Search Results (1,145)

Background: Corticosteroid injections provide short-term relief for chronic subacromial bursitis but are associated with high recurrence rates. This study investigates the efficacy of a mobile health-supported home-based resistance exercise program compared with exercise education in patients with chronic recurrent subacromial bursitis after ultrasound-guided corticosteroid injections. Methods: Participants with chronic subacromial bursitis were assigned via computer-generated block randomization to either an intervention group receiving ultrasound-guided corticosteroid injections followed by a 12-week home-based exercise program (50 min strengthening and resistance/session, 5 days per week) supported via instant messaging applications, or a control group receiving the same injection followed by printed educational materials covering the same exercise protocol. Shoulder Pain and Disability Index (SPADI) scores, Visual Analog Scale (VAS) pain scores and active pain-free range of motion (ROM) were evaluated by a blinded assessor at weeks 4 and 12. Between-group comparisons were analyzed using two-way ANOVA after confirming normality and homoscedasticity. Results: Fifty-three patients (mean age: 55.6 ± 10.5 years; 47.2% female) were randomized to the intervention (n = 27) or control (n = 26) groups. Significant interaction effects were identified for SPADI (p = 0.040) and ROM (abduction: p = 0.036/ flexion: p = 0.032). Post hoc analysis revealed that the intervention group exhibited a significantly greater reduction in SPADI scores (p = 0.007, d = 0.72) and greater increase in abduction ROM (p = 0.004, d = 0.84) at 12 weeks; both gains surpassed the MCID. Conclusions: A mobile health-supported home-based resistance exercise program can significantly extend the benefits of corticosteroid injections in patients with chronic subacromial bursitis. Trial Registration: NCT06220643, registered 14 December 2023. Full article

Background: Knee osteoarthritis (KOA) is a major cause of pain, mobility limitation, and increased fall risk among older adults. Gait dysfunction, characterized by spatiotemporal and kinematic alterations, is a key functional consequence of KOA. While sagittal-plane gait deviations are well-established, multiplanar kinematic changes—particularly in the frontal and transverse planes—remain less clearly understood. This study aimed to compare three-dimensional gait characteristics between older adults with and without KOA. Methods: Ninety older adults (45 with KOA and 45 controls) completed gait assessments using a VICON™ motion capture system. Participants walked at a self-selected speed along a straight walkway without turning movements during data collection. Spatiotemporal parameters and lower-limb joint kinematics (hip, knee, and ankle) were recorded during key gait phases: initial contact, mid-stance, toe-off, and mid-swing. Group comparisons were performed using independent t-tests with statistical significance set at p < 0.05. Results: Compared with controls, participants with KOA demonstrated significantly slower gait velocity (p = 0.001), reduced cadence (p = 0.020), shorter stride length (p = 0.011), increased step time (p = 0.006), prolonged double support time (p = 0.009), and reduced single support time (p = 0.012). Kinematic analysis revealed greater knee adduction at initial contact (p = 0.001), reduced hip adduction (p = 0.002) and greater knee adduction (p = 0.003) during mid-stance, and increased ankle plantarflexion at toe-off (p = 0.004) in the KOA group. No significant between-group differences were observed during the mid-swing phase. Conclusions: Older adults with KOA exhibit distinct spatiotemporal and multiplanar kinematic gait alterations, particularly during weight-bearing phases. These changes may reflect adaptive gait patterns associated with joint dysfunction rather than definitive compensatory mechanisms. Three-dimensional gait analysis may provide valuable biomechanical insights to support early identification of mobility impairments and inform targeted rehabilitation planning in individuals with KOA. Full article

