Search Results (481)

The Red River Jig is a traditional Métis dance practiced among Indigenous and non-Indigenous Peoples. While exercise improves physical health and fitness, the impacts of cultural dances on wholistic health are less clear. This study aimed to investigate the psychosocial (cultural and mental), social, physical function, and physical fitness benefits of a Red River Jig intervention. In partnership with Li Toneur Nimiyitoohk Métis Dance Group, Indigenous and non-Indigenous adults (N = 40, 39 ± 15 years, 32 females) completed an 8-week Red River Jig intervention. Social support, cultural identity, memory, and mental wellbeing questionnaires, seated blood pressure and heart rate, weight, pulse-wave velocity, heart rate variability, baroreceptor sensitivity, jump height, sit-and-reach flexibility, one-leg and tandem balance, and six-minute walk test were assessed pre- and post-intervention. Community, family, and friend support scores, six-minute walk distance (553.0 ± 88.7 m vs. 602.2 ± 138.6 m, p = 0.002), jump, leg power, and systolic blood pressure low-to-high-frequency ratio increased after the intervention. Ethnic identity remained the same while affirmation and belonging declined, leading to declines in overall cultural identity, as learning about Métis culture through the Red River Jig may highlight gaps in cultural knowledge. Seated systolic blood pressure (116.5 ± 7.3 mmHg vs. 112.5 ± 10.7 mmHg, p = 0.01) and lower peripheral pulse-wave velocity (10.0 ± 2.0 m·s⁻¹ vs. 9.4 ± 1.9 m·s⁻¹, p = 0.04) decreased after the intervention. Red River Jig dance training can improve social support, physical function, and physical fitness for Indigenous and non-Indigenous adults. Full article

This pilot, randomized, double-blind, placebo-controlled trial investigated the effects of branched-chain amino acids (BCAAs)—provided in a 2:1:1 ratio of leucine:isoleucine:valine—combined with exercise on fatigue, physical performance, and quality of life in older adults. Twenty participants (63% female; BMI: 35 ± 2 kg/m²; age: 70.5 ± 1.2 years) were randomized to 8 weeks of either exercise + BCAAs (100 mg/kg body weight/d) or exercise + placebo. The program included moderate aerobic and resistance training three times weekly. Physical function was assessed using handgrip strength, chair stands, gait speed, VO₂ max, and a 400 m walk. Psychological health was evaluated using the CES-D, Fatigue Assessment Scale (FAS), Insomnia Severity Index (ISI), and global pain, fatigue, and quality of life using a visual analog scale (VAS). Significant group x time interactions were found for handgrip strength (p = 0.03), chair stands (p < 0.01), and 400 m walk time (p < 0.01). Compared to exercise + placebo, exercise + BCAAs showed greater improvements in strength, mobility, and endurance, along with reductions in fatigue (−45% vs. +92%) and depressive symptoms (−29% vs. +5%). Time effects were also observed for ISI (−30%), FAS (−21%), and VAS quality of life (16%) following exercise + BCAA supplementation. These preliminary results suggest that BCAAs combined with exercise may be an effective way to improve physical performance and reduce fatigue and depressive symptoms in older adults. Full article

In this study, four types of fall detection systems for seniors living alone using x-y scatter and Doppler range images measured from frequency-modulated continuous wave (FMCW) millimeter-wave (mmWave) sensors were introduced. Despite advancements in fall detection, existing long short-term memory (LSTM)-based approaches often struggle with effectively distinguishing falls from similar activities of daily living (ADLs) due to their uniform treatment of all time steps, potentially overlooking critical motion cues. To address this limitation, an attention mechanism has been integrated. Data was collected from seven participants, resulting in a dataset of 669 samples, including 285 falls and 384 ADLs with walking, lying, inactivity, and sitting. Four LSTM-based architectures for fall detection were proposed and evaluated: Raw-LSTM, Raw-LSTM-Attention, HOG-LSTM, and HOG-LSTM-Attention. The histogram of oriented gradient (HOG) method was used for feature extraction, while LSTM networks captured temporal dependencies. The attention mechanism further enhanced model performance by focusing on relevant input features. The Raw-LSTM model processed raw mmWave radar images through LSTM layers and dense layers for classification. The Raw-LSTM-Attention model extended Raw-LSTM with an added self-attention mechanism within the traditional attention framework. The HOG-LSTM model included an additional preprocessing step upon the RAW-LSTM model where HOG features were extracted and classified using an SVM. The HOG-LSTM-Attention model built upon the HOG-LSTM model by incorporating a self-attention mechanism to enhance the model’s ability to accurately classify activities. Evaluation metrics such as Sensitivity, Precision, Accuracy, and F1-Score were used to compare four architectural models. The results showed that the HOG-LSTM-Attention model achieved the highest performance, with an Accuracy of 95.3% and an F1-Score of 95.5%. Optimal self-attention configuration was found at a 2:64 ratio of number of attention heads to channels for keys and queries. Full article

