Search Results (175)

Background: Resynchronization therapy has become a cornerstone in patients with heart failure (HF). Recent advancements in this field have led to the development of the so-called “left bundle branch area pacing” (LBBAP), a form of pacing where a single ventricular catheter directly addresses the left bundle for a more physiological stimulation. The current literature provides encouraging evidence regarding this topic, but there is still limited data for the older population, particularly those aged ≥75 years. This review aims to clarify how LBBAP has been explored in this cohort and if its application could be safe and effective even in the most advanced stages of life. Methods: A search of articles from PubMed was conducted. Patients were considered older if above 75 years of age. Data regarding Italian statistics were obtained from national registries. Results: The current literature supports the safety and effectiveness of LBBAP in older patients across different indications, with outcomes comparable to those reported in younger patients and a suggested cost-effectiveness. Conversely, data regarding patients affected by cardiac amyloidosis are still inconclusive. Conclusions: LBBAP represents a valuable resource for patients of all ages, but frailty is a major issue in the older population that needs to be addressed. The potential integration of this technology with defibrillator capabilities will enable an even more extensive application in the near future. Full article

Marathons are one of the ultimate challenges of human endeavor. As a consequence of the growing passion of amateur runners for this discipline, a strong need has been shown for counselling during the preparation and for advice on how to manage their efforts during the race. This monitoring should be based on parameters collected during the race and correctly interpreted. Multifractality parameters, which have proved their relevance in many other areas of signal processing, are natural candidates for this purpose. This paper shows that, due to the extreme irregularity of the data, the previously used multifractal techniques cannot be applied in this context, in contrast with the recently introduced parameters based on the weak scaling exponent, which require no a priori assumptions for their use; these parameters yield new classification parameters in the processing of physiological data captured on marathon runners. The comparison of their values reveals how marathon runners handle variations in the irregularity of their races and therefore gives a new insight on the way that runners of different levels conduct their run; therefore, this study shows that the use of these parameters offers a promising tool in order to give advice on how to improve performances. Full article

Cardiac pacing has undergone a significant transformation in the last decade. Leadless pacing (LP), once only a conceptual idea stemming from the early interest in eliminating lead-related complications of transvenous pacemakers, has now become a reality in clinical practice. Since the introduction of the first human single-chamber asynchronous leadless ventricular pacing in 2012, atrioventricular-synchronized single- or dual-chamber leadless pacing systems have been approved for clinical use since 2020. Leadless cardiac resynchronization therapy (CRT) has shown optimistic results in case series and awaits its full utility in real-world clinical practice. With the successful feasibility study of leadless conduction system pacing, we are eagerly awaiting long-term safety and efficacy data on a large scale. Another important frontier is the development of self-rechargeable LP, which may be an ideal pacemaker for the future and may reduce the burden of multiple device replacements as batteries near the end-of-service. Totally extravascular percutaneous leadless pericardial micro-pacemaker system implantation is under development. In this state-of-the-art review, we examine the evolution of cardiac pacing, emphasizing the development and utility of LP to meet maximum physiological pacing needs, optimize atrioventricular synchrony and cardiac resynchronization, and broaden its indications. Full article

Heart Rate Variability (HRV) biofeedback could be considered as a tool to help athletes to optimize their performance. This study aimed to examine the effects of a one-week HRV biofeedback (HRV-BFB) program on physiological indices, sensorimotor functions, and kata performance in Eastern martial arts athletes. Forty high-level martial arts athletes (karate, wushu, taekwondo, kyokushinkai) aged 17–27 years were divided into two groups: a control group (n = 20) and a biofeedback group (BFB, n = 20). Athletes from both groups underwent assessment of sensorimotor functions and the technical quality of their kata routines. The primary outcome was the expert-rated kata performance score. All routines were video-recorded and independently rated by three certified judges. The BFB group completed a hybrid HRV-BFB program consisting of supervised resonance-frequency breathing sessions in the laboratory and one week of home-based practice. During supervised sessions, athletes performed slow abdominal-paced breathing (6 breaths/min). At home, they practiced the same breathing pattern twice daily for one week (5 min per session, smartphone-guided). Nonparametric tests were used because several variables deviated from normality, and the sample size per group was limited (n = 20). After completing the HRV-BFB training, movement oscillation frequency improved significantly, reflected by lower movement oscillation frequency (p = 0.0009, r = 0.79), faster choice reaction time at a tendency level (p = 0.0793, r = 0.39), and an increase in blood volume pulse (BVP) (p = 0.037, r = 0.48) in BFB group compared to control group. Following BFB training, the judges’ scores did not change in the control group, while a significant increase was observed in the BFB group (p = 0.038, r = 0.44), indicating a positive effect of BFB training on kata performance. Regular HRV-BFB training emphasizing slow-paced abdominal breathing may enhance autonomic regulation, fine motor control, and improve the technical execution of kata routines in athletes. Full article