Modern-day urban warehouses face exploding large inventory and tight spaces requiring fast, accurate, and safe stocktaking in a narrow aisle in a GPS-denied environment. This paper proposes a complete UAV-enabled framework performing real-time QR code scanning with inventory synchronization through a safety-aware trajectory generation for obtaining collision-free motion. A novel hybrid workflow integrating MATLAB/Simulink R2024b and Unreal Engine is used for dynamics and photorealistic rendering, alongside a real-time warehouse setup using drone cameras and 3D LiDAR coupled with a ground control station and live dashboard. The system in this paper was evaluated by testing with single and multi-UAV models across high-fidelity simulations and experiments. Results demonstrate simulated QR accuracy of approximately 95 to 96%, with experimental validation achieving between 86 and 90.5% due to real-world environmental factors. In experimental and simulation analysis, mean end-to-end latency remained under half a second, trajectory error range between 8 and 10 cm, and safety margins were consistently maintained throughout the test. It was further observed that multi-UAV coordination halved mission time compared to single-drone tests while keeping duplicate reads negligible, indicating a scalable and safe pipeline for industry application. Full article

High-speed precision positioning systems require motion profiles that achieve rapid transfer while suppressing motion-induced vibration. Conventional time-optimal trajectories often minimize travel time at the expense of residual vibration, which prolongs settling and degrades positioning accuracy. This paper proposes a systematic framework for designing optimized time-shifted sine motion profiles that explicitly incorporate vibration suppression in the frequency domain. By integrating time-domain profile construction with Laplace-domain analysis, motion profiles are derived in a unified manner from 1^st-order to generalized $n^{\mathrm{th}}$-order forms. A key theoretical result shows that the residual vibration amplitude after motion completion is proportional to the magnitude of $\left|sX\right(s\left)\right|$ evaluated at the system poles, providing a clear analytical basis for a closed-form zero placement strategy. Explicit algebraic design conditions are obtained without iterative numerical optimization. Simulation-based case studies demonstrate that the proposed approach drastically reduces transient and residual vibrations while maintaining competitive motion completion times compared with time-optimal designs. Robustness is quantitatively evaluated using insensitivity and high-frequency roll-off metrics, revealing that increasing the profile order improves uncertainty tolerance by approximately $-20$ dB/decade per order. Furthermore, a short-stroke scenario shows that lower-order sine profiles can be advantageous under moderate uncertainty. The proposed framework provides a practical guideline for vibration-aware high-speed motion control. Full article

Objective: The objective of this study was to explore the motion characteristics and movement strategies of the hip and knee joints in overweight individuals during sit-to-stand (STS) transfers using statistical parametric mapping (SPM). Methods: Twenty subjects were divided into an overweight group (n = 10) and a normal-weight group (n = 10) based on body mass index (BMI). The Qualisys infrared motion capture system and Kistler three-dimensional force platform were used for motion data collection, and Visual 3D and Matlab were used to calculate the angles and torque indicators of the lower limb hip and knee joints. Results: During the STS process, the maximum hip flexion angle of the overweight group was smaller than that of the control group (Z = −1.83, p = 0.043, r = 0.39), while the maximum abduction and external rotation angles were greater than those of the control group (Z = −2.15, p = 0.022, r = 0.46; Z = −2.02, p = 0.028, r = 0.48). SPM analysis showed that during the 0–52% phase of the hip joint in the frontal plane, the abduction amplitude of the overweight population was greater than that of the normal population (p < 0.05). The minimum external rotation angle of the knee joint was less than that of the control group (F(1,18) = 9.135, p = 0.043). The peak internal adduction and abduction torque of the hip joint in the overweight group was greater than that of the control group (Z = 2.37, p = 0.017, r = 0.54). Conclusions: Compared with the normal-weight population, the overweight population exhibited distinct motion characteristics of the hip and knee joints during the STS, with particularly pronounced differences in the hip joint. To maintain stability during STS, the overweight population adopts a compensatory movement strategy featuring a wider base of support via hip abduction and increased muscular torque to control frontal plane stability, which imposes greater functional loads on the hip joint. BMI-related movement characteristics should be studied in young adults under controlled experimental conditions, and future studies are needed to verify whether similar patterns exist in older adults. Full article

