Does motor activity during psychophysiological paradigms confound the quantification and interpretation of heart rate and heart rate variability measures in young children?

Respiratory sinus arrhythmia (RSA), heart period, and motor activity were monitored in preschoolers during a variety of tasks varying in required movement. The data analyses indicate: (1) that when activity increases during tasks, there are synchronous decreases in heart period and RSA; (2) that correlations between changes in RSA and heart period are related to activity only during exercise when there is a major demand for increased metabolic resources; and (3) that the covariation among the variables within each condition is low except during exercise. These findings suggest that the slight increases in motor activity (i.e., hand movements) often required in attention demanding psychophysiological protocols are not related to RSA and heart period responses. However, when tasks necessitate large increases in motor activity (e.g., exercise), the decreases in heart period and RSA are related to the change in motor activity.     

Correlation among Poincare´plot indexes and time and frequency domain measures of heart rate variability

Primary objective: In order to corroborate the reported performance advantage of Poincar´eplot indexes as autonomic activity markers, the correlation among these indexes and those computed from the time and frequency domains were obtained. Methods and procedures: Starting from the RR series derived from the ECG of 21 healthy volunteers during five manoeuvres, longitudinal (L), transverse (T) axis, and autocorrelation (r) from Poincar´eplots, rMSSD and standard deviation (SD) in the temporal domain, and frequency domain indexes were computed. Main outcomes and results: Poincar´e plot indexes were correlated in a better way with the time indexes, rather than the spectral measures. A strong correlation (0.997) between L and SD was observed, while an underlying mathematical relationship was established for T vs rMSSD. Conclusions: Poincaré plot indexes may be considered as equivalent or surrogates of the temporal ones, and they do not have a better performance as autonomic markers.     

Correlation among Poincaré plot indexes and time and frequency domain measures of heart rate variability.

PRIMARY OBJECTIVE: In order to corroborate the rported performance advantage of Poincaré plot indexes as autonomic activity markers, the correlation among these indexes and those computed from the time and frequency domains were obtained. METHODS AND PROCEDURES: Starting from the RR series derived from the ECG of 21 healthy volunteers during five manoeuvres, longitudinal (L), transverse (T) axis, and autocorrelation (r) from Poincaré plots, rMSSD and standard deviation (SD) in the temporal domain, and frequency domain indexes were computed. MAIN OUTCOMES AND RESULTS: Poincaré plot indexes were correlated in a better way with the time indexes, rather than the spectral measures. A strong correlation (0.997) between L and SD was observed, while an underlying mathematical relationship was established for T vs rMSSD. CONCLUSIONS: Poincaré plot indexes may be considered as equivalent or surrogates of the temporal ones, and they do not have a better performance as autonomic markers.     

Quantitative Poincaré plot analysis of heart rate variability: effect of endurance training

The aim of the study was to evaluate the effectiveness of the Poincaré plot analysis of heart rate variability (HRV) in observing endurance training-induced changes. Four 10-min manoeuvres were performed (supine lying, standing, steady state exercising and subsequent recovery) by eight control subjects before and after a short-term endurance training and by eight subjects trained for at least 3 years. HRV was assessed by traditional time- and frequency-domain indexes, in parallel with the Poincaré plot analysis. In the latter each R-R interval is plotted as a function of the previous one, and the standard deviations of the instantaneous and long-term R-R interval variability are calculated. In our subjects, the Poincaré scatter grams became gradually narrower from supine to exercising, with progressive parasympathetic withdrawal. Short- and long-term endurance training led to higher aerobic power (p<0.05) and ventilatory threshold shifted towards higher power output (p<0.05). All HRV evaluation methods showed that HRV values were higher after training both during supine lying and standing (p<0.05). The Poincaré scatter grams were wider in the trained state. Standard deviations of the Poincaré plot were significantly correlated with the main parameters of the time- and frequency-domain analyses, especially concerning the parasympathetic indicators. These results suggested that Poincaré plot parameters as well as the "width" of the scatter gram could be considered as surrogates of time- and frequency-domain analysis to assess training-induced changes in HRV.     

Musculoskeletal overuse injuries and heart rate variability: Is there a link?

Accurate detection and prevention of overuse musculoskeletal injuries is limited by the nature of somatic tissue injury. In the pathogenesis of overuse injuries, it is well recognized that an abnormal inflammatory response occurs within somatic tissue before pain is perceived which can disrupt the normal remodeling process and lead to subsequent degeneration. Current overuse injury prevention methods focused on biomechanical faults or performance standards lack the sensitivity needed to identify the status of tissue injury or repair. Recent evidence has revealed an apparent increase in the prevalence and impact of overuse musculoskeletal injuries in athletics. When compared to acute injuries, overuse injuries have a potentially greater negative impact on athletes’ overall health burden. Further, return to sport rehabilitation following overuse injury is complicated by the fact that the absence of pain does not equate to complete physiological healing of the injured tissue. Together, this highlights the need for exercise monitoring and injury prevention methods which incorporate assessment of somatic tissue response to loading. One system primarily involved in the activation of pathways and neuromediators responsible for somatic tissue repair is the autonomic nervous system (ANS). Although not completely understood, emerging research supports the critical importance of peripheral ANS activity in the health and repair of somatic tissue injury. Due to its significant contributions to cardiac function, ANS activity can be measured indirectly with heart rate monitoring. Heart rate variability (HRV) is one index of ANS activity that has been used to investigate the relationship between athletes’ physiological response to accumulating training load. Research findings indicated that HRV may provide a reflection of ANS homeostasis, or the body’s stress-recovery status. This noninvasive marker of the body’s primary driver of recovery has the potential to incorporate important and as yet unmonitored physiological mechanisms involved in overuse injury development. We hypothesize that abnormal somatic tissue response to accumulating microtrauma may modulate ANS activity at the level of HRV. Exploring the link between HRV modulation and somatic tissue injury has the potential to reveal the putative role of ANS homeostasis on overuse musculoskeletal injury development.     