Resilience is commonly framed as a psychological trait, yet clinical and experimental evidence demonstrates that resilience failures emerge concurrently across metabolic, endocrine, immune, and cognitive domains. This review examines resilience as a bioenergetic property constrained by how organisms allocate finite metabolic resources under stress. We synthesize evidence from endocrinology, mitochondrial biology, immunometabolism, and stress physiology to propose a parsimonious, hypothesis-driven Energy Allocation System (EAS) in which the hypothalamic-pituitary-adrenal (HPA), thyroid (HPT), and gonadal (HPG) axes are conceptualized as a coordinated energy-governance network. Despite extensive investigation within these individual fields, the literature lacks an integrative physiological framework explaining why multisystem stress responses co-occur in predictable endocrine and metabolic patterns. Within this framework, mitochondrial reserve capacity serves as the limiting substrate through which hormonal signals regulate mobilization, metabolic pacing, immune tolerance, and recovery. The reviewed literature supports predictable patterns of endocrine reorganization during energetic strain, including prioritization of glucocorticoid-mediated mobilization, constrained thyroid hormone activation, suppression of long-term anabolic investment, and impaired recovery following stress. These configurations reflect adaptive energy-conserving strategies rather than isolated organ dysfunction. The novelty of this review lies in organizing established biological mechanisms into a unified, energy-allocation-based framework that generates falsifiable predictions linking endocrine coordination to bioenergetic capacity and recovery dynamics. We further discuss how routinely available biomarkers and validated psychometric measures can be interpreted as functional readouts of energetic allocation rather than static disease markers. Framing resilience through coordinated energy governance offers a unifying mechanistic lens for interpreting multisystem stress responses and generates testable predictions for future experimental and clinical investigation. Full article

Background/Objectives: Left bundle branch area pacing (LBBAP) has rapidly emerged as a physiological alternative to conventional pacing. However, the learning curve for new operators remains poorly characterized. We aimed to describe the learning curve of LBBAP using cumulative sum (CUSUM) analysis in a single-center, single-operator setting. Methods: We conducted a retrospective analysis of 108 consecutive LBBAP attempts performed by a first-time operator with no prior conduction system pacing experience. Fluoroscopy time was selected as the primary performance metric. A predefined procedural target (≤6 min for non-CRT and ≤9 min for CRT implants) was used to classify each case as a success or failure. CUSUM plots were generated to identify the inflection point marking proficiency acquisition. Results: In non-CRT cases (n = 95), fluoroscopy time progressively decreased, and the CUSUM curve showed a distinct inflection after approximately 65 cases, indicating the attainment of procedural proficiency. In CRT implants (n = 9), acceptable fluoroscopy exposure was achieved soon after the non-CRT proficiency threshold was reached. Electrical performance and safety outcomes remained stable throughout the learning process. Conclusions: CUSUM provides a clear, objective, and real-time measure of operator progression during the initial learning phase of LBBAP. The technique reliably identified the proficiency transition and can be readily implemented for procedural training, credentialing, and competency monitoring in centers adopting LBBAP. Full article

