Clinical practice guidelines for walking recovery post-stroke recommend high aerobic intensity training, which usually involves walking at fast speeds. However, the acute effect of fast speeds on the neuromuscular control of walking is unclear. (1) Assess the criterion validity of the Dynamic Motor Control Index (WalkDMC) as a measure of coactivation post-stroke. (2) Assess acute speed-dependent coactivation post-stroke. (3) Assess how clinical characteristics shape the speed-dependent coactivation response. (4) Assess the relationship between heart rate and coactivation post-stroke. We hypothesized that WalkDMC is correlated with function and impairment measures. We also hypothesize that coactivation measured via the WalkDMC increases for speeds above or below self-selected speeds (SSS). 32 chronic stroke survivors and 17 age and sex-matched controls walked at SSS, fast, and slow speeds. EMGs were measured bilaterally on 7 lower extremity muscles. We used non-negative matrix factorization to calculate WalkDMC. We used regression to assess the relationship between WalkDMC, speed, heart rate, and clinical outcomes. WalkDMC was correlated with clinical outcomes, supporting its criterion validity. We observed a quadratic relationship between speed and coactivation: for the paretic extremity, the predicted speed that would lead to the lowest coactivation was ~120% higher than SSS. Slow speeds consistently increased coactivation in controls and participants post-stroke. Coactivation in the paretic extremity was significantly predicted by speed, balance, and impairment. Our results suggest that increased speeds lead to differential improvements in coactivation in the paretic and non-paretic extremities. These results may inform speed prescriptions for HIT interventions.

Generally, triathletes participating in short events should aim to finish the swim stage with the leading group to improve their chances in the subsequent cycling and running stages. However, the fatigue associated with very intense swimming can impair subsequent split times. This study aimed to investigate the impact of swimming bout intensity on performance in subsequent cycling, running, and overall racing among well-trained male and female amateur triathletes. Twenty athletes (12 men and 8 women) participated in this study. Critical velocity (CV) was estimated for swimming using a simple linear model. Body composition and maximal oxygen uptake were measured. Participants visited the laboratory three times to swim 750 m at intensities below CV, at CV, and above CV (in randomized order), before they cycled 20 km and ran 5 km as fast as they could to simulate a sprint triathlon. Heart rate, blood lactate level, perceived exertion, muscle pain, and dyspnea levels were measured at the end of each modality. For women, on the day on which swimming intensity was below the CV, the overall race time was higher than on the day on which swimming intensity was at the CV (p = 0.041) or faster than the CV (p = 0.002). For men, there was no significant difference in the overall race time among the three intensities (p > 0.05). The results showed that, for men, swimming at higher intensity did not significantly change total time, whereas for women, lower intensity was associated with poorer performance. The study was registered in ReBEC - Registro Brasileiro de Ensaios Clinicos: Rio de Janeiro (RJ): Instituto de Informação Científica e Tecnológica em Saúde (Brazil); 2010 - Identifier RBR-73vcyff. Available from http://ensaiosclinicos.gov.br/rg/RBR-73vcyff .

Remote photoplethysmography (rPPG) offers a non-invasive means of estimating heart rate in telemedicine settings. Yet its reliability remains uncertain due to the limited diversity and ecological validity of existing benchmark datasets. In this work, we systematically investigate the robustness of rPPG methods under challenging conditions, specifically low illumination and elevated heart rates. We introduce the CHILL dataset, which comprises video and PPG signals collected from 45 participants across two lighting conditions (bright and dark) and exercise-induced heart rates ranging from 54 to 141 beats per minute. We assessed eight rPPG algorithms, including four signal processing-based and four deep learning-based approaches, across three datasets: the newly collected CHILL dataset and two widely used public benchmarks, PURE and COHFACE. Within-dataset analysis on the CHILL dataset revealed that many existing rPPG methods struggle under challenging conditions. Five of the eight methods experienced a statistically significant decline in performance at elevated heart rates. In contrast, low illumination had a comparatively smaller impact. Cross-dataset analysis further revealed that several deep learning models failed to generalize effectively to the CHILL dataset. Among the models that did generalize, many still showed a significant decline in performance under elevated heart rate conditions, regardless of the training dataset. These findings highlight a critical limitation in current rPPG algorithms, namely their susceptibility to high heart rates. Our evaluation of rPPG methods on the CHILL dataset underscores the need for more robust approaches to enable accurate, non-invasive physiological monitoring in real-world digital health environments.

