Search Results (2,671)

Wearable devices are increasingly used for health and stress monitoring, yet their accuracy under dynamic, real-world conditions remains uncertain. This study validated the heart rate measurement accuracy of one chest-worn device (Zephyr BioHarness 3.0), a research-grade wrist-worn device (EmbracePlus), and five commercial wrist-worn wearable devices (Fitbit Charge 5, Fitbit Sense 2, Garmin Vivosmart 4, WHOOP 4.0, and Withings Scanwatch) against a 12-lead ECG using a 20 min protocol simulating real-life dynamics, including rest and varied-intensity walking. Device performance was evaluated across the full protocol and during transient states, defined as periods of rapid heart rate change. Accuracy and agreement were evaluated across per-second, 10 s, and 60 s resolutions. The Zephyr device showed a strong performance during all dynamic conditions. Among the wrist-worn devices, the Fitbit Charge 5 and Sense 2 showed the highest accuracy overall, while the Garmin Vivosmart 4 demonstrated greater stability during transitions. The WHOOP 4.0, Withings Scanwatch, and EmbracePlus devices performed acceptably during steady-state conditions, but were less accurate during transitions. Performance notably declined across all wrist-worn devices during transient states, with motion onset and large step changes in heart rate exacerbating measurement errors. Larger averaging windows improved accuracy by smoothing variability. The findings underscore that wrist-worn wearable devices may be better suited for average and trend heart rate monitoring rather than capturing acute dynamics. However, the Garmin and Fitbit devices showed suitable when requiring moderate accuracy during dynamic conditions. These results highlight the importance of context-specific validation and informed device selection to ensure effective use in health and stress-related applications. Full article

This study examines the impact of canopy structural characteristics on pedestrians’ visual perception and psychophysiological responses along four roads in the subtropical city of Guangzhou: Huadi Avenue, Jixiang Road, Yuejiang Middle Road, and Huan Dao Road. A Canopy Structural Index (CSI) was innovatively developed by integrating tree height, crown width, diffuse non-interceptance, and leaf area index, establishing a five-tier quantitative grading system. The study used multimodal data fusion techniques combined with heart rate variability (HRV) analysis and eye-tracking experiments to quantitatively decipher the patterns of autonomic nervous regulation and visual attention allocation under different levels of CSI. The results demonstrate that CSI levels are significantly correlated with psychological relaxation states: as CSI levels increase, time-domain HRV metrics (SDNN and RMSSD) rise by 15%–43%, while the frequency-domain metric (LF/HF) decreases by 31%, indicating enhanced parasympathetic activity and a transition from stress to relaxation. Concurrently, the allocation of visual attention toward canopies intensifies. The proportion of fixation duration increases to nearly 50%, and the duration of the first fixation extends by 0.3–0.8 s. The study proposes CSI ≤ 0.15 as an optimization threshold, offering scientific guidance for designing and pruning subtropical urban street tree canopies. Full article

Objectives: To compare the acute effects of upper cervical manipulation (CM) and manual massage (MM) to simulated CM (Sham) and Control conditions (Control) on heart rate variability (HRV) and blood pressure (BP) responses in women with non-elevated BP. Methods: A single-blind, four-arm, parallel-group, randomized, crossover, placebo-controlled trial recruited 15 apparently healthy women with non-elevated BP who visited the lab on four occasions with 48 h intervals to ensure adequate washout between interventions. A Latin square randomization approach was employed to assign participants to one of four experimental conditions: (1) Control: Rest without intervention; (2) CM: Bilateral high-velocity, low-amplitude manipulation of the upper cervical spine (C0–C2); (3) MM: A single 120 s session of MM release applied unilaterally to the anterior and posterior thigh, posterior lower leg, and lumbar musculature; or (4) Sham: Mimicking the positioning used in CM without the application of thrust manipulation. In each experiment, HRV, systolic and diastolic BP were measured at rest (Baseline) and every 15 min for 60 min after each intervention. All procedures were performed in the morning to avoid any confounding circadian rhythm effect on HRV and BP. Results: We found significant increases within conditions for RMSSDms (Control: Post-0 (p = 0.032), Post-15 (p = 0.023); Sham: Post-15 (p = 0.014); CM: Post-15 (p = 0.027)); SDNNms (Control: Post-45 (p = 0.037); CM: Post-45 (p = 0.014) and Post-60 (p = 0.019)); PNN50% (CM: Post-0 (p = 0.044), Post-15 (p = 0.044) and Post-45 (p = 0.019)); LF Power (ms2) (CM: Post-60 (p = 0.001)), and LF/HF ratio (MM: Post-60 (p = 0.022). Conclusions: Although no statistically significant between-condition differences were detected, within-condition changes with moderate-to-large effect sizes suggest potential clinical relevance of CM and MM. These preliminary findings emphasize the importance of effect sizes and may indicate greater translational significance in populations with non-elevated cardiovascular risk. Full article

