Heart Period Variability Research Articles

Impact of surgical aortic valve replacement and transcatheter aortic valve implantation on cardiovascular and cerebrovascular controls: A pilot study.

Surgical aortic valve replacement (SAVR) and transcatheter aortic valve implantation (TAVI) are options in severe aortic valve stenosis (AVS). Cardiovascular (CV) and cerebrovascular (CBV) control markers, derived from variability of heart period, systolic arterial pressure, mean cerebral blood velocity and mean arterial pressure, were acquired in 19 AVS patients (age: 76.8 ± 3.1 yrs, eight males) scheduled for SAVR and in 19 AVS patients (age: 79.9 + 6.5 yrs, 11 males) scheduled for TAVI before (PRE) and after intervention (POST, <7 days). Left ventricular function was preserved in both groups. Patients were studied at supine resting (REST) and during active standing (STAND). We found that: (i) both SAVR and TAVI groups featured a weak pre-procedure CV control; (ii) TAVI ensured better CV control; (iii) cerebral autoregulation was working in PRE in both SAVR and TAVI groups; (iv) SAVR and TAVI had no impact on the CBV control; (v) regardless of group, CV and CBV control markers were not influenced by STAND in POST. Even though the post-procedure preservation of both CV and CBV controls in TAVI group might lead to privilege this procedure in patients at higher risk, the missing response to STAND suggests that this advantage could be insignificant.

Testing dynamic correlations and nonlinearity in bivariate time series through information measures and surrogate data analysis.

The increasing availability of time series data depicting the evolution of physical system properties has prompted the development of methods focused on extracting insights into the system behavior over time, discerning whether it stems from deterministic or stochastic dynamical systems. Surrogate data testing plays a crucial role in this process by facilitating robust statistical assessments. This ensures that the observed results are not mere occurrences by chance, but genuinely reflect the inherent characteristics of the underlying system. The initial process involves formulating a null hypothesis, which is tested using surrogate data in cases where assumptions about the underlying distributions are absent. A discriminating statistic is then computed for both the original data and each surrogate data set. Significantly deviating values between the original data and the surrogate data ensemble lead to the rejection of the null hypothesis. In this work, we present various surrogate methods designed to assess specific statistical properties in random processes. Specifically, we introduce methods for evaluating the presence of autodependencies and nonlinear dynamics within individual processes, using Information Storage as a discriminating statistic. Additionally, methods are introduced for detecting coupling and nonlinearities in bivariate processes, employing the Mutual Information Rate for this purpose. The surrogate methods introduced are first tested through simulations involving univariate and bivariate processes exhibiting both linear and nonlinear dynamics. Then, they are applied to physiological time series of Heart Period (RR intervals) and respiratory flow (RESP) variability measured during spontaneous and paced breathing. Simulations demonstrated that the proposed methods effectively identify essential dynamical features of stochastic systems. The real data application showed that paced breathing, at low breathing rate, increases the predictability of the individual dynamics of RR and RESP and dampens nonlinearity in their coupled dynamics.

On the validity of the state space correspondence strategy based on k-nearest neighbor cross-predictability in assessing directionality in stochastic systems: Application to cardiorespiratory coupling estimation.

We tested the validity of the state space correspondence (SSC) strategy based on k-nearest neighbor cross-predictability (KNNCP) to assess the directionality of coupling in stochastic nonlinear bivariate autoregressive (NBAR) processes. The approach was applied to assess closed-loop cardiorespiratory interactions between heart period (HP) variability and respiration (R) during a controlled respiration (CR) protocol in 19 healthy humans (aged from 27 to 35 yrs, 11 females) and during active standing (STAND) in 25 athletes (aged from 20 to 40 yrs, all men) and 25 non-athletes (aged from 20 to 40 yrs, all men). Over simulated NBAR processes, we found that (i) the SSC approach can detect the correct causal relationship as the direction leads to better KNNCP from the past of the driver to the future state of the target and (ii) simulations suggest that the ability of the method is preserved in any condition of complexity of the interacting series. Over CR and STAND protocols, we found that (a) slowing the breathing rate increases the strength of the causal relationship in both temporal directions in a balanced modality; (b) STAND is more powerful in modulating the coupling strength on the pathway from HP to R; (c) regardless of protocol and experimental condition, the strength of the link from HP to R is stronger than that from R to HP; (d) significant causal relationships in both temporal directions are found regardless of the level of complexity of HP variability and R. The SSC strategy is useful to disentangle closed-loop cardiorespiratory interactions.