According to the World Health Organization (WHO), indoor air quality (IAQ) is becoming a serious global concern due to its significant impact on human health. However, not all relevant health parameters are currently regulated. For example, particle number concentration (PNC) and its associated carbonaceous species, such as black carbon (BC), which are classified as carcinogenic by the International Agency for Research on Cancer (IARC), are not currently regulated. Compared with IAQ studies in other types of buildings, studies focusing on IAQ in hospitals or other healthcare facilities are scarce. Therefore, this study aims to evaluate the impact of these outdoor pollutants, among others, on the indoor environment of a hospital under different atmospheric conditions. To identify the seasonal influence, two different periods of two consecutive seasons (summer 2020 and winter 2021) were selected for the measurements. Regulated pollutants (NO, NO₂, O₃, PM₁₀, and PM_2.5) and nonregulated pollutants (PM₁, PNC, and equivalent BC (eBC)) in outdoor air were simultaneously measured indoor and outdoor. This study also investigated the impact of indoor activities on indoor air quality. In the absence of indoor activities, outdoor sources significantly contribute to indoor traffic-related pollutants. Indoor and outdoor (I-O) measurements showed similar behavior, but indoor concentrations were lower, with peak levels delayed by up to two hours. Seasonal variations in indoor/outdoor ($\mathrm{I}/\mathrm{O}$) ratios were lower for particles than for associated gaseous pollutants. Particle infiltration depended on particle size, with it being higher the smaller the particle size. Indoor activities also significantly affected indoor pollutants. PM_x (especially PM₁₀ and PM_2.5) concentrations were mainly modulated by walking-induced particle resuspension. Vertical eBC profiles indicated a relatively well-mixed environment. Ventilation through open windows rapidly altered indoor air quality. Outdoor-dominant pollutants (PNC, eBC, and NO_X) had $\mathrm{I}/\mathrm{O}$ ratios ≥ 1. Staying in the room with an open window had a synergistic effect, increasing the $\mathrm{I}/\mathrm{O}$ ratios for all pollutants. Higher I/O ratios were associated with turbulent outdoor conditions in both unoccupied and occupied conditions. Statistically significant differences were observed between stable (TKE ≤ 1 m² s⁻²) and unstable (TKE > 1 m² s⁻²) conditions, except for NO₂ in summer. This finding was particularly significant when the wind direction was westerly or easterly during unstable conditions. The results of this study highlight the importance of understanding the behavior of indoor particulate matter and related pollutants. These pollutants are highly variable, and knowledge about them is crucial for determining their health effects, particularly in public buildings such as hospitals, where information on IAQ is often limited. More measurement data is particularly important for further research into I-O transport mechanisms, which are essential for developing preventive measures and improving IAQ. Full article

Cross-line operation and express–local train coordination are both crucial for enhancing the efficiency of multi-level urban rail transit systems. Most studies address suburban railway operations in isolation, overlooking coordination and inducing supply–demand mismatches that weaken system efficiency. This study addresses the joint optimization of cross-line operation and express–local scheduling by proposing a novel train timetable model. The model determines train service plans and departure times to minimize total system cost, including train operating and passenger travel costs. A space–time network represents integrated train–passenger interactions, and an extended adaptive large neighborhood search (E-ALNS) algorithm is developed to solve the model efficiently. Numerical experiments verify the effectiveness of the proposed approach. The E-ALNS achieves near-optimal solutions with less than 4% deviation from Gurobi. Comparative analysis shows that the proposed hybrid operation mode reduces total passenger travel cost by 6% and improves the cost efficiency ratio by 13% compared to independent operations. Sensitivity analyses further confirm the model’s robustness to variations in transfer walking time, passenger penalties, and waiting thresholds. This study provides a practical and scalable framework for optimizing train timetables in complex cross-line transit systems, offering insights for enhancing system coordination and passenger service quality. Full article

