Stress Relieving Program. The authors explain their findings by the backdraft phenomenon: inducing positive emotions such as self-compassion in depressed patients may cause an eruption of negative emotions towards themselves. Similarly to the previous publications, small size, female dominance, uncontrolled disease duration represent limitations.

In a randomized-controlled study, the participants received conventional psychotherapy with or without HRVB training.137 Thirty female college students were enrolled, 20 with MD and 10 healthy controls. Strict age-restrictions were applied (18–25 years) in this study. The participants were asked to refrain from exercise, caffeine or tobacco consumption 3 hrs prior to the testing. Only one of them reported current use of medication, the others were free of treatment. MINI and BDI-II were used in this study for psychological measurements. Guidelines of HRVB intervention and HRV determination were followed. Similarly to the first open-label study, the authors have implemented uncontrolled home-practice as part of the training routine. The HRVB group showed the greatest decline in depressive symptoms and SDNN, HF and LF/HF showed vagal activity increment in this group of patients. They have also demonstrated that depressive symptom improvement seen in HRVB group was partially driven by improvement in HRV (SDNN). Small sample size, narrow age-range and female exclusivity represent limitations. Furthermore, HRVB was studied with psychotherapy only, HRVB combined with antidepressant therapy is lacking. There was no group that received only HRVB treatment.

In summary, the patients were dominantly females, which have been listed as limitation of the studies; however, the depressive disorder affects women more. All subjects were diagnosed in accordance with the DSM-IV. Treatment-wise, there is large heterogeneity between types of medications and dosing regimens. In each study, there were patients who discontinued the study protocols. Exclusion criteria were not concordant throughout the studies, CVD was not part of them in two studies. Two studies did not enroll control arms in their investigation.134,137 As for the design of the studies, the only randomized-controlled study was performed in the latest study.137 Three studies followed the protocol of HRVB and HRV guidelines. All studies, except for one, could show significant reduction of the depressive symptoms and increases in HRV parameters as the effect of HRVB sessions. It seems the HRVB technique produces a reduction in depressive symptomatology and its effects may last beyond the direct time frame of the experiment (2 weeks after). Furthermore, it would also be of interest if remission is achieved. To improve the precise assessment the use of exact questionnaires can be suggested, especially those monitoring anxiety. Comorbid anxiety and anxiety symptoms were described as a confounder when investigating HRV in depression.139 Favorable changes in HRV parameters, however, are less conclusive. Two studies have found wide range of HRV parameters to improve as an effect of HRVB, one of them described that by the end of the 10th session, the parameters tended to return back to baseline values.135,137 It seems likely that the cumulative time spent practicing HRVB correlates with the improvement of neurocardiac function; therefore it may be advisable to include this value to assess a “dose–response” relationship. One study reported changes only in pNN50 and heart rate, however, these changes were also observed at 2-week follow-up.136

Unfortunately, the standard antidepressant and psychotherapy seem not to increase HRV to physiologic levels.82,140 The effective treatment of depression might not reduce stress physiology which contributes to decreased HRV. Reducing stress levels early and adequately with the HRVB could increase the motivation of patients to adhere to the therapy and cooperate. The correlation between the improvement of HRV and reduced depressive symptoms means a further question for this research area. The first study reported no significant relationship between the two findings, whereas the last study found that improved HRV accounted partially for positive changes in mood. A possible explanation for these mixed findings could be that HRV improvements are related more closely to specific depression symptoms such as sadness, crying and poor sleep.141

Studies in different pathologies with depressive symptoms

In an open-label study with 12 female fibromyalgia patients (18–60 years), HRVB improved the overall functioning and the depressive symptoms by the end of the 10 sessions and later at the 3 months follow-up.142 Immediate, after-session HRV values showed increment, but HRV and BRS measures did not differ among sessions and at follow up. Small sample size and the lack of control group are major limitations of the study.

The prevalence of heroin use has increased dramatically lately, serious comorbidities such as depression have to be taken also in account. Heroin users exhibiting depressive symptoms were enrolled in the following study with counterbalanced, within-subject experimental design.143 HRVB technique was applied during six sessions, only nine abusers completed all the sessions which was found to improve HRV parameters. Depression severity also showed amelioration; however, it was not statistically significant.

The following three papers investigated HRVB effects in CVDs and surgery complicated with depression. As outlined earlier, CVDs are independently associated with depression and stress, as well as impaired cardiovagal control of heart rate. Their promising results indicate that this novel neurocardiac intervention facilitates psychological-emotional coping and also improves cardiovagal regulation. Therefore, adding HRVB may represent a low-risk therapeutic tool in rehabilitation and postoperative risk reduction programs for patients with CVDs.

Post-stroke depression is one of the common complications of cerebrovascular events.144 Li et al recruited 13 poststroke patients (mean age: 55 years, dominantly females) for a randomized controlled trial and trained them in line with the 10 session-long HRVB protocol. Another group of 11 poststroke patients (mean age: 60 years, dominantly males) received treatment as usual only. Improvements in sleep disturbance and daytime dysfunction have been observed. Furthermore, gains in certain HRV parameters were also found. Although there has been a significant drop in several depression severity scores, an overall clinical remission (≥50% improvement at HAM-D) was not achieved. It is hypothesized that the specific characteristics and pathogenesis of post-stroke depression have caused an altered effectiveness of HRVB in this setting. It seems possible that selecting patients based on their baseline HRV would characterize a group more responsive to HRVB treatment.

Nolan et al have conducted a randomized-controlled study in 46 patients with coronary heart disease and associated depression who were randomly assigned to an HRVB performing and an active control group.145 HRVB improved psychological adjustment, indicated by reduced scores of Perceived Stress and Centre for Epidemiologic Studies in Depression Scales and augmented vagal regulation, measured by increased HF, were reported. Above this, the two beneficial findings were found to be associated.

Finally, Patron et al in a randomized controlled study aimed to apply HRVB in 26 patients (mean age: 61 years) after cardiac surgery in order to increase their cardiovagal activity – expressed as RSA – and reduce their depressive symptoms.146 Amplified RSA and a drop of depression scores were described, the changes were inversely related to each other from pre to post training.

