scholarly journals Resonance frequency is not always stable over time and could be related to the inter-beat interval

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Lluis Capdevila ◽  
Eva Parrado ◽  
Juan Ramos-Castro ◽  
Rafael Zapata-Lamana ◽  
Jaume F. Lalanza
Keyword(s):  
Heart Rate ◽  
Resonance Frequency ◽  
Breathing Rate ◽  
Lower Heart Rate ◽  
Sinus Arrhythmia ◽  
Heart Rate Variability Biofeedback ◽  
Stable Factor ◽  
Slow Breathing ◽  
Momentary Frequency ◽  
Cardiac Variability

AbstractHeart Rate Variability Biofeedback (HRVB) is based on breathing at an optimal rate (or resonance frequency, RF) corresponding to the respiratory sinus arrhythmia (RSA). Our aim is to check whether the RF is a stable factor and analyse the HRV parameters individually per each breathing rate, comparing it with free slow breathing. A sample of 21 participants were trained in a test–retest HRVB protocol. The results indicated that RF changed between Test and Retest sessions in 66.7% of participants. This instability could be related to the average of interbeat interval (IBI). HRV time domain parameters (SDNN and RMSSD) were significantly higher for RF than for other breathing rates, including 6 breath/min and free slow breathing. Free slow breathing showed a lower heart rate averages than RF and other slow breathing rates. Overall, our study suggests the relevance of assessing RF individually and before each HRVB session, because the maximum cardiovascular benefits in terms of increasing HRV were found only at RF. Thus, breathing at the individualized and momentary frequency of resonance increases cardiac variability.

Resonance breathing is associated with improvements in depression and anxiety symptoms during heart rate variability biofeedback sessions

2021 ◽  
Author(s):  
Adam Khan Pettitt ◽  
Benjamin W Nelson ◽  
Richard Gevirtz ◽  
Paul Lehrer ◽  
Kristian Ranta ◽  
...  
Keyword(s):  
Mental Health ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Resonance Frequency ◽  
Treatment Protocol ◽  
Anxiety Symptoms ◽  
Adjunctive Treatment ◽  
Depression And Anxiety ◽  
Heart Rate Variability Biofeedback ◽  
Item Scale

Heart rate variability (HRV) appears to be a transdiagnostic biomarker for health and disease. Although initial studies using HRV biofeedback (HRVB) to regulate HRV as a potential adjunctive treatment to gold-standard interventions seem promising, more research is needed to determine which aspects of HRVB training provide the most clinical benefits to those suffering from mental health symptoms. In the current study, we sought to investigate whether time spent in resonance, between-person differences in resonance frequency, and/or within-person resonance frequency trajectory across repeated HRVB sessions were related to changes in depression and/or anxiety symptoms during a 12-week digital mental health intervention that contains HRVB as part of the treatment protocol. We used a retrospective cohort study to examine these associations among 387 participants in the Meru Health Program. For depression, we found that average resonance time per HRVB session, but not total time in resonance, was significantly associated with decreased depression as measured by the Patient Health Questionnaire 9-item scale (PHQ-9) across treatment (b=-0.38, 95% CI [-0.76,-0.01], t(377)=-1.99, p=.047). For anxiety symptoms as measured by the Generalized Anxiety Disorder 7-item scale (GAD-7), we found neither association significant. Within-person effects were significant for both depression and anxiety, with steeper slopes of time spent in resonance significantly related to reductions in PHQ-9 and GAD-7 symptoms, respectively. Between-person effects were not significant for either depression or anxiety. Our results demonstrate that improvements in resonance efficiency over time in treatment, independent of how each participant starts, are related to reductions in depression and anxiety symptoms.

scholarly journals A Practical Guide to Resonance Frequency Assessment for Heart Rate Variability Biofeedback

2020 ◽  
Vol 14 ◽  
Author(s):  
Fred Shaffer ◽  
Zachary M. Meehan
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Resonance Frequency ◽  
Muscle Tension ◽  
Initial Assessment ◽  
Cardiorespiratory System ◽  
Frequency Model ◽  
Heart Rate Variability Biofeedback ◽  
Resonance Frequencies ◽  
Non Linear