Urban outdoor thermal comfort (OTC) has become an increasingly critical issue under the pressures of urbanization and climate change. Comparative analyses of urban blocks with distinct spatial morphologies are essential for identifying OTC issues and proposing targeted optimization strategies. However, existing studies predominantly rely on microclimate numerical simulations, while comparative assessments of OTC from the human thermal perception perspective remain limited. This study employs the thermal walk method, integrating microclimatic measurements with thermal perception questionnaires, to conduct on-site OTC investigations across three urban blocks with contrasting spatial morphologies—a business district (BD), a residential area (RA), and a historical neighborhood (HN)—in Beijing, a hot summer and cold winter climate city. The results reveal substantial OTC differences among the blocks. However, these differences demonstrated great seasonal and temporal variations. In summer, BD exhibited the best OTC (mTSV = 1.21), while HN performed the worst (mTSV = 1.72). In contrast, BD showed the poorest OTC in winter (mTSV = −1.57), significantly lower than HN (−1.11) and RA (−1.05). This discrepancy was caused by the unique morphology of different blocks. The sky view factor emerged as a more influential factor affecting OTC over building coverage ratio and building height, particularly in RA (r = 0.689, p < 0.01), but its impact varied by block, season, and sunlight conditions. North–South streets generally perform better OTC than East–West streets, being 0.26 units cooler in summer and 0.20 units warmer in winter on the TSV scale. The study highlights the importance of incorporating more applicable physical parameters to optimize OTC in complex urban contexts and offering theoretical support for designing climate adaptive urban spaces. Full article

The electrocardiogram (ECG) signal plays a crucial role in medical diagnosis, home care, and exercise intensity assessment. However, traditional ECG monitoring devices are difficult to blend with users’ daily routines due to their lack of portability, poor wearability, and inconvenient electrode usage methods. Therefore, utilizing reusable and cost-effective flexible bioelectrodes (with a signal-to-noise ratio of 33 dB), a miniaturized wearable system (MWS) is proposed for unconstrained ECG monitoring, which holds a size of 65 × 52 × 12 mm³ and a weight of 69 g. Given these compelling features, this system enables reliable and high-quality ECG signal monitoring in individuals’ daily activities, including sitting, walking, and cycling, with the acquired signals exhibiting distinguishable QRS characteristics. Furthermore, an exercise intensity classification model was developed based on ECG characteristics and a fully connected neural network (FCNN) algorithm, with an evaluation accuracy of 98%. These results exhibit the promising potential of the MWS in tracking individuals’ physiological signals and assessing exercise intensity. Full article

The last-mile delivery crisis, exacerbated by the surge in e-commerce demands, continues to face persistent challenges. Logistics companies often overlook the possibility that recipients may not be at the designated delivery location during courier distribution, leading to interruptions in the delivery process and spatiotemporal mismatches between couriers and users. Parcel lockers (PLCs), as a contactless self-pickup solution, mitigate these mismatches but suffer from low utilization rates and user dissatisfaction caused by detour-heavy pickup paths. Existing PLC strategies prioritize operational costs over behavioral preferences, limiting their real-world applicability. To address this gap, we propose a user-centric path planning model that integrates spatiotemporal trajectory mining with kernel density estimation (KDE) to optimize PLC selection and conducted a small-scale experimental study. Our framework integrated user behavior and package characteristics elements: (1) Behavioral filtering: This extracted walking trajectories (speed of 4–5 km/h) from 1856 GPS tracks of four campus users, capturing daily mobility patterns. (2) Hotspot clustering: This identified 82% accuracy-aligned activity hotspots (50 m radius; ≥1 h stay) via spatiotemporal aggregation. (3) KDE-driven decision-making: This dynamically weighed parcel attributes (weight–volume–urgency ratio) and route regularity to minimize detour distances. Key results demonstrate the model’s effectiveness: a 68% reduction in detour distance for User A was achieved, with similar improvements across all test subjects. This study enhances last-mile logistics by integrating user behavior analytics with operational optimization, providing a scalable tool for smart cities. The KDE-based framework has proven effective in campus environments. Its future potential for expansion to various urban settings, ranging from campuses to metropolitan hubs, supports carbon-neutral goals by reducing unnecessary travel, demonstrating its potential for application. Full article