Clinical implications of heart rate variability biofeedback

HRVB has shown encouraging results so far. Certain conditions, such as anxiety, stress, mood fluctuations are highly related to modern lifestyles. When lacking appropriate coping-supportive solutions that reduce vulnerability and increase the sense of control, they may culminate into mental illness and impair cardiovascular functions. In-lab training sessions withdraw liberty of the individuals, and may not be enough for the complete understanding of how HRVB works or for mastering physiological improvements at aim of the technique. There are PC-compatible breath tracers, mobile applications, home breathing tracers available to help and promote the acquisition of the breathing technique. Furthermore, HRV spectral analysis feature for biofeedback purposes has also been implemented into smartphone application, which could bring this intervention closer to the general population. The present review did not aim to summarize all these approaches; however, some examples are provided here. First, in an earlier study, a system was created containing a wireless monitoring belt (Zephyr BioHarness) to gather HRV and breathing frequencies.147 Ubiquitous smartphone was used to process and display real-time information for biofeedback. In 2014, United States Patent was issued for a system called Mobile Wellness Device. It was reported to acquire ECG signals and transmit them to a server via a mobile device offering accurate HRVB measurement which is portable. In a preliminary efficiency study, a smartphone solution for cardiac coherence training was presented.148 It was based on a photopletysmographic imaging through the smartphone camera. This sensor-less technology allows controlling biofeedback exercise through simplified HRVB algorithm. Further validation with existing computer-based technologies such as Freeze Framer or Symbioline would be necessary. As a further application, pattern recognition might be used to alert and predict acute and chronic psychophysiological events. When combined with other platforms, like actigraphy, sleep characteristics could be assessed. Adherence to treatment and compliance of the patients with depression could also be improved by a reliable home-monitoring device.


Depressive disorders represent a devastatingly common, recurring disease with immense financial burdens. Therefore, there is a definitive need for more adequate prevention and treatment amelioration. Better understanding of pathophysiological processes involved in depression could be to assistance to that. Recent advances in neuroscience indicate pathophysiological interconnections between affective, autonomic and cardiovascular regulations. In line with this, reduced HRV and BRS – widely accepted measures of the autonomic functions – are established independent risk factors for CVDs. Furthermore, diminished HRV and BRS have also been shown in depression. Comprehensive approach that addresses mood disorder, autonomic dysfunction and cardiovascular dysregulation may plead gainful. Recent therapies for depression do not target autonomic dysfunction or even worsen it. HRVB is an available, easy of attainment method, which aims to restore autonomic homeostasis and cardiovascular function. Enteroceptive regulation can be improved by this self-management technique to a clinically relevant extent. Recent investigations reported that HRVB application alleviated anxiety and improved mood in psychiatric diseases, including depression. Implementation of HRVB into depression treatment strategies and home-monitoring techniques may ameliorate patient compliance and treatment adherence. The effective treatment of depression might not reduce stress physiology which contributes to decrease HRV. An early reduction in stress levels with the HRVB could increase motivation of patients to adhere to the therapy and cooperate. However, clinical utility of this method is still a question and larger clinical trials are necessary to explore the therapeutic potential of HRVB.


The present review has been written in a narrative review format in order to provide comprehensive and up-to-date summary of available research findings. Similarly to systematic reviews, the search methodology was described in detail, in order to assure reproducibility. However, our exclusion criteria did not involve study designs or article types, compared to systematic reviews, our sample of articles represent a broader group with a higher risk for bias. The pathological processes linking depression, CVD to autonomic nervous system are, in part, hypothetical, future research would have to address its further investigation. When selecting papers for cardiac dysautonomia in depression, two authors have reviewed them (AP and SzSz) and applied the GRAPH guideline in order to include studies that were performed at high methodological standards. Still, not all checkpoints were always fulfilled in the included articles. Furthermore, the diverse patient characteristics (duration, severity of the disease, pharmacological and/or non-pharmacological treatment), comorbidity issues, which were often not reported, differing design characteristics weaken the strength of the conclusions drawn here.

It has to be emphasized, that HRVB is a somewhat promising, non-pharmacological intervention, but it is experimental. Large-scale clinical trials are mandatory to investigate its clinical efficacy in diseased states. There is still very limited data available that investigates the effects of HRVB in depression. The patient characteristics and study design heterogeneity, especially at this low amount of data, represents a considerable bias and limits the merit of their discussion.


The authors wish to thank Viktor Lakatos for his valuable language editing contribution.


TS and KB are editorial board members of Neuropsychiatric Disease and Treatment. TH was sponsored by the National Research, Development and Innovation Office (NKFIH) postdoctoral program, grant number: PD 121186. SS Jr reports grants from New National Excellence Program (UNKP-17-3) of the Ministry of Human Resources of the Government of Hungary, grants from Society of Transylvanian Museum – Section of Medicine and Pharmacy, outside the submitted work. The authors report no other conflicts of interest in this work.


1. Lépine J-P, Briley M. The increasing burden of depression. Neuropsychiatr Dis Treat. 2011;7(Suppl 1):3–7. doi:10.2147/NDT.S19617

2. Bostwick JM, Pankratz VS. Affective disorders and suicide risk: a reexamination. Am J Psychiatry. 2000;157(12):1925–1932. doi:10.1176/appi.ajp.157.12.1925

3. American Psychiatric Association. Diagnostic and Statistical Manual of Mental Disorders. American Psychiatric Association; 2013.

4. Tolentino JC, Schmidt SL. DSM-5 criteria and depression severity: implications for clinical practice. Front Psychiatry. 2018;9:450. doi:10.3389/fpsyt.2018.00450

5. Roehrig C. Mental disorders top the list of the most costly conditions in the United States: $201 billion. Health Aff. 2016;35(6):1130–1135. doi:10.1377/hlthaff.2015.1659

6. Trogdon JG, Murphy LB, Khavjou OA, et al. Costs of chronic diseases at the state level: the chronic disease cost calculator. Prev Chronic Dis. 2015;12:E140. doi:10.5888/pcd12.150131

7. Greenberg PE, Fournier A-A, Sisitsky T, Pike CT, Kessler RC. The economic burden of adults with major depressive disorder in the United States (2005 and 2010). J Clin Psychiatry. 2015;76(2):155–162. doi:10.4088/JCP.14m09298

8. Sobocki P, Jönsson B, Angst J, Rehnberg C. Cost of depression in Europe. J Ment Health Policy Econ. 2006;9(2):87–98. Available from: Accessed September 13, 2018.

