Search Results (881)

Background: Since sedentary habits have become a growing global public health concern, the promotion of physical activity (PA) from early childhood could help children live healthy lifestyles. The aim of this systematic review was to analyze the level of compliance with PA in preschoolers in relation to the reference guidelines. Method: A systematic review of relevant articles was carried out using four databases (PubMed, ProQuest, SCOPUS, and FECYT (Web of Sciences, CCC, CIDW, KJD, MEDLINE, RSCI, and SCIELO)) until 14 May 2025. The methodological assessment process was performed by using an adapted version of the MINORS assessment criteria. Results: A total of 623 studies were initially found and 23 were included in the qualitative synthesis. Conclusions: The results revealed that the average in most contexts usually ranges between 30% and 65% of the child population. Due to different operational criteria, compliance was generally higher when PA was assessed separately using single-behavior guidelines as opposed to when integrated 24 h movement frameworks were used. However, these results should be considered with caution because establishing the level of adherence to PA guidelines is difficult due to the different outcomes and guidelines used to compare the level of children’s PA. In future research, it is important to establish common baseline criteria (specifying more specific ages, common questionnaires, and criteria for calculating PA quantity and intensity) to facilitate more objective and reliable comparisons between studies. This systematic review is important because it highlights the need for healthy educational habits from the first years of a person’s life. Full article

Background: Orthodontic tooth movement is traditionally explained through mechanical deformation of the periodontal ligament (PDL); however, increasing evidence indicates that immune mechanisms critically shape bone remodeling outcomes. Mechanical stimuli influence immune cell recruitment, cytokine release, and phenotypic polarization, but these components are rarely integrated into a unified framework. Conceptual framework: We propose the Osteoimmune Axis Model, a conceptual framework describing how mechanical loading may bias immune polarity and thereby gate periodontal remodeling. Compressive loading appears to favor an M1 macrophage/Th17-dominant program associated with pro-inflammatory cytokines and enhanced RANKL-mediated osteoclastogenesis. In contrast, tensile or physiological strains may favor M2 macrophages and regulatory T cells (Treg), supporting IL-10, TGF-β, angiogenesis, extracellular-matrix repair, and osteoblastic activity. Stromal cells are proposed to act as mechanosensors and immune amplifiers that shape cytokine gradients and feedback loops. Predictions: The model predicts that identical forces may produce divergent outcomes depending on immune baseline; load duration may be more destructive than peak magnitude; tensile strain may stabilize M2/Treg pathways; thin periodontal phenotypes may shift toward the catabolic pole at lower mechanical loads; ROS may amplify immune-mediated bone loss; and immunomodulation may raise the threshold for pathological remodeling. Conclusion: The Osteoimmune Axis integrates mechanobiology and immunology into a testable framework for explaining variability in orthodontic periodontal remodeling and for generating hypothesis-driven, immune-aware risk assessment. Full article

Background/Objectives: Virtual surgical planning (VSP) allows three-dimensional assessment of complex dentofacial deformities and has become integral to modern orthognathic surgery. However, evidence remains limited regarding how skeletal characteristics and malocclusion patterns translate into surgical movement selection. This study aimed to evaluate demographic features, skeletal malocclusion patterns, and clinical treatment strategies in patients undergoing VSP-guided orthognathic surgery. Methods: This retrospective study included 158 patients who underwent VSP-assisted orthognathic surgery between 2019 and 2025. Sagittal skeletal classification, vertical growth pattern, facial asymmetry, and maxillary crossbite were evaluated together with planned maxillary and mandibular movements. Surgical procedures were analyzed according to skeletal malocclusion classes (Class I, II, and III). Group comparisons were performed using chi-square and Kruskal–Wallis tests. Multivariable logistic regression analysis was conducted to assess factors associated with bimaxillary surgery (p < 0.05). Results: Skeletal Class I malocclusion was most prevalent (46.8%), followed by Class III (29.7%) and Class II (23.4%). Hyperdivergent growth patterns were predominantly observed in Class II patients, whereas normodivergent patterns were most common in Class III cases (p < 0.05). Mandibular advancement and setback generally followed expected class-based trends but were also observed across non-corresponding skeletal classes. Maxillary impaction and mandibular autorotation were frequently incorporated. Bimaxillary surgery was performed in 84.2% of cases. Logistic regression analysis showed no independent predictors of bimaxillary surgery (p > 0.05). Conclusions: VSP-assisted orthognathic surgery demonstrates that surgical planning cannot be reduced to sagittal skeletal classification alone. Treatment decisions are shaped by combined sagittal, vertical, transverse, and patient-specific factors, supporting a multidimensional and individualized planning approach. Full article

