Heart Rate Variability Anatomy and Physiology

Heart rate variability (HRV) is generated by the interaction of multiple regulatory mechanisms that operate on different time scales. This article examines the regulation of the heart, the meaning of HRV, Thayer and Lane's neurovisceral integration model, the sources of HRV, HRV frequency and time domain measurements, Porges's polyvagal theory, and resonance frequency breathing. The medical implications of HRV biofeedback for cardiovascular rehabilitation and inflammatory disorders are considered.

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Resting high frequency heart rate variability is not associated with the recognition of emotional facial expressions in healthy human adults

10.1101/077784 ◽

2016 ◽

Author(s):

Brice Beffara ◽

Nicolas Vermeulen ◽

Martial Mermillod

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Facial Expressions ◽

High Frequency ◽

Vagal Activity ◽

Emotional Facial Expressions ◽

Polyvagal Theory ◽

Healthy Human ◽

Integration Model ◽

Human Adults

This study explores whether the myelinated vagal connection between the heart and the brain is involved in emotion recognition. The Polyvagal theory postulates that the activity of the myelinated vagus nerve underlies socio-emotional skills. It has been proposed that the perception of emotions could be one of this skills dependent on heart-brain interactions. However, this assumption was differently supported by diverging results suggesting that it could be related to confounded factors. In the current study, we recorded the resting state vagal activity (reflected by High Frequency Heart Rate Variability, HF-HRV) of 77 (68 suitable for analysis) healthy human adults and measured their ability to identify dynamic emotional facial expressions. Results show that HF-HRV is not related to the recognition of emotional facial expressions in healthy human adults. We discuss this result in the frameworks of the polyvagal theory and the neurovisceral integration model.

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Is Low Heart Rate Variability Associated with Emotional Dysregulation, Psychopathological Dimensions, and Prefrontal Dysfunctions? An Integrative View

Journal of Personalized Medicine ◽

10.3390/jpm11090872 ◽

2021 ◽

Vol 11 (9) ◽

pp. 872

Author(s):

Lorena Angela Cattaneo ◽

Anna Chiara Franquillo ◽

Alessandro Grecucci ◽

Laura Beccia ◽

Vincenzo Caretti ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Low Frequency ◽

Emotional Dysregulation ◽

Theoretical Ground ◽

Polyvagal Theory ◽

Integration Model ◽

Theoretical Perspectives ◽

Integrative View ◽

Starting Point

Several studies have suggested a correlation between heart rate variability (HRV), emotion regulation (ER), psychopathological conditions, and cognitive functions in the past two decades. Specifically, recent data seem to support the hypothesis that low-frequency heart rate variability (LF-HRV), an index of sympathetic cardiac control, correlates with worse executive performances, worse ER, and specific psychopathological dimensions. The present work aims to review the previous findings on these topics and integrate them from two main cornerstones of this perspective: Porges’ Polyvagal Theory and Thayer and Lane’s Neurovisceral Integration Model, which are necessary to understand these associations better. For this reason, based on these two approaches, we point out that low HRV is associated with emotional dysregulation, worse cognitive performance, and transversal psychopathological conditions. We report studies that underline the importance of considering the heart-brain relation in order to shed light on the necessity to implement psychophysiology into a broader perspective on emotions, mental health, and good cognitive functioning. This integration is beneficial not only as a theoretical ground from which to start for further research studies but as a starting point for new theoretical perspectives useful in clinical practice.

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Novel, robust indexes for time-domain analysis of heart rate variability

Proceedings of 18th Annual International Conference of the IEEE Engineering in Medicine and Biology Society ◽

10.1109/iembs.1996.647600 ◽

2002 ◽

Cited By ~ 1

Author(s):

M.A. Garcia-Gonzalez ◽

R. Pallas-Areny

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Time Domain ◽

Time Domain Analysis ◽

Domain Analysis

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Heart rate variability: Analysis of time-domain indices in patients with chronic Chagas disease before and after an exercise program

Revista Portuguesa de Cardiologia (English Edition) ◽

10.1016/j.repce.2013.03.003 ◽

2013 ◽

Vol 32 (3) ◽

pp. 219-227 ◽

Cited By ~ 1

Author(s):

Marcus Vinicius Amaral da Silva Souza ◽

Carla Cristiane Santos Soares ◽

Juliana Rega de Oliveira ◽

Cláudia Rosa de Oliveira ◽

Paloma Hargreaves Fialho ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Chagas Disease ◽

Time Domain ◽

Exercise Program ◽

Heart Rate Variability Analysis ◽

Variability Analysis ◽

Before And After ◽

Chronic Chagas Disease

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Identification of Obstructive Sleep Apnea Syndrome by Ambulatory Electrocardiography: Clinical Evaluation of Time-domain and Frequency-domain Analyses of Heart Rate Variability in Chinese Patients

Cell Biochemistry and Biophysics ◽

10.1007/s12013-010-9128-6 ◽

2010 ◽

Vol 59 (3) ◽

pp. 165-170 ◽

Cited By ~ 9

Author(s):

Sun Jianling ◽

Li Xiaoying ◽

Guo Jihong ◽

Han Fang ◽

Zhang Haicheng

Keyword(s):