Automated detection of perinatal hypoxia using time–frequency-based heart rate variability features

Perinatal hypoxia is a cause of cerebral injury in foetuses and neonates. Detection of foetal hypoxia during labour based on the pattern recognition of heart rate signals suffers from high observer variability and low specificity. We describe a new automated hypoxia detection method using time–frequency analysis of heart rate variability (HRV) signals. This approach uses features extracted from the instantaneous frequency and instantaneous amplitude of HRV signal components as well as features based on matrix decomposition of the signals’ time–frequency distributions using singular value decomposition and non-negative matrix factorization. The classification between hypoxia and non-hypoxia data is performed using a support vector machine classifier. The proposed method is tested on a dataset obtained from a newborn piglet model with a controlled hypoxic insult. The chosen HRV features show strong performance compared to conventional spectral features and other existing methods of hypoxia detection with a sensitivity 93.3 %, specificity 98.3 % and accuracy 95.8 %. The high predictive value of this approach to detecting hypoxia is a substantial step towards developing a more accurate and reliable hypoxia detection method for use in human foetal monitoring.     

Effect of β-adrenoblockers on heart rate variability in awake and narcotized rats

In narcotized rats, β-adrenoceptor blockers changed all parameters of heart rate variability indicating up-regulation of parasympathetic activity and down-regulation of the sympathetic one. In immobilized awake rats, the temporal and geometrical parameters varied similarly, while spectral analysis indicated possible activation of other neurohumoral mechanisms against the background of β-blocker treatment. __________ Translated from Byulleten’ Eksperimental’noi Biologii i Meditsiny, Vol. 144, No. 10, pp. 372–264, October, 2007     

Spectral analysis of heart rate variability with the autoregressive method: What model order to choose?

This work assessed the influence of the autoregressive model order (ARMO) on the spectral analysis of the heart rate variability (HRV). A sample of 68 R-R series obtained from digital ECG records of young healthy adults in the supine position was used. Normalized spectral indexes for each ARMO were compared by Friedman test followed by the Dunn's procedure and statistical significance was set at P<0.05. The results showed that the AR method using orders from 9 to 25 produces normalized spectral parameters statistically similar and, hence, the algorithms commonly employed to estimate optimum order are not mandatory in this case.     

Estimation of maximal heart rate using the relationship between heart rate variability and exercise intensity in 40–67 years old men

Large interindividual variation in maximal heart rate (HR_max) may not be accounted for by age alone. In order to evaluate a novel method in the prediction of HR_max, this study examined the profile of HR variability (HRV) during exercise in 40–67 years old men (n = 74). R–R intervals were recorded during supine rest and during a graded exercise test by cycle ergometry until exhaustion. A third-degree polynomial function was fitted to the HRV data recorded during exercise to represent the HRV profile of each subject. The instantaneous beat-to-beat R–R interval variability (SD1), high (HF) and low frequency power decreased between all consecutive exercise intensities (P < 0.033). The relationship between HR_max and a variable illustrating the declining rate of HF (HR_HF50%) was stronger (r = 0.50, P < 0.001) than between HR_max and age (r = −0.36, P < 0.01). The regression analysis showed that a more accurate estimation of HR_max was attained when HRV was used in the equation in addition to age: HR_max = 160.633–0.603(age) + 0.441(HR_HF50%) (SEE = 9.8 bpm vs. 11.6 bpm in the equation based on age alone). The decline of HRV during incremental exercise seems to be useful for accurate estimation of maximal heart rate.     

Should heart rate variability be “corrected” for heart rate? Biological,quantitative, and interpretive considerations

Metrics of heart period variability are widely used in the behavioral and biomedical sciences, although somewhat confusingly labeled as heart rate variability (HRV). Despite their wide use, HRV metrics are usually analyzed and interpreted without reference to prevailing levels of cardiac chronotropic state (i.e., mean heart rate or mean heart period). This isolated treatment of HRV metrics is nontrivial. All HRV metrics routinely used in the literature exhibit a known and positive relationship with the mean duration of the interval between two beats (heart period): as the heart period increases, so does its variability. This raises the question of whether HRV metrics should be “corrected” for the mean heart period (or its inverse, the heart rate). Here, we outline biological, quantitative, and interpretive issues engendered by this question. We provide arguments that HRV is neither uniformly nor simply a surrogate for heart period. We also identify knowledge gaps that remain to be satisfactorily addressed with respect to assumptions underlying existing HRV correction approaches. In doing so, we aim to stimulate further progress toward the rigorous use and disciplined interpretation of HRV. We close with provisional guidance on HRV reporting that acknowledges the complex interplay between the mean and variability of the heart period.     

