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.

This exploratory study investigates changes in the autonomic cardiac system of young analog astronauts in a hostile, confined, and isolated environment. It uses linear and nonlinear indices of heart rate variability (HRV) during a Mars analog mission to assess how HRV varies under day and night stressors. This study is guided by the hypothesis that significant HRV changes occur based on adaptation days, aiming to offer insights into autonomic nervous system (ANS) adaptation to environmental stressors. Over five days in August 2022, five analog astronauts faced adverse conditions in the Mojave Desert, simulating Martian conditions. Electrocardiograms were recorded daily for five minutes during morning and evening sessions to extract short-term RR time series. HRV parameters were analyzed using both time- and frequency-domain indices and nonlinear measures. Significant differences in HRV parameters across days highlight the mission environment’s impact on autonomic cardiac function. Morning measurements showed significant changes in average RR intervals and heart rate, indicating ANS adaptation. Nonlinear indices such as detrended fluctuation analysis and approximate entropy also showed significant differences, reflecting shifts in autonomic function. The Borg scale indicated reduced perceived exertion over time, aligning with HRV changes. Increased vagal activity during Mars analog adaptation under confinement/isolation may be crucial for cardiovascular adaptation and survival in future space flights.

This research explores maternal–fetal heart rhythm coupling (MFHRC) in full-term and moderate preterm labor using high-resolution joint symbolic dynamics (HRJSD) to identify distinct heart rate patterns indicative of physiological system couplings during active labor stages. This study evidences that preterm labor exhibits unique MFHRC patterns compared to full-term labor, potentially reflecting physiological responses and system complexities differences. The analysis involved 25 maternal–fetal RR time series from women in active full-term labor and 18 from those in moderate preterm labor. HRJSD was utilized to dissect the degree of coupling by examining specific maternal–fetal heart rhythm patterns and calculating global Shannon entropy for both groups. We observed that specific dominant heart rate patterns are preserved in both term and moderate preterm labor, suggesting an intrinsic aspect of cardiovascular coupling irrespective of the labor's condition. Additionally, we found variations in non-dominant patterns between term and preterm labor, which may reflect subtle differences in cardiac responses, hinting at possible adaptive fetal strategies in response to preterm labor conditions. An important finding of our research is the overall decrease in MFHRC in preterm labor, as indicated by higher Shannon entropy values. This decrease suggests a reduced synchronization of maternal–fetal heart rate rhythm during labor in preterm conditions. These insights highlight the importance of MFHRC analysis in understanding the distinct physiological interactions between mother and fetus during labor. The study's findings may pave the way for further research on prenatal health and developing interventions that may guide outcomes in preterm labor.

The aim of this study was to improve the diagnostic ability of fall risk classifiers using a Bayesian approach and the Simulated Annealing (SA) algorithm. A total of 47 features from 181 records (40 Center of Pressure (CoP) indices and 7 patient descriptive variables) were analyzed. The wrapper method of feature selection using the SA algorithm was applied to optimize the cost function based on the difference of the mean minus the standard deviation of the Area Under the Curve (AUC) of the fall risk classifiers across multiple dimensions. A stratified 60–20–20% hold-out method was used for train, test, and validation sets, respectively. The results showed that although the highest performance was observed with 31 features (0.815 ± 0.110), lower variability and higher explainability were achieved with only 15 features (0.780 ± 0.055). These findings suggest that the SA algorithm is a valuable tool for feature selection for acceptable fall risk diagnosis. This method offers an alternative or complementary resource in situations where clinical tools are difficult to apply.

Breathing rate asymmetry (BRA) refers to the observed disparities in the acceleration and deceleration phases of human respiration. The techniques employed to assess BRA could also be utilized in exploring hypertensive disorders like pre-eclampsia, which is known to cause autonomic cardiorespiratory changes. This study explores features of complexity, including the asymmetry (time irreversibility) of short-term breath-to-breath breathing rate variability among women with severe and moderate pre-eclampsia features compared to those with normal blood pressure. In our study, we retrospectively analyzed continuous respirogram recordings from women in labor, including those diagnosed with severe pre-eclampsia (SP = 22), moderate pre-eclampsia (P = 19), and normotensive control group (C = 35). Using these data, we calculated 5 min of breath-to-breath (BB) time series to measure Porta's index (P%), Guzik's index (G%), and Ehlers' index (E), alongside measures of asymmetrical entropy, including the entropy of acceleration runs (HAR), the entropy of deceleration runs (HDR), and total entropy (H). In addition, Fuzzy Entropy (FuzzEn) and Multiscale Fuzzy Entropy (MFE) over timescales 1–20 were calculated from the BB time series. The nonlinearity was assessed by surrogate analysis. The study's results revealed significant differences in short-term BRA; specifically, mean values of G% and E were the lowest in SP compared to C and P. Conversely, mean values of the HDR were higher in the SP group than the C. Higher mean values of MFE and a greater percentage of nonlinearity were observed in the SP group as compared to the C group. Our results suggest that women with severe pre-eclampsia may exhibit a higher short-term BRA characterized by a lower contribution of breathing rate decelerations to short-term variability, higher irregularity and nonlinearity of BB time series, and particularly more irregular behavior of decelerations compared to normotensive women. This may indicate a potential modification in the autonomic control of breathing rate and breathing instability.