9. Murray CJ, Lopez AD. Global mortality, disability, and the contribution of risk factors: global burden of disease study. Lancet. 1997;349(9063):1436–1442. doi:10.1016/S0140-6736(96)07495-8

10. Mathers CD, Loncar D. Projections of global mortality and burden of disease from 2002 to 2030. Samet J, ed. PLoS Med. 2006;3(11):e442. doi:10.1371/journal.pmed.0030442

11. Licinio J, Yildiz B, Wong M-L. Depression and cardiovascular disease: co-occurrence or shared genetic substrates? Mol Psychiatry. 2002;7(10):1031–1032. doi:10.1038/

12. Quintana DS, Alvares GA, Heathers JAJ. Guidelines for Reporting Articles on Psychiatry and Heart rate variability (GRAPH): recommendations to advance research communication. Transl Psychiatry. 2016;6(5):e803–e803. doi:10.1038/tp.2016.73

13. Lichtman JH, Froelicher ES, Blumenthal JA, et al. Depression as a risk factor for poor prognosis among patients with acute coronary syndrome: systematic review and recommendations: a scientific statement from the american heart association. Circulation. 2014;129(12):1350–1369. doi:10.1161/CIR.0000000000000019

14. Kano O, Ikeda K, Cridebring D, Takazawa T, Yoshii Y, Iwasaki Y. Neurobiology of depression and anxiety in Parkinson’s disease. Parkinsons Dis. 2011;2011:143547. doi:10.4061/2011/143547

15. Byers AL, Yaffe K. Depression and risk of developing dementia. Nat Rev Neurol. 2011;7(6):323–331. doi:10.1038/nrneurol.2011.60

16. Martin-Subero M, Anderson G, Kanchanatawan B, Berk M, Maes M. Comorbidity between depression and inflammatory bowel disease explained by immune-inflammatory, oxidative, and nitrosative stress; tryptophan catabolite; and gut–brain pathways. CNS Spectr. 2016;21(02):184–198. doi:10.1017/S1092852915000449

17. Joynt KE, Whellan DJ, O’Connor CM. Depression and cardiovascular disease: mechanisms of interaction. Biol Psychiatry. 2003;54(3):248–261. doi:10.1016/S0006-3223(03)00568-7

18. Penninx BW, Beekman AT, Honig A, et al. Depression and cardiac mortality: results from a community-based longitudinal study. Arch Gen Psychiatry. 2001;58(3):221–227. Available from: Accessed September 21, 2018.

19. Glassman AH. Depression and cardiovascular comorbidity. Dialogues Clin Neurosci. 2007;9(1):9–17. Available from: Accessed September 21, 2018.

20. Frasure-Smith N, Lesperance F. Depression and cardiac risk: present status and future directions. Heart. 2010;96(3):173–176. doi:10.1136/hrt.2009.186957

21. Zellweger MJ, Osterwalder RH, Langewitz W, Pfisterer ME. Coronary artery disease and depression. Eur Heart J. 2004;25(1):3–9. Available from: Accessed October 12, 2018.

22. Lett HS, Blumenthal JA, Babyak MA, et al. Depression as a risk factor for coronary artery disease: evidence, mechanisms, and treatment. Psychosom Med. 66(3):305–315. Available from: Accessed October 12, 2018.

23. Barefoot JC, Schroll M. Symptoms of depression, acute myocardial infarction, and total mortality in a community sample. Circulation. 1996;93(11):1976–1980. Available from: Accessed September 21, 2018.

24. Carney RM, Blumenthal JA, Stein PK, et al. Depression, heart rate variability, and acute myocardial infarction. Circulation. 2001. doi:10.1161/hc4201.097834

25. Freedland KE, Carney RM, Rich MW. Effect of depression on prognosis in heart failure. Heart Fail Clin. 2011;7(1):11–21. doi:10.1016/j.hfc.2010.08.003

26. Meng L, Chen D, Yang Y, Zheng Y, Hui R. Depression increases the risk of hypertension incidence. J Hypertens. 2012;30(5):842–851. doi:10.1097/HJH.0b013e32835080b7

27. Dhar AK, Barton DA. Depression and the link with cardiovascular disease. Front Psychiatry. 2016;7:33. doi:10.3389/fpsyt.2016.00033

28. Gehi A, Haas D, Pipkin S, Whooley MA. Depression and medication adherence in outpatients with coronary heart disease: findings from the heart and soul study. Arch Intern Med. 2005;165(21):2508–2513. doi:10.1001/archinte.165.21.2508

29. Kronish IM, Rieckmann N, Halm EA, et al. Persistent depression affects adherence to secondary prevention behaviors after acute coronary syndromes. J Gen Intern Med. 2006;21(11):1178–1183. doi:10.1111/j.1525-1497.2006.00586.x

30. Stapelberg NJC, Neumann DL, Shum DHK, McConnell H, Hamilton-Craig I. A topographical map of the causal network of mechanisms underlying the relationship between major depressive disorder and coronary heart disease. Aust New Zeal J Psychiatry. 2011;45(5):351–369. doi:10.3109/00048674.2011.570427

31. Meijer A, Conradi HJ, Bos EH, et al. Adjusted prognostic association of depression following myocardial infarction with mortality and cardiovascular events: individual patient data meta-analysis. Br J Psychiatry. 2013;203(02):90–102. doi:10.1192/bjp.bp.112.111195

32. Fiedorowicz JG, He J, Merikangas KR. The association between mood and anxiety disorders with vascular diseases and risk factors in a nationally representative sample. J Psychosom Res. 2011;70(2):145–154. doi:10.1016/j.jpsychores.2010.07.010

33. Glassman AH, Shapiro PA. Depression and the course of coronary artery disease. Am J Psychiatry. 1998;155(1):4–11. doi:10.1176/ajp.155.1.4

34. Fiedorowicz JG. Depression and cardiovascular disease: an update on how course of illness may influence risk. Curr Psychiatry Rep. 2014;16(10):492. doi:10.1007/s11920-014-0492-6

35. Abboud FM, Harwani SC, Chapleau MW. Autonomic neural regulation of the immune system: implications for hypertension and cardiovascular disease. Hypertens (Dallas, Tex 1979). 2012;59(4):755–762. doi:10.1161/HYPERTENSIONAHA.111.186833

36. Pizzi C, Manzoli L, Mancini S, Costa GM. Analysis of potential predictors of depression among coronary heart disease risk factors including heart rate variability, markers of inflammation, and endothelial function. Eur Heart J. 2008;29(9):1110–1117. doi:10.1093/eurheartj/ehn137

37. Howren MB, Lamkin DM, Suls J. Associations of depression with C-reactive protein, IL-1, and IL-6: a meta-analysis. Psychosom Med. 2009;71(2):171–186. doi:10.1097/PSY.0b013e3181907c1b

38. Fontoura PC, Pinto VLM, Matsuura C, et al. Defective nitric oxide-cyclic guanosine monophosphate signaling in patients with bipolar disorder: a potential role for platelet dysfunction. Psychosom Med. 2012;74(8):873–877. doi:10.1097/PSY.0b013e3182689460

39. Thayer JF, Lane RD. A model of neurovisceral integration in emotion regulation and dysregulation. J Affect Disord. 2000;61(3):201–216. Available from: Accessed October 10, 2018.

40. Damasio AR, Grabowski TJ, Bechara A, et al. Subcortical and cortical brain activity during the feeling of self-generated emotions. Nat Neurosci. 2000;3(10):1049–1056. doi:10.1038/79871

41. Benarroch EE. The central autonomic network: functional organization, dysfunction, and perspective. Mayo Clin Proc. 1993;68(10):988–1001. Available from: Accessed October 13, 2018.