Muscle onset detection is a fundamental problem in electromyography signal analysis, human–machine interaction, and rehabilitation assessment. In medical and biomedical applications, slow muscle activation onset processes are widely encountered in scenarios such as rehabilitation training, postural regulation, and fine motor control. Such processes are typically characterized by slowly varying amplitudes, long temporal durations, and high susceptibility to noise interference, which poses significant challenges for accurate identification of onset timing. To address these issues, a lightweight temporal attention method for slow muscle activation onset detection is proposed and systematically validated under multimodal experimental settings. The proposed method takes surface electromyography signals as the primary input, while synchronously acquired optical motion image data are incorporated into the experimental design and result analysis, thereby aligning with the common joint use of optical imaging and physiological signals in medical and biomedical research. From a methodological perspective, the proposed framework is composed of lightweight temporal feature encoding, a slow activation-aware temporal attention mechanism, and noise suppression with stable decision strategies. Under the constraint of low computational complexity, the ability to model progressive activation signals is effectively enhanced. Experiments are conducted on a dataset containing multiple types of slow activation movements, and model performance is evaluated using five-fold cross-validation. The results demonstrate that under regular signal-to-noise ratio conditions, the proposed method significantly outperforms traditional threshold-based approaches, classical machine learning models, and several deep learning baselines in terms of onset detection accuracy, recall, and precision. Specifically, onset detection accuracy reaches approximately $92\%$, recall is around $90\%$, and precision is approximately $93\%$. Meanwhile, the average onset detection error and detection delay are reduced to about $41\mathrm{ms}$ and $28\mathrm{ms}$, respectively, with the false positive rate controlled at approximately $2.2\%$. Stable performance is further maintained under different noise levels and cross-subject settings, indicating strong robustness and generalization capability. Full article

Sports performance in aquatic environments is governed by biomechanical, physiological, neuromuscular and perceptual–mental constraints that differ fundamentally from those encountered on land. As a result, athletes with comparable general physiological or motor capacities may achieve markedly different performance outcomes in aquatic sports. Within functional kinesiology and sport science, aquatic performance is still frequently interpreted through isolated physiological, biomechanical, or technical variables, which limits both explanatory depth and applied relevance. This Perspective article introduces aquaticity as an integrated latent construct representing a multidimensional determinant of sports performance specific to the aquatic environment. Aquaticity is conceptualized as a functional framework that modulates how general physiological and motor capacities are expressed under aquatic constraints, integrating key domains of exercise physiology, sport biomechanics, neuromuscular control, energetic regulation, and perceptual–mental stability. The relative contribution of these domains is considered discipline-specific and dependent on task and environmental demands. Breath-hold diving is presented as a particularly suitable model for examining aquaticity, as apnea and hypoxic–hypercapnic stress amplify interactions between physiological regulation, neuromuscular control, and biomechanical efficiency. Training and diagnostic tasks performed in real aquatic settings are interpreted as manifest indicators of aquaticity, enabling ecologically valid athlete monitoring and performance assessment. Within this framework, energetic aquaticity is highlighted as a central functional sub-construct linking metabolic regulation, movement efficiency, and neural control during performance under respiratory constraints. The proposed conceptual framework has important implications for functional kinesiology, sport biomechanics, exercise physiology, and applied athlete monitoring in aquatic sports. Aquaticity is advanced not merely as a descriptive concept, but as a unifying framework that can guide future experimental research, discipline-specific diagnostics, individualized training design, and safety-oriented performance assessment in aquatic environments. Full article

