Search Results (33)

The complex interplay between the cardiac and the respiratory systems, termed cardiorespiratory coupling (CRC), is a bidirectional phenomenon that can be affected by pathologies such as heart failure (HF). In the present work, the potential changes in strength of directional CRC were assessed in HF patients classified according to their cardiac rhythm via two measures of coupling based on k-nearest neighbor (KNN) estimation approaches, cross-entropy (CrossEn) and state space correspondence (SSC), applied on the heart period (HP) and respiratory (RESP) variability series, while also accounting for the complexity of the cardiac and respiratory rhythms. We tested the measures on 25 HF patients with sinus rhythm (SR, age: 58.9 ± 9.7 years; 23 males) and 41 HF patients with ventricular arrhythmia (VA, age 62.2 ± 11.0 years; 30 males). A predominant directionality of interaction from the cardiac to the respiratory rhythm was observed in both cohorts and using both methodologies, with similar statistical power, while a lower complexity for the RESP series compared to HP series was observed in the SR cohort. We conclude that CrossEn and SSC can be considered strictly related to each other when using a KNN technique for the estimation of the cross-predictability markers. Full article

Background: Selenium (Se) is a trace mineral element with important roles in enhancing athletic performance and athlete recovery. Objectives: This study aimed to observe the differences in plasma, urinary, erythrocyte, and platelet Se concentrations between sexes and analyze the variations in Se concentrations during the soccer season. The main hypothesis was that significant differences in Se levels would be observed between male and female athletes and that these differences would fluctuate throughout the season due to varying training loads and nutritional factors. Methods: Twenty-two male (20 ± 2 years; 1.76 ± 0.06 m; 14.73 ± 3.13 years’ experience; fifth Spanish division) and twenty-four female soccer players (23 ± 4 years; 1.65 ± 0.06 m; 14.51 ± 4.94 years’ experience; second Spanish division) participated. Three assessments were conducted during the season. Evaluations included anthropometry, body composition, fitness (cardiorespiratory and vertical jump), and nutritional intake. Venous samples of blood and urine were obtained. The concentrations of Se in the plasma, urine, erythrocytes, and platelets were analyzed through inductively coupled plasma mass spectrometry. Results: No differences in Se intake were observed. The Se concentrations in the plasma, urine, and platelets were found to be higher in males, while females showed elevated levels in their erythrocytes (p < 0.05). Throughout the season, plasma and platelet Se concentrations exhibited a progressive increase (p < 0.05). Conclusions: Assessing Se status during the season is essential for evaluating nutritional supplementation to maintain performance given Se’s vital role in the immune and antioxidant systems. Full article

Biological signals such as respiration (RSP) and heart rate (HR) are oscillatory and physiologically coupled, maintaining homeostasis through regulatory mechanisms. This report models the dynamic relationship between RSP and HR in 45 healthy volunteers at rest. Cross-correlation between RSP and HR was computed, along with regression analysis to predict HR from RSP and its first-order time derivative in continuous signals. A simulation model tested the possibility of replicating the RSP–HR relationship. Cross-correlation results showed a time lag in the sub-second range of these signals (849.21 ms ± SD 344.84). The possible modulation of HR by RSP was mediated by the RSP amplitude and its first-order time derivative (in 45 of 45 cases). A simulation of this process allowed us to replicate the physiological relationship between RSP and HR. These results provide support for understanding the dynamic interactions in cardiorespiratory coupling at rest, showing a short time lag between RSP and HR and a modulation of the HR signal by the first-order time derivative of the RSP. This dynamic would optionally be incorporated into dynamic models of resting cardiopulmonary coupling and suggests a mechanism for optimizing respiration in the alveolar system by promoting synchrony between the gases and hemoglobin in the alveolar pulmonary system. Full article

