Search Results (1,571)

This review examines what constitutes heart rate variability (HRV), the relationship between HRV and the autonomic nervous system, and the physiology driving HRV. HRV is correlated with vagal nerve activity and parasympathetic nervous activation. Higher HRV is correlated with youth, active lifestyle, adaptive capacity, and good health. Next, the review examines the medical significance of HRV, especially the correlation between lower HRV and the presence of medical and psychological disorders. In general, HRV serves as a biomarker for health and disease, an index of autonomic nervous system dysregulation, an index of prefrontal cortical functionality, and a marker for psychopathology across diagnoses. Higher HRV is associated with several characteristics associated with successful psychotherapy and hypnotherapy: social engagement, compassion, emotional regulation, and cognitive flexibility. Given this association, somatic regulation should be regarded as integral to treatment alongside psychotherapy and hypnosis. Understanding HRV can enable the psychotherapist and hypnotherapist to optimize treatment. In effect, the therapist can harness the power of the brain and nervous system to better prepare the patient for therapy and to enhance the process of therapy. This review encourages therapists to utilize several strategies and interventions to increase patients’ HRV levels prior to and during therapy. The review will be most applicable for those hypnotherapists who integrate hypnosis into counseling and psychotherapy. The review describes the process by which HRV biofeedback training guides the individual to voluntarily increase HRV. It also identifies a number of lifestyle parameters and self-care practices (including self-hypnosis) that increase HRV. Encouraging lifestyle and self-care practices to increase HRV can support a greater response to hypnotherapy and psychotherapy. With additional training, hypnotherapists can integrate HRV biofeedback into a hypnosis practice. Further, several simple interventions already within the scope of most hypnosis practitioners can be utilized to enhance HRV at the beginning of a hypnotherapy process, and again during the process of therapy. Full article

Human rhinoviruses (HRVs) are the primary cause of the common cold, a highly contagious upper respiratory tract infection characterized by nasal congestion, sneezing, and sore throat. HRV replication depends on its 3C protease (HRV-3Cpro), a key enzyme that cleaves the viral polyprotein into functional proteins essential for viral maturation. Currently, no FDA-approved inhibitors specifically target HRV-3Cpro. While rupintrivir, a synthetic inhibitor, advanced to clinical trials, it ultimately failed due to limited efficacy. This study investigated the potential of Vitex negundo (or lagundi)—a medicinal plant traditionally used in the Philippines for treating colds and respiratory ailments—as a source of natural HRV-3Cpro inhibitors through in silico molecular docking and pharmacokinetic (ADMET) evaluation. Fifteen phytochemicals were screened, with five compounds exhibiting strong binding affinities exceeding that of the reference inhibitor rupintrivir (−6.1 kcal/mol): agnuside (−6.9 kcal/mol), luteolin 7-O-glucoside (−6.7 kcal/mol), 2′-p-hydroxybenzoyl mussaenosidic acid (−6.5 kcal/mol), 6′-(p-hydroxybenzoyl) mussaenosidic acid (−6.5 kcal/mol), and luteolin (−6.2 kcal/mol). Among these, luteolin emerged as a particularly promising lead compound, forming stable hydrogen bonding and hydrophobic interactions with HRV-3Cpro. Luteolin also demonstrates a favorable ADMET and safety profile, predicted to be non-mutagenic and non-hepatotoxic. These findings position luteolin as a potential plant-based HRV-3Cpro inhibitor, warranting further in vitro and in vivo studies to validate its antiviral efficacy and pharmacokinetic properties. Full article