Background: Optimizing training load and recovery is crucial for achieving peak performance in competitive wrestling, a sport characterized by high physical, technical, and psychological demands. Methods: This study compared the effects of two different training programs—one emphasizing high-intensity interval training (HIIT) sessions and the other based on traditional volume-oriented training—on both competitive performance and autonomic regulation measured by heart rate variability (HRV). A total of 24 elite wrestlers were divided into two equal groups, each following a different weekly training regimen over a 3-month period. HRV was recorded using a wearable 3-channel ECG Holter before training, immediately after training, and during recovery phases (up to 2 h post-exercise). HRV parameters were analyzed to assess training-induced stress and recovery status. Competitive performance was evaluated using official national championship scores and ranking positions. Results: Both training programs improved competitive performance, the HIIT-based regimen induced greater short-term suppression of parasympathetic activity (RMSSD: −32% vs. −14%; HF power: −40% vs. −18%) and increased sympathetic dominance (LF/HF: +56% vs. +22%) after training. Wrestlers in the HIIT group achieved a mean competition score of 17.92 ± 4.50 points, compared to 15.08 ± 6.26 points in the volume-oriented group. These acute autonomic shifts may provide a higher readiness for intense and explosive actions, which is advantageous in short and dynamic matches. In contrast, the volume-oriented program induced smaller acute autonomic changes but showed a slower recovery to baseline. Conclusions: These findings suggest that HRV-derived measures can serve as sensitive indicators of training load tolerance, recovery capacity, and stress susceptibility in combat sports athletes. This study highlights the value of integrating HRV monitoring into the periodization of combat training to individualize the load, prevent overtraining, and optimize performance outcomes. Full article

Treatment options for major depression are limited: only about one-third of patients achieve remission with first line treatments with no established predictive markers. Parameters associated with treatment refractory depression, including metabolic markers (increased BMI, increased triglyceride levels), inflammation markers (C-reactive protein, CRP), autonomic disturbances (reduced blood pressure, reduced heart rate variability), and brain morphology changes (increased volume of the choroid plexus and brain ventricle volumes), may serve such purpose. These features can be linked mechanistically to an increase in aldosterone plasma concentration due to a reduced mineralocorticoid receptor (MR) sensitivity. The primary CNS target of aldosterone is the nucleus of the solitary tract (NTS), which is also the entry point of the vagus nerve. This nucleus integrates signals from endocrine, inflammatory, chemoreceptive, and physiological parameters, including blood pressure. In search of a mechanism to overcome this pathology, we identified a molecule which is derived from the licorice plant glycyrrhiza glabra, namely glycyrrhizin and its biologically active metabolite enoxolone. These molecules potentially reverse the above-described pathology. They inhibit the enzyme 11beta hydroxysteroid-dehydrogenase type 2 (11betaHSD2) and the toll-like receptor 4 (TLR4). 11betaHSD2 regulates the activity of the mineralocorticoid receptor (MR) by degrading cortisol/corticosterone, which allows aldosterone to bind to the MR. TLR4 is the ligand for lipopolysaccharide (LPS, endotoxin) and trigger of innate immunity. Consequently, patients with increased inflammation markers, increased aldosterone, or low blood pressure may preferentially benefit from the treatment with glycyrrhizin/enoxolone. Importantly, these patients can be identified BEFORE treatment is initiated. Clinically, patients sharing these biological indicators are primarily young females or patients with a history of childhood trauma. A combination of enoxolone with standard antidepressants may therefore avoid a trial-and-error approach and allow to achieve recovery faster. Full article

