Respiratory Sinus Arrhythmia Mechanisms in Young Obese Subjects

Cardiorespiratory dynamics in the brain: Review on the significance of cardiovascular and respiratory correlates in functional MRI signal

Cardiorespiratory signals have long been treated as "noise" in functional magnetic resonance imaging (fMRI) research, with the goal of minimizing their impact to isolate neural activity. However, there is a growing recognition that these signals, once seen as confounding variables, provide valuable insights into brain function and overall health. This shift reflects the dynamic interaction between the cardiovascular, respiratory, and neural systems, which together support brain activity. In this review, we explore the role of cardiorespiratory dynamics-such as heart rate variability (HRV), respiratory sinus arrhythmia (RSA), and changes in blood flow, oxygenation, and carbon dioxide levels-embedded within fMRI signals. These physiological signals reflect critical aspects of neurovascular coupling and are influenced by factors such as physiological stress, breathing patterns, and age-related changes. We also discuss the complexities of distinguishing these signals from neuronal activity in fMRI data, given their significant contribution to signal variability and interactions with cerebrospinal fluid (CSF). Recognizing the influence of these cardiorespiratory dynamics is crucial for improving the interpretation of fMRI data, shedding light on heart-brain and respiratory-brain connections, and enhancing our understanding of circulation, oxygen delivery, and waste elimination within the brain.

Benefits From Different Modes of Slow and Deep Breathing on Vagal Modulation

Slow and deep breathing (SDB) is a relaxation technique that can increase vagal activity. Respiratory sinus arrhythmia (RSA) serves as an index of vagal function usually quantified by the high-frequency power of heart rate variability (HRV). However, the low breathing rate during SDB results in deviations when estimating RSA by HRV. Besides, the impact of the inspiration-expiration (I: E) ratio and guidelines ways (fixed breathing rate or intelligent guidance) on SDB is not yet clear. In our study, 30 healthy people (mean age = 26.5 years, 17 females) participated in three SDB modes, including 6 breaths per minute (bpm) with an I:E ratio of 1:1/ 1:2, and intelligent guidance mode (I:E ratio of 1:2 with guiding to gradually lower breathing rate to 6 bpm). Parameters derived from HRV, multimodal coupling analysis (MMCA), Poincaré plot, and detrended fluctuation analysis were introduced to examine the effects of SDB exercises. Besides, multiple machine learning methods were applied to classify breathing patterns (spontaneous breathing vs. SDB) after feature selection by max-relevance and min-redundancy. All vagal-activity markers, especially MMCA-derived RSA, statistically increased during SDB. Among all SDB modes, breathing at 6 bpm with a 1:1 I:E ratio activated the vagal function the most statistically, while the intelligent guidance mode had more indicators that still significantly increased after training, including SDRR and MMCA-derived RSA, etc. About the classification of breathing patterns, the Naive Bayes classifier has the highest accuracy (92.2%) with input features including LFn, CPercent, pNN50, [Formula: see text], SDRatio, [Formula: see text], and LF. Our study proposed a system that can be applied to medical devices for automatic SDB identification and real-time feedback on the training effect. We demonstrated that breathing at 6 bpm with an I:E ratio of 1:1 performed best during the training phase, while intelligent guidance mode had a more long-lasting effect.

Cardiorespiratory dynamics during respiratory maneuver in athletes

Introduction: The modern practice of sports medicine and medical rehabilitation requires the search for subtle criteria for the development of conditions and recovery of the body after diseases, which would have a prognostic value for the prevention of negative effects of training and rehabilitation tools, and also testify to the development and course of mechanisms for counteracting pathogenetic processes in the body. The purpose of this study was to determine the informative directions of the cardiorespiratory system parameters dynamics during the performing a maneuver with a change in breathing rate, which may indicate the body functional state violation.

Methods: The results of the study of 183 healthy men aged 21.2 ± 2.3 years who regularly engaged in various sports were analyzed. The procedure for studying the cardiorespiratory system included conducting combined measurements of indicators of activity of the respiratory and cardiovascular systems in a sitting position using a spiroarteriocardiograph device. The duration of the study was 6 min and involved the sequential registration of three measurements with a change in breathing rate (spontaneous breathing, breathing at 0.1 Hz and 0.25 Hz).