The Bayan Obo Mining District, recognized as the largest rare-earth resource base worldwide, has experienced significant surface instability due to intensive mining and large-scale dumping activities. To address the challenges posed by complex geological conditions and mining-induced disturbances, this study employs dual-ascending Sentinel-1A C-band Synthetic Aperture Radar (SAR) datasets (Path 11 and Path 113) and applies the Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) technique to retrieve time-series deformation along the line-of-sight (LOS) direction for each track. Through temporal normalization and spatial matching, paired LOS observations from the two tracks were established. Based on the SAR observation geometry and under the assumption that the north–south component is negligible, a LOS projection model was constructed and a geometric decomposition was performed to derive the east–west and vertical two-dimensional deformation fields. The results indicate that the study area is generally stable, while significant subsidence occurs in the northern pit and adjacent waste-dump zones, with local maximum rates approaching 50 mm/year, predominantly controlled by the vertical component. The two-dimensional deformation analysis reveals that vertical displacement dominates surface motion, whereas east–west movement shows smaller amplitudes but clear directional concentration. In particular, the east–west slopes exhibit slightly higher velocities, suggesting a lateral adjustment tendency along this direction, likely related to the overall east–west geometric configuration of the open-pit and waste-dump areas. Time-series observations further reveal that precipitation-related surface deformation occurs with an approximate two-month delay, reflecting the hydrological–mechanical coupling processes of rainfall infiltration, pore-water pressure propagation, and dump-material consolidation. Overall, this study reveals the multi-dimensional deformation characteristics and precipitation-driven stage-wise response of the mining area, demonstrating the effectiveness of the dual-ascending SBAS-InSAR for two-dimensional deformation monitoring in highly disturbed environments, and providing a scientific basis for surface stability assessment and geohazard prevention. Full article

This study focuses on enhancing the performance of piezoelectric nanogenerators (PENGs) fabricated by electrospinning (ES) of polyvinylidene fluoride (PVDF) infused with varying concentrations (0, 1, 3, 5, and 7 wt.-%) of copper oxide (CuO) nanoparticles. Structural changes and the β-phase proportion in nanofibers (NFs) were examined using XRD and FTIR-ATR. Surface morphology and roughness were characterized using FE-SEM and AFM, respectively. The water-repellent characteristics of the NFs were assessed through WCA measurements. Electrical output (voltage and current) was evaluated under mechanical pressure using a customized setup that applied 1.0 kgf at 1.0 Hz. The pristine PVDF-based PENG generated an output of 1.7 V and 0.53 μA, while the composite NF with 5 wt.-% CuO (5PCu) delivered a significantly enhanced output of 13.7 V and 1.6 μA. The 5PCu device was further tested for detecting human activities, including tapping, wrist movements, walking, and jumping, thereby demonstrating its potential for self-powered wearable electronics. Full article

Individuals with intellectual disabilities (IDs) consistently demonstrate lower levels of objectively measured physical activity (PA) compared to the general population, yet limited evidence exists regarding how activity accumulated during physical education (PE) contributes to overall daily movement within structured school contexts. Within the school setting, PE represents one of the primary structured opportunities for engaging students with IDs in PA. Although objective physical activity monitoring approaches are recommended for school-based PA assessment, limited evidence exists on the contribution of PE to total school-day activity in students with intellectual disabilities, a gap addressed in the present study. In this context, the present study objectively recorded PA levels of students with IDs both during PE lessons and across five school days, in order to examine the contribution of PE to overall PA. Potential differences in PA according to gender and severity of the ID were also examined. Twenty students aged 15–25 years with mild and moderate IDs participated in the study. PA was assessed using the YAMAX Power Walker EX-510 pedometer, which automatically recorded step counts. The results indicated that only six participants reached step-count reference values. Students with mild IDs accumulated significantly more steps than those with moderate IDs, while male students were more physically active than female students, both during PE lessons and across the school day. PE lessons contributed approximately 4% to the total PA accumulated across the five monitored school days. These findings highlight the limited contribution of PE to overall PA and underscore the importance of promoting greater movement opportunities within adapted PE lessons. Full article