Vocal production requires the coordinated control of respiratory, laryngeal, and autonomic systems. In individuals with high vocal demand, this physiological load may influence autonomic regulation, even in the absence of voice disorders. This scoping review systematically mapped current evidence on the relationship between voice production and autonomic nervous system (ANS) activity in adults, focusing exclusively on studies that assessed both systems simultaneously. A systematic search was conducted in PubMed, Scopus, Web of Science, Embase, and CINAHL, following PRISMA-ScR guidelines. Eligible studies included adults performing structured vocal tasks with concurrent autonomic measurements. Data were extracted and synthesized descriptively. Fifteen studies met the inclusion criteria. Most involved healthy adults with high vocal demand, while some included participants with subclinical or functional voice traits. Vocal tasks ranged from singing and sustained phonation to speech under cognitive or emotional load. Autonomic measures included heart rate (HR), heart rate variability (HRV), and electrodermal activity (EDA), among others. Four thematic trends emerged: autonomic synchronization during group vocalization; modulation of autonomic tone by vocal rhythm and structure; voice–ANS interplay under stress; and physiological coupling in hyperfunctional vocal behaviours. This review’s findings suggest that vocal activity can modulate autonomic function, supporting the potential integration of autonomic markers into experimental and clinical voice research. Full article

This study investigated differences in energy-expenditure (EE) modeling between badminton players of varying competitive levels during aerobic training. It evaluated the impact of sensor quantity and sample size on prediction model accuracy and generalizability, providing evidence for personalized training-load monitoring. Fifty badminton players (25 elite, 25 enthusiasts) performed treadmill running, cycling, rope skipping, and stair walking. Data were collected using accelerometers (waist, wrists, ankles), a heart rate monitor, and indirect calorimetry (criterion EE). Multiple machine learning models (Linear Regression, Bayesian Ridge Regression, Random Forest, Gradient Boosting) were employed to develop EE prediction models. Performance was assessed using R², mean absolute percentage error (MAPE), and root mean square error (RMSE), with further evaluation via the Triple-E framework (Effectiveness, Efficiency, Extension). Elite athletes demonstrated stable, coordinated movement patterns, achieving the best values for R² and the smallest errors using minimal core sensors (typically dominant side). Enthusiasts required multi-site sensors to compensate for greater execution variability. Increasing sensors beyond three yielded no performance gains; optimal configurations involved 2–3 core accelerometers combined with heart rate data. Expanding sample size significantly enhanced model stability and generalizability (e.g., running task R² increased from 0.49 (N = 20) to 0.95 (N = 40)). Triple-E evaluation indicated that strategic sensor minimization coupled with sufficient sample size maximized predictive performance while reducing computational cost and deployment burden. Competitive level significantly influences EE modeling requirements. Elite athletes are suited to a “low-sensor, small-sample” scenario, whereas enthusiasts necessitate a “multi-sensor, large-sample” strategy. Full article

Aims: The present study evaluated the acute morning effect of melatonin supplementation (5 mg) on cardiometabolic responses. Methods: For this purpose, 12 physically active men (22.1 ± 1.3 years; 1.7 ± 01 m; 74.7 ± 12.1 kg; 24.3 ± 2.7 m/kg²; VO₂max: 46.9 ± 2.3 mL/kg/min; 17.3 ± 5.2%F) were measured in a double-blind crossover protocol, where participants were measured before, during, and after a high-intensity interval exercise (HIIE) protocol [4 × 4 min at 95% of maximum heart rate (HRmax) with a 3 min interval at 60–70% of HRmax] followed by 30 min of recovery. At rest, the following variables were measured: HR, systolic blood pressure (SBP), diastolic blood pressure (DBP), lactate, and maximum oxygen consumption (VO₂max). At the end of each stage and interval, VO₂, respiratory exchange ratio (RER), and HR were measured. During recovery, VO₂, VCO₂, RER, SBP, DBP, and HR were measured. Results: Melatonin significantly enhanced recovery metabolism, as evidenced by increased VO₂ at Interval 3 (+2.2 mL/kg/min, p = 0.03, d = 0.69) and 5 min postexercise (+2.4 mL/kg/min, p = 0.02, d = 0.81). The RER was higher during Sprint 4 (+0.08, p = 0.01, d = 0.84), indicating greater carbohydrate reliance. Cardiovascular recovery was also improved, with a reduced HR at 30 min (−5 bpm, p = 0.04, d = 0.66) and lower SBP at 15 min (−8 mmHg, p = 0.02, d = 0.75). Lactate concentration at 30 min was lower with melatonin (−0.7 mmol/L, p = 0.03, d = 0.72). No significant effects were observed at rest or during early exercise. Conclusions: Acute morning melatonin intake may amplify metabolic responses to HIIE while facilitating cardiometabolic recovery. This dual-phase action may benefit athletes aiming to optimize energy expenditure, fat metabolism, and recovery during early-day training. Full article