42. Rauch SL, Shin LM, Phelps EA. neurocircuitry models of posttraumatic stress disorder and extinction: human neuroimaging research – past, present, and future. Biol Psychiatry. 2006;60(4):376–382. doi:10.1016/j.biopsych.2006.06.004

43. Quirk GJ, Garcia R, González-Lima F. Prefrontal mechanisms in extinction of conditioned fear. Biol Psychiatry. 2006;60(4):337–343. doi:10.1016/j.biopsych.2006.03.010

44. Thayer JF, Hansen AL, Saus-Rose E, Johnsen BH. Heart rate variability, prefrontal neural function, and cognitive performance: the neurovisceral integration perspective on self-regulation, adaptation, and health. Ann Behav Med. 2009;37(2):141–153. doi:10.1007/s12160-009-9101-z

45. Motzkin JC, Philippi CL, Wolf RC, Baskaya MK, Koenigs M. Ventromedial prefrontal cortex is critical for the regulation of amygdala activity in humans. Biol Psychiatry. 2015;77(3):276–284. doi:10.1016/j.biopsych.2014.02.014

46. Toyoda H, Li X-Y, Wu L-J, et al. Interplay of amygdala and cingulate plasticity in emotional fear. Neural Plast. 2011;2011:813749. doi:10.1155/2011/813749

47. Hamilton JP, Siemer M, Gotlib IH. Amygdala volume in major depressive disorder: a meta-analysis of magnetic resonance imaging studies. Mol Psychiatry. 2008;13(11):993–1000. doi:10.1038/mp.2008.57

48. Drevets WC, Price JL, Bardgett ME, Reich T, Todd RD, Raichle ME. Glucose metabolism in the amygdala in depression: relationship to diagnostic subtype and plasma cortisol levels. Pharmacol Biochem Behav. 2002;71(3):431–447. Available from: Accessed October 20, 2018.

49. Critchley HD, Wiens S, Rotshtein P, Öhman A, Dolan RJ. Neural systems supporting interoceptive awareness. Nat Neurosci. 2004;7(2):189–195. doi:10.1038/nn1176

50. Sliz D, Hayley S. Major depressive disorder and alterations in insular cortical activity: a review of current functional magnetic imaging research. Front Hum Neurosci. 2012;6:323. doi:10.3389/fnhum.2012.00323

51. Lee B-T, Cho SW, Khang HS, et al. The neural substrates of affective processing toward positive and negative affective pictures in patients with major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2007;31(7):1487–1492. doi:10.1016/j.pnpbp.2007.06.030

52. Nagai M, Hoshide S, Kario K. The insular cortex and cardiovascular system: a new insight into the brain-heart axis. J Am Soc Hypertens. 2010;4(4):174–182. doi:10.1016/j.jash.2010.05.001

53. Kollai M, Jokkel G, Bonyhay I, Tomcsanyi J, Naszlady A. Relation between baroreflex sensitivity and cardiac vagal tone in humans. Am J Physiol Circ Physiol. 1994;266(1):H21–H27. doi:10.1152/ajpheart.1994.266.1.H21

54. Shaffer F, McCraty R, Zerr CL. A healthy heart is not a metronome: an integrative review of the heart’s anatomy and heart rate variability. Front Psychol. 2014;5:1040. doi:10.3389/fpsyg.2014.01040

55. Lehrer P, Eddie D. Dynamic processes in regulation and some implications for biofeedback and biobehavioral interventions. Appl Psychophysiol Biofeedback. 2013;38(2):143–155. doi:10.1007/s10484-013-9217-6

56. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology. Heart rate variability: standards of measurement, physiological interpretation and clinical use. Circulation. 1996;93(5):1043–1065. Available from: Accessed October 14, 2018.

57. Goldberger JJ, Challapalli S, Tung R, Parker MA, Kadish AH. Relationship of heart rate variability to parasympathetic effect. Circulation. 2001;103(15):1977–1983. Available from: Accessed October 14, 2018.

58. Reynard A, Gevirtz R, Berlow R, Brown M, Boutelle K. Heart rate variability as a marker of self-regulation. Appl Psychophysiol Biofeedback. 2011;36(3):209–215. doi:10.1007/s10484-011-9162-1

59. Appelhans BM, Luecken LJ. Heart rate variability as an index of regulated emotional responding. Rev Gen Psychol. 2006;10(3):229–240. doi:10.1037/1089-2680.10.3.229

60. An E, Nolty A, Rensberger J, Hennig N, Amano S, Buckwalter J. B-65Heart rate variability as an index of stress resilience. Arch Clin Neuropsychol. 2016;31(6):637.3–637. doi:10.1093/arclin/acw043.140

61. Critchley HD, Garfinkel SN. Interactions between visceral afferent signaling and stimulus processing. Front Neurosci. 2015;9:286. doi:10.3389/fnins.2015.00286

62. Critchley HD, Harrison NA. Visceral influences on brain and behavior. Neuron. 2013;77(4):624–638. doi:10.1016/j.neuron.2013.02.008

63. McIntyre D, Kavussanu M, Ring C. Effects of arterial and cardiopulmonary baroreceptor activation on the upper limb nociceptive flexion reflex and electrocutaneous pain in humans. Pain. 2008;137(3):550–555. doi:10.1016/j.pain.2007.10.018

64. Edwards L, McIntyre D, Carroll D, Ring C, Martin U. The human nociceptive flexion reflex threshold is higher during systole than diastole. Psychophysiology. 2002;39(5):678–681. 10.1017.S0048577202011770

65. Gray MA, Beacher FD, Minati L, et al. Emotional appraisal is influenced by cardiac afferent information. Emotion. 2012;12(1):180–191. doi:10.1037/a0025083

66. Garfinkel SN, Minati L, Gray MA, Seth AK, Dolan RJ, Critchley HD. Fear from the heart: sensitivity to fear stimuli depends on individual heartbeats. J Neurosci. 2014;34(19):6573–6582. doi:10.1523/JNEUROSCI.3507-13.2014

67. Usui H, Nishida Y. The very low-frequency band of heart rate variability represents the slow recovery component after a mental stress task. PLoS One. 2017;12(8):e0182611. doi:10.1371/journal.pone.0182611

68. Bertinieri G, Di Rienzo M, Cavallazzi A, Ferrari AU, Pedotti A, Mancia G. Evaluation of baroreceptor reflex by blood pressure monitoring in unanesthetized cats. Am J Physiol Circ Physiol. 1988;254(2):H377–H383. doi:10.1152/ajpheart.1988.254.2.H377

69. La Rovere MT, Pinna GD, Raczak G. Baroreflex sensitivity: measurement and clinical implications. Ann Noninvasive Electrocardiol. 2008;13(2):191–207. doi:10.1111/j.1542-474X.2008.00219.x

70. Maestri R, Raczak G, Danilowicz-Szymanowicz L, et al. Reliability of heart rate variability measurements in patients with a history of myocardial infarction. Clin Sci. 2010;118:195–201. doi:10.1042/CS20090183

71. Schwartz PJ, Billman GE, Stone HL. Autonomic mechanisms in ventricular fibrillation induced by myocardial ischemia during exercise in dogs with healed myocardial infarction. An experimental preparation for sudden cardiac death. Circulation. 1984;69(4):790–800. Available from: Accessed October 14, 2018.