Background/Objectives: This study aimed to evaluate the accuracy of machine learning (ML) techniques in classifying pediatric individuals—cardiological patients, healthy participants, and athletes—based on cardiorespiratory features from short-term static measurements. It also examined the impact of cardiorespiratory coupling (CRC)-related features (from causal and information domains) on the modeling accuracy to identify a preferred cardiorespiratory feature set that could be further explored for specialized tasks, such as monitoring training progress or diagnosing health conditions. Methods: We utilized six self-prepared datasets that comprised various subsets of cardiorespiratory parameters and applied several ML algorithms to classify subjects into three distinct groups. This research also leveraged explainable artificial intelligence (XAI) techniques to interpret model decisions and investigate feature importance. Results: The highest accuracy, over 89%, was obtained using the dataset that included most important demographic, cardiac, respiratory, and interrelated (causal and information) domain features. The dataset that comprised the most influential features but without demographic data yielded the second best accuracy, equal to 85%. Incorporation of the causal and information domain features significantly improved the classification accuracy. The use of XAI tools further highlighted the importance of these features with respect to each individual group. Conclusions: The integration of ML algorithms with a broad spectrum of cardiorespiratory features provided satisfactory efficiency in classifying pediatric individuals into groups according to their actual health status. This study underscored the potential of ML and XAI in advancing the analysis of cardiorespiratory signals and emphasized the importance of CRC-related features. The established set of features that appeared optimal for the classification of pediatric patients should be further explored for their potential in assessing individual progress through training or rehabilitation. Full article

Background: Understanding the responses of the cardio and respiratory systems during exercise, as well as their coupling in post-exercise recovery, is important for the prescription of exercise programs in physically recreative subjects. Aim: In this work, we aimed to set up an adjusted experiment to evaluate the relations and changes in parameters obtained from an analysis of cardiac and respiratory signals under three physiological conditions: relaxation, exercise, and post-exercise recovery. Material and Methods: Simultaneously recorded ECG (RR intervals) and respiratory signal during relaxation, bicycle ergometry exercise until submaximal heart rate (HR), and recovery in 10 healthy men were analyzed. The exercise included consecutive phases of 3 min in duration with a constant workload. Parasympathetic cardiac control (RMSSD), heart rate (HR), breathing frequency (BF), and respiratory cycle amplitude (RCA) were calculated. Anthropometric data were also collected. Results: Based on time series analysis, our results show that: (1) during exercise, an increase in HR was related to a reduction in HR variability and RMSSD, while an increase in BF was related to an increase in RCA, and (2) during recovery, HR and RCA significantly decreased, while RMSSD had a biphasic response. The results of multiple linear regressions showed that the averaged HR, RMSSD, and BF during 3 min segments of recovery were determined by several calculated and collected parameters. Conclusions: The parameters from the analysis of respiratory signals and RR interval time series under conditions of relaxation and exercise, along with anthropometric data, contributed to the complexity of the post-exercise recovery of cardiopulmonary parameters after submaximal HR exercise in healthy recreative males. Full article

Bradycardia, frequently observed in preterm infants, presents significant risks due to the immaturity of their autonomic nervous system (ANS) and respiratory systems. These infants may face cardiorespiratory events, leading to severe complications like hypoxemia and neurodevelopmental disorders. Although neonatal care has advanced, the influence of bradycardia on cardiorespiratory coupling (CRC) remains elusive. This exploratory study delves into CRC in preterm infants, emphasizing disparities between events with and without bradycardia. Using the Preterm Infant Cardio-Respiratory Signals (PICS) database, we analyzed interbeat (R-R) and inter-breath intervals (IBI) from 10 preterm infants. The time series were segmented into bradycardic (B) and non-bradycardic (NB) segments. Employing information theory measures, we quantified the irregularity of cardiac and respiratory time series. Notably, B segments had significantly lower entropy values for R-R and IBI than NB segments, while mutual information was higher in NB segments. This could imply a reduction in the complexity of respiratory and cardiac dynamics during bradycardic events, potentially indicating weaker CRC. Building on these insights, this research highlights the distinctive physiological characteristics of preterm infants and underscores the potential of emerging non-invasive diagnostic tools. Full article