Small fiber neuropathy (SFN) is an early and common manifestation of diabetic polyneuropathy in type 2 diabetes mellitus (T2DM), often presenting with pain, dysesthesia, and autonomic dysfunction. Conventional diagnostic methods primarily assess large nerve fibers and may miss early small fiber damage, while skin biopsy, though considered the reference standard, is invasive. Corneal confocal microscopy (CCM) offers a rapid, noninvasive alternative for visualizing and quantifying small nerve fiber pathology in vivo. This was a monocentric observational study including 80 adults with T2DM (18–75 years), conducted at Alexandrovska Hospital, Sofia. Peripheral neuropathy was evaluated using a modified Neuropathy Disability Score and CCM-derived corneal nerve fiber density (CNFD), length (CNFL), and branching density (CNBD). Autonomic and sudomotor function were assessed by cardiovascular reflex tests and Sudoscan. Additional measures included vibration perception threshold, carotid intima–media thickness, body composition analysis, and laboratory parameters. Autonomic neuropathy was present in 66.7% and peripheral neuropathy in 57.5% of participants. Affected patients were older and had higher BMI and longer diabetes duration; peripheral neuropathy was additionally associated with higher HbA1c. Corneal nerve parameters negatively correlated with diabetes duration, HbA1c, intima–media thickness, and vibration threshold. Patients with diabetic retinopathy showed significantly reduced CNFD and CNFL. ROC analysis demonstrated significant discriminative ability of the HRV index for identifying peripheral neuropathy and of CNFD for detecting sudomotor dysfunction. These findings support CCM as a valuable, noninvasive marker of small fiber damage, closely linked to metabolic control, vascular impairment, and both sensory and autonomic dysfunction in T2DM. Full article

Background/Objectives: Heart rate variability (HRV) is a non-invasive marker of autonomic nervous system function with established prognostic value after acute coronary syndrome (ACS). The clinical relevance of temporal changes in short-term HRV remains insufficiently defined. This study evaluated short-term HRV dynamics and their association with mortality after ACS. Methods: This retrospective–prospective study included 230 patients with acute myocardial infarction. Five-minute resting ECG recordings were obtained on day 1 and day 21. Time- and frequency-domain HRV parameters were analyzed, and delta values were calculated. The primary endpoint was overall mortality. Survival was assessed using Kaplan–Meier analysis and Cox regression. Results: Patients who died during follow-up had lower HRV values on day 21 and more pronounced declines in selected parameters. In multivariable analysis, decreased ΔLF and shorter RR intervals independently predicted overall mortality. Conclusions: Short-term HRV provides a practical bedside assessment of autonomic function after ACS. Unfavorable temporal changes likely reflect persistent autonomic imbalance and may offer additional prognostic insight. Larger contemporary studies are needed to confirm these findings. Full article

Paradoxical insomnia (PI) is characterized by a discrepancy between subjective sleep complaints and objectively preserved sleep, yet its autonomic mechanisms remain poorly understood. This study examined stage-specific autonomic characteristics of PI using heart rate variability (HRV) analyses in a large population-based cohort. HRV features were extracted from non-overlapping five-minute windows across non-rapid eye movement (NREM) sleep, rapid eye movement (REM) sleep, and wake after sleep onset (WASO). Group differences were evaluated using FDR-corrected univariate analysis, multivariate embedding, and supervised machine learning. Whole-night, NREM, and REM features showed substantial overlap among groups. In contrast, the most consistent between-group differences emerged during WASO. Multivariate analysis showed the greatest group displacement during WASO, with UMAP centroid distances exceeding those observed during NREM and REM sleep. Supervised models trained on WASO-specific features achieved the highest classification performance, yielding an accuracy of 0.629 and an F1-score of 0.683 for PI versus normal sleep. Taken together, these findings suggest that WASO is the stage in which between-group HRV differences are most consistently detectable across complementary analyses, although several dispersion-based findings were substantially influenced by WASO window count. Full article