72. Kleiger RE, Miller JP, Bigger JT, Moss AJ. Decreased heart rate variability and its association with increased mortality after acute myocardial infarction. Am J Cardiol. 1987;59(4):256–262. Available from: Accessed October 14, 2018.

73. Singh JP, Larson MG, Tsuji H, Evans JC, O’Donnell CJ, Levy D. Reduced heart rate variability and new-onset hypertension: insights into pathogenesis of hypertension: the framingham heart study. Hypertens (Dallas, Tex 1979). 1998;32(2):293–297. Available from: Accessed October 14, 2018.

74. Nolan J, Batin PD, Andrews R, et al. Prospective study of heart rate variability and mortality in chronic heart failure: results of the United Kingdom heart failure evaluation and assessment of risk trial (UK-heart). Circulation. 1998;98(15):1510–1516. Available from: Accessed October 14, 2018.

75. Ponikowski P, Anker SD, Chua TP, et al. Depressed heart rate variability as an independent predictor of death in chronic congestive heart failure secondary to ischemic or idiopathic dilated cardiomyopathy. Am J Cardiol. 1997;79(12):1645–1650. Available from: Accessed October 14, 2018.

76. Mortara A, La Rovere MT, Pinna GD, et al. Arterial baroreflex modulation of heart rate in chronic heart failure: clinical and hemodynamic correlates and prognostic implications. Circulation. 1997;96(10):3450–3458. Available from: Accessed, 2018.

77. Bristow JD, Honour AJ, Pickering GW, Sleight P, Smyth HS. Diminished baroreflex sensitivity in high blood pressure. Circulation. 1969;39(1):48–54. Available from: Accessed October 14, 2018.

78. Mortara A, La Rovere MT, Pinna GD, et al. Depressed arterial baroreflex sensitivity and not reduced heart rate variability identifies patients with chronic heart failure and nonsustained ventricular tachycardia: the effect of high ventricular filling pressure. Am Heart J. 1997;134(5 Pt 1):879–888. Available from: Accessed October 14, 2018.

79. La Rovere MT, Bigger JT, Marcus FI, Mortara A, Schwartz PJ; ATRAMI (Autonomic Tone and Reflexes After Myocardial Infarction) Investigators. Baroreflex sensitivity and heart-rate variability in prediction of total cardiac mortality after myocardial infarction. Lancet (London, England). 1998;351(9101):478–484. Available from: Accessed October 14, 2018.

80. Robinson TG, Dawson SL, Eames PJ, Panerai RB, Potter JF. Cardiac baroreceptor sensitivity predicts long-term outcome after acute ischemic stroke. Stroke. 2003;34(3):705–712. doi:10.1161/01.STR.0000058493.94875.9F

81. Sgoifo A, Carnevali L, Pico Alfonso MA, Amore M. Autonomic dysfunction and heart rate variability in depression. Stress. 2015;18(3):343–352. doi:10.3109/10253890.2015.1045868

82. 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;67(11):1067–1074. doi:10.1016/j.biopsych.2009.12.012

83. Bassett D. A literature review of heart rate variability in depressive and bipolar disorders. Aust New Zeal J Psychiatry. 2016;50(6):511–519. doi:10.1177/0004867415622689

84. Bobo WV, Angleró GC, Jenkins G, Hall-Flavin DK, Weinshilboum R, Biernacka JM. Validation of the 17-item hamilton depression rating scale definition of response for adults with major depressive disorder using equipercentile linking to clinical global impression scale ratings: analysis of Pharmacogenomic Research Network Antidepressant Medication Pharmacogenomic Study (PGRN-AMPS) data. Hum Psychopharmacol. 2016;31(3):185–192. doi:10.1002/hup.2526

85. Yekehtaz H, Farokhnia M, Akhondzadeh S. Cardiovascular considerations in antidepressant therapy: an evidence-based review. J Tehran Heart Cent. 2013;8(4):169–176. Available from: Accessed October 20, 2018.

86. Shah A, Carreno FR, Frazer A. Therapeutic modalities for treatment resistant depression: focus on vagal nerve stimulation and ketamine. Clin Psychopharmacol Neurosci. 2014;12(2):83–93. doi:10.9758/cpn.2014.12.2.83

87. Mayberg HS, Lozano AM, Voon V, et al. Deep brain stimulation for treatment-resistant depression. Neuron. 2005;45(5):651–660. doi:10.1016/j.neuron.2005.02.014

88. Hilimire MR, Mayberg HS, Holtzheimer PE, et al. Effects of subcallosal cingulate deep brain stimulation on negative self-bias in patients with treatment-resistant depression. Brain Stimul. 2015;8(2):185–191. doi:10.1016/j.brs.2014.11.010

89. Gartlehner G, Wagner G, Matyas N, et al. Pharmacological and non-pharmacological treatments for major depressive disorder: review of systematic reviews. BMJ Open. 2017;7(6):e014912. doi:10.1136/bmjopen-2016-014912

90. Udupa K, Thirthalli J, Sathyaprabha TN, Kishore KR, Raju TR, Gangadhar BN. Differential actions of antidepressant treatments on cardiac autonomic alterations in depression: A prospective comparison. Asian J Psychiatr. 2011;4(2):100–106. doi:10.1016/j.ajp.2011.02.006

91. Raij T, Nummenmaa A, Marin M-F, et al. Prefrontal cortex stimulation enhances fear extinction memory in humans. Biol Psychiatry. 2018;84(2):129–137. doi:10.1016/j.biopsych.2017.10.022

92. Serafini G, Pompili M, Belvederi Murri M, et al. The effects of repetitive transcranial magnetic stimulation on cognitive performance in treatment-resistant depression. A systematic review. Neuropsychobiology. 2015;71(3):125–139. doi:10.1159/000381351

93. Vaschillo E, Lehrer P, Rishe N, Konstantinov M. Heart rate variability biofeedback as a method for assessing baroreflex function: a preliminary study of resonance in the cardiovascular system. Appl Psychophysiol Biofeedback. 2002;27(1):1–27. Available from: Accessed September 18, 2018.