Background and Objectives: Surface electromyography (EMG) is widely used to assess muscle activation. However, direct interpretation of its functional biomechanical consequences remains challenging. This study aimed to develop and evaluate an EMG-driven musculoskeletal simulation framework for investigating how controlled modifications of muscle activation patterns influence joint-level biomechanics in the upper limb. The objective was not to reproduce specific clinical pathologies but to enable systematic virtual scenario analysis of activation-dependent movement alterations. Materials and Methods: Surface EMG signals were recorded from five healthy adults (3 males, 2 females; age 22 ± 1 years) during cyclic elbow flexion/extension tasks using a wireless system (sampling frequency: 2000 Hz). Processed and normalized EMG envelopes were directly applied as prescribed neural inputs in forward dynamic simulations implemented in OpenSim, without optimization-based muscle recruitment. Controlled virtual scenarios were generated through parametric modification of activation signals to represent reduced activation capacity, increased antagonist co-activation, spasticity-like activation modulation, and tremor-like oscillatory modulation. Joint kinematics, joint moments, and movement stability were evaluated. A Movement Quality Index (MQI) was introduced as a comparative research metric integrating biomechanical performance indicators. Simulations were deterministic and analyzed descriptively. Results: Distinct activation modifications produced characteristic kinematic and kinetic responses. Reduced activation capacity decreased simulated joint moment output, increased co-activation altered joint moment timing and mechanical stability, and tremor-like oscillatory modulation generated periodic fluctuations in joint kinematics and kinetics. The MQI enabled quantitative differentiation between simulated scenarios and severity levels within the controlled modelling framework. Conclusions: The proposed EMG-driven forward dynamic simulation framework provides a methodological platform for controlled virtual scenario analysis of activation-dependent biomechanical changes. The findings highlight the sensitivity of joint-level mechanics to altered muscle activation patterns, within the deterministic modelling environment. The framework is intended for research-oriented biomechanical investigation and hypothesis testing rather than direct clinical diagnosis of neuromuscular disorders. Full article

Background/Objectives: Clinical and scientific professionalization in orthodontics requires a comprehensive understanding of the biomechanical principles governing force generation and distribution produced by orthodontic appliances, beyond purely esthetic considerations. In this context, finite element analysis (FEA) has emerged as a fundamental computational tool for the detailed evaluation of the biomechanical behavior of the dentoalveolar system. The aim of this study was to map and synthesize the available scientific evidence on the application of FEA in the assessment of force distribution, tooth movement, and the mechanical response of periodontal tissues during orthodontic treatment. Methods: Original studies published between 2020 and 2025 that relied exclusively on computational simulations using FEA were included. Eligible studies addressed orthodontic biomechanics, including tooth movement, appliance–tooth–periodontium interactions, or the mechanical evaluation of orthodontic attachments. Clinical studies, narrative reviews, and articles without finite element modeling were excluded. A systematic literature search was conducted in the PubMed and ScienceDirect databases to answer the following question: Which FEA methodologies have been used to evaluate the biomechanical behavior of orthodontic appliances? Results: Data were categorized according to key biomechanical variables. The findings indicate an increasing use of FEA as a supportive tool in orthodontic research. However, significant limitations were identified, including lack of methodological standardization, limited model validation, and insufficient correlation between computational outcomes and clinical evidence. Conclusions: Currently, FEA in orthodontics is used predominantly for descriptive purposes, particularly for visualizing stress and strain distributions. Greater standardization and validation are required to enhance its translational applicability in clinical relevance. Full article