This study systematically examines the robustness of the Akaike Information Criterion (AIC) in determining the optimal order (p) of an autoregressive (AR) model applied to the RR interval time series of the PhysioNet healthy subject database. The AR approach is widely used to estimate the power spectral density (PSD) of heart rate variability (HRV), and accurate order selection is essential for model stability and reliable spectral estimation. Although the AIC is designed to balance model fit and complexity, it suffers from the problem of arbitrary model selection. This study provides a quantitative robustness analysis of information-criterion-based AR order selection under controlled expansion of the search space. Specifically, we investigated the behavior of the AIC using the PhysioNet database (N = 1257) under conditions where the maximum search order was set to an excessively high value (p = 50), far exceeding the commonly recommended range. Our analysis suggested that the AR model began to capture subtle noise and nonstationary components rather than the intrinsic HRV structure, leading to overfitting and excessive order selection, resulting in false peaks in the PSD and reduced robustness. In conclusion, order decisions based solely on information criteria such as the AIC become unstable when the search range is too large. To ensure robustness, it is recommended to complement the AIC with more stringent criteria such as the Bayesian Information Criterion (BIC) or Final Prediction Error (FPE), in addition to the traditional maximum order restriction. Full article

Type 2 diabetes mellitus is associated with major cardiovascular complications, including cardiac autonomic neuropathy, which contributes to sympathetic–parasympathetic imbalance and increases susceptibility to arrhythmias and sudden cardiac death. Heart rate variability, assessed through R–R intervals on electrocardiography and 24 h Holter monitoring, represents a sensitive, non-invasive marker of autonomic dysfunction and arrhythmogenic risk. In patients with type 2 diabetes mellitus, chronic hyperglycaemia, oxidative stress, and metabolic inflammation lead to early impairment of the autonomic nervous system, manifested by consistent reductions in SDNN, RMSSD, pNN50, total power, and the high-frequency component, indicating diminished parasympathetic tone and sympathetic predominance. Nonlinear HRV indices demonstrate a loss of complexity and fractal organisation, providing additional prognostic value beyond conventional time- and frequency-domain analyses. Reduced HRV correlates with the severity of cardiac autonomic neuropathy, duration of diabetes, and poor glycaemic control, identifying patients with increased arrhythmogenic vulnerability. HRV analysis enables prediction of arrhythmic risk, facilitating the identification of high-risk individuals and guiding personalised interventions. The integration of HRV assessment into routine clinical practice may improve the early detection of subclinical autonomic neuropathy and optimise cardiovascular risk stratification and management in patients with type 2 diabetes mellitus. Full article

Introduction: This study investigated heart rate variability (HRV) and perceived recovery status (PRS) in relation to sprint performance in competitive athletes involved in sprint events. A secondary aim was to explore potential gender-based differences in these relationships. Methods: Fifty-six sprint-trained athletes (21 males, 35 females; age 16–21) participated in a 5-day in-season microcycle. Daily morning HRV was measured using Polar H10 chest straps and the HRV4Training app, with the root mean square of successive differences (LnRMSSD) used as the primary HRV marker. Perceived recovery was assessed each morning using the PRS scale. On each day, athletes completed 20 m maximal sprint tests. Linear mixed-effects models were used to examine the relationships between LnRMSSD, PRS, gender, and sprint performance while accounting for repeated measurements within athletes. Results: Linear mixed-effects modeling revealed that LnRMSSD was a significant negative predictor of sprint time (β = −0.019, p = 0.003), indicating that higher parasympathetic activity was associated with faster sprint performance. PRS was also a significant negative predictor of sprint performance (β = −0.014, p = 0.008). Conclusions: Daily recovery markers were associated with sprint performance in competitive sprint athletes, with potential gender-specific patterns that should be interpreted cautiously. Both LnRMSSD and PRS were significantly associated with sprint performance, highlighting the relevance of combining physiological and subjective recovery markers in athlete monitoring. Full article