94. Song H-S, Lehrer PM. The effects of specific respiratory rates on heart rate and heart rate variability. Appl Psychophysiol Biofeedback. 2003;28(1):13–23. Available from: Accessed October 20, 2018.

95. Vaschillo EG, Vaschillo B, Lehrer PM. Characteristics of resonance in heart rate variability stimulated by biofeedback. Appl Psychophysiol Biofeedback. 2006;31(2):129–142. doi:10.1007/s10484-006-9009-3

96. Lehrer PM, Gevirtz R. Heart rate variability biofeedback: how and why does it work? Front Psychol. 2014. doi:10.3389/fpsyg.2014.00756

97. Steffen PR, Austin T, DeBarros A, Brown T. The impact of resonance frequency breathing on measures of heart rate variability, blood pressure, and mood. Front Public Heal. 2017;5:222. doi:10.3389/fpubh.2017.00222

98. Lin G, Xiang Q, Fu X, et al. Heart rate variability biofeedback decreases blood pressure in prehypertensive subjects by improving autonomic function and baroreflex. J Altern Complement Med. 2012;18(2):143–152. doi:10.1089/acm.2010.0607

99. Chen S, Sun P, Wang S, Lin G, Wang T. Effects of heart rate variability biofeedback on cardiovascular responses and autonomic sympathovagal modulation following stressor tasks in prehypertensives. J Hum Hypertens. 2016;30(2):105–111. doi:10.1038/jhh.2015.27

100. Overhaus S, Rüddel H, Curio I, Mussgay L, Scholz OB. Biofeedback of baroreflex sensitivity in patients with mild essential hypertension. Int J Behav Med. 2003;10(1):66–78. doi:10.1207/S15327558IJBM1001_06. Available from: Accessed September 18, 2018.

101. Moravec CS. Biofeedback therapy in cardiovascular disease: rationale and research overview. Cleve Clin J Med. 2008;75(Suppl 2):S35–S38. doi:10.3949/ccjm.75.Suppl_2.S35. Available from: Accessed October 13, 2018.

102. Del Pozo JM, Gevirtz RN, Scher B, Guarneri E. Biofeedback treatment increases heart rate variability in patients with known coronary artery disease. Am Heart J. 2004;147(3):E11. doi:10.1016/j.ahj.2003.08.013

103. Moravec CS, McKee MG. Psychophysiologic remodeling of the failing human heart. Biofeedback. 2013;41(1):7–12. doi:10.5298/1081-5937-41.1.04

104. Luskin F, Reitz M, Newell K, Quinn TG, Haskell W. A controlled pilot study of stress management training of elderly patients with congestive heart failure. Prev Cardiol. 2002;5(4):168–174. doi:10.1111/j.1520.037X.2002.01029.x

105. MacKinnon S, Gevirtz R, McCraty R, Brown M. Utilizing heartbeat evoked potentials to identify cardiac regulation of vagal afferents during emotion and resonant breathing. Appl Psychophysiol Biofeedback. 2013;38(4):241–255. doi:10.1007/s10484-013-9226-5

106. Avery JA, Drevets WC, Moseman SE, Bodurka J, Barcalow JC, Simmons WK. Major depressive disorder is associated with abnormal interoceptive activity and functional connectivity in the insula. Biol Psychiatry. 2014;76(3):258–266. doi:10.1016/j.biopsych.2013.11.027

107. Terhaar J, Viola FC, Bär K-J, Debener S. Heartbeat evoked potentials mirror altered body perception in depressed patients. Clin Neurophysiol. 2012;123(10):1950–1957. doi:10.1016/J.CLINPH.2012.02.086

108. Lehrer PM, Vaschillo E, Vaschillo B. Resonant frequency biofeedback training to increase cardiac variability: rationale and manual for training. Appl Psychophysiol Biofeedback. 2000;25(3):177–191. doi:10.1023/A:1009554825745. Available from: Accessed September 18, 2018.

109. Lehrer P, Vaschillo B, Zucker T, et al. Protocol for heart rate variability biofeedback training. Biofeedback. 2013;41:98–109. doi:10.5298/1081-5937-41.3.08

110. Peira N, Fredrikson M, Pourtois G. Controlling the emotional heart: heart rate biofeedback improves cardiac control during emotional reactions. Int J Psychophysiol. 2014;91(3):225–231. doi:10.1016/J.IJPSYCHO.2013.12.008

111. Peira N, Pourtois G, Fredrikson M. Learned cardiac control with heart rate biofeedback transfers to emotional reactions. Gray M, ed. PLoS One. 2013;8(7):e70004. doi:10.1371/journal.pone.0070004

112. Goessl VC, Curtiss JE, Hofmann SG. The effect of heart rate variability biofeedback training on stress and anxiety: A meta-analysis. Psychol Med. 2017;47:2578–2586. doi:10.1017/S0033291717001003

113. Henriques G, Keffer S, Abrahamson C, Jeanne Horst S. Exploring the effectiveness of a computer-based heart rate variability biofeedback program in reducing anxiety in college students. Appl Psychophysiol Biofeedback. 2011;36(2):101–112. doi:10.1007/s10484-011-9151-4

114. McCraty R, Atkinson M, Lipsenthal L, Arguelles L. New hope for correctional officers: an innovative program for reducing stress and health risks. Appl Psychophysiol Biofeedback. 2009;34(4):251–272. doi:10.1007/s10484-009-9087-0

115. Jiménez Morgan S, Molina Mora JA. Effect of heart rate variability biofeedback on sport performance, a systematic review. Appl Psychophysiol Biofeedback. 2017;42(3):235–245. doi:10.1007/s10484-017-9364-2

116. Thurber MR, Bodenhamer-Davis E, Johnson M, Chesky K, Chandler CK. Effects of heart rate variability coherence biofeedback training and emotional management techniques to decrease music performance anxiety. Biofeedback. 2010;38(1):28–40. doi:10.5298/1081-5937-38.1.28

117. Gruzelier JH, Thompson T, Redding E, Brandt R, Steffert T. Application of alpha/theta neurofeedback and heart rate variability training to young contemporary dancers: state anxiety and creativity. Int J Psychophysiol. 2014;93:105–111. doi:10.1016/j.ijpsycho.2013.05.004

118. Herbell K. Reducing psychological stress in peripartum women with heart rate variability biofeedback: a systematic review. J Holist Nurs. 2018;089801011878303. doi:10.1177/0898010118783030

119. Kudo N, Shinohara H, Kodama H. Heart rate variability biofeedback intervention for reduction of psychological stress during the early postpartum period. Appl Psychophysiol Biofeedback. 2014;39(3–4):203–211. doi:10.1007/s10484-014-9259-4

