Components of heart rate variability have attracted considerable attention in psychology and medicine and have become important dependent measures in psychophysiology and behavioral medicine. Quantification and interpretation of heart rate variability, however, remain complex issues and are fraught with pitfalls. The present report (a) examines the physiological origins and mechanisms of heart rate variability, (b) considers quantitative approaches to measurement, and (c) highlights important caveats in the interpretation of heart rate variability. Summary guidelines for research in this area are outlined, and suggestions and prospects for future developments are considered.

https://www.onlinelibrary.wiley.com/doi/epdf/10.1111/j.1469-8986.1997.tb02140.x

Heart rate variability: Origins, methods, and interpretive caveats

Heart rate variability (HRV) is a reliable reflection of the many physiological factors modulating the normal rhythm of the heart. In fact, they provide a powerful means of observing the interplay between the sympathetic and parasympathetic nervous systems. It shows that the structure generating the signal is not only simply linear, but also involves nonlinear contributions. Heart rate (HR) is a nonstationary signal; its variation may contain indicators of current disease, or warnings about impending cardiac diseases. The indicators may be present at all times or may occur at random-during certain intervals of the day. It is strenuous and time consuming to study and pinpoint abnormalities in voluminous data collected over several hours. Hence, HR variation analysis (instantaneous HR against time axis) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system. Computer based analytical tools for in-depth study of data over daylong intervals can be very useful in diagnostics. Therefore, the HRV signal parameters, extracted and analyzed using computers, are highly useful in diagnostics. In this paper, we have discussed the various applications of HRV and different linear, frequency domain, wavelet domain, nonlinear techniques used for the analysis of the HRV.

Heart rate variability: a review

The relationship of autonomic imbalance, heart rate variability and cardiovascular disease risk factors

Psychophysiological research integrating heart rate variability (HRV) has increased during the last two decades, particularly given the fact that HRV is able to index cardiac vagal tone. Vagal tone, which represents the activity of the parasympathetic system, is acknowledged to be linked with many phenomena relevant for psychophysiological research, including self-regulation at the cognitive, emotional, social, and health levels. The ease of HRV collection and measurement coupled with the fact it is relatively affordable, non-invasive and pain free makes it widely accessible to many researchers. This ease of access should not obscure the difficulty of interpretation of HRV findings that can be easily misconstrued, however this can be controlled to some extent through correct methodological processes. Standards of measurement were developed two decades ago by a Task Force within HRV research, and recent reviews updated several aspects of the Task Force paper. However, many methodological aspects related to HRV in psychophysiological research have to be considered if one aims to be able to draw sound conclusions, which makes it difficult to interpret findings and to compare results across laboratories. Those methodological issues have mainly been discussed in separate outlets, making difficult to get a grasp on them, and thus this paper aims to address this issue. It will help to provide psychophysiological researchers with recommendations and practical advice concerning experimental designs, data analysis, and data reporting. This will ensure that researchers starting a project with HRV and cardiac vagal tone are well informed regarding methodological considerations in order for their findings to contribute to knowledge advancement in their field.

/pdf/heart-rate-variability-and-cardiac-vagal-tone-in-3ty5nxgoqb.pdf

Heart Rate Variability and Cardiac Vagal Tone in Psychophysiological Research - Recommendations for Experiment Planning, Data Analysis, and Data Reporting.

Given the importance of the autonomic nervous system to cardiovascular health, it is not surprising that there is and has been great interest in measurements of human sympathetic and vagus nerve traffic as tools that might inform physiological and pathophysiological mechanisms. Pagani and coworkers1 advanced the provocative notion that the instantaneous balance between sympathetic and vagal nerve activities can be captured by a single number, obtained by dividing RR-interval spectral power centered at ≈0.1 Hz by spectral power centered at higher, primarily respiratory frequencies. This ratio, or sympathovagal balance, has been embraced with great enthusiasm2 because it offers new possibilities for understanding dynamic, critically important autonomic interrelations in humans by the use of totally noninvasive, unobtrusive means.3

The broad bases for this mathematical treatment are as follows: (1) 0.1-Hz RR intervals are importantly mediated by fluctuations of sympathetic nerve activity; (2) higher-frequency RR-interval rhythms are mediated almost exclusively by fluctuations of vagal-cardiac nerve activity; and (3) physiological interventions tend to provoke reciprocal changes of sympathetic and vagal neural outflows. Sympathovagal balance, the ratio of these periodicities, is taken to reflect the balance between the opposing neural mechanisms. This review examines the physiological foundations of sympathovagal balance.

