Correlation between heart rate variability and pulmonary function adjusted by confounding factors in healthy adults

The autonomic nervous system maintains homeostasis, which is the state of balance in the body. That balance can be determined simply and noninvasively by evaluating heart rate variability (HRV). However, independently of autonomic control of the heart, HRV can be influenced by other factors, such as respiratory parameters. Little is known about the relationship between HRV and spirometric indices. In this study, our objective was to determine whether HRV correlates with spirometric indices in adults without cardiopulmonary disease, considering the main confounders (e.g., smoking and physical inactivity). In a sample of 119 asymptomatic adults (age 20-80 years), we evaluated forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1). We evaluated resting HRV indices within a 5-min window in the middle of a 10-min recording period, thereafter analyzing time and frequency domains. To evaluate daily physical activity, we instructed participants to use a triaxial accelerometer for 7 days. Physical inactivity was defined as <150 min/week of moderate to intense physical activity. We found that FVC and FEV1, respectively, correlated significantly with the following aspects of the RR interval: standard deviation of the RR intervals (r= 0.31 and 0.35), low-frequency component (r= 0.38 and 0.40), and Poincare plot SD2 (r= 0.34 and 0.36). Multivariate regression analysis, adjusted for age, sex, smoking, physical inactivity, and cardiovascular risk, identified the SD2 and dyslipidemia as independent predictors of FVC and FEV1 (R-2= 0.125 and 0.180, respectively, for both). We conclude that pulmonary function is influenced by autonomic control of cardiovascular function, independently of the main confounders.Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)Univ Fed Sao Paulo, Dept Ciencias Movimento Humano, Lab Epidemiol & Movimento Humano, Santos, SP, BrazilUniv Fed Sao Paulo, Dept Biociencias, Santos, SP, BrazilAngioCorpore Inst Med Cardiovasc, Santos, SP, BrazilUniv Fed Sao Paulo, Dept Ciencias Movimento Humano, Lab Epidemiol & Movimento Humano, Santos, SP, BrazilUniv Fed Sao Paulo, Dept Biociencias, Santos, SP, BrazilFAPESP: 2011/07282-6Web of Scienc

Assessment of quadratic nonlinear cardiorespiratory couplings during tilt table test by means of real wavelet biphase

In this paper a method for assessment of Quadratic Phase Coupling (QPC) between respiration and Heart Rate Variability (HRV) is presented. Methods: First, a method for QPC detection is proposed named Real Wavelet Biphase (RWB). Then, a method for QPC quantification is proposed based on the Normalized Wavelet Biamplitude (NWB). A simulation study has been conducted to test the reliability of RWB to identify QPC, even in the presence of constant delays between interacting oscillations, and to discriminate it from Quadratic Phase Uncoupling. Significant QPC was assessed based on surrogate data analysis. Then, quadratic cardiorespiratory couplings were studied during a tilt table test protocol of 17 young healthy subjects. Results: Simulation study showed that RWB is able to detect even weak QPC with delays in the range of 0 - 2 s, which are usual in the Autonomic Nervous System (ANS) control of heart rate. Results from the database revealed a significant reduction (p<0.05) of NWB between respiration and both low and high frequencies of HRV in head-up tilt position compared to early supine. Conclusion: The proposed technique detects and quantifies robustly QPC and is able to track the coupling between respiration and various HRV components during ANS changes. Significance: The proposed method can help to assess alternations of nonlinear cardiorespiratory interactions related to ANS dysfunction and physiological regulation of HRV in cardiovascular diseases

Nonlinear dynamical analysis of brain electrical activity due to exposure to weak environmentally relevant electromagnetic fields

The reports dealing with the effects of weak electromagnetic fields (EMFs) on brain electrical activity have been inconsistent. We suspected that the use of linear models and their associated methods accounted for some of the variability, and we explored the issue by using a novel approach to study the effects of EMFs on the electroencephalogram (EEG) from rabbits and humans. The EEG was embedded in phase space and local recurrence plots were calculated and quantified to permit comparisons between exposed and control epochs from individual subjects. Statistically significant alterations in brain activity were observed in each subject when exposed to weak EMFs, as assessed using each of two recurrence-plot quantifiers. Each result was replicated; a sham exposure control procedure ruled out the possibility that the effect of the field was a product of the method of analysis. No differences were found between exposed and control epochs in any animal when the experiment was repeated after the rabbits had been killed, indicating that a putative interaction between the field and the EEG electrodes could not account for the observed effects. We conclude that EMF transduction resulting in changes in brain electrical activity could be demonstrated consistently using methods derived from nonlinear dynamical systems theory