This study evaluated the test–retest reliability of a depth sensor-based Fukuda Stepping Test and examined associations between sensor-derived kinematic parameters and established clinical outcomes in older adults. Eighty-six community-dwelling older adults (mean age 70.3 ± 4.7 years) performed an eyes-closed stepping task monitored by a Microsoft Kinect v2 sensor. Clinical assessments included the Berg Balance Scale, Timed Up and Go test, Five Times Sit-to-Stand, Montreal Cognitive Assessment, International Physical Activity Questionnaire, and WHOQOL-OLD. Test–retest reliability was assessed using intraclass correlation coefficients in a randomly selected subgroup. Reliability estimates varied across parameters, with temporal and displacement-based measures demonstrating more consistent agreement across sessions, whereas selected angular variables showed greater variability. Correlation analyses identified statistically significant associations between trunk kinematic changes and clinical measures, with effect sizes generally ranging from weak to moderate magnitude. Upper trunk rotation was associated with functional mobility measures, while traditional displacement-based metrics demonstrated limited clinical relationships. These findings support the feasibility of markerless depth-sensing technology for objective quantification of movement during the Fukuda Stepping Test and highlight the potential contribution of segmental kinematic parameters to multidimensional functional assessment in older adults. Full article

Background: Periodontitis is a highly prevalent chronic inflammatory disease characterized by a complex host–microbe interaction and modulated by systemic regulatory pathways, including stress-related neuroendocrine and immunological mechanisms. Mind–body movement-based interventions such as yoga, tai chi, and qigong have demonstrated beneficial effects on stress and inflammation in general medicine, yet their relevance for periodontal health has not been systematically mapped. Methods: A scoping review was conducted in accordance with the Joanna Briggs Institute methodology and the PRISMA-ScR guidelines. Eligibility criteria included studies conducted in adult human participants examining mind–body movement-based interventions in relation to periodontal health. Sources of evidence comprised peer-reviewed studies identified through systematic searches in CINAHL, BIOSIS, Embase, PubMed/MEDLINE, the Cochrane Library, Web of Science, and LIVIVO. Data were charted using a standardized extraction form capturing key study characteristics and outcomes. Eligible studies reported clinical periodontal parameters and/or biological or psychosocial outcomes related to stress or inflammation. Results: Eleven studies investigating mind–body movement-based interventions and periodontal health were included. Interventions comprised yoga, pranayama, tai chi, and qigong, with study designs ranging from one randomized controlled trial to non-randomized interventional and observational studies. Most studies reported clinical periodontal parameters and/or periodontal-related biological markers, including inflammatory, oxidative, and immune markers, and several also assessed stress-related outcomes. The interventions were applied both as adjuncts to conventional periodontal therapy and as stand-alone approaches. Overall, the included studies reported short-term changes in periodontal parameters and stress-related measures that were generally directed towards associated with improvement; however, long-term periodontal outcomes were rarely assessed. Conclusions: Mind–body movement-based interventions, such as yoga and pranayama, have been examined in relation to periodontal health, with studies reporting periodontal clinical parameters, biological markers, and stress-related outcomes. The available evidence is heterogeneous and largely limited to short-term observations. Further methodologically rigorous studies with standardized outcome measures and longer follow-up periods are needed to better characterize the relationship between mind–body interventions and their potential adjunctive relevance in periodontal care, as current evidence does not allow conclusions regarding their routine adjunctive use. Full article