Results: Performing a breathing maneuver at breathing 0.1 Hz and breathing 0.25 Hz in comparison with spontaneous breathing leads to multidirectional significant changes in heart rate variability indicators–TP (ms2), LF (ms2), LFHF (ms2/ms2); of blood pressure variability indicators–TPDBP (mmHg2), LFSBP (mmHg2), LFDBP (mmHg2), HFSBP (mmHg2); of volume respiration variability indicators - LFR, (L×min-1)2; HFR, (L×min-1)2; LFHFR, (L×min-1)2/(L×min-1)2; of arterial baroreflex sensitivity indicators - BRLF (ms×mmHg-1), BRHF (ms×mmHg-1). Differences in indicators of systemic hemodynamics and indicators of cardiovascular and respiratory systems synchronization were also informative.

Conclusion: According to the results of the study, it is shown that during performing a breathing maneuver with a change in the rate of breathing, there are significant changes in cardiorespiratory parameters, the analysis of which the increments made it possible to determine of the changes directions dynamics, their absolute values and informative limits regarding the possible occurrence of the cardiorespiratory interactions dysregulation.

Cardiorespiratory dynamics during respiratory maneuver in athletes

Introduction: The modern practice of sports medicine and medical rehabilitation requires the search for subtle criteria for the development of conditions and recovery of the body after diseases, which would have a prognostic value for the prevention of negative effects of training and rehabilitation tools, and also testify to the development and course of mechanisms for counteracting pathogenetic processes in the body. The purpose of this study was to determine the informative directions of the cardiorespiratory system parameters dynamics during the performing a maneuver with a change in breathing rate, which may indicate the body functional state violation. Methods: The results of the study of 183 healthy men aged 21.2 ± 2.3 years who regularly engaged in various sports were analyzed. The procedure for studying the cardiorespiratory system included conducting combined measurements of indicators of activity of the respiratory and cardiovascular systems in a sitting position using a spiroarteriocardiograph device. The duration of the study was 6 min and involved the sequential registration of three measurements with a change in breathing rate (spontaneous breathing, breathing at 0.1 Hz and 0.25 Hz). Results: Performing a breathing maneuver at breathing 0.1 Hz and breathing 0.25 Hz in comparison with spontaneous breathing leads to multidirectional significant changes in heart rate variability indicators-TP (ms2), LF (ms2), LFHF (ms2/ms2); of blood pressure variability indicators-TPDBP (mmHg2), LFSBP (mmHg2), LFDBP (mmHg2), HFSBP (mmHg2); of volume respiration variability indicators - LFR, (L×min-1)2; HFR, (L×min-1)2; LFHFR, (L×min-1)2/(L×min-1)2; of arterial baroreflex sensitivity indicators - BRLF (ms×mmHg-1), BRHF (ms×mmHg-1). Differences in indicators of systemic hemodynamics and indicators of cardiovascular and respiratory systems synchronization were also informative. Conclusion: According to the results of the study, it is shown that during performing a breathing maneuver with a change in the rate of breathing, there are significant changes in cardiorespiratory parameters, the analysis of which the increments made it possible to determine of the changes directions dynamics, their absolute values and informative limits regarding the possible occurrence of the cardiorespiratory interactions dysregulation.

A framework based on the information domain to measure coupling changes in electrophysiological signals

Objectives.In this paper, the features of physiological signals of healthy dataset are extracted using the linear and non-linear techniques, and a comparison has been made on healthy young and old subjects to study the aging and gender-related changes in the contribution of Heart Rate (HR), Blood Pressure (BP), and Respiration (RESP).Methods. To quantify the coupling changes in cardiovascular, cardiorespiratory, and vasculorespiratory complexity, an information domain approach based on compensated transfer entropy (cTE) is proposed.Result. The results show that there is a substantial decrease in the flow of information from BP tro the time interval between successive R-peaks (RR) and from RR to BP. There is also a significant decrease in the flow of information from RESP to BP and RESP to RR but there is no significant change in the information flow from BP to RESP and RR to RESP.Conclusion. We have done linear and non-linear analysis on the healthy datasets of young and old subjects. As already existed techniques lacks in studying complex behaviours of electrophysiological signals so to overcome these limitations, we have proposed compensated transfer entropy (cTE). We conducted an investigation to determine the degree to which recordings of RESP, BP, and HR can be utilized to predict changes in the other parameters. Specifically, the proposed analysis examined the relationship between these variables and assessed their consistency across different age groups and genders. By analyzing the data, we aimed to gain insights into the interdependencies and predictive potential of these physiological measures in relation to each other.