Heart rate variability (HRV) represents fluctuations in the time intervals between successive heartbeats, which are termed interbeat intervals. HRV is an emergent property of complex cardiac-brain interactions and non-linear autonomic nervous system (ANS) processes. A healthy heart is not a metronome because it exhibits complex non-linear oscillations characterized by mathematical chaos. HRV biofeedback displays both heart rate and frequently, respiration, to individuals who can then adjust their physiology to improve affective, cognitive, and cardiovascular functioning. The central premise of the HRV biofeedback resonance frequency model is that the adult cardiorespiratory system has a fixed resonance frequency. Stimulation at rates near the resonance frequency produces large-amplitude blood pressure oscillations that can increase baroreflex sensitivity over time. The authors explain the rationale for the resonance frequency model and provide detailed instructions on how to monitor and assess the resonance frequency. They caution that patterns of physiological change must be compared across several breathing rates to evaluate candidate resonance frequencies. They describe how to fine-tune the resonance frequency following an initial assessment. Furthermore, the authors critically assess the minimum epochs required to measure key HRV indices, resonance frequency test-retest reliability, and whether rhythmic skeletal muscle tension can replace slow paced breathing in resonance frequency assessment.

Resonance Frequency Assessment: The Challenge of Standardizing Heart Rate Variability Biofeedback Research

Biofeedback ◽  
2020 ◽  
Vol 48 (1) ◽  
pp. 7-15 ◽  
Author(s):  
Fredric Shaffer
Keyword(s):  
Decision Making ◽  
Heart Rate ◽  
Resonance Frequency ◽  
Physiological Activity ◽  
Performance Outcomes ◽  
Decision Making Process ◽  
Heart Rate Variability Biofeedback ◽  
Rf Measurement ◽  
Measurement Protocol ◽  
Biofeedback Research

The resonance frequency (RF) is the rate at which a system, like the cardiovascular system, can be activated or stimulated for maximal variability. Precise RF measurement is needed to standardize training protocols to help researchers determine the importance of RF breathing in achieving clinical and optimal performance outcomes. Lehrer and colleagues have developed and standardized a psychometrically reliable RF measurement protocol that can facilitate training and replication. This article provides a detailed description of their protocol and explains the nuanced decision-making process involved in identifying the RF. The validity and reproducibility of results using this protocol depend on quality control in (a) confirming that individuals successfully follow a breathing pacer, and (b) manually removing artifacts from data records. While this protocol requires an electrocardiogram or photoplethysmograph sensor and a respirometer, professionals should consider the addition of autonomic, musculoskeletal, and respiratory measures to better understand the patterns of physiological activity produced by different breathing rates.

scholarly journals A computational physiology approach to personalized treatment models: the beneficial effects of slow breathing on the human cardiovascular system

2014 ◽  
Vol 307 (7) ◽  
pp. H1073-H1091 ◽  
Author(s):  
Maria Fonoberova ◽  
Igor Mezić ◽  
Jennifer F. Buckman ◽  
Vladimir A. Fonoberov ◽  
Adriana Mezić ◽  
...  
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Cardiovascular System ◽  
Empirical Support ◽  
System Level ◽  
Heart Period ◽  
Heart Rate Variability Biofeedback ◽  
Human Cardiovascular System ◽  
Slow Breathing