(1) Background: This study presents an adaptive, contactless, and privacy-preserving respiratory-rate monitoring system based on thermal imaging, designed for real-time operation on embedded edge hardware. The system continuously processes temperature data from a compact thermal camera without external computation, enabling practical deployment for home or clinical vital-sign monitoring. (2) Methods: Thermal frames are captured using a $256\times 192$ TOPDON TC001 camera and processed entirely on an NVIDIA Jetson Orin Nano. A YOLO-based detector localizes the nostril region in every even frame (stride = 2) to reduce the computation load, while a Kalman filter predicts the ROI position on skipped frames to maintain spatial continuity and suppress motion jitter. From the stabilized ROI, a temperature-based breathing signal is extracted and analyzed through an adaptive median–MAD hysteresis algorithm that dynamically adjusts to signal amplitude and noise variations for breathing phase detection. Respiratory rate ($RR$) is computed from inter-breath intervals (IBI) validated within physiological constraints. (3) Results: Ten healthy subjects participated in six experimental conditions including resting, paced breathing, speech, off-axis yaw, posture (supine), and distance variations up to 2.0 m. Across these conditions, the system attained a MAE of $0.57\pm 0.36$ BPM and an RMSE of $0.64\pm 0.42$ BPM, demonstrating stable accuracy under motion and thermal drift. Compared with peak-based and FFT spectral baselines, the proposed method reduced errors by a large margin across all conditions. (4) Conclusions: The findings confirm that accurate and robust respiratory-rate estimation can be achieved using a low-resolution thermal sensor running entirely on an embedded edge device. The combination of YOLO-based nostril detector, Kalman ROI prediction, and adaptive MAD–hysteresis phase that self-adjusts to signal variability provides a compact, efficient, and privacy-preserving solution for non-invasive vital-sign monitoring in real-world environments. Full article

Background/Objectives: Transthyretin cardiomyopathy (ATTR-CM) is frequently associated with conduction disease requiring pacing. Conventional right ventricular pacing may worsen cardiac function, whereas left bundle branch area pacing (LBBAP) aims to preserve physiological activation. Evidence for LBBAP in ATTR-CM remains limited. Methods: A structured narrative review of PubMed and Google Scholar was performed through November 2025 using predefined terms related to LBBAP and ATTR-CM. Peer-reviewed articles, case reports, case series, and relevant abstracts were included. Studies exclusively on light-chain cardiac amyloidosis were excluded. Results: Ten publications met inclusion criteria, comprising three case reports, five case series, one retrospective cohort without a comparator, and one cohort comparing LBBAP with cardiac resynchronization therapy (CRT). In total, 56 patients with ATTR-CM underwent LBBAP. Implantation success was high, with stable acute and mid-term electrical parameters. Follow-up (typically 3–12 months) showed stable electrical parameters with narrow paced QRS complexes and preserved or improved left ventricular ejection fraction in most reports. Symptomatic improvement and reductions in natriuretic peptides were variably described. No major lead-related complications were reported. Comparative data remain sparse and inconclusive. Conclusions: This review suggests that LBBAP is a feasible and safe pacing approach in patients with ATTR-CM and may help to stabilize or improve heart failure symptoms. Further prospective studies are needed to confirm its clinical effectiveness. Full article

Background/Objectives: Biventricular pacing (BVP) to deliver cardiac resynchronization therapy (CRT) is a standard intervention for heart failure, yet suboptimal response remains common due to challenges in left ventricular (LV) lead placement. Left bundle branch area pacing (LBBAP) has emerged as a promising alternative, offering physiological activation via direct conduction system engagement. However, comparative data on electrocardiographic (ECG) and procedural outcomes between LBBAP-CRT and BVP-CRT are limited. Methods: This retrospective, single-center study compared LBBAP-CRT and BVP-CRT in 114 patients with left bundle branch block and LV ejection fraction ≤ 35%. LBBAP-CRT was performed using a Medtronic SelectSecure™ 3830 lead via a fixed-curve sheath Medtronic C315HIS, with successful capture confirmed by ECG criteria (Qr/qR in V1, LV activation time < 100 ms). BVP-CRT involved coronary sinus LV lead placement. Outcomes included QRS duration, pacing thresholds, complications, and procedural metrics. Statistical analysis employed logistic regression to identify predictors of optimal pacing thresholds (≤1.0 V at 0.5 ms). Results: LBBAP-CRT yielded greater degree of QRS narrowing than BVP-CRT (136.7 ± 13.5 ms vs. 147.2 ± 14.6 ms, p < 0.001) and lower pacing thresholds (p < 0.05). Complications occurred in 18.1% of BVP-CRT patients (phrenic nerve stimulation, lead dislocation) versus none in LBBAP-CRT (p = 0.011). According to the multivariable analysis LBBAP-CRT was associated with an optimal thresholds (p = 0.007), alongside lower E/e′ ratio and lead impedance. Conclusions: LBBAP-CRT was associated with superior electrical resynchronization, fewer complications, and better pacing thresholds compared to BVP, suggesting its potential as a preferred CRT strategy. Larger randomized trials are needed to validate long-term outcomes. Full article