Autonomic Function and Baroreflex Control in COVID-19 Patients Admitted to the Intensive Care Unit.

Background: Autonomic function and baroreflex control might influence the survival rate of coronavirus disease 2019 (COVID-19) patients admitted to the intensive care unit (ICU) compared to respiratory failure patients without COVID-19 (non-COVID-19). This study describes physiological control mechanisms in critically ill COVID-19 patients admitted to the ICU in comparison to non-COVID-19 individuals with the aim of improving stratification of mortality risk. Methods: We evaluated autonomic and baroreflex control markers extracted from heart period (HP) and systolic arterial pressure (SAP) variability acquired at rest in the supine position (REST) and during a modified head-up tilt (MHUT) in 17 COVID-19 patients (age: 63 ± 10 years, 14 men) and 33 non-COVID-19 patients (age: 60 ± 12 years, 23 men) during their ICU stays. Patients were categorized as survivors (SURVs) or non-survivors (non-SURVs). Results: We found that COVID-19 and non-COVID-19 populations exhibited similar vagal and sympathetic control markers; however, non-COVID-19 individuals featured a smaller baroreflex sensitivity and an unexpected reduction in the HP-SAP association during the MHUT compared to the COVID-19 group. Nevertheless, none of the markers of the autonomic and baroreflex functions could distinguish SURVs from non-SURVs in either population. Conclusions: We concluded that COVID-19 patients exhibited a more preserved baroreflex control compared to non-COVID-19 individuals, even though this information is ineffective in stratifying mortality risk.

The degree of engagement of cardiac and sympathetic arms of the baroreflex does not depend on the absolute value and sign of arterial pressure variations

Objective. The percentages of cardiac and sympathetic baroreflex patterns detected via baroreflex sequence (SEQ) technique from spontaneous variability of heart period (HP) and systolic arterial pressure (SAP) and of muscle nerve sympathetic activity (MSNA) burst rate and diastolic arterial pressure (DAP) are utilized to assess the level of the baroreflex engagement. The cardiac baroreflex patterns can be distinguished in those featuring both HP and SAP increases (cSEQ++) and decreases (cSEQ−−), while the sympathetic baroreflex patterns in those featuring a MSNA burst rate decrease and a DAP increase (sSEQ+−) and vice versa (sSEQ−+). The present study aims to assess the modifications of the involvement of the cardiac and sympathetic arms of the baroreflex with age and postural stimulus intensity. Approach. We monitored the percentages of cSEQ++ (%cSEQ++) and cSEQ−− (%cSEQ−−) in 100 healthy subjects (age: 21–70 years, 54 males, 46 females), divided into five sex-balanced groups consisting of 20 subjects in each decade at rest in supine position and during active standing (STAND). We evaluated %cSEQ++, %cSEQ−−, and the percentages of sSEQ+− (%sSEQ+−) and sSEQ−+ (%sSEQ−+) in 12 young healthy subjects (age 23 ± 2 years, 3 females, 9 males) undergoing incremental head-up tilt. Main results. We found that: (i) %cSEQ++ and %cSEQ−− decreased with age and increased with STAND and postural stimulus intensity; (ii) %sSEQ+− and %sSEQ−+ augmented with postural challenge magnitude; (iii) the level of cardiac and sympathetic baroreflex engagement did not depend on either the absolute value of arterial pressure or the direction of its changes. Significance. This study stresses the limited ability of the cardiac and sympathetic arms of the baroreflex in controlling absolute arterial pressure values and the equivalent ability of both positive and negative arterial pressure changes in soliciting them.

Assessing cardiorespiratory interactions via lagged joint symbolic dynamics during spontaneous and controlled breathing.