ABSTRACT The aim of this study was to determine the physical and physiological demands of intercounty Camogie match-play between competitions. Data was collected across a two-year period, using global positioning systems (10-Hz) and heart rate monitors (2.4-GHz). There were statistically significant increases between competitions in total distance (TD) (p < 0.05), Relative Distance (RD) (p < 0.05), HRmax (p < 0.01), HRmean (p < 0.01), number of High-Speed Running (HSR), (p < 0.05) between competitions. There were also significant increases between competitions in very high-speed running (VHSR) (p < 0.05), sprinting (p < 0.02) between the National League (NL) and All-Ireland Championship (AIC). From a positional difference, half-forwards covered a significantly greater RD (p < 0.02) than full forwards during the NL (p < 0.02). Midfielders covered a significantly greater TD than full backs (p < 0.01) and full forwards (p < 0.05) during the AIC. Midfielders covered a significantly greater HSR distance than full-backs (p < 0.02) and half backs during the AIC (p < 0.05). Midfielders covered a significantly greater number of sprints than full backs during the AIC (p < 0.02). The findings provide distinct physical and physiological values of the between competition demands of intercounty Camogie match-play.

This study investigated how unsteady flow conditions influence the swimming physiology and energetic performance of Chinook salmon using co-implanted heart rate (HR) and acceleration (AC) sensors. Fish were monitored for HR, AC, and overall dynamic body acceleration (ODBA) in two experimental settings: (1) controlled swimming at increasing speeds (0.15-0.90 m s⁻¹) in a swim-tunnel under steady and unsteady flow, and (2) free-swimming sentinel fish in tanks under steady and subsequent unsteady flow for two weeks each. In experiment 1, HR remained consistently high (81-84 bpm) across all speeds under both flow conditions, suggesting limited capacity to further elevate cardiac output. MO2 increased from 213±10 to 307±16 and from 225±12 to 330±17 mg kg-1 h-1 under steady and unsteady flow, respectively. AC and ODBA increased linearly with speed and were positively correlated under both flow conditions. In experiment 2, circadian patterns were evident in HR, AC, and ODBA of the free-swimming fish. Fish exhibited higher daytime and nighttime HR and AC under unsteady flow compared to steady flow conditions, while ODBA remained similar. Regression models based on swim-tunnel data accurately predicted AC and ODBA in free-swimming fish, indicating consistent relationships between swimming speed and acceleration dynamics. The higher HR and AC of free-swimming fish under unsteady conditions indicated a 3-5% increased energetic investment. Overall, this study provides insight into how dynamic flow environments shape the physiological responses of Chinook salmon, informing predictions of fish performance in offshore aquaculture systems.

BackgroundWe compared ultrahigh-resolution (UHR) photon-counting detector-computed tomography (PCD-CT) and spectral post-processed images for coronary stent visualization in a dynamic, anthropomorphic, and circulatory phantom.Materials and methodsTen coronary stents were scanned at 60, 80, and 100 beats per min (bpm) using UHR-spectral PCD-CT (96 × 0.2 mm collimation). Reconstructions included UHR (0.2 mm), downsampled (0.6 mm), and spectral post-processed images (0.4 mm), including virtual monoenergetic images (VMI; 45–100 keV), lumen-preserving images, and iodine maps (IM). Objective quality was assessed by measurable stent lumen visibility and stent strut width overestimation factor, compared to nominal strut width. Subjective quality was rated using a 4-point Likert scale. Repeated-measures analysis of variance−ANOVA and Friedman test with post hoc corrections were applied.ResultsUHR images provided the highest lumen visibility (62.6 ± 7.6%) at 60 bpm, outperforming all reconstructions ranging 43.5–52.7% (p ≤ 0.001) except IM (59.6 ± 11.9%, pairwise p = 0.839). UHR showed the lowest strut overestimation factor (18.1 ± 3.4), better than all spectral images (20.2–26.2, p ≤ 0.003) and DS (32.1 ± 6.5, p < 0.001). Subjective quality was best for UHR at 60 bpm (4.0 [interquartile range, IQR 4.0–4.0]) but declined at 100 bpm (3.0 [IQR 2.0–3.0], p < 0.01). VMI at 55 keV and IM maintained stable quality across heart rates (p ≥ 0.09).ConclusionPCD-CT combining UHR and spectral imaging enhances stent assessment. UHR provides the best lumen visibility and strut accuracy but suffers from motion artifacts, whereas VMIs at 55 keV and IM remain stable across heart rates and potentially provide incremental value.Relevance statementCombining UHR and spectral PCD-CT enhances coronary stent visualization by balancing high spatial detail with artifact reduction, potentially improving diagnostic confidence and enabling more reliable non-invasive follow-up across a range of heart rates in clinical practice.Key PointsThe combined value of spectral UHR CT for stent imaging remains largely unexplored.UHR PCD-CT showed the highest lumen visibility and sharpest strut delineation, whilst being prone to motion artifacts.Spectral reconstructions complement UHR by reducing artifacts and stabilizing image quality, especially at higher heart rates.Graphical