Adiposity, a state characterized by excessive accumulation of body fat, is closely linked to metabolic complications and the secretion of specific adipokines. This study explores the potential of exercise and Spirulina supplementation to mitigate these complications and modulate adipokine release associated with obesity. The primary objective of this investigation was to examine the impact of a 12-week regimen of high-intensity training combined with Spirulina supplementation on adipokine concentrations and lipid profiles in male individuals with obesity (N = 44). The participants were randomly distributed into four groups, each consisting of 11 participants: a control group (CG), a supplement group (SG), a training group (TG), and a training plus supplement group (TSG). The intervention comprised a 12-week treatment involving Spirulina supplementation (6 g capsule daily), a 12-week high-intensity interval training (HIIT) protocol with three sessions per week, or a combined approach. Following the interventions, metabolic parameters, anthropometric measurements, cardiorespiratory indices, and circulating adipokines [CRP, Sema3C, TNF-α, IL-6, MCP1, IL-8] were assessed within 48 h of the before and final training session. Statistical analyses revealed significant differences across all measures among the groups (p < 0.05). Notably, post hoc analyses indicated substantial disparities between the CG and the three interventional groups regarding body weight (p < 0.05). The combined training and supplementation approach led to noteworthy reductions in low-density lipoprotein (LDL), total cholesterol (TC), and triglyceride (TGL) levels (all p < 0.0001), coupled with an elevation in high-density lipoprotein–cholesterol (HDL-C) levels (p = 0.0001). Furthermore, adipokine levels significantly declined in the three intervention groups relative to the CG (p < 0.05). The findings from this 12-week study demonstrate that Spirulina supplementation in conjunction with high-intensity interval training reduced adipokine levels, improved body weight and BMI, and enhanced lipid profiles. This investigation underscores the potential of Spirulina supplementation and high-intensity interval training as a synergistic strategy to ameliorate obesity-related complications and enhance overall cardiometabolic well-being in obese males. Full article

Background: Chronic spinal cord injury (SCI) significantly accelerates morbidity and mortality, partly due to the increased risk of cardiometabolic diseases (CMD), including neurogenic obesity, dyslipidemia, and impaired glucose metabolism. While exercise and dietary interventions have shown some transient benefits in reducing CMD risk, they often fail to improve clinically relevant disease markers and cardiovascular events. Moreover, SCI also places caregiving demands on their caregivers, who themselves experience health and functional decline. This underscores the need for more substantial interventions that incorporate appropriate physical activity, heart-healthy nutrition, and behavioral support tailored to the SCI population. Objectives: This randomized clinical trial (RCT) protocol will (1) assess the health and functional effects, user acceptance, and satisfaction of a 6-month comprehensive therapeutic lifestyle intervention (TLI) adapted from the National Diabetes Prevention Program (DPP) for individuals with chronic SCI and (2) examine the impact of a complementary caregiver program on the health and function of SCI caregivers and evaluate user acceptance and satisfaction. Caregivers (linked with their partners) will be randomized to ‘behavioral support’ or ‘control condition’. Methods: Dyadic couples comprise individuals with SCI (18–65 years, >1-year post-injury, ASIA Impairment Scale A-C, injury levels C5-L1) and non-disabled SCI caregivers (18–65 years). Both groups undergo lock-step circuit resistance training, a calorie-restricted Mediterranean-style diet, and 16 educational sessions focused on diet/exercise goals, self-monitoring, psychological and social challenges, cognitive behavioral therapy, and motivational interviewing. The outcome measures encompass the cardiometabolic risks, cardiorespiratory fitness, inflammatory stress, multidimensional function, pain, life quality, independence, self-efficacy, program acceptance, and life satisfaction for SCI participants. The caregiver outcomes include multidimensional function, pain, quality of life, independence, and perceived caregiver burden. Discussion/Conclusions: This study evaluates the effects and durability of a structured, multi-modal intervention on health and function. The results and intervention material will be disseminated to professionals and consumers for broader implementation. Trial Registration: ClinicalTrials.gov, ID: NCT02853149 Registered 2 August 2016. Full article

The properties of cardio-respiratory coupling (CRC) are affected by various pathological conditions related to the cardiovascular and/or respiratory systems. In heart failure, one of the most common cardiac pathological conditions, the degree of CRC changes primarily depend on the type of heart-rhythm alterations. In this work, we investigated CRC in heart-failure patients, applying measures from information theory, i.e., Granger Causality (GC), Transfer Entropy (TE) and Cross Entropy (CE), to quantify the directed coupling and causality between cardiac (RR interval) and respiratory (Resp) time series. Patients were divided into three groups depending on their heart rhythm (sinus rhythm and presence of low/high number of ventricular extrasystoles) and were studied also after cardiac resynchronization therapy (CRT), distinguishing responders and non-responders to the therapy. The information-theoretic analysis of bidirectional cardio-respiratory interactions in HF patients revealed the strong effect of nonlinear components in the RR (high number of ventricular extrasystoles) and in the Resp time series (respiratory sinus arrhythmia) as well as in their causal interactions. We showed that GC as a linear model measure is not sensitive to both nonlinear components and only model free measures as TE and CE may quantify them. CRT responders mainly exhibit unchanged asymmetry in the TE values, with statistically significant dominance of the information flow from Resp to RR over the opposite flow from RR to Resp, before and after CRT. In non-responders this asymmetry was statistically significant only after CRT. Our results indicate that the success of CRT is related to corresponding information transfer between the cardiac and respiratory signal quantified at baseline measurements, which could contribute to a better selection of patients for this type of therapy. Full article