Occupational demands, such as load carriage in tactical professions, do not discriminate based on sex. The aim of this study was to explore the differences in metabolic cost of a loaded pack march between the sexes in both absolute and relative terms. Twelve Army personnel (six males and six females) volunteered to complete three identical load carriage marches (5 km at 5.5 km/h, carrying 30 kg), across flat (on road) and undulating (gravelled path) terrain as part of a larger equipment trial. Heart rate (HR) response (HR average and maximum) was monitored with a Polar Team Pro unit and oxygen consumption with VO Master Pro (VO₂ average and maximum) with the level of significance set at 0.05. There were no significant differences in age, years of experience, absolute loads carried, or completion time for each of the three events. Male soldiers were significantly taller (182.3 ± 6.2 cm vs. 167.4 ± 6.9 cm), heavier (88.2 ± 8.7 kg vs. 70.9 ± 10.6 kg), carried significantly less relative load (34.3 ± 3.4% vs. 43.2 ± 7.5%), and had significantly greater predicted VO_2max (56.7 ± 6.1 mL/kg/min vs. 45.0 ± 2.9 mL/kg/min). A linear mixed model identified a significant main effect of sex on both average HR (β = −1.10) and peak HR (β = −1.27), and on average VO₂ (β = −0.68), but not peak VO₂. While the study was not powered to detect sex differences, the large effect sizes observed suggest meaningful physiological differences warranting further investigation. Female soldiers faced significantly greater metabolic costs when carrying the same loads and moving at the same speed and across the same terrain as their male counterparts. Adequate recovery and pacing strategies should be considered for these events, especially during training. Full article

Background/Objectives: Frailty is an age-related clinical syndrome characterized by diminished physiological reserves and increased vulnerability to adverse outcomes. Growing evidence suggests that frailty involves shared brain networks that regulate both gait and cognitive functions. This study aimed to examine the relationship between frailty status, spatiotemporal gait parameters, and cognitive functions in community-dwelling older adults. Methods: A cross-sectional study was conducted with 99 adults aged ≥70 years, classified as non-frail, prefrail, or frail according to the Fried phenotype. Gait parameters were measured under usual and fast walking conditions using the OptoGait^® photoelectric system. Cognitive status was assessed with the Montreal Cognitive Assessment (MoCA) and a comprehensive neuropsychological battery. Multivariate logistic regression analyses were performed to identify factors associated with transitions between frailty stages. Results: The prevalence of frailty was 9.1%, with 51.5% prefrail and 39.4% non-frail. The transition from non-frail to prefrail was associated with shorter stride length at fast pace (OR = 0.92, 95% CI: 0.88–0.96), mild cognitive impairment (OR = 3.71, 95% CI: 1.08–12.69), depressive symptoms (OR = 1.82, 95% CI: 1.26–2.62), and female sex (OR = 4.94, 95% CI: 1.20–16.77). The transition from prefrail to frail was linked to increased stride time variability at fast pace (OR = 2.94, 95% CI: 1.34–6.44) and poorer working memory (OR = 0.40, 95% CI: 0.16–0.97). Conclusions: Shorter stride length, mild cognitive impairment, and depressive symptoms emerged as key markers of the transition from non-frailty to prefrailty, whereas increased stride time variability and poorer working memory distinguished prefrail from frail individuals. These findings highlight gait- and executive-function-related markers as sensitive early indicators of vulnerability. Incorporating quantitative gait assessment and brief cognitive screening into routine geriatric evaluations may substantially enhance early detection and support targeted preventive strategies for healthy aging. Full article