Characteristics and coupling of cardiac and locomotor rhythms during treadmill walking tasks

Studying the variability of physiological subsystems (e.g., cardiac and locomotor control systems) has been insightful in understanding how functional and dysfunctional patterns emerge within their behaviors. The coupling of these subsystems (termed cardiolocomotor coupling) is believed to be important to maintain healthy functioning in the diverse conditions in which individuals must operate. Aging and pathology result in alterations to both the patterns of individual systems, as well as to how those systems couple to each other. By examining cardiac and locomotor rhythms concurrently during treadmill walking, it is possible to ascertain how these two rhythms relate to each other in different populations (i.e., younger and older adults) and with varying task constraints (i.e., a gait synchronization task or fast walking task). The purpose of this research was to simultaneously document the characteristics of cardiac and gait rhythms in younger (18-35 yrs) and older (63-80 yrs) healthy adults while walking and to establish the extent to which changes in these systems are coupled when gait is constrained. This study consisted of two repeated-measures experiments that participants completed on two separate days. Both experiments consisted of three 15-minute phases. During the first (baseline) and third (retention) phases of both experiments, participants walked with no cues or specific instructions at their preferred walking speed. During the second phase, participants were asked to synchronize their step falls to the timing of a visual cue (experiment 1) or to walk at 125% of their preferred walking speed (experiment 2). Fifty-one healthy adults (26 older, 67.67±4.70 yrs, 1.72±0.09 m, 70.13±14.30 kg; 25 younger, 24.57±4.29 yrs, 1.76±0.09 m, 73.34±15.35 kg) participated in this study. Participants’ cardiac rhythms (R-R interval time series) and locomotor rhythms (stride interval, step width, and step length time series) were measured while walking on a treadmill. Characteristics of variability in cardiac and locomotor rhythms and the coupling between cardiac and gait rhythms were measured. Results revealed that younger and older healthy adults alter gait patterns similarly when presented with a gait synchronization or fast walking task and that these tasks also alter cardiac patterns. Likewise, both groups exhibited enhanced cardiolocomotor coupling when tasked with a step timing constraint or increased speed during treadmill walking. Combined, these findings suggest that walking tasks likely alter both locomotor and cardiac dynamics and the coupling of physiological subsystems could be insightful in understanding the diverse effects aging and pathology have on individuals

Coupling patterns between spontaneous rhythms and respiration in cardiovascular variability signals

Abstract We performed a quantitative study of coupling patterns between respiration and spontaneous rhythms of heart rate and blood pressure variability signals by using the Recurrence Quantification Analysis (RQA). We applied RQA to both simulated and experimental data obtained in control breathing at three different frequencies (0.25, 0.20, and 0.13 Hz) from ten normal subjects. RQA succeeded in quantifying different degrees of non-linear coupling associated to several interference patterns. We found higher degrees of non-linear coupling when the respiratory frequency was close to the spontaneous Low Frequency (LF) rhythm (0.13 Hz), or almost twice the LF frequency (0.2 Hz), whereas weaker coupling was observed when the respiratory frequency was 0.25 Hz. Clinical applications of our approach should focus on new experimental protocols, featuring the stimulation of one of the two branches of the autonomic nervous system (ANS) or aimed at the analysis of pathologies linked to the ANS

Coupling patterns between spontaneous rhythms and respiration in cardiovascular variability signals

Abstract We performed a quantitative study of coupling patterns between respiration and spontaneous rhythms of heart rate and blood pressure variability signals by using the Recurrence Quantification Analysis (RQA). We applied RQA to both simulated and experimental data obtained in control breathing at three different frequencies (0.25, 0.20, and 0.13 Hz) from ten normal subjects. RQA succeeded in quantifying different degrees of non-linear coupling associated to several interference patterns. We found higher degrees of non-linear coupling when the respiratory frequency was close to the spontaneous Low Frequency (LF) rhythm (0.13 Hz), or almost twice the LF frequency (0.2 Hz), whereas weaker coupling was observed when the respiratory frequency was 0.25 Hz. Clinical applications of our approach should focus on new experimental protocols, featuring the stimulation of one of the two branches of the autonomic nervous system (ANS) or aimed at the analysis of pathologies linked to the ANS