Background/Objectives: Semi-active prosthetic feet present a promising solution that enhances adaptability while maintaining modest size, weight, and cost. We propose a semi-active Two-Keel Variable-Stiffness Foot (VSF-2K), the first prosthetic foot where both the hindfoot and forefoot stiffness can be independently and actively modulated. We present a model-based analysis of the effects of different VSF-2K settings on prosthesis characteristics and gait metrics. Methods: The study introduces a simulation model for the VSF-2K: (1) one sub-model to optimize the design of the keels of VSF-2K to maximize compliance, (2) another sub-model to simulate the stance phase of walking with different stiffness setting pairs and ankle alignment angles (dorsiflexion/plantarflexion), and (3) a third sub-model to simulate the keel stiffness of the hindfoot and forefoot keels comparably to typical mechanical testing. We quantitatively analyze how the VSF-2K’s hindfoot and forefoot stiffness settings and ankle alignments affect gait metrics: Roll-over Shape ($ROS$), Effective Foot Length Ratio ($EFLR$), and Dynamic Mean Ankle Moment Arm ($DMAMA$). We also introduce an Equally Spaced Resampling Algorithm (ESRA) to address the unequal-weight issue in the least-squares circle fit of the Roll-over Shape. Results: We show that the optimal-designed VSF-2K successfully achieves controlled stiffness that approximates the stiffness range observed in prior studies of commercial prostheses. Our findings suggest that stiffness modulation significantly affects gait metrics, and it can mimic or counteract ankle angle adjustments, enabling adaptation to sloped terrain. We show that $DMAMA$ is the most promising metric for use as a control parameter in semi-active or variable-stiffness prosthetic feet. We identify the limitations in $ROS$ and $EFLR$, including their nonmonotonic relationship with hindfoot/forefoot stiffness, insensitivity to hindfoot stiffness, and inconsistent trends across ankle alignments. We also validate that the angular stiffness of a two-independent-keel prosthetic foot can be predicted using either keel stiffness from our model or from a standardized test. Conclusions: These findings show that semi-active variation of hindfoot and forefoot stiffness based on single-stride metrics such as $DMAMA$ is a promising control approach to enabling prostheses to adapt to a variety of terrain and alignment challenges. Full article

Objectives: Interval block resistance training (IBRT) and circuit resistance training (CRT) are periodization models aimed at enhancing neuromuscular and metabolic adaptations. This study aims to evaluate the effects of a 12-week IBRT program compared to CRT on body composition, muscle strength, speed, functional capacity, and autonomic recovery in young Chilean adults. Methods: A randomized, parallel, double-blind study was conducted with 30 participants assigned to IBRT (n = 15) or CRT (n = 15). Assessments included body mass index (BMI), waist circumference, right-hand grip strength, the running anaerobic sprint test (RAST), the 6 min walk test (6 MWT), and heart rate variability (HRV) indices: low-frequency to high-frequency ratio (LF/HF) and root mean square of successive differences (RMSSD, a time-domain HRV metric reflecting parasympathetic activity). Statistical analyses included t-tests and ANCOVA. Results: Groups were similar in age (IBRT: 25.2 ± 3.19; CRT: 23.27 ± 3.69, p = 0.14) and BMI (IBRT: 21.56 ± 2.22; CRT: 22.36 ± 1.70 kg/m², p = 0.40). Both groups improved significantly in waist circumference (IBRT: −1.85%; CRT: −2.37%), grip strength (IBRT: +5.47%; CRT: +4.02%), RAST (IBRT: −2.67%; CRT: −1.04%), 6 MWT (IBRT: +4.53%; CRT: +2.17%), LF/HF (IBRT: −11.43%; CRT: −5.11%), and RMSSD (IBRT: +5.36%; CRT: +3.81%) (all p ≤ 0.01). IBRT produced significantly greater gains in 6 MWT (B = 19.51, 95% CI: 0.79 to 38.23, p = 0.04). Conclusions: Both IBRT and CRT effectively improved body composition, muscle strength, speed, functional capacity, and autonomic recovery. However, IBRT demonstrated a superior effect on aerobic capacity. Full article