The ECG is recorded with the subject in a steady state (when rhythms are stationary) for a period sufficiently long to define events occurring over frequencies of interest. RR-interval spectral power is calculated from this series of intervals with an autoregressive algorithm, which yields center frequencies and absolute power of component fluctuations, based on a model whose order (the number of parameters) is selected automatically to minimize Akaike’s information criterion statistic.4 (The statistical uncertainty and consequences of the automatic selection of the autoregressive model have not been defined fully; however, it is clear that the model order importantly determines both …

Sympathovagal Balance A Critical Appraisal

The correlations of 11 indexes of heart rate variability were examined with pharmacologically determined cardiac vagal tone in 15 normal subjects at supine rest. After sympathetic influences by intravenous propranolol were eliminated, RR interval variability was measured for 10 minutes under controlled respiration (0.25 Hz), and cardiac vagal tone was determined as the decrease in mean RR interval following complete vagal blockade with atropine. Time domain indexes (standard deviation, coefficient of variance and mean successive difference) correlated strongly with vagal tone (r = 0.87, 0.81 and 0.92, respectively; p less than 0.001 for all). The same was true for frequency domain indexes for the high-frequency (0.25 Hz) component calculated both by autoregressive spectrum analysis (square root of power and coefficient of component variance) and by fast Fourier transform (mean amplitude) (r = 0.91, 0.85 and 0.86, respectively; p less than 0.0001 for all). However, frequency domain indexes for the low-frequency spectral component (0.03 to 0.15 Hz) correlated less strongly (r = 0.69, 0.55 and 0.70, respectively), and the fraction of power [power/(total power greater than 0.03 Hz)] of both components showed no correlation. Principal component analysis showed that the first 6 indexes with strong correlations contained solely the first principal component closely related to vagal tone, whereas the remaining 5 indexes also contained the second component unrelated to vagal tone. These results indicate that most of the time and frequency domain analyses in use provides an accurate and common measure of cardiac vagal tone at rest.

Accuracy of assessment of cardiac vagal tone by heart rate variability in normal subjects.

The short- and long-term effects of cigarette smoking on autonomic cardiac regulation were investigated by power spectral analysis of heart rate variability under controlled respiration (15/min). The short-term effects were examined in 9 smokers without evidence of cardiopulmonary disorders after an overnight abstinence from smoking. The heart rate spectral component reflecting the respiratory sinus arrhythmia (0.25 Hz), a quantitative index of vagal cardiac control, decreased 3 minutes after smoking 1 cigarette (p = 0.0061) and the component reflecting Mayer wave sinus arrhythmia (0.04 to 0.15 Hz), which includes sympathetically mediated activity, increased after 10 to 17 minutes (p = 0.0124). The long-term effects were examined in 81 normal subjects comprising 25 nonsmokers, 31 moderate (1 to 24 cigarettes/day) smokers and 25 heavy (greater than 25 cigarettes/day) smokers after an overnight abstinence. Although the magnitude of the Mayer wave component was unaffected by the smoking status, the respiratory component in the supine position was smaller in the young (less than or equal to 30 years) heavy smokers than in the young nonsmokers or moderate smokers (p = 0.0078). Also, postural changes in the components, a decrease in the respiratory component and an increase in the Mayer wave component with standing, were observed in the nonsmokers but not in the heavy smokers. These results suggest that smoking causes an acute and transient decrease in vagal cardiac control, and that heavy smoking causes long-term reduction in vagal cardiac control in young people and blunted postural responses in autonomic cardiac regulation.

Short- and long-term effects of cigarette smoking on heart rate variability.

Method for spectral analysis of heart rate variability (HRV), and physiological characteristics of their spectral components are discussed. Respiratory component has a liner relationship with cardiac parasympathetic activity. Other component ranging around 0.1Hz is related to Mayer wave of arterial blood pressure. They provide a quantitative index of autonomic nervous function.

https://www.jstage.jst.go.jp/article/biophys1961/28/4/28_4_198/_pdf

Yosaku Watanabe

Papers

Accuracy of assessment of cardiac vagal tone by heart rate variability in normal subjects.

Short- and long-term effects of cigarette smoking on heart rate variability.

Spectral component of heart rate variability as an index of autonomic nervous function.

Evaluation of control mechanism in upright standing posture under a load

Estimation of Intensity of Human Emotion using Facia Expression and Physiological Data