This study developed and validated simplified, individualized heart rate (HR)-based regression models to predict energy expenditure (EE) during treadmill exercise without direct VO2 calibration, addressing the need for more practical and accurate methods that overcome limitations of existing predictions and facilitate precise EE estimation outside specialized laboratory conditions. Energy expenditure was measured by assessing oxygen uptake (VO₂) using a portable gas analyzer and predicted across three treadmill protocols: Bruce, Modified Bruce, and Progressive Speed. These protocols were selected to capture a wide range of exercise intensities and improve the accuracy of heart rate-based EE predictions. The six models combined heart rate, heart rate reserve (HRres), and demographic variables (sex, age, BMI, resting HR) using the Enter method of multiple regression, where all variables were included simultaneously to enhance the real-world applicability of the energy expenditure predictions. All models showed high accuracy with R² values between 0.80 and 0.89, and there were no significant differences between measured and predicted energy expenditure (p ≥ 0.05). HRres-based models outperformed others at submaximal intensities and remained consistent across sex, weight, BMI, and resting HR variations. By incorporating individual resting and maximal HR values, HRres models offer a personalized, physiologically relevant estimation method. These results support integrating HRres-based EE prediction into wearable devices to improve accessible and precise monitoring of physiological energy metabolism. Full article

CrossFit performance is influenced by physiological, neuromuscular, and perceptual factors, yet the extent to which these determinants vary by sex or training experience in standardized CrossFit Workouts of the Day (WODs) remains unclear. This study examined whether variables such as lactate accumulation, oxygen uptake dynamics, jump performance loss, and ventilatory responses relate differently to performance when stratified by sex and expertise. Fifteen trained athletes (eight males, seven females; overall mean age 27.7 ± 4.6 years) took part. Assessments included body composition, squat (SJ) and countermovement jumps (CMJ), and maximal oxygen consumption [VO₂max]. On a separate day, they performed Fran (21-15-9 thrusters and pull-ups, Rx or scaled) The prescribed (‘Rx’) version used standardized barbell loads (43 kg for men, 29 kg for women), while the scaled version involved reduced loads or pull-up modifications. Respiratory gas exchange and heart rate were continuously monitored, while blood lactate and jump performance were measured pre- and post-WOD. Workout completion time [s] was the primary outcome. Correlation heatmaps explored associations in the overall sample and by sex and expertise. Mean completion time was 422.1 ± 173.2 s (range: 200–840). Faster performance correlated with higher ventilatory responses [ΔVe, r = −0.60, p = 0.018], greater mean VO₂ (r = −0.62, p = 0.014), superior jump power [CMJ pre, r = −0.65, p = 0.009], and higher post-WOD lactate [r = −0.54, p = 0.036]. Sex-stratified analyses showed that males relied on ventilatory efficiency and neuromuscular power, whereas females were more constrained by performance loss and higher resting perceived exertion (RPE). Experts depended on ventilatory and neuromuscular efficiency, while initiates showed stronger associations with decrements in jump performance and higher RPE. These findings highlight subgroup-specific performance profiles and reinforce the need for tailored training strategies in CrossFit athletes. Full article