Health monitoring systems play a crucial role in every life. In the 21st century, advanced technologies like wearable sensors have emerged and make healthcare better overall. These sensors collect massive amounts of data about our health over time in many dimensions. In this paper, our objective is to develop and evaluate a machine learning-based clinical decision support system using wearable sensor data to accurately classify users’ physiological states and activity contexts. The most accurate and effective model is for identifying wearable sensor-based physiological signal classification. However, there are serious privacy and security issues with sending raw sensor data to centralized computers. We gathered the multivariate physiological and activity data from wearable technology, including smartwatches and fitness trackers, which make up the dataset. Physiological signals, including heart rate, resting heart rate, normalized heart rate, entropy of heart rate variability, and caloric expenditure, are all included in the dataset. Lying, sitting, self-paced walking, and running at different MET(Metabolic Equivalent of Task) levels are examples of activity context labels. To secure our data, we proposed an architecture based on federated learning that helps machine learning model training across several dispersed devices without exchanging raw data. In this study, we used eight classifiers, and these are XGBoost, RF, Extra Trees, LightGBM, CatBoost, Bagging, DT, and GB. It has been observed that XGBoost performs well in comparison to the other classifiers with an accuracy of 0.94, a precision of 0.90, a recall of 0.89, an F1-score of 0.90, and an AUC-ROC of 0.98. This study demonstrates the potential of wearable sensor data, combined with machine learning, for accurately classifying activity and physiological conditions. The ML boosting family, especially XGBoost, exhibited strong generalization across diverse signal inputs and activity contexts. These results suggest that explainable, non-invasive wearable analytics can support early detection and monitoring frameworks in personalized healthcare systems. The proposed federated learning framework effectively combines privacy-aware computation and accurate classification using wearable sensor data. Full article

Anxiety and emotional stress are pervasive psychological challenges that profoundly impact human health in today’s fast-paced society. Traditional assessment methods, such as self-reports and clinical interviews, often suffer from subjective biases and lack the capability for objective, real-time evaluation of mental states. However, the integration of physiological signals—including electroencephalography (EEG), heart rate (HR), electrodermal activity (EDA), and eye movements—with advanced machine learning (ML) techniques, offers a promising approach to automate and objectify mental health assessments. A systematic review was conducted to explore recent advances in the early detection of anxiety and stress by combining physiological signals and ML methods. To assess methodological quality, a specific analysis framework was designed for the 113 studies included, which identified significant deficiencies in the literature. This highlights the urgent need to adopt standardized reporting guidelines in this field. The role of these technologies in feature extraction, classification, and predictive modeling was analyzed, also addressing critical challenges related to data quality, model interpretability, and the influence of intersectional factors like gender and age. Ethical and privacy considerations in the current research were also included. Finally, potential avenues for future research were summarized, highlighting the potential of ML technologies for early detection and proactive intervention in mental disorders. Full article

Background/Objectives: Pacemaker-induced cardiomyopathy (PICM) develops in up to 30% of patients with chronic right ventricular pacing. While biventricular (BIV) upgrade is the conventional strategy, conduction system pacing (CSP) offers a physiologic alternative recently endorsed by the 2025 ESC/EHRA Consensus Statement. However, comparative evidence in PICM is limited. Therefore, we aimed to compare outcomes of PICM patients undergoing CSP versus BIV upgrade. Methods: This retrospective analysis included consecutive PICM patients who were upgraded to CSP or BIV between 2022 and 2024 at a single, experienced center. Follow-up averaged >19 months. Clinical outcomes, lead performance, echocardiographic parameters, complications, and quality of life (QoL) were evaluated. Results: Sixty-three patients were included (CSP: 26; BIV: 37). Mean age and sex distribution were similar; both groups had wide paced QRS complexes and a high ventricular pacing burden. Baseline left ventricular ejection fraction (LVEF) was lower in BIV patients (29 ± 7% vs. 35 ± 6%, p = 0.01). Procedure duration was comparable, but fluoroscopy was shorter with CSP. QRS duration narrowed significantly in both groups (CSP: 163 ± 28→132 ± 12 ms; BIV: 171 ± 23→140 ± 18 ms; both p < 0.05). During follow-up, LVEF improved (CSP: 41 ± 8%; p = 0.008; BIV: 39 ± 8%, p = 0.0001), as did NYHA class, with no significant intergroup differences. The rates of heart failure hospitalization, all-cause mortality, and QoL were similar. Notably, 34.6% of CSP patients retained their existing generator, suggesting procedural and economic benefits. Conclusions: CSP is a feasible and potentially cost-efficient alternative to BIV upgrade in PICM, with comparable improvements in ventricular function, symptoms, and clinical outcomes. Larger prospective trials are warranted. Full article