Walking Football is a growing adapted sport offering a viable alternative to traditional exercise for middle-aged and older adults. While rule modifications aim to reduce injury risk, this has yet to be established. This study conducted injury surveillance in community-based Walking Football to determine injury incidence and characteristics in training and matches. A four-month observational cohort study remotely tracked injuries and exposure time across seven Walking Football clubs in England using a sub-elite injury surveillance framework. Injuries were classified as medical attention (requiring on-field attention without subsequent absence) or time-loss (≥1 day of participation absence). Injury incidence was calculated per 1000 h of play. Across 6364.55 h of exposure, 45 injuries were reported: 30 (66.7%) medical attention and 15 (33.3%) time-loss injuries. Injury incidence was 5.3 [1.5–11.5] per 1000 h in training (medical attention: 3.3 [0.8–7.3]; time-loss: 2.0 [0.5–4.5]) and 37.6 [8.7–83.9] per 1000 h in matches (medical attention: 28.9 [5.8–66.6]; time-loss: 8.7 [0–23.2]). Match injury incidence was significantly higher than training (rate ratio: 7.1 [1.3–31.4]). Findings suggest that injury incidence in community-based Walking Football is low, supporting its safety and potential as a sustainable physical activity strategy for middle-aged and older adults. Full article

Background: The aging population in Japan has led to an increase in traffic accidents involving elderly drivers, highlighting the need for measures to enhance driving safety. Post-total knee arthroplasty (TKA) patients must regain their driving ability to maintain independence; however, clear guidelines for driving resumption are lacking. This study assessed the movement time (MT) and brake pedal force (BPF) using a driving simulator and investigated their associations with lower limb motor function. Methods: This single-center prospective cohort study included 21 patients (mean age: 66.7 ± 7.4 years) who underwent right TKA and intended to resume driving. Driving ability was assessed on postoperative day 13 using a driving simulator to measure MT and BPF. Physical function was evaluated using the following parameters: range of motion (ROM), muscle strength, gait parameters, and pain assessment. Pearson’s correlation and multiple regression analyses were performed to identify significant associations. Results: MT was significantly correlated with knee extension strength (r = −0.56, p = 0.02) and walking ratio (r = 0.55, p = 0.03). BPF was significantly correlated with walking ratio (r = 0.52, p = 0.04) and pain levels VAS (r = −0.54, p = 0.02). Multiple regression analysis identified walking ratio (β = 0.54, p = 0.02) as a significant predictor of MT. For BPF, significant predictors included walking ratio (β = 0.49, p = 0.03) and VAS (β = −0.54, p = 0.02). Discussion: The findings of this study suggest that MT is associated with walking ratio, while BPF is significantly associated with both walking ratio and VAS scores. In particular, walking ratio was found to have a significant impact on both MT and BPF, indicating that it may be an important factor influencing postoperative driving performance. Conclusion: Improvement in the walking ratio and pain management affect accelerator and brake operation during driving after TKA. Full article