Introduction: Joint symbolic analysis (JSA) can be utilized to describe interactions between time series while accounting for time scales and nonlinear features. JSA is based on the computation of the rate of occurrence of joint patterns built after symbolization. Lagged JSA (LJSA) is obtained from the more classical JSA by introducing a delay/lead between patterns built over the two series and combined to form the joint scheme, thus monitoring coordinated patterns at different lags. Methods: In the present study, we applied LJSA for the assessment of cardiorespiratory coupling (CRC) from heart period (HP) variability and respiratory activity (R) in 19 healthy subjects (age: 27-35years; 8 males, 11 females) during spontaneous breathing (SB) and controlled breathing (CB). The R rate of CB was selected to be indistinguishable from that of SB, namely, 15 breaths·minute-1 (CB15), or slower than SB, namely, 10 breaths·minute-1 (CB10), but in both cases, very rapid interactions between heart rate and R were known to be present. The ability of the LJSA approach to follow variations of the coupling strength was tested over a unidirectionally or bidirectionally coupled stochastic process and using surrogate data to test the null hypothesis of uncoupling. Results: We found that: i) the analysis of surrogate data proved that HP and R were significantly coupled in any experimental condition, and coupling was not more likely to occur at a specific time lag; ii) CB10 reduced CRC strength at the fastest time scales while increasing that at intermediate time scales, thus leaving the overall CRC strength unvaried; iii) despite exhibiting similar R rates and respiratory sinus arrhythmia, SB and CB15 induced different cardiorespiratory interactions; iv) no dominant temporal scheme was observed with relevant contributions of HP patterns either leading or lagging R. Discussion: LJSA is a useful methodology to explore HP-R dynamic interactions while accounting for time shifts and scales.

Decomposing the Mutual Information Rate of Heart Period and Respiration Variability Series to Assess Cardiorespiratory Interactions.

Heart rate variability results from the coupled activity of the cardiovascular and cardiorespiratory systems, which have their own internal regulation mechanisms but also interact with each other and with the autonomic nervous system to maintain homeostasis. In this work, the assessment of these physiological mechanisms is carried out decomposing the Mutual Information Rate (MIR), an information-theoretic measure of the interdependence between coupled processes, into terms of entropy rate or conditional mutual information related respectively to complexity and causality measures. These measures are computed using a non-parametric approach based on nearest-neighbors. The proposed framework is first tested on simulated autoregressive processes and then applied to experimental data consisting of heart period and respiratory time series measured in healthy subjects monitored at rest and during head-up tilt. Our results evidence that MIR decomposition is able to highlight the interdependence of short-term physiological mechanisms of cardiorespiratory interactions during postural stress.

Concomitant evaluation of cardiovascular and cerebrovascular controls via Geweke spectral causality to assess the propensity to postural syncope

The evaluation of propensity to postural syncope necessitates the concomitant characterization of the cardiovascular and cerebrovascular controls and a method capable of disentangling closed loop relationships and decomposing causal links in the frequency domain. We applied Geweke spectral causality (GSC) to assess cardiovascular control from heart period and systolic arterial pressure variability and cerebrovascular regulation from mean arterial pressure and mean cerebral blood velocity variability in 13 control subjects and 13 individuals prone to develop orthostatic syncope. Analysis was made at rest in supine position and during head-up tilt at 60°, well before observing presyncope signs. Two different linear model structures were compared, namely bivariate autoregressive and bivariate dynamic adjustment classes. We found that (i) GSC markers did not depend on the model structure; (ii) the concomitant assessment of cardiovascular and cerebrovascular controls was useful for a deeper comprehension of postural disturbances; (iii) orthostatic syncope appeared to be favored by the loss of a coordinated behavior between the baroreflex feedback and mechanical feedforward pathway in the frequency band typical of the baroreflex functioning during the postural challenge, and by a weak cerebral autoregulation as revealed by the increased strength of the pressure-to-flow link in the respiratory band. GSC applied to spontaneous cardiovascular and cerebrovascular oscillations is a promising tool for describing and monitoring disturbances associated with posture modification.Graphical

Anticipatory cardiac deceleration estimates cognitive performance in virtual reality beyond tonic heart period and heart period variability

Anticipatory cardiac deceleration is the lengthening of heart period before an expected event. It appears to reflect preparation that supports rapid action. The current study sought to bolster anticipatory deceleration as a practical and unique estimator of performance efficiency. To this end, we examined relationships between deceleration and virtual reality performance under low and high time pressure. Importantly, we investigated whether deceleration separately estimates performance beyond basal heart period and basal high-frequency heart rate variability (other vagally influenced metrics related to cognition). Thirty participants completed an immersive virtual reality (VR) cognitive performance task across six longitudinal sessions. Anticipatory deceleration and basal heart period/heart period variability were quantified from electrocardiography collected during pre-task anticipatory countdowns and baseline periods, respectively. At the between-person level, we found that greater anticipatory declaration was related to superior accuracy and faster response times (RT). The relation between deceleration and accuracy was stronger under high relative to low time pressure, when good performance requires greater efficiency. Findings for heart period and heart period variability largely converge with the prior literature, but importantly, were statistically separate from deceleration effects on performance. Lastly, deceleration effects were detected using anticipatory periods that are more practical (shorter and more intermittent) than those typically employed. Taken together, findings suggest that anticipatory deceleration is a unique and practical correlate of cognitive-motor efficiency apart from heart period and heart period variability in virtual reality.