120. Siepmann M, Hennig U-D, Siepmann T, et al. The effects of heart rate variability biofeedback in patients with preterm labour. Appl Psychophysiol Biofeedback. 2014;39(1):27–35. doi:10.1007/s10484-013-9238-1

121. McAusland L, Addington J. Biofeedback to treat anxiety in young people at clinical high risk for developing psychosis. Early Interv Psychiatry. 2018;12(4):694–701. doi:10.1111/eip.12368

122. Antelmi I, De Paula RS, Shinzato AR, Peres CA, Mansur AJ, Grupi CJ. Influence of age, gender, body mass index, and functional capacity on heart rate variability in a cohort of subjects without heart disease. Am J Cardiol. 2004;93(3):381–385. doi:10.1016/j.amjcard.2003.09.065

123. Hautala AJ, Mäkikallio TH, Kiviniemi A, et al. Cardiovascular autonomic function correlates with the response to aerobic training in healthy sedentary subjects. Am J Physiol Circ Physiol. 2003;285(4):H1747–H1752. doi:10.1152/ajpheart.00202.2003

124. Lehrer P, Vaschillo E, Lu S-E, et al. Heart rate variability biofeedback: effects of age on heart rate variability, baroreflex gain, and asthma. Chest. 2006;129(2):278–284. doi:10.1378/chest.129.2.278

125. Giardino ND, Chan L, Borson S. Combined heart rate variability and pulse oximetry biofeedback for chronic obstructive pulmonary disease: preliminary findings. Appl Psychophysiol Biofeedback. 2004;29(2):121–133. doi:10.1023/B:APBI.0000026638.64386.89. Available from: Accessed, 2018.

126. Hallman DM, Olsson EMG, von Schéele B, Melin L, Lyskov E. Effects of heart rate variability biofeedback in subjects with stress-related chronic neck pain: a pilot study. Appl Psychophysiol Biofeedback. 2011;36(2):71–80. doi:10.1007/s10484-011-9147-0

127. Katsamanis M, Lehrer PM, Escobar JI, Gara MA, Kotay A, Liu R. Psychophysiologic treatment for patients with medically unexplained symptoms: a randomized controlled trial. Psychosomatics. 2011;52(3):218–229. doi:10.1016/j.psym.2011.01.015

128. Tan G, Dao TK, Farmer L, Sutherland RJ, Gevirtz R. Heart Rate Variability (HRV) and Posttraumatic Stress Disorder (PTSD): a pilot study. Appl Psychophysiol Biofeedback. 2011;36(1):27–35. doi:10.1007/s10484-010-9141-y

129. Meule A, Freund R, Skirde AK, Vögele C, Kübler A. Heart rate variability biofeedback reduces food cravings in high food cravers. Appl Psychophysiol Biofeedback. 2012;37(4):241–251. doi:10.1007/s10484-012-9197-y

130. Eddie D, Vaschillo E, Vaschillo B, Lehrer P. Heart rate variability biofeedback: theoretical basis, delivery, and its potential for the treatment of substance use disorders. Addict Res Theory. 2015;23(4):266–272. doi:10.3109/16066359.2015.1011625

131. Eddie D, Kim C, Lehrer P, Deneke E, Bates ME. A pilot study of brief heart rate variability biofeedback to reduce craving in young adult men receiving inpatient treatment for substance use disorders. Appl Psychophysiol Biofeedback. 2014;39:181–192. doi:10.1007/s10484-014-9251-z

132. Penzlin AI, Siepmann T, Min-Woo Illigens B, Weidner K, Siepmann M. Heart rate variability biofeedback in patients with alcohol dependence: a randomized controlled study. Neuropsychiatr Dis Treat. 2015;11:2619. doi:10.2147/NDT.S84798

133. Penzlin AI, Barlinn K, Illigens BM-W, Weidner K, Siepmann M, Siepmann T. Effect of short-term heart rate variability biofeedback on long-term abstinence in alcohol dependent patients – a one-year follow-up. BMC Psychiatry. 2017;17(1):325. doi:10.1186/s12888-017-1480-2

134. Karavidas MK, Lehrer PM, Vaschillo E, et al. Preliminary results of an open label study of heart rate variability biofeedback for the treatment of major depression. Appl Psychophysiol Biofeedback. 2007;32(1):19–30. doi:10.1007/s10484-006-9029-z

135. Siepmann M, Aykac V, Unterdörfer J, Petrowski K, Mueck-Weymann M. A pilot study on the effects of heart rate variability biofeedback in patients with depression and in healthy subjects. Appl Psychophysiol Biofeedback. 2008;33:195–201. doi:10.1007/s10484-008-9064-z

136. Hartogs BM, Bartels-Velthuis AA, Van der Ploeg K, Bos EH. Heart rate variability biofeedback stress relief program for depression. Methods Inf Med. 2017;56(06):419–426. doi:10.3414/ME16-02-0033

137. Caldwell YT, Steffen PR. Adding HRV biofeedback to psychotherapy increases heart rate variability and improves the treatment of major depressive disorder. Int J Psychophysiol. 2018;131:96–101. doi:10.1016/j.ijpsycho.2018.01.001

138. Stapelberg NJ, Hamilton-Craig I, Neumann DL, Shum DH, McConnell H. Mind and heart: heart rate variability in major depressive disorder and coronary heart disease – a review and recommendations. Aust New Zeal J Psychiatry. 2012;46(10):946–957. doi:10.1177/0004867412444624

139. Lehrer P. How does heart rate variability biofeedback work? Resonance, the baroreflex, and other mechanisms. Biofeedback. 2013;41:26–31. doi:10.5298/1081-5937-41.1.02

140. Bassett D, Bear N, Nutt D, Hood S, Bassett S, Hans D. Reduced heart rate variability in remitted bipolar disorder and recurrent depression. Aust New Zeal J Psychiatry. 2016;50(8):793–804. doi:10.1177/0004867416652734

141. Rottenberg J, Chambers AS, Allen JJB, Manber R. Cardiac vagal control in the severity and course of depression: the importance of symptomatic heterogeneity. J Affect Disord. 2007;103(1–3):173–179. doi:10.1016/j.jad.2007.01.028

142. Hassett AL, Radvanski DC, Vaschillo EG, et al. A pilot study of the efficacy of heart rate variability (hrv) biofeedback in patients with fibromyalgia. Appl Psychophysiol Biofeedback. 2007;32(1):1–10. doi:10.1007/s10484-006-9028-0

143. Lin I-M, Ko J-M, Fan S-Y, Yen C-F. Heart rate variability and the efficacy of biofeedback in heroin users with depressive symptoms. Clin Psychopharmacol Neurosci. 2016;14(2):168–176. doi:10.9758/cpn.2016.14.2.168