Heart Rate ◽

Obstructive Sleep Apnea ◽

Heart Rate Variability ◽

Sleep Apnea ◽

Time Domain ◽

Sleep Apnea Syndrome ◽

Chinese Patients ◽

Ambulatory Electrocardiography ◽

Obstructive Sleep ◽

Apnea Syndrome

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Effect of short-term mental stress on time- domain indices of heart rate variability in obese individuals – A case- control study

Biomedicine ◽

10.51248/.v41i2.795 ◽

2021 ◽

Vol 41 (2) ◽

pp. 274-277

Author(s):

Priya S.A. ◽

R. Rajalakshmi

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Neuronal Activity ◽

Time Domain ◽

Mental Stress ◽

Mental Arithmetic ◽

High Body Mass Index ◽

Control Group ◽

Stress Task ◽

The Individual

Introduction and Aim: Mental stress may impact dramatically on dynamic autonomic control on heart. Many studies have demonstrated association of high body mass index (BMI) with greater risk for cardiovascular disease with disturbance in autonomic neuronal activity. Analysis of Heart rate variability (HRV)during acute mental stress assesses the autonomic status of the individual. Hence, we aimed to study the effect of acute mental stress on time domain measures in obese adults. Materials and Methods:Sixty male volunteers of 30 each in study group (obese individuals) and control group (non-obese individuals) were recruited for the study. A basal recording of ECG in lead II was done on all the individuals. Then they underwent mental arithmetic stress task for 5 minutes during which again ECG was recorded. The change in time domain measures of HRV during rest and stress task was analyzed and compared between both the groups. Results: Analysis of time domain measures of HRV revealed a statistically significant increase (p ? 0.001) in mean heart rate in both obese and non-obese individuals, while rMSSD(root mean square differences of successive RR interval) and SDNN (standard deviation of all NN intervals) showed a statistically significant (p? 0.001) decrease in obese individuals and non-obese individuals did not show any statistically significant change during the mental stress task. Conclusion: In response to acute mental stress there was increased heart rate in both the groups. But the autonomic neuronal activity differed by way of sympathetic dominance in non-obese individuals and parasympathetic withdrawal in obese individuals.

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Time Domain Analysis of Heart Rate Variability: An Approach for Cardiac Stress Assessment

2021 4th Biennial International Conference on Nascent Technologies in Engineering (ICNTE) ◽

10.1109/icnte51185.2021.9487677 ◽

2021 ◽

Author(s):

Ulka Shirole ◽

Manjusha Joshi

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Time Domain ◽

Time Domain Analysis ◽

Domain Analysis ◽

Stress Assessment ◽

Cardiac Stress

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Trends in Heart Rate and Heart Rate Variability during Pregnancy and Three Months Postpartum: Continuous Monitoring in a Free-Living Context (Preprint)

10.2196/preprints.33458 ◽

2021 ◽

Author(s):

Fatemeh Sarhaddi ◽

Iman Azimi ◽

Anna Axelin ◽

Hannakaisa Niela-Vilen ◽

Pasi Liljeberg ◽

...

Keyword(s):

Heart Rate ◽

Heart Rate Variability ◽

Pregnant Women ◽

Time Domain ◽

Second Trimester ◽

Third Trimester ◽

Non Invasive ◽

The Third ◽

Invasive Method ◽

Frequency Power

BACKGROUND Heart rate variability (HRV) is a non-invasive method reflecting autonomic nervous system (ANS) regulations. Altered HRV is associated with adverse mental or physical health complications. ANS also has a central role in physiological adaption during pregnancy causing normal changes in HRV. OBJECTIVE Assessing trends in heart rate (HR) and HRV parameters as a non-invasive method for remote maternal health monitoring during pregnancy and three months postpartum. METHODS Fifty-eight pregnant women were monitored using an Internet-of-Things (IoT)-based remote monitoring system during pregnancy and 3-months postpartum. Pregnant women were asked to continuously wear Gear sport smartwatch to monitor their HR and HRV. In addition, a cross-platform mobile application was utilized for collecting pregnancy-related information. The trends of HR and HRV parameters were extracted using reliable data. We also analyzed the trends of normalized HRV parameters based on HR to remove the effect of HR changes on HRV trends. Finally, we exploited hierarchical linear mixed models to analyze the trends of HR, HRV, and normalized HRV parameters. RESULTS HR increased significantly during the second trimester (P<.001) and decreased significantly during the third trimester (P<.01). Time-domain HRV parameters, average normal interbeat intervals (AVNN), standard deviation of normal interbeat intervals (SDNN), root mean square of the successive difference of normal interbeat intervals (RMSSD), normalized SDNN (nSDNN), and normalized RMSSD (nRMSSD) decreased significantly during the second trimester (P<.001) then increased significantly during the third trimester (P<.01). Some of the frequency domain parameters, low-frequency power (LF), high-frequency power (HF), and normalized HF (nHF) decreased significantly during the second trimester (P<.01), and HF increased significantly during the third trimester (P<.01). In the postpartum period, nRMSSD decreased (P<.05), and the LF to HF ratio (LF/HF) increased significantly (P<.01). CONCLUSIONS Our study showed that HR increased and HRV parameters decreased as the pregnancy proceeded, and the values returned to normal after the delivery. Moreover, our results show that HR started to decrease while time-domain HRV parameters and HF started to increase during the third trimester. Our results also demonstrate the possibility of continuous HRV monitoring in everyday life settings.

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