Cardiorespiratory coupling as an early marker of cardiac autonomic dysfunction in type 2 diabetes mellitus patients

The aim of this study was to assess cardiorespiratory coupling (CRC) in type 2 diabetes mellitus patients (T2DM) and apparently healthy individuals, in order to test the hypothesis that this method can provide additional knowledge to the information obtained through the heart rate variability (HRV). A cross-sectional study was conducted in T2DM patients(T2DMG=32) and health controls (CON=32). For CRC analysis, the electrocardiogram, arterial pressure, and thoracic respiratory movement were recorded at rest in supine position and during active standing. Beat-to-beat series of heart period and systolic arterial pressure were analyzed with the respiratory movement signal via a traditional non-causal approach, such as squared coherence function. In this sample of T2DM, no differences in HRV were observed when compared to the CON, but the T2DMG showed a reduction in resting CRC. We conclude that in CRC in T2DM, reflected by the squared coherence may already be compromised even before HRV changes.

Wearable Multisensor Ring-Shaped Probe for Assessing Stress and Blood Oxygenation: Design and Preliminary Measurements

The increasing interest in innovative solutions for health and physiological monitoring has recently fostered the development of smaller biomedical devices. These devices are capable of recording an increasingly large number of biosignals simultaneously, while maximizing the user's comfort. In this study, we have designed and realized a novel wearable multisensor ring-shaped probe that enables synchronous, real-time acquisition of photoplethysmographic (PPG) and galvanic skin response (GSR) signals. The device integrates both the PPG and GSR sensors onto a single probe that can be easily placed on the finger, thereby minimizing the device footprint and overall size. The system enables the extraction of various physiological indices, including heart rate (HR) and its variability, oxygen saturation (SpO₂), and GSR levels, as well as their dynamic changes over time, to facilitate the detection of different physiological states, e.g., rest and stress. After a preliminary SpO₂ calibration procedure, measurements have been carried out in laboratory on healthy subjects to demonstrate the feasibility of using our system to detect rapid changes in HR, skin conductance, and SpO₂ across various physiological conditions (i.e., rest, sudden stress-like situation and breath holding). The early findings encourage the use of the device in daily-life conditions for real-time monitoring of different physiological states.

Presence of physical symptoms in healthy adolescence found to be associated with female gender, obesity, tachycardia, diastolic hypertension and smoking

BACKGROUND

The goal of this study was to evaluate any association between physical symptoms and abnormal clinical history in adolescence undergoing screening echocardiography performed by Anthony Bates Foundation.

METHOD

The Anthony Bates Foundation has been performing screening echocardiography across the United States for the prevention of sudden death since 2001. We performed uni- and multivariate analysis to evaluate any association between physical symptoms with gender, smoking, obesity, heart rate, and hypertension.

RESULTS

We found a strong association between symptoms and the female gender (33% vs. 17.5% of males, P < 0.001). Furthermore, obesity (46.5% vs. 22.5%, P < 0.001), smoking (46.2% vs. 22.5%, P = 0.04), heart rate > 90 (34.8 vs. 22.8%, P = 0.001), and diastolic blood pressure > 90 (34.9% vs. 23.4%, P = 0.03) were all associated with symptoms. Increased systolic pressure was not associated with physical symptoms (24.3% vs. 21.9%, P = 0.4). Using multivariate analysis, female gender, diastolic blood pressure and obesity remained independently associated with physical symptoms. (Female gender: OR: 2.2, CI: 1.7-2.9, P < 0.001, obesity: OR: 2.5, CI 1.2-5.05, P = 0.009, and high diastolic blood pressure: OR: 2.08, CI 1.1-3.7, P = 0.01).

CONCLUSION

Physical symptoms are associated with smoking, female gender, obesity, tachycardia, and high diastolic blood pressure but not systolic pressure in adolescence undergoing routine screening echocardiography.

Cardiorespiratory coupling strength in athletes and non-athletes

PURPOSE

Despite the relevant presence of nonlinear components on heart period (HP) likely due to cardiorespiratory coupling (CRC), the HP is frequently analyzed in absence of concomitant recordings of respiratory movements (RESP). This study aims to assess the cardiovascular dynamics and CRC during postural challenge in athletes and non-athletes via joint symbolic analysis (JSA).