Evaluation of cardiovascular and cerebrovascular control mechanisms in postural orthostatic tachycardia syndrome via conditional transfer entropy: the impact of the respiratory signal type

Objective. Closed loop cardiovascular (CV) and cerebrovascular (CBV) variability interactions are assessed via transfer entropy (TE) from systolic arterial pressure (SAP) to heart period (HP) and vice versa and from mean arterial pressure (MAP) to mean cerebral blood velocity (MCBv) and vice versa. This analysis is exploited to assess the efficiency of baroreflex and cerebral autoregulation. This study aims at characterizing CV and CBV controls in postural orthostatic tachycardiac syndrome (POTS) subjects experiencing exaggerated sympathetic response during orthostatic challenge via unconditional TE and TE conditioned on respiratory activity (R). Approach. In 18 healthy controls (age: 28 ± 13 yrs; 5 males, 13 females) and 15 POTS individuals (age: 29 ± 11 yrs; 3 males, 12 females) we acquired beat-to-beat variability of HP, SAP, MAP and MCBv and two R signals, namely respiratory chest movement (RCM) and capnogram (CAP). Recordings were made at sitting rest and during active standing (STAND). TE was computed via vector autoregressive approach. Main results. We found that: (i) when assessing CV interactions, the increase of the TE from SAP to HP during STAND, indicating baroreflex activation, is detected solely when conditioning on RCM; (ii) when assessing CBV interactions, the impact of R on the TE computation is negligible; (iii) POTS shows baroreflex impairment during STAND; (iv) POTS exhibits a normal CBV response to STAND. Significance. TE is useful for detecting the impairment of specific regulatory mechanisms in POTS. Moreover, using different R signals highlights the sensitivity of CV and CBV controls to specific R aspects.

Model-based spectral causality of cardiovascular variability interactions during head-down tilt

Objective. Cardiovascular control mechanisms are commonly studied during baroreceptor unloading induced by head-up tilt. Conversely, the effect of a baroreceptor loading induced by head-down tilt (HDT) is less studied especially when the stimulus is of moderate intensity and using model-based spectral causality markers. Thus, this study computes model-based causality markers in the frequency domain derived via causal squared coherence and Geweke spectral causality approach from heart period (HP) and systolic arterial pressure (SAP) variability series. Approach. We recorded HP and SAP variability series in 12 healthy men (age: from 41 to 71 yrs, median: 57 yrs) during HDT at −25°. The approaches are compared by considering two different bivariate model structures, namely the autoregressive and dynamic adjustment models. Markers are computed in traditional frequency bands utilized in cardiovascular control analysis, namely the low frequency (LF, from 0.04 to 0.15 Hz) and high frequency (HF, from 0.15 to 0.4 Hz) bands. Main results. We found that: (i) the two spectral causality metrics are deterministically related but spectral causality markers exhibit different discriminative ability; (ii) HDT reduces the involvement of the baroreflex in regulating HP-SAP variability interactions in the LF band, while leaving unmodified the action of mechanical feedforward mechanisms in both LF and HF bands; (iii) this conclusion does not depend on the model structure. Significance. We conclude that HDT can be utilized to reduce the impact of baroreflex and to study the contribution of regulatory mechanisms different from baroreflex to the complexity of cardiovascular control in humans.