Cardiovascular diseases (CVDs) remain a major global health challenge, highlighting the urgent need for advanced cardiac monitoring solutions. Continuous, contactless cardiac monitoring using seismic sensors enables comfortable, privacy-preserving assessments by capturing subtle heart vibrations. However, these systems are highly susceptible to diverse noise sources. Existing denoising methods struggle to handle the complex noise in cardiac seismic signals and poorly leverage the abundant unlabeled data. To address these challenges, we propose SelfDenoiser, a self-supervised framework for denoising and reconstructing cardiac seismic signals using unlabeled data. During training, SelfDenoiser first selects clean segments from the unlabeled pool, then injects adaptive noise into each segment to simulate shared, hard-to-remove interference commonly observed in real-world noise distributions. In addition, realistic artifacts are extracted and integrated into clean signals to model high-intensity, abrupt noise events. An encoder-decoder network designed with fixed temporal resolution is subsequently trained to recover the clean signals, guided by a loss function that captures both temporal and spectral characteristics. We evaluated SelfDenoiser on 11,392 hours of data collected in an Intensive Care Unit (ICU) using seismic sensor-based systems. The model was trained on 610 hours of clean signals selected from a 5176-hour unlabeled pool and tested on a 6216-hour labeled dataset. Results showed substantial improvements in two downstream tasks: heart rate (HR) and inter-beat interval (IBI) estimation, with notably increased data utilization and better accuracy compared to conventional denoising methods. This highlights SelfDenoiser's capability to transform low-quality, noisy signals into high-fidelity, reliable cardiac data.

Background Working mules are essential for human livelihoods, yet scientific evidence on their physiological limits during load-carrying tasks remains scarce. Objectives To evaluate the physiological responses of mules to increasing loads during short-distance work. Study design A crossover design. For this, 12 Chilean Army mules of three sizes (small, medium, large) were subjected to a 2-km walk carrying loads of 0, 80, 105, and 130 kg, equivalent to 20–42% of live body weight, under ambient temperatures of 32–39 °C. Blood and physiological parameters were measured before, immediately after, 10 min, and 2 h after work, with additional blood samples for biochemical parameters collected up to 105 h after exercise. Linear mixed models were applied to evaluate the effects of load, time, and body size. Results The size of the mule did not have an effect on their physiological response to work. On the other hand, increasing load significantly elevated cortisol, lactate, and rectal temperature, indicating activation of both the hypothalamic–pituitary–adrenal axis and anaerobic metabolism. Enzymatic activities of γ-glutamyltransferase (GGT), lactate dehydrogenase (LDH), and alkaline phosphatase (SAP/ALP) also increased with heavier loads, suggesting greater muscular effort and mild tissue stress. Conversely, glutathione peroxidase (GPx) activity decreased as load increased, implying increased oxidative demand. Total protein and neutrophil-to-lymphocyte ratios rose with higher loads, reflecting systemic stress response and hemoconcentration. Heart rate and respiratory rate were not significantly affected, suggesting adequate cardiovascular adaptation. Most parameters returned to baseline within 2 h post-exercise, demonstrating effective short-term recovery. Conclusion These findings confirm that short-distance work carrying heavy loads, in particular over 105 kg, does activate a physiological stress response in mules, though within adaptive limits. Loads of 105–130 kg triggered greater metabolic and enzymatic adjustments, indicating that while trained mules can cope with high loads over short distances, care should be taken when asking mules to work for longer distances or heavier loads since it can negatively affect their welfare. Establishing evidence-based workload thresholds is essential for balancing performance efficiency and welfare in working mules. Future studies should evaluate long-term work under field conditions, incorporating other welfare indicators such as behavior for a more comprehensive welfare assessment.

Background Multifocal transcranial direct current stimulation (m-tDCS) may modulate distributed motor networks in a polarity-dependent and task-state-dependent manner to support performance near exhaustion. To this end, this study aims to test whether m-tDCS targeting lower-limb-specific cortical areas could optimize late-stage performance and phase-specific muscle coordination during cycling. Methods Two independent trials were conducted: (i) a tolerability assessment (Trial 1) and (ii) a randomized, double-blind, sham-controlled parallel study (Trial 2). In Trial 1, participants completed the tolerability test and recorded pain and side effects during a 21-min stimulation period. In Trial 2, healthy adults completed an incremental cycling test; late-stage performance was operationalized a priori as the 85%–100% peak power output (PPO) phase, during which the time-to-exhaustion (TTE), work (W), mean power (P), revolutions per minute (RPM), heart rate (HR), blood lactate level (ΔL), ratings of perceived exertion (RPE), and EMG-derived muscle contribution ratio (MCR) and knee co-activation index (CAI) were analyzed across propulsion and pull. Results (1) m-tDCS was well-tolerated; pain ratings declined progressively across the stimulation, with typical transient sensations. (2) At the 85%–100% PPO phase, m-tDCS increased W and RPM relative to sham without altering the mean power or ΔL; HR decreased after m-tDCS, and RPE rose only after sham. (3) At the coordination level, m-tDCS preserved quadriceps MCR during propulsion and reduced antagonistic activation during pull to prevent the CAI increase observed in the sham. Conclusion m-tDCS did not augment peak mechanical output but preserved late-stage endurance via phase-specific coordination tuning, which is consistent with improved neural efficiency near exhaustion. These findings refine mechanistic interpretations of the effects of tDCS on endurance and support m-tDCS as a safe, coordination-centric adjunct for high-intensity cycling.