Background: Globally, over 15 million people live with spinal cord injury (SCI), which often leads to permanent motor impairment. In these cases, functional electrical stimulation (FES) can generate muscle forces and active movements in affected body parts, enabling patients to perform cycling tasks using their own paralyzed legs. Incomplete spinal cord injuries are more prevalent than complete injuries and FES cycling can be performed in both cases. However, differences in its effects between the two groups remain to be further investigated. Our objective is to compare the effects of FES-assisted cycling on blood pressure, heart rate, and power output in patients with incomplete (iSCI) versus complete (cSCI) spinal cord injuries. We aim to provide comparative data currently missing from existing research. Methods: Thirty-two patients (20 iSCI, 12 cSCI), completed at least ten FES cycling training sessions. Each session consisted of 30 min of cycling on a MOTOmed Viva2 cycle-ergometer (Reck GMBH, Betzenweiler, Germany) equipped with a multi-channel electrical stimulator. The outcome measures were assessed in each session four times: before and after the session, and approximately at the 10th and 20th minutes. Statistical analyses compared mean arterial pressure (MAP), heart rate (HR), average and peak power output between the two groups. Results: Regarding within session differences, the iSCI group maintained significantly higher MAP than the cSCI group at all measurement points. HR patterns also differed significantly, showing higher values in the iSCI group at the second and third measurement points. On the course of the sessions in iSCI patients, average and peak power output increased significantly from the first to the tenth session. In cSCI patients the average power output was nearly constant throughout the ten sessions. Conclusions: Patients with iSCI and cSCI show different cardiovascular adaptations, and increasing FES cycling power output indicates that patients with incomplete injuries can achieve greater improvements even after ten training sessions. Full article

Precisely assessing driving danger is essential for various applications, including the advancement of autonomous driving systems and traffic engineering decisions. This study presents a driving risk analysis framework based on the Next-Generation Simulation (NGSIM) dataset. First, vehicles were classified into four risk classes using the Fuzzy C-Means algorithm using five key risk indicators. Subsequently, comprehensive driving behavior features representing vehicle movements were extracted and evaluated for both risk class prediction and driving behavior feature selection. A new driving risk score was developed using Spearman’s rho coefficient weights, which reflect the relationship of each risk indicator to risk levels. This score was observed to exhibit an increasing trend consistent with the sequential structure of the Fuzzy C-Means (FCM) clustering based on risk labels, thus confirming that it accurately reflects the labeling process. Furthermore, the findings show that the 26 key driving behavior features selected can predict the driving risk score developed using the XGBoost algorithm with over 85% accuracy. Moreover, feature importance analysis reveals that the following distances and inter-vehicle distance variability are particularly effective in determining driving risk. The study discusses the limitations of driving risk assessment based solely on vehicle dynamics and highlights the importance of developing enriched datasets that include multidimensional data sources such as environmental conditions, infrastructure features, traffic density, and autonomous vehicles in future risk prediction studies. Ultimately, this framework contributes to the development of safer and more efficient transportation systems, supporting environmental sustainability by reducing accident-related congestion and promoting resource-efficient traffic management. Full article

The purpose of this review was to evaluate the current literature using plane-based analyses to describe open-chain proximal-to-distal sport motions and to clarify how these approaches can extend to other activities to advance biomechanical assessment. Open-chain sport motions typically rely on a coordinated rotational axis that allows momentum to be transferred efficiently through the kinetic chain. Although this directional organization is central to performance, most biomechanical studies have relied on discrete, event-based variables rather than modeling the continuous trajectory structure of the movement. This review summarizes applications of motion-plane models in sports and discusses how their conceptual foundations can apply to other movements. Four primary approaches for deriving optimal-fit planes from three-dimensional trajectories are described: Principal Component Analysis (PCA), Singular Value Decomposition (SVD), Orthogonal Least Squares (OLS), and the Functional Swing Plane (FSP). These methods rely on different algebraic formulations to model kinematic trajectories. By comparing their mathematical foundations, strengths, and limitations, we highlight how plane-based models provide a meaningful perspective for examining movement efficiency, movement strategy, and potential injury risk across open-chain proximal-to-distal sports. Future research should apply these models across multiple sports to generate individualized trajectory planes, quantify plane deviation, and integrate measures of joint loading and performance, and may combine models to build motion planes. Full article