Spectral decomposition of cerebrovascular and cardiovascular interactions in patients prone to postural syncope and healthy controls

We present a framework for the linear parametric analysis of pairwise interactions in bivariate time series in the time and frequency domains, which allows the evaluation of total, causal and instantaneous interactions and connects time- and frequency-domain measures. The framework is applied to physiological time series to investigate the cerebrovascular regulation from the variability of mean cerebral blood flow velocity (CBFV) and mean arterial pressure (MAP), and the cardiovascular regulation from the variability of heart period (HP) and systolic arterial pressure (SAP). We analyze time series acquired at rest and during the early and late phase of head-up tilt in subjects developing orthostatic syncope in response to prolonged postural stress, and in healthy controls. The spectral measures of total, causal and instantaneous coupling between HP and SAP, and between MAP and CBFV, are averaged in the low-frequency band of the spectrum to focus on specific rhythms, and over all frequencies to get time-domain measures. The analysis of cardiovascular interactions indicates that postural stress induces baroreflex involvement, and its prolongation induces baroreflex dysregulation in syncope subjects. The analysis of cerebrovascular interactions indicates that the postural stress enhances the total coupling between MAP and CBFV, and challenges cerebral autoregulation in syncope subjects, while the strong sympathetic activation elicited by prolonged postural stress in healthy controls may determine an increased coupling from CBFV to MAP during late tilt. These results document that the combination of time-domain and spectral measures allows us to obtain an integrated view of cardiovascular and cerebrovascular regulation in healthy and diseased subjects.

Improvement of Sympathovagal Balance by Regular Exercise May Counteract the Ageing Process. A Study by the Analysis of QT Variability.

QT interval (QT) variability analysis provides pathophysiological and prognostic information utilized in cardiac and non-cardiac diseases, complementary to those obtained from the analysis of heart period (HP) variability. An increased QT variability has been associated to a higher risk for cardiac events and poorest prognosis. Autonomic cardiovascular adaptation to internal and external challenges, such those occurring in athletes exposed to high levels of physical stress and in ageing could also be deepen by analyzing QT variability, searching for early prognostic signatures. The aim of the study was to analyze the QT variability and cardiac control complexity in a group of middle-aged half-marathon runners at baseline (B) and at a 10-year follow-up (FU). We found that the overall QT variability decreased at FU, despite the inescapable increase in age (52.3 ± 8.0 years at FU). This change was accompanied by an increase of the HP variability complexity without changes of the QT variability complexity. Of notice, over the years, the group of athletes maintained their regular physical activity by switching to a moderate intensity rather than strenuous. In conclusion, regular and moderate exercise over the years was beneficial for this group of athletes, as reflected by the decreased overall QT variability that is known to be associated to lower cardiovascular risk. The concomitant enhanced cardiac control complexity also suggests a trend opposite to what usually occurs with ageing, resulting in a more flexible cardiac control, typical of younger people.

Dynamic cerebrovascular autoregulation in patients prone to postural syncope: Comparison of techniques assessing the autoregulation index from spontaneous variability series.

Three approaches to the assessment of cerebrovascular autoregulation (CA) via the computation of the autoregulation index (ARI) from spontaneous variability of mean arterial pressure (MAP) and mean cerebral blood flow velocity (MCBFV) were applied: 1) a time domain method (TDM); 2) a nonparametric method (nonPM); 3) a parametric method (PM). Performances were tested over matched and surrogate unmatched pairs. Data were analyzed at supine resting (REST) and during the early phase of 60° head-up tilt (TILT) in 13 subjects with previous history of postural syncope (SYNC, age: 28±9yrs.; 5 males) and 13 control individuals (noSYNC, age: 27±8yrs.; 5 males). Analysis was completed by computing autonomic markers from heart period (HP) and systolic arterial pressure (SAP) variability series via spectral approach. HP and SAP spectral indexes suggested that noSYNC and SYNC groups exhibited different autonomic responses to TILT. ARI analysis indicated that: i) all methods have a sufficient statistical power to separate matched from unmatched pairs with the exception of nonPM applied to impulse response; ii) ARI estimates derived from different methods might be uncorrelated and, even when correlated, might exhibit a significant bias; iii) orthostatic stressor did not induce any evident ARI change in either noSYNC or SYNC individuals; iv) this conclusion held regardless of the method. Methods for the ARI estimation from spontaneous variability provide different ARIs but none indicate that noSYNC and SYNC subjects have different dynamic component of CA.