Most COVID-19 survivors report experiencing at least one persistent symptom after recovery, including sympathovagal imbalance. Relaxation techniques based on slow-paced breathing have proven to be beneficial for cardiovascular and respiratory dynamics in healthy subjects and patients with various diseases. Therefore, the present study aimed to explore the cardiorespiratory dynamics by linear and nonlinear analysis of photoplethysmographic and respiratory time series on COVID-19 survivors under a psychophysiological assessment that includes slow-paced breathing. We analyzed photoplethysmographic and respiratory signals of 49 COVID-19 survivors to assess breathing rate variability (BRV), pulse rate variability (PRV), and pulse–respiration quotient (PRQ) during a psychophysiological assessment. Additionally, a comorbidity-based analysis was conducted to evaluate group changes. Our results indicate that all BRV indices significantly differed when performing slow-paced breathing. Nonlinear parameters of PRV were more appropriate for identifying changes in breathing patterns than linear indices. Furthermore, the mean and standard deviation of PRQ exhibited a significant increase while sample and fuzzy entropies decreased during diaphragmatic breathing. Thus, our findings suggest that slow-paced breathing may improve the cardiorespiratory dynamics of COVID-19 survivors in the short term by enhancing cardiorespiratory coupling via increased vagal activity. Full article

Nonlinear markers of coupling strength are often utilized to typify cardiorespiratory and cerebrovascular regulations. The computation of these indices requires techniques describing nonlinear interactions between respiration (R) and heart period (HP) and between mean arterial pressure (MAP) and mean cerebral blood velocity (MCBv). We compared two model-free methods for the assessment of dynamic HP–R and MCBv–MAP interactions, namely the cross-sample entropy (CSampEn) and k-nearest-neighbor cross-unpredictability (KNNCUP). Comparison was carried out first over simulations generated by linear and nonlinear unidirectional causal, bidirectional linear causal, and lag-zero linear noncausal models, and then over experimental data acquired from 19 subjects at supine rest during spontaneous breathing and controlled respiration at 10, 15, and 20 ${\mathrm{b}\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{t}\mathrm{h}\mathrm{s}·\mathrm{m}\mathrm{i}\mathrm{n}\mathrm{u}\mathrm{t}\mathrm{e}}^{-1}$ as well as from 13 subjects at supine rest and during 60° head-up tilt. Linear markers were computed for comparison. We found that: (i) over simulations, CSampEn and KNNCUP exhibit different abilities in evaluating coupling strength; (ii) KNNCUP is more reliable than CSampEn when interactions occur according to a causal structure, while performances are similar in noncausal models; (iii) in healthy subjects, KNNCUP is more powerful in characterizing cardiorespiratory and cerebrovascular variability interactions than CSampEn and linear markers. We recommend KNNCUP for quantifying cardiorespiratory and cerebrovascular coupling. Full article

Background: Respiratory sinus arrhythmia (RSA) denotes decrease of cardiac beat-to-beat intervals (RRI) during inspiration and RRI increase during expiration, but an inverse pattern (termed negative RSA) was also found in healthy humans with elevated anxiety. It was detected using wave-by-wave analysis of cardiorespiratory rhythms and was considered to reflect a strategy of anxiety management involving the activation of a neural pacemaker. Results were consistent with slow breathing, but contained uncertainty at normal breathing rates (0.2–0.4 Hz). Objectives and methods: We combined wave-by-wave analysis and directed information flow analysis to obtain information on anxiety management at higher breathing rates. We analyzed cardiorespiratory rhythms and blood oxygen level-dependent (BOLD) signals from the brainstem and cortex in 10 healthy fMRI participants with elevated anxiety. Results: Three subjects with slow respiratory, RRI, and neural BOLD oscillations showed 57 ± 26% negative RSA and significant anxiety reduction by 54 ± 9%. Six participants with breathing rate of ~0.3 Hz showed 41 ± 16% negative RSA and weaker anxiety reduction. They presented significant information flow from RRI to respiration and from the middle frontal cortex to the brainstem, which may result from respiration-entrained brain oscillations, indicating another anxiety management strategy. Conclusions: The two analytical approaches applied here indicate at least two different anxiety management strategies in healthy subjects. Full article