METHODS

A cross-sectional study was conducted in 50 men, aged between 20 and 40 yrs, divided into athletes (n = 25) and non-athletes (n = 25) groups. The electrocardiogram, blood pressure and RESP signals were recorded during 15 min in both supine position (REST) and after active postural maneuver (STAND). From the beat-to-beat series of HP, systolic arterial pressure (SAP) and RESP, we computed the time and frequency domain indexes and baroreflex sensitivity. The JSA was based on the definition of symbolic HP and RESP patterns and on the evaluation of the rate of their simultaneous occurrence in both HP and RESP series.

RESULTS

The JSA analysis was able to identify higher CRC strength at REST in athletes. Moreover, the response of CRC to STAND depended on the time scales of the analysis and was much more evident in athletes than in non-athletes, thus indicating a more reactive autonomic control in athletes.

CONCLUSION

Assessing CRC in athletes via JSA provides additional information compared to standard linear time and frequency domain tools likely due to the more relevant presence of nonlinearities in HP-RESP variability relationship.

Assessment of Cardiorespiratory Interactions during Apneic Events in Sleep via Fuzzy Kernel Measures of Information Dynamics

Apnea and other breathing-related disorders have been linked to the development of hypertension or impairments of the cardiovascular, cognitive or metabolic systems. The combined assessment of multiple physiological signals acquired during sleep is of fundamental importance for providing additional insights about breathing disorder events and the associated impairments. In this work, we apply information-theoretic measures to describe the joint dynamics of cardiorespiratory physiological processes in a large group of patients reporting repeated episodes of hypopneas, apneas (central, obstructive, mixed) and respiratory effort related arousals (RERAs). We analyze the heart period as the target process and the airflow amplitude as the driver, computing the predictive information, the information storage, the information transfer, the internal information and the cross information, using a fuzzy kernel entropy estimator. The analyses were performed comparing the information measures among segments during, immediately before and after the respiratory event and with control segments. Results highlight a general tendency to decrease of predictive information and information storage of heart period, as well as of cross information and information transfer from respiration to heart period, during the breathing disordered events. The information-theoretic measures also vary according to the breathing disorder, and significant changes of information transfer can be detected during RERAs, suggesting that the latter could represent a risk factor for developing cardiovascular diseases. These findings reflect the impact of different sleep breathing disorders on respiratory sinus arrhythmia, suggesting overall higher complexity of the cardiac dynamics and weaker cardiorespiratory interactions which may have physiological and clinical relevance.

Multivariate Correlation Measures Reveal Structure and Strength of Brain-Body Physiological Networks at Rest and During Mental Stress

In this work, we extend to the multivariate case the classical correlation analysis used in the field of network physiology to probe dynamic interactions between organ systems in the human body. To this end, we define different correlation-based measures of the multivariate interaction (MI) within and between the brain and body subnetworks of the human physiological network, represented, respectively, by the time series of δ, θ, α, and β electroencephalographic (EEG) wave amplitudes, and of heart rate, respiration amplitude, and pulse arrival time (PAT) variability (η, ρ, π). MI is computed: (i) considering all variables in the two subnetworks to evaluate overall brain-body interactions; (ii) focusing on a single target variable and dissecting its global interaction with all other variables into contributions arising from the same subnetwork and from the other subnetwork; and (iii) considering two variables conditioned to all the others to infer the network topology. The framework is applied to the time series measured from the EEG, electrocardiographic (ECG), respiration, and blood volume pulse (BVP) signals recorded synchronously via wearable sensors in a group of healthy subjects monitored at rest and during mental arithmetic and sustained attention tasks. We find that the human physiological network is highly connected, with predominance of the links internal of each subnetwork (mainly η-ρ and δ-θ, θ-α, α-β), but also statistically significant interactions between the two subnetworks (mainly η-β and η-δ). MI values are often spatially heterogeneous across the scalp and are modulated by the physiological state, as indicated by the decrease of cardiorespiratory interactions during sustained attention and by the increase of brain-heart interactions and of brain-brain interactions at the frontal scalp regions during mental arithmetic. These findings illustrate the complex and multi-faceted structure of interactions manifested within and between different physiological systems and subsystems across different levels of mental stress.