A New Framework for the Time- and Frequency-Domain Assessment of High-Order Interactions in Networks of Random Processes

While the standard network description of complex systems is based on quantifying the link between pairs of system units, higher-order interactions (HOIs) involving three or more units often play a major role in governing the collective network behavior. This work introduces a new approach to quantify pairwise and HOIs for multivariate rhythmic processes interacting across multiple time scales. We define the so-called O-information rate (OIR) as a new metric to assess HOIs for multivariate time series, and present a framework to decompose the OIR into measures quantifying Granger-causal and instantaneous influences, as well as to expand all measures in the frequency domain. The framework exploits the spectral representation of vector autoregressive and state space models to assess the synergistic and redundant interaction among groups of processes, both in specific bands of interest and in the time domain after whole-band integration. Validation of the framework on simulated networks illustrates how the spectral OIR can highlight redundant and synergistic HOIs emerging at specific frequencies, which cannot be detected using time-domain measures. The applications to physiological networks described by heart period, arterial pressure and respiration variability measured in healthy subjects during a protocol of paced breathing, and to brain networks described by electrocorticographic signals acquired in an animal experiment during anesthesia, document the capability of our approach to identify informational circuits relevant to well-defined cardiovascular oscillations and brain rhythms and related to specific physiological mechanisms involving autonomic control and altered consciousness. The proposed framework allows a hierarchically-organized evaluation of time- and frequency-domain interactions in dynamic networks mapped by multivariate time series, and its high flexibility and scalability make it suitable for the investigation of networks beyond pairwise interactions in neuroscience, physiology and many other fields.

Gender Differences in Cardiac Chronotropic Control: Implications for Heart Rate Variability Research

There is a continuing debate concerning “adjustments” to heart period variability [i.e., heart rate variability (HRV)] for the heart period [i.e., increases inter-beat-intervals (IBI)]. To date, such arguments have not seriously considered the impact a demographic variable, such as gender, can have on the association between HRV and the heart period. A prior meta-analysis showed women to have greater HRV compared to men despite having shorter IBI and higher heart rate (HR). Thus, it is plausible that men and women differ in the association between HRV and HR/IBI. Thus, the present study investigates the potential moderating effect of gender on the association between HRV and indices of cardiac chronotropy, including both HR and IBI. Data from 633 participants (339 women) were available for analysis. Cardiac measures were assessed during a 5-min baseline-resting period. HRV measures included the standard deviation of inter-beat-intervals, root mean square of successive differences, and autoregressive high frequency power. Moderation analyses showed gender significantly moderated the association between all HRV variables and both HR and IBI (each p < 0.05). However, results were not consistent when using recently recommended HRV variables “adjusted” for IBI. Overall, the current investigation provides data illustrating a differential association between HRV and the heart period based on gender. Substantial neurophysiological evidence support the current findings; women show greater sensitivity to acetylcholine compared to men. If women show greater sensitivity to acetylcholine, and acetylcholine increases HRV and the heart period, then the association between HRV and the heart period indeed should be stronger in women compared to men. Taken together, these data suggest that routine “adjustments” to HRV for the heart period are unjustified and problematic at best. As it relates to the application of future HRV research, it is imperative that researchers continue to consider the potential impact of gender.

Assessing Correlation between Heart Rate Variability Markers Based on Laguerre Expansion and Direct Measures of Sympathetic Activity during Incremental Head-up Tilt.

Traditional frequency domain analysis of heart period (HP) variability allows the estimation of the parasympathetic modulation directed to the heart but the sympathetic one remains largely unknown. Recently, sympathetic and parasympathetic activity indexes (SAI and PAI) have been proposed to address this issue. SAI and PAI were derived from HP variability via the application of an orthonormal Laguerre expansion allowing the separation of HP variations driven by sympathetic and parasympathetic outflows. In this study, SAI and PAI were validated against tonic and variability measures of muscle sympathetic nerve activity (MSNA) and more traditional markers derived from HP variability. Indexes were calculated in 12 healthy subjects (9 females, age from 20 to 36 years, median 22.5 years) undergoing incremental head-up tilt. Results showed that traditional HP and MSNA variability markers as well as SAI and PAI were modified in proportion to the magnitude of the postural challenge. However, SAI was not correlated with any MSNA markers and PAI was not linked to respiratory sinus arrhythmia. SAI and PAI can capture modifications of cardiac control induced by the orthostatic challenge but they might be weak surrogates of vagal and sympathetic activities and/or modulations.Clinical Relevance- SAI and PAI markers are useful to characterize cardiac control but poorly linked with autonomic nervous system state.