Due to the fact that respiratory breath-to-breath and cardiac intervals between two successive R peaks (BBI and RRI, respectively) are not temporally concurrent, in a previous paper, we proposed a method to calculate both the integer and non-integer parts of the pulse respiration quotient (PRQ = BBI/RRI = PRQ_int + b1 + b2), b1 and b2 being parts of the border RRIs for each BBI. In this work, we study the correlations between BBI and PRQ, as well as those between BBI and mean RRI within each BBI (mRRI), on a group of twenty subjects in four conditions: in supine and standing positions, in combination with spontaneous and slow breathing. Results show that the BBI vs. PRQ correlations are positive; whereas the breathing regime had little or no effect on the linear regression slopes, body posture did. Two types of scatter plots were obtained with the BBI vs. mRRI correlations: one showed points aggregated around the concurrent PRQ_int lines, while the other showed randomly distributed points. Five out of six of the proposed aggregation measures confirmed the existence of these two cardio-respiratory coupling regimes. We also used b1 to study the positions of R pulses relative to the respiration onsets and showed that they were more synchronous with sympathetic activation. Overall, this method should be used in different pathological states. Full article

Purpose: This study aimed to compare the effects of high-intensity interval training (HIT), sprint interval training (SIT) and moderate-intensity continuous training (MICT) on cardiorespiratory fitness (CRF), weight (kg), body fat mass (%), plasma glucose (fasting) and lipid levels in reproductive-age women. Method: The search was conducted in Pubmed, Cochrane Library, Virtual Health Library and Scielo. The meta-analyses were conducted using Review Manager software for random-effects models. The results were presented as standardized mean differences and 95%CI, which were calculated to determine the effect size of HIT/SIT and MICT interventions. Results: Eleven articles meet the inclusion criteria. The analyses demonstrated that all exercise modes improved body composition and metabolic profile, but nevertheless, MICT was significantly better at improving CRF (mL·min⁻¹·kg⁻¹) compared with HIT (2.45 mL·min⁻¹·kg⁻¹ (95% CI: 1.15 to 3.75 mL·min⁻¹·kg⁻¹); p < 0.05; I2 = 0%) and with SIT (0.98 mL·min⁻¹·kg⁻¹ (95% CI: −0.98 to 2.93 mL·min⁻¹·kg⁻¹); p = 0.33; I2 = 53%). Conclusion: Both HIT and SIT have the potential to be used as a training modality in reproductive-age women, with similar effects to MICT on body composition/metabolic markers but inferior effects on CRF, suggesting that HIT/SIT may be considered a “time-efficient component″ of weight management programs. However, the variability in the secondary outcome measures, coupled with the small sample sizes in studies, limits this finding. Full article

(1) Background: Cardiopulmonary and brain functions are frequently impaired after COVID-19 infection. Exercise rehabilitation could have a major impact on the healing process of patients affected by long COVID-19. (2) Methods: The COVID-Rehab study will investigate the effectiveness of an eight-week cardiopulmonary rehabilitation program on cardiorespiratory fitness ($\dot{V}$O₂max) in long-COVID-19 individuals. Secondary objectives will include functional capacity, quality of life, perceived stress, sleep quality (questionnaires), respiratory capacity (spirometry test), coagulation, inflammatory and oxidative-stress profile (blood draw), cognition (neuropsychological tests), neurovascular coupling and pulsatility (fNIRS). The COVID-Rehab project was a randomised clinical trial with two intervention arms (1:1 ratio) that will be blindly evaluated. It will recruit a total of 40 individuals: (1) rehabilitation: centre-based exercise-training program (eight weeks, three times per week); (2) control: individuals will have to maintain their daily habits. (3) Conclusions: Currently, there are no specific rehabilitation guidelines for long-COVID-19 patients, but preliminary studies show encouraging results. Clinicaltrials.gov (NCT05035628). Full article