We here delve into the intricate and evolving concepts of brain death and consciousness, particularly at the end of life. We examine the historical and technological advancements that have influenced our understanding of death, such as mechanical ventilation and resuscitation techniques. These developments have challenged traditional definitions of death, leading to the concept of brain death, defined as the irreversible loss of all brain functions, including the brainstem. We emphasize that consciousness exists on a continuum, ranging from full alertness to deep coma and complete cessation of brain activity. It explores various disorders of consciousness, including coma, vegetative state, minimally conscious state, and locked-in syndrome, each with distinct characteristics and levels of awareness. Neuroimaging techniques, such as EEG, fMRI, and DTI, are highlighted for their crucial role in diagnosing and understanding disorders of consciousness. These techniques help to detect covert consciousness, assess brain activity, and predict recovery potential. The phenomenon of the “wave of death,” which includes a paradoxical surge in brain activity at the point of death, is also discussed. We address the challenges in defining and understanding both death and consciousness, calling for biologically grounded, ethically defensible, and culturally sensitive definitions. We advocate for standardized neuroimaging protocols, longitudinal studies, and the integration of artificial intelligence to improve diagnosis and treatment. In conclusion, the document underscores the importance of an integrated, evidence-based approach to understanding the gray zones between life and death, recognizing that consciousness and death are dynamic processes with both biological and experiential dimensions. Full article

This study tested whether classic and specific bioelectrical impedance vector analysis (BIVA) parameters could explain metabolic and mechanical performance in endurance-trained trail runners. Fifteen males ($\dot{\mathrm{V}}$O₂max 61.04 ± 6.91 mL·kg⁻¹·min⁻¹) completed a 60-min treadmill protocol at 70% $\dot{\mathrm{V}}$O₂max across randomized slopes (−7% to +7%), with continuous gas-exchange, heart-rate, and running-power recording; whole-body BIVA was obtained immediately pre- and post-exercise. Post-test, impedance and resistance increased (+2.73%, +2.84%), while reactance (Xc) and phase angle decreased (−2.36%, −4.91%); all were significant and mirrored by both classic and specific indices, consistent with acute fluid loss and altered cellular status. After Benjamini–Hochberg adjustment, baseline Xc/height correlated inversely with $\dot{\mathrm{V}}$CO₂peak and $\dot{\mathrm{V}}$CO₂mean, whereas exercise-induced changes in ΔXc/height and ΔXcspecific correlated positively with both metabolic variables and mean power. Stepwise regression retained ΔXc/h or ΔXcspecific as the only BIVA predictors for $\dot{\mathrm{V}}$CO₂peak, $\dot{\mathrm{V}}$CO₂mean, and mean power output, explaining ~31–36% and ~22–23% of the variance, respectively; classic and specific approaches performed similarly. No bioelectrical variable predicted $\dot{\mathrm{V}}$O₂max. These preliminary findings suggest that acute reactance shifts may provide a modest yet sensitive, non-invasive index of exercise-induced physiological responses, warranting confirmation in larger and more diverse cohorts. Full article

Metabolic syndrome (MetS) is a multifactorial clinical condition characterized by the co-occurrence of abdominal obesity, impaired glucose metabolism, high blood pressure, and dyslipidemia. Non-pharmacological strategies, such as hypocaloric diets (HD) and structured physical training (PT), have shown promise in improving metabolic and functional outcomes in this population. The aim of this prospective interventional study was to evaluate the effects of a 16-week program combining HD with PT on ventilatory efficiency and cardiometabolic risk markers in women with MetS. Forty-one sedentary women (aged 45–55 years) with clinically diagnosed MetS underwent anthropometric, metabolic, nutritional, and cardiopulmonary assessments before and after the intervention. Participants engaged in 60 min exercise sessions three times per week and followed a personalized hypocaloric diet targeting 5–10% weight loss. Post-intervention analyses revealed significant reductions (p ≤ 0.05) in body weight (from 86.6 kg ± 3.3 kg to 78.2 kg ± 3.3 kg), body fat percentage (40.1% ± 0.6% to 33.4% ± 1.6%), and waist circumference (105.1 cm ± 1.2 cm to 95.7 cm ± 1.9 cm). Improvements were also observed in fasting glucose (from 117.1 mg/dL to 95.1 mg/dL) and triglycerides (158.8 mg/dL ± 9.1 mg/dL to 111.8 mg/dL ± 9.1 mg/dL), and in lean mass percentage (59.9% ± 6.5% to 66.6% ± 1.7%). Cardiopulmonary variables showed enhanced ventilatory function, with increased VO₂peak (1.59 L/min ± 0.1 L/min to 1.74 ± 0.1 L/min), improved oxygen uptake efficiency slope (OUES), and a steeper VO₂/workload relationship. Resting heart rate and blood pressure declined significantly (69.9 bpm ± 2.0 bpm to 64.9 ± 1.8 bpm; 145.4 mmHg ± 3.9/80.2 ± 3.0 mmHg to 140.1 mmHg ± 2.7/75.2 ± 1.6 mmHg). In conclusion, the 16-week intervention combining HD with PT proved effective for reducing cardiometabolic risk factors and enhancing ventilatory efficiency, suggesting improved integration of oxygen uptake, transport, and utilization in the women with MetS assessed. Full article