Each year, around 10% of infants globally will require resuscitation at birth. Pediatricians can use stethoscope, electrocardiogram (ECG) or pulse oximetry to determine heart rate (HR) which is used to guide resuscitation steps. HR must be acquired accurately and quickly. However, current HR detection modalities are either inaccurate or too slow. This work offers a novel infant heart rate detector (iHRD) using single-lead dry electrode ECG that can display HR accurately within the first 10 seconds of initial contact. A research ethics board approved validation study is conducted on 50 healthy newborns comparing iHRD’s HR with clinical HR monitors at a community hospital. 3-minute newborn single-lead ECGs and HR are recorded, and HR is annotated every 2 seconds. Statistical HR analysis is performed to ensure iHRD’s feasibility and reliability. With 2741 HR datapoints, excluding outliers, the iHRD detected HR with 94.5% accuracy with time from contact to HR display under 10 seconds. Overall, the iHRD using dry electrode single-lead ECG showed good results in providing reliable HR quickly for neonatal resuscitation efforts.

Abdominal-only compression garments reduce orthostatic tachycardia and improve symptoms in patients with postural orthostatic tachycardia syndrome.

Methodological approach to assess cardiovascular dynamics in elite cyclists.

Prolonged passive vibration of Achilles and patellar tendons decreases effort perception during subsequent cycling tasks.

Microfluidic tesla valve sweat patch integrated smartwatch for optical continuous monitoring of glucose, oxygen, and heart rate.

How the presence of a dog and types of interaction affect physiological responses to experimental heat pain induction in healthy humans - a randomized controlled study.

The effectiveness of music on pain during heel blood collection in premature infants: A randomized controlled trial.

Background: Long working time, night shifts, and strenuous clinical duties all present as a challenge to medical residents expose them to chronic sleep deprivation. Autonomic imbalance, disturbed circadian rhythm, and premature cardiovascular dysfunction have all been associated with persistent sleep loss. Objectives: To examine how chronic sleep deprivation affects blood pressure fluctuations and early cardiovascular changes among tertiary care medical residents. Methods: It was a clinical observational study conducted at Sahara Medical College, Narowal, Pakistan, between January 2024 and May 2025, and in 80 medical residents aged between 24-35 years. The 14-day wrist-worn sleep trackers and the Pittsburgh Sleep Quality Index were used to measure the time of sleep. The cardiovascular exam included 24-h ambulatory blood pressure, heart rate variability, resting heart rate, 12-lead ecg and hs-CRP. The respondents were separated into sleep-deprived (less than 6 hours/night) and adequate sleepers (6 hours/night and more). Her statistical analysis was performed with the assistance of SPSS 26, and p less than 0.05 may be regarded as significant. Results: Systolic (14.9 ± 3.7 mmHg) and diastolic (12.6 ± 3.2 mmHg) blood pressure variability, nighttime systolic pressure (131 ± 11 mmHg), and non-dipping patterns were more common in sleep-deprived residents. They also had a lower level of heart rate variability (31.8 ± 8.3 ms) and an elevated resting heart rate (91.3 ± 10.9 bpm), elevated levels of hs-CRP (3.9 ± 1.2 mg /L), and more ECG abnormalities than became the case with adequately rested residents. Conclusion: The increased blood pressure variability, autonomic dysfunction, systemic inflammation, and early cardiovascular changes are highly connected with chronic sleep deprivation among medical residents. Structured duty-hour reforms and better sleep hygiene practices are required to prevent cardiovascular damage in this group.

Effects of oral and intravenous dimethylglycine treatment on hematobiochemical profiles and total oxidant/antioxidant status in low-intensity exercised horses.

High Heart Rate, Sympathetic Overdrive, and Cardiovascular Risk in Hypertension.

Meta analysis of the intervention of Baduanjin in middle-aged and elderly patients with essential hypertension.