Background/Objectives: Heart rate variability (HRV) and cerebral autoregulation (CAR) reflect physiologic processes that may influence neurological injury in children supported with extracorporeal membrane oxygenation (ECMO). Although abnormalities in both have been associated with adverse neurological outcomes, their physiologic relationship during ECMO remains unclear. Methods: This retrospective single-center study evaluated the association between HRV and CAR during the first 24 h of ECMO support and assessed their independent relationships with neurological outcome. Patients with at least two hours of simultaneous HRV and CAR monitoring within 24 h of ECMO initiation were included. HRV metrics were derived from artifact-free NN intervals across time, frequency, and nonlinear domains, while CAR was quantified using the cerebral oximetry index (COx), with impaired CAR defined as COx > 0.3. Associations between HRV indices and COx were examined using Spearman correlations at hourly and 24 h resolutions. Unfavorable outcome was defined as death or a Pediatric Cerebral Performance Category (PCPC) score ≥3 at discharge with deterioration from baseline. Results: Eighty-nine patients met inclusion criteria, and 16% demonstrated impaired CAR. HRV measures were reduced relative to age-adjusted norms in both CAR groups without significant differences between groups. Correlations between HRV indices and COx were consistently weak. Overall, 50% experienced unfavorable neurological outcomes. In adjusted logistic regression models, NN skewness and COx were independently associated with outcome, although only NN skewness remained significant in interaction analyses. Conclusions: HRV and CAR exhibited limited physiological coupling during early ECMO support, while each measure provided independent prognostic information with respect to neurological outcome. Full article

Remote tower (rTWR) operations are reshaping air traffic control but introduce significant human-factor risks, notably cognitive fatigue induced by prolonged screen-based visual surveillance. To mitigate these risks in a safety-critical domain where missed detections can be catastrophic, we propose a non-intrusive, multimodal fatigue detection framework fusing ocular and cardiac signals. A high-fidelity simulation study with 36 controllers was conducted to collect eye-tracking and electrocardiogram (ECG) data, from which a 12-dimensional feature vector—integrating gaze entropy and heart rate variability (HRV)—was extracted. Addressing the severe class imbalance and scarcity of fatigue samples in physiological data, we developed a cost-sensitive XGBoost classifier combining SMOTE oversampling with a dynamically weighted loss function. Experimental results show that the proposed framework performed well under mixed-subject evaluation and improved sensitivity to fatigue events. Although a marked performance drop was observed under LOSO evaluation, personalized calibration partially alleviated this limitation, indicating the potential of the framework for real-time fatigue monitoring in remote tower operations. Full article

This study proposes an exploratory framework for identifying stress locations during travel with low-speed mobility devices (LMDs), such as electric wheelchairs. In this framework, stress factors perceived during LMD travel were identified through a post-ride questionnaire, and the travel route was divided into 100 m segments to enable location-specific stress evaluation. The identified factors were quantified using environmental data to construct an environment-based stress estimation index. Based on these quantified factors, a Composite Stress Score (CSS) was calculated to estimate stress levels along the route. Experiments with healthy adult participants were conducted to examine the feasibility of the proposed method. The results identified poor road surface conditions and vibrations, encounters with other road users, and narrow sidewalks as key stress factors during LMD travel. To examine whether the proposed method captures stress-related responses, correlations between CSS-based stress estimates and heart rate variability (HRV) indices were analyzed. The results showed that CSS calculated from poor road surface/vibrations, encounters with other road users, and narrow sidewalks exhibited moderate negative correlations with SDNN, suggesting that higher CSS values may correspond to increased physiological stress responses. These findings provide preliminary support for the exploratory feasibility of estimating potential stress locations during LMD travel using environmental data. However, the generalizability of the results is limited due to the specific experimental route and the use of healthy adult participants. Full article

Background/Objectives: Aortic stenosis is associated with autonomic nervous system (ANS) imbalance, while diabetes mellitus is a major contributor to cardiac autonomic neuropathy. Their coexistence may result in more pronounced autonomic dysfunction not fully captured by conventional assessment. This study aimed to compare ANS function in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement (TAVR), according to diabetes status. Methods: This cross-sectional study included 74 patients with severe aortic stenosis referred for TAVR, including 21 patients with diabetes mellitus. Autonomic function was evaluated using non-invasive ECG-based analysis, incorporating short-term and 24 h Holter-derived heart rate variability (HRV), nonlinear Poincaré plot indices, and deceleration and acceleration capacity. Ambulatory blood pressure monitoring and standard clinical and echocardiographic assessment were performed. Results: Patients with diabetes mellitus demonstrated significantly lower long-term HRV parameters and reduced nonlinear Poincaré plot indices compared with non-diabetic patients, indicating altered autonomic modulation. Short-term HRV showed similar trends without statistical significance. Echocardiographic severity of aortic stenosis and left ventricular systolic function were comparable between groups. Conclusions: Autonomic dysfunction appears to be more pronounced in patients with severe aortic stenosis and diabetes mellitus, predominantly affecting parasympathetic modulation. ECG-derived autonomic parameters may offer complementary insight into ANS involvement in this population and warrant further investigation. Full article