Cardiomyopathies affect over 3 million individuals globally, with conventional treatments exhibiting up to 60% resistance and 25% 30-day readmission rates. This review synthesizes the current evidence on the role of neuro-immune interactions in the pathogenesis of cardiomyopathy and evaluates emerging therapies targeting this axis. We systematically examined clinical trials and mechanistic and multi-omics data across cardiomyopathy phenotypes, focusing on autonomic-immune dysregulation. Sympathetic overactivation, present in approximately 85% of patients, correlates with elevated pro-inflammatory cytokines (TNF-α, IL-1β, and IL-6) and contributes significantly to therapeutic non-response. Concurrent parasympathetic withdrawal impairs cholinergic anti-inflammatory pathways, as reflected by reduced heart rate variability and baroreflex sensitivity. At the molecular level, shared mechanisms include inflammasome activation, neuroimmune synaptic signaling, and neurogenic inflammation. Emerging therapies targeting this axis are promising. Vagus nerve stimulation, as demonstrated in the INOVATE-HF trial, improves functional outcomes, whereas IL-1β antagonists reduce cardiovascular events by 15–20% in the context of inflammatory diseases. Bioelectronic interventions, such as transcutaneous vagal nerve stimulation and baroreflex activation therapy, offer noninvasive dual-modulatory strategies that address both neural and immune pathways, positioning the neuroimmune axis as a central driver of cardiomyopathy, regardless of etiology. The integration of genetic and metabolomic profiling may enable precision therapies targeting neuroimmune circuits, thereby overcoming the limitations of hemodynamic-focused care. This mechanistic framework shifts the therapeutic paradigm from symptomatic relief to targeted modulation of pathogenic pathways, with implications for millions of patients with cardiomyopathy and broader inflammatory cardiovascular disorders. Full article

Cardiovascular diseases (CVDs) remain the leading cause of global mortality, with ischemic heart disease (IHD) being the most prevalent and deadly subtype. The growing burden of IHD underscores the urgent need for effective early detection methods that are scalable and non-invasive. Heart Rate Variability (HRV), a non-invasive physiological marker influenced by the autonomic nervous system (ANS), has shown clinical relevance in predicting adverse cardiac events. This study presents a photoplethysmography (PPG)-based Zhurek IoT device, a custom-developed Internet of Things (IoT) device for non-invasive HRV monitoring. The platform’s effectiveness was evaluated using HRV metrics from electrocardiography (ECG) and PPG signals, with machine learning (ML) models applied to the task of early IHD risk detection. ML classifiers were trained on HRV features, and the Random Forest (RF) model achieved the highest classification accuracy of 90.82%, precision of 92.11%, and recall of 91.00% when tested on real data. The model demonstrated excellent discriminative ability with an area under the ROC curve (AUC) of 0.98, reaching a sensitivity of 88% and specificity of 100% at its optimal threshold. The preliminary results suggest that data collected with the “Zhurek” IoT devices are promising for the further development of ML models for IHD risk detection. This study aimed to address the limitations of previous work, such as small datasets and a lack of validation, by utilizing real and synthetically augmented data (conditional tabular GAN (CTGAN)), as well as multi-sensor input (ECG and PPG). The findings of this pilot study can serve as a starting point for developing scalable, remote, and cost-effective screening systems. The further integration of wearable devices and intelligent algorithms is a promising direction for improving routine monitoring and advancing preventative cardiology. Full article