144. Li X, Zhang T, Song L-P, et al. Effects of heart rate variability biofeedback therapy on patients with poststroke depression: a case study. Chin Med J. 2015;128(18):2542–2545. doi:10.4103/0366-6999.164986

145. Nolan RP, Kamath MV, Floras JS, et al. Heart rate variability biofeedback as a behavioral neurocardiac intervention to enhance vagal heart rate control. Am Heart J. 2005. doi:10.1016/j.ahj.2005.03.015

146. Patron E, Messerotti Benvenuti S, Favretto G, et al. Biofeedback assisted control of respiratory sinus arrhythmia as a biobehavioral intervention for depressive symptoms in patients after cardiac surgery: a preliminary study. Appl Psychophysiol Biofeedback. 2013;38(1):1–9. doi:10.1007/s10484-012-9202-5

147. Maurício M, Cânovas M HRV in smartphone for biofeedback application; 2011. Accessed September 14, 2018.

148. De Jonckheere J, Ibarissene I, Flocteil M, Logier R. A smartphone based cardiac coherence biofeedback system. In: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE; 2014: 4791–4794. doi:10.1109/EMBC.2014.6944695

149. Vasudev A, O’Brien JT, Tan MP, Parry SW, Thomas AJ. A study of orthostatic hypotension, heart rate variability and baroreflex sensitivity in late-life depression. J Affect Disord. 2011;131(1–3):374–378. doi:10.1016/j.jad.2010.11.001

150. Wang Y, Zhao X, O’Neil A, Turner A, Liu X, Berk M. Altered cardiac autonomic nervous function in depression. BMC Psychiatry. 2013;13(1):187. doi:10.1186/1471-244X-13-187

151. Johansson M, Ehnvall A, Friberg P, Myredal A. Arterial baroreflex dysfunction in major depressive disorder. Clin Auton Res. 2010;20(4):235–240. doi:10.1007/s10286-010-0053-y

152. Hughes JW, Dennis MF, Beckham JC. Baroreceptor sensitivity at rest and during stress in women with posttraumatic stress disorder or major depressive disorder. J Trauma Stress. 2007;20(5):667–676. doi:10.1002/jts.20285

153. Broadley AJM, Frenneaux MP, Moskvina V, Jones CJH, Korszun A. Baroreflex sensitivity is reduced in depression. Psychosom Med. 2005;67(4):648–651. doi:10.1097/01.psy.0000170829.91643.24

154. Moon E, Lee S-H, Kim D-H, Hwang B. Comparative study of heart rate variability in patients with schizophrenia, bipolar disorder, post-traumatic stress disorder, or major depressive disorder. Clin Psychopharmacol Neurosci. 2013;11(3):137–143. doi:10.9758/cpn.2013.11.3.137

155. Dauphinot V, Rouch I, Kossovsky MP, et al. Depressive symptoms and autonomic nervous system dysfunction in an elderly population-based study: the PROOF study. J Affect Disord. 2012;143(1–3):153–159. doi:10.1016/j.jad.2012.05.045

156. Chang H-A, Chang -C-C, Kuo TBJ, Huang S-Y. Distinguishing bipolar II depression from unipolar major depressive disorder: differences in heart rate variability. World J Biol Psychiatry. 2015;16(5):351–360. doi:10.3109/15622975.2015.1017606

157. Kemp AH, Brunoni AR, Santos IS, et al. Effects of depression, anxiety, comorbidity, and antidepressants on resting-state heart rate and its variability: an ELSA-Brasil cohort baseline study. Am J Psychiatry. 2014. doi:10.1176/appi.ajp.2014.13121605

158. Agelink M, Ullrich H, Baumann B, Strum S, Majewski T. Effects of reboxetine, a selective norepinephrine reuptake inhibitor, on sympathetic and parasympathetic outflow to the heart: preliminary data. Psychopharmacology (Berl). 2002;163(2):151–156. doi:10.1007/s00213-002-1146-7

159. Voss A, Boettger MK, Schulz S, Gross K, Bär KJ. Gender-dependent impact of major depression on autonomic cardiovascular modulation. Prog Neuropsychopharmacol Biol Psychiatry. 2011;35(4):1131–1138. doi:10.1016/j.pnpbp.2011.03.015

160. Terhardt J, Lederbogen F, Feuerhack A, et al. Heart rate variability during antidepressant treatment with venlafaxine and mirtazapine. Clin Neuropharmacol. 2013;36(6):198–202. doi:10.1097/WNF.0b013e3182a76fbb

161. Kikuchi M, Hanaoka A, Kidani T, et al. Heart rate variability in drug-naïve patients with panic disorder and major depressive disorder. Prog Neuropsychopharmacol Biol Psychiatry. 2009;33(8):1474–1478. doi:10.1016/j.pnpbp.2009.08.002

162. Brunoni AR, Kemp AH, Dantas EM, et al. Heart rate variability is a trait marker of major depressive disorder: evidence from the sertraline vs. electric current therapy to treat depression clinical study. Int J Neuropsychopharmacol. 2013;16(9):1937–1949. doi:10.1017/S1461145713000497

163. Hage B, Britton B, Daniels D, Heilman K, Porges SW, Halaris A. Low cardiac vagal tone index by heart rate variability differentiates bipolar from major depression. World J Biol Psychiatry. 2017;1–9. doi:10.1080/15622975.2017.1376113

164. Kemp AH, Quintana DS, Quinn CR, Hopkinson P, Harris AWF. Major depressive disorder with melancholia displays robust alterations in resting state heart rate and its variability: implications for future morbidity and mortality. Front Psychol. 2014;5:1387. doi:10.3389/fpsyg.2014.01387

165. Boettger S, Hoyer D, Falkenhahn K, Kaatz M, Yeragani VK, Bär K-J. Nonlinear broad band dynamics are less complex in major depression. Bipolar Disord. 2008;10(2):276–284. doi:10.1111/j.1399-5618.2007.00503.x

166. Ha JH, Park S, Yoon D, Kim B. Short-term heart rate variability in older patients with newly diagnosed depression. Psychiatry Res. 2015;226(2–3):484–488. doi:10.1016/j.psyc-hres.2015.02.005

167. Schulz S, Koschke M, Bär KJ, Voss A. The altered complexity of cardiovascular regulation in depressed patients. Physiol Meas. 2010;31(3):303–321. doi:10.1088/0967-3334/31/3/003

168. Bär K-J, Greiner W, Jochum T, Friedrich M, Wagner G, Sauer H. The influence of major depression and its treatment on heart rate variability and pupillary light reflex parameters. J Affect Disord. 2004;82(2):245–252. doi:10.1016/j.jad.2003.12.016

Creative Commons License This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License. By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms.

Download Article [PDF]