Frontal alpha asymmetry (FAA), a pattern of brain activity that reflects the difference in alpha wave power between the left and right frontal areas of the brain, is considered a stable marker for an individual’s tendency to experience either more approach-related or withdrawal-related emotions. On the other hand, electrodermal activity (EDA) measures arousal by tracking changes in skin sweat, which are controlled by the sympathetic nervous system. This study explores the interrelation between EDA features, obtained from time and frequency domains, with FAA by means of the mutual information. Multiple cognitive tasks such as EAT, ship search, PVT and N-Back were analyzed in 10 participants in intervals of two hours over 24 h (12 trials), in which they had to face sleep deprivation conditions. The most informative EDA features about FAA, were used to identify the two main clusters associated to high and low FAA values through the hierarchical agglomerative clustering approach. Once data is labeled, a supervised classifier based on support vector machines (SVMs) is used to identify positive and negative emotional states by using a rigorous one-trial out cross-validation scheme. Results show consistent performance within tasks and trials, achieving accuracy values over 80% on average, giving an important insight about the use of EDA signal as an alternative to the more complex FAA measurement for tracking positive or negative emotional states. Full article

Objective: This study examined whether changes in electroencephalography (EEG)-derived indices, photoplethysmography (PPG)-derived autonomic nervous system indices, heart rate, and rating of perceived exertion (RPE) post-high-intensity exercise differ depending on sleep duration. Methods: Forty physically healthy female university students in their twenties were randomly assigned to the sleep restriction (SR) or normal sleep (NS) group. EEG-derived indices—the theta-to-beta ratio (TBR) and spectral edge frequency at 90% (SEF-90)—and PPG-derived autonomic nervous system indices (HRV index, sympathetic activity, and parasympathetic activity) were measured for one minute at rest before exercise and for one minute immediately after exercise. Heart rate was assessed at rest, immediately after exercise, and at 5, 10, and 15 min post-exercise. The group × time interaction effects were assessed using two-way mixed-design analysis of variance, followed by post hoc analyses. Results: TBR increased significantly post-exercise in the SR group (p = 0.002) with no significant change in the NS group. SEF-90 decreased significantly in the SR group (p < 0.001) with no significant change in the NS group. The HRV index decreased significantly in the SR group (p = 0.004) with no significant change in the NS group. Sympathetic activity increased and parasympathetic activity decreased significantly in the SR group (both p < 0.001). Heart rate was significantly higher in the SR group at rest (p < 0.001), immediately after exercise (p = 0.020), and 5 min post-exercise (p = 0.009). RPE was significantly higher in the SR group (p = 0.003). Conclusions: In healthy young adult women, the central and autonomic nervous systems respond differently to high-intensity exercise depending on sleep duration. Full article

We investigate the use of non-invasive, dual-wavelength (630 nm red/940 nm near-infrared) LED irradiation of the skull for relieving chronic neck and shoulder pain. A low-energy device was applied bilaterally for 15 min, with assessments of pain performed using the numeric rating scale (NRS), muscle relaxation assessed via infrared thermography, and autonomic function determined through heart-rate variability (HRV) analysis. The results demonstrated a mean NRS score reduction of 2.4 points, a 0.6 °C increase in cervical skin temperature, and a significant increase in HRV’s root mean square of successive differences, indicating improved autonomic regulation. This technique shows promise for effectively relaxing muscles, alleviating pain, and enhancing autonomic function. Full article