Effort—reward imbalance,heart rate,and heart rate variability: the cardiovascular risk in young finns study

Background: Work stress indicated by effort—reward imbalance is hypothesized to cause autonomic arousal, which, if prolonged or frequent, could contribute to cardiovascular pathology. However, only limited empirical evidence on this mechanism is available. Purpose: This study examined associations between effort-reward imbalance, heart rate (HR), and heart rate variability (HRV). Method: The participants were 457 women and 406 men (mean age 32.3 years) derived from the population-based Young Finns Study. Effort—reward imbalance was defined as the ratio between effort and reward, higher efforts compared to rewards indicating greater imbalance. Results: In age-adjusted regression models, higher effort-reward imbalance was associated with lower HRV, and lower reward was associated with higher HR among women. These associations were not attenuated after additional adjustments for demographic characteristics and coronary risk factors. No significant associations of effort—reward imbalance or its components with HR and HRV were found in men. Conclusion: Our finding of lower HRV and higher HR in young healthy women with high effort—reward imbalance and low rewards provides evidence of a potential mechanism that may link effort-reward imbalance to the development of coronary heart disease (CHD) in women.     

Does cardiac reactivity in the laboratory predict ambulatory heart rate? Baseline counts

Cardiovascular reactivity to laboratory stress might predict cardiovascular load in everyday life. However, previous research throws doubt on this hypothesis. This study examined associations between heart rate (HR) to a public speaking task and ambulatory HR throughout a day. Electrocardiogram, bodily movement, and psychosocial variables (affect, context) were recorded in 111 individuals. Ambulatory HR was positively associated with both positive and negative affect. Baseline HR in the laboratory significantly predicted ambulatory HR, but HR reactivity did not. The interaction of momentary negative affect and cardiac reactivity in the laboratory was also not significant. However, a significant interaction of baseline HR and reactivity indicated that, when baseline was high, there was a positive relation between HR reactivity and ambulatory HR. Findings suggest that baseline has to be considered when aiming to predict cardiovascular load in everyday life.     

Recovery of heart rate variability after treadmill exercise analyzed by lagged Poincaré plot and spectral characteristics

The aim of this study was to analyze the recovery of heart rate variability (HRV) after treadmill exercise and to investigate the autonomic nervous system response after exercise. Frequency domain indices, i.e., LF(ms²), HF(ms²), LF(n.u.), HF(n.u.) and LF/HF, and lagged Poincaré plot width (SD1 _m ) and length (SD2 _m ) were introduced for comparison between the baseline period (Pre-E) before treadmill running and two periods after treadmill running (Post-E1 and Post-E2). The correlations between lagged Poincaré plot indices and frequency domain indices were applied to reveal the long-range correlation between linear and nonlinear indices during the recovery of HRV. The results suggested entirely attenuated autonomic nervous activity to the heart following the treadmill exercise. After the treadmill running, the sympathetic nerves achieved dominance and the parasympathetic activity was suppressed, which lasted for more than 4 min. The correlation coefficients between lagged Poincaré plot indices and spectral power indices could separate not only Pre-E and two sessions after the treadmill running, but also the two sessions in recovery periods, i.e., Post-E1 and Post-E2. Lagged Poincaré plot as an innovative nonlinear method showed a better performance over linear frequency domain analysis and conventional nonlinear Poincaré plot.     

Can arterial elasticity be estimated from heart rate variability response to paced 0.066 Hz sighing?

Arterial elasticity is an important indicator of risk for cardiovascular disease (CVD). It is influenced by both gradual vessel wall damage due to aging and disease and vascular tone that responds, at the moment, to system loading. Measuring changes in arterial elasticity are critical to early detection of CVD but can be time and resource intensive. This study proposes and tests a new method to approximate arterial elasticity from heart rate variability (HRV). ECG and pulse were simultaneously recording in 71 young healthy adults during three rhythmical sighing tasks paced at 0.02, 0.033, and 0.066 Hz. We evaluated arterial elasticity by measuring the reaction of pulse transit time (PTT) and RRI to each task specifically at the pacing frequency. The goal of the study was to describe our method, ground the methodology in current theory and mechanisms, and scientifically justify and validate this method by assessing differences in arterial elasticity in groups of healthy adults who differed in drinking behaviors. The amplitude PTT and HR oscillation responses at the pacing frequency were significantly correlated only when sighing was paced at 0.066 Hz. Both amplitudes also significantly correlated with power in the very low-frequency range of the baseline HRV spectrum. Abnormalities in these measures were observed among binge drinking healthy adults compared to non-drinkers and social drinkers. These preliminary results support using the HRV response to paced 0.066 Hz sighing as a correlate of arterial elasticity and warrant further study.