Background: Post-stroke equinovarus foot (EVF) impairs gait stability, increases the risk of secondary injuries, and contributes to elevated healthcare costs. However, effective targeted interventions for EVF remain limited. Patient concerns: Two patients with chronic EVF—a 63.5-year-old male (9.7 months post-stroke) and a 35.7-year-old female (24.5 months post-stroke)—presented with ankle deformity, gait asymmetry, and impaired balance, all of which interfered with daily activities. Intervention and outcomes: Both patients underwent ultrasound-guided acupotomy targeting spastic ankle muscles, administered over four sessions within two weeks. A quantitative gait analysis revealed substantial improvements in step length ratios (Case 1: 0.61 → 0.86; Case 2: 0.67 → 0.88), as well as enhancements in walking velocity, lateral symmetry, postural balance, and Modified Ashworth Scale scores. No adverse events were reported. Protocol proposal: Based on these observations, a prospective randomized controlled trial is planned to compare ultrasound-guided acupotomy plus conventional therapy versus conventional therapy alone. Outcomes will be assessed quantitatively using gait analysis. Lessons and implications: Ultrasound-guided acupotomy may offer a minimally invasive, targeted approach to releasing spastic muscles while preserving neurovascular structures, thereby improving gait function in patients with post-stroke EVF. Full article

In equine surface electromyography (sEMG), challenges related to the reliability and interpretability of data arise, among other factors, from methodological differences, including signal processing and analysis. The aim of this study is to demonstrate the filtering–induced changes in basic signal features in relation to the balance between signal loss and noise attenuation. Raw sEMG signals were collected from the quadriceps muscle of six horses during walk, trot, and canter and then filtered using eight filtering methods with varying cut–off frequencies (low–pass at 10 Hz, high–pass at 20 Hz and 40 Hz, and bandpass at 20–450 Hz, 40–450 Hz, 7–200 Hz, 15–500 Hz, and 30–500 Hz). For each signal variation, signal features—such as amplitude, root mean square (RMS), integrated electromyography (iEMG), median frequency (MF), and signal–to–noise ratio (SNR)—along with signal loss metrics and power spectral density (PSD), were calculated. High–pass filtering at 40 Hz and bandpass filtering at 40–450 Hz introduced significant filtering–induced changes in signal features while providing full attenuation of low–frequency noise contamination, with no observed differences in signal loss between these two methods. Other filtering methods led to only partial attenuation of low–frequency noise, resulting in lower signal loss and less consistent changes across gaits in signal features. Therefore, filtering–induced changes should be carefully considered when comparing signal features from studies using different filtering approaches. These findings may support cross-referencing in equine sEMG research related to training, rehabilitation programs, and the diagnosis of musculoskeletal diseases, and emphasize the importance of applying standardized filtering methods, particularly with a high–pass cut–off frequency set at 40 Hz. Full article

Background: The accuracy of measurement of cardiometabolic outcomes in terms of gaseous exchange and energy expenditure of individuals is crucial. The objective of this study was to compare the validity and reliability of the PNO$\overline{\mathrm{E}}$ in measuring cardiometabolic outcomes from the respiratory gaseous exchange of healthy individuals during treadmill walking exercise. Methods: A total of 21 healthy subjects (15 male and 6 female) aged 22.76 ± 3.85 years took part in this study. Oxygen uptake (VO₂), carbon dioxide production (VCO₂), respiratory exchange ratio (RER), metabolic equivalents (METs), tidal volume (VT), and energy expenditure (EE) were measured using the PNO$\overline{\mathrm{E}}$ and COSMED K5 portable systems during a twenty-eight-minute, four-stage incremental protocol, where speed increased from 1.7 mph to 4.2 mph with a 2% incline on a treadmill. Test–retest reliability was tested on separate days with trail repetition. Validity was evaluated by Bland–Altman plots, intraclass correlation coefficients (ICCs) and mean percentage difference. Results: ICCs showed that VCO₂ was in the good range (0.75–0.90). The ICC of the RER from stages 1 to 3 of the incremental protocol and the VT from stages 2 to 4 of the incremental protocol showed good to excellent reliability. No clear trend was seen for VO₂, VCO₂, and EE datapoints with variations in speed. Pearson’s correlation coefficients were moderately high (r = 0.60–0.79) between VO₂, VCO₂, RER, METs, VT, and EE measured by the PNO$\overline{\mathrm{E}}$ and K5 systems. All subjects, except for a few cases in VT, were within the upper and lower 95% confidence intervals of the acceptable range of the Bland–Altman plots. Conclusions: The PNO$\overline{\mathrm{E}}$ system is a valid and reliable measure of cardiometabolic outcomes and is comparable to the COSMED K5 system. Full article