Development of an Optical System for Non-Contact Type Measurement of Heart Rate and Heart Rate Variability

Self-mixing optical coherent detection is a non-contact measurement technique which provides accurate information about the vibration frequency of any test subject. In this research, novel designs of optical homodyne and heterodyne detection techniques are explained. Homodyne and heterodyne setups are used for measuring the frequency of the modulated optical signal. This technique works on the principle of the optical interferometer, which provides a coherent detection of two self-mixing beams. In the optical homodyne technique, one of the two beams receives direct modulation from the vibration frequency of the test subject. In the optical heterodyne detection technique, one of the two optical beams is subjected to modulation by an acousto-optics modulator before becoming further modulated by the vibration frequency of the test subject. These two optical signals form an interference pattern that contains the information of the vibration frequency. The measurement of cardiovascular signals, such as heart rate and heart rate variability, are performed with both homodyne and heterodyne techniques. The optical coherent detection technique provides a high accuracy for the measurement of heart period and heart rate variability. The vibrocardiogram output obtained from both techniques are compared for different heart rate values. Results obtained from both optical homodyne and heterodyne detection techniques are compared and found to be within 1% of deviation value. The results obtained from both the optical techniques have a deviation of less than 1 beat per minute from their corresponding ECG values.

Comparison of frequency domain measures based on spectral decomposition for spontaneous baroreflex sensitivity assessment after Acute Myocardial Infarction

The objective of this study is to present a new method to assess in the frequency domain the directed interactions between the spontaneous variability of systolic arterial pressure (SAP) and heart period (HP) from their linear model representation, and to apply it for studying the baroreflex control of arterial pressure in healthy physiological states and after acute myocardial infarction (AMI). The method is based on pole decomposition of the model transfer function and on the following evaluation of causal measures of coupling and gain from the poles associated to low frequency (0.04−0.15 Hz) oscillatory components. It is compared with traditional non-causal approaches for the spectral analysis of the baroreflex gain, and with causal approaches based on the directed coherence, in a group of AMI patients and in Young and Old healthy controls studied at rest and during head-up tilt. Analysis of feedforward interactions from RR to SAP is also performed. Our results support the importance of using local causal approaches to quantify separately baroreflex and feedforward interactions between RR and SAP, allowing both to confirm known physiological behaviors (e.g., weaker baroreflex effectiveness and lower sensitivity after AMI) and to suggest novel findings (e.g., preserved low frequency baroreflex response to postural stress after AMI). We also find that the postural stress alters feedforward interactions selectively across groups, being related to decreased coupling only in Young and to increased gain mostly in AMI. These results have a significance for the clinical assessment of the baroreflex and the physiological evaluation of cardiovascular interactions.

Lack of association between heart period variability asymmetry and respiratory sinus arrhythmia in healthy and chronic heart failure individuals.

Temporal asymmetry is a peculiar aspect of heart period (HP) variability (HPV). HPV asymmetry (HPVA) is reduced with aging and pathology, but its origin is not fully elucidated. Given the impact of respiration on HPV resulting in the respiratory sinus arrhythmia (RSA) and the asymmetric shape of the respiratory pattern, a possible link between HPVA and RSA might be expected. In this study we tested the hypothesis that HPVA is significantly associated with RSA and asymmetry of the respiratory rhythm. We studied 42 middle-aged healthy (H) subjects, and 56 chronic heart failure (CHF) patients of whom 26 assigned to the New York Heart Association (NYHA) class II (CHF-II) and 30 to NYHA class III (CHF-III). Electrocardiogram and lung volume were monitored for 8 minutes during spontaneous breathing (SB) and controlled breathing (CB) at 15 breaths/minute. The ratio of inspiratory (INSP) to expiratory (EXP) phases, namely the I/E ratio, and RSA were calculated. HPVA was estimated as the percentage of negative HP variations, traditionally measured via the Porta’s index (PI). Departures of PI from 50% indicated HPVA and its significance was tested via surrogate data. We found that RSA increased during CB and I/E ratio was smaller than 1 in all groups and experimental conditions. In H subjects the PI was about 50% during SB and it increased significantly during CB. In both CHF-II and CHF-III groups the PI was about 50% during SB and remained unmodified during CB. The PI was uncorrelated with RSA and I/E ratio regardless of the experimental condition and group. Pooling together data of different experimental conditions did not affect conclusions. Therefore, we conclude that the HPVA cannot be explained by RSA and/or I/E ratio, thus representing a peculiar feature of the cardiac control that can be aroused in middle-aged H individuals via CB.