Heart rate variability biofeedback intervention involves slow breathing at a rate of ∼6 breaths/min (resonance breathing) to maximize respiratory and baroreflex effects on heart period oscillations. This intervention has wide-ranging clinical benefits and is gaining empirical support as an adjunct therapy for biobehavioral disorders, including asthma and depression. Yet, little is known about the system-level cardiovascular changes that occur during resonance breathing or the extent to which individuals differ in cardiovascular benefit. This study used a computational physiology approach to dynamically model the human cardiovascular system at rest and during resonance breathing. Noninvasive measurements of heart period, beat-to-beat systolic and diastolic blood pressure, and respiration period were obtained from 24 healthy young men and women. A model with respiration as input was parameterized to better understand how the cardiovascular processes that control variability in heart period and blood pressure change from rest to resonance breathing. The cost function used in model calibration corresponded to the difference between the experimental data and model outputs. A good match was observed between the data and model outputs (heart period, blood pressure, and corresponding power spectral densities). Significant improvements in several modeled cardiovascular functions (e.g., blood flow to internal organs, sensitivity of the sympathetic component of the baroreflex, ventricular elastance) were observed during resonance breathing. Individual differences in the magnitude and nature of these dynamic responses suggest that computational physiology may be clinically useful for tailoring heart rate variability biofeedback interventions for the needs of individual patients.

How Does Heart Rate Variability Biofeedback Work? Resonance, the Baroreflex, and Other Mechanisms

Biofeedback ◽  
2013 ◽  
Vol 41 (1) ◽  
pp. 26-31 ◽  
Author(s):  
Paul Lehrer
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Cardiovascular System ◽  
Vascular Tone ◽  
Emotional Reactivity ◽  
Clinical Applications ◽  
Direct Effects ◽  
Sinus Arrhythmia ◽  
Heart Rate Variability Biofeedback ◽  
Resonance Effects

Heart rate variability biofeedback is known to have multiple effects on the cardiovascular system, the respiratory system, and emotional reactivity. This paper reviews the origins of work on heart rate variability biofeedback, and mechanisms for its various effects, including direct effects on the baroreflex system and gas exchange efficiency, as well as indirect effects on emotional reactivity and possibly inflammatory activity. Resonance in the cardiovascular system is explained, as well as ways that heart rate variability biofeedback stimulates these resonance effects, through interactions between respiratory sinus arrhythmia and the baroreflex system. Relationships of these mechanisms to various clinical applications of heart rate variability biofeedback are explored, as are future extensions of biofeedback to the vascular tone baroreflex.

scholarly journals Anthropometric Determinants of Respiratory Sinus Arrhythmia in Children

2022 ◽  
Vol 19 (1) ◽  
pp. 566
Author(s):  
Paulina Lubocka ◽  
Robert Sabiniewicz ◽  
Klaudia Suligowska ◽  
Tomasz Zdrojewski
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Respiratory Sinus Arrhythmia ◽  
Overweight And Obesity ◽  
Clinical Settings ◽  
Healthy Children ◽  
Resting Heart Rate ◽  
Lower Heart Rate ◽  
Sinus Arrhythmia ◽  
School Aged Children

Background: The study was conducted to investigate the implications of anthropometry in school-aged children on the degree of respiratory sinus arrhythmia observed in clinical settings. Methods: In a cohort study, 626 healthy children (52% male) aged 10.8 ± 0.5 years attending primary school in a single town underwent a 12-lead electrocardiogram coupled with measurements of height, weight and blood pressure. Indices of respiratory sinus arrhythmia (pvRSA, RMSSD, RMSSDc) were derived from semi-automatic measurements of RR intervals. Height, weight, BMI, blood pressure as well as waist and hip circumferences were compared between subjects with rhythmic heart rate and respiratory sinus arrhythmia, and correlations between indices of sinus arrhythmia and anthropometry were investigated. Results: Respiratory sinus arrhythmia was recognized in 43% of the participants. Subjects with sinus arrhythmia had lower heart rate (p < 0.001), weight (p = 0.009), BMI (p = 0.005) and systolic (p = 0.018) and diastolic (p = 0.004) blood pressure. There were important inverse correlations of heart rate and indices of sinus arrhythmia (r = −0.52 for pvRSA and r = −0.58 for RMSSD), but not the anthropometry. Conclusion: Lower prevalence of respiratory sinus arrhythmia among children with overweight and obesity is a result of higher resting heart rate observed in this population.

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