Terrestrial laser scanning (TLS) provides dense point clouds for landslide monitoring, yet occlusion, heterogeneous point density, and seasonal vegetation introduce noise and unstable deformation boundaries in multi-temporal change detection. To overcome the limitations of the multiscale model-to-model cloud comparison (M3C2) method under dominant downslope tangential motion and vegetation disturbance, we propose a block-wise ICP method to retrieve 3D displacement vectors. The scene is partitioned into local sub-blocks; rigid registration is performed within each sub-block, and the estimated translation is assigned to the sub-block center. A two-stage matching and quality control procedure removes under-constrained sub-blocks, enabling the direct retrieval of 3D displacement vectors and interpretable boundaries. Applied to the Longxigou landslide in Wenchuan using RIEGL VZ-2000i surveys on 1 November 2023 and 23 May 2024, the proposed method produces a more continuous displacement field and clearer boundaries than M3C2. For a tower target, manual measurements indicate a displacement of 0.41–0.63 m; our estimates are within 0.33–0.40 m, whereas M3C2 mostly falls between −0.25 and 0.25 m. In a seasonal vegetation change scene, we detect a canopy envelope expansion of approximately 0.20–0.40 m, while M3C2 shows scattered canopy responses that hinder boundary interpretation. A sensitivity analysis indicates a block-scale trade-off between boundary stability and peak preservation, motivating adaptive multi-scale blocking and uncertainty quantification. Full article

Background: Qualitative motion analysis revealed that the cervical spine moves according to a consistent pattern. Current data analysis methods are limited by the extensive time required to process the retrieved data. A previous study demonstrated the feasibility of using a deep-learning model to automate analysis methods. However, segmentation accuracy needed to be improved. This study aims to improve segmentation model performance to enable reliable motion analysis. Methods: Four nnU-Net configurations were tested: baseline (A), pre-trained (B), with histogram equalization (C), and pre-trained with histogram equalization (D). Segmentation performance was evaluated using Dice Similarity Coefficient (DSC), Intersection over Union (IoU) and 95th percentile Hausdorff Distance (HD95). Vertebral rotation was estimated using mean shapes. Reliability was assessed using the Intraclass Correlation Coefficient (ICC). Sensitivity analyses were conducted. Results: Across all models, mean DSC ranged from 0.67 to 0.92, mean IoU from 0.55 to 0.85, and mean HD95 from 2.35 to 19.67 mm. After sensitivity analysis for low segmental range of motion (sROM) and low-quality recordings, the mean ICC ranged from 0.617 to 0.837 for model A, from 0.609 to 0.780 for model B, from 0.409 to 0.689 for model C, and from 0.480 to 0.835 for model D. Conclusions: This study shows that Models A and B can accurately analyze cervical motion patterns. High image contrast and an adequate sROM are essential for robust model performance. It also marks an important step toward automated qualitative motion analysis, increasing the accessibility of motion pattern evaluation. Full article

Gears are one of the most important machine elements widely used to transmit motion and power in various machines. The gear tooth stiffness has a significant impact on the load distribution, vibration characteristics, and overall efficiency of gear systems. Therefore, accurate analysis of tooth stiffness is crucial for optimizing gear performance and ensuring reliable operation. In this study, the effects of geometric parameters on single tooth stiffness (STS) and time-varying mesh stiffness (TVMS) of involute spur gears are investigated numerically. The gear design parameters, such as drive side pressure angle (DSPA) (20°, 25°, 30°), addendum (1–1.5 × module), and dedendum (1.25–1.7 × module), are varied. Gear configurations with both low contact ratio (LCR) and high contact ratio (HCR) are evaluated. Parametric models are first developed using MATLAB, and then 3D CAD models are created in CATIA for static structural analysis in ANSYS Workbench. The results indicate that increasing the pressure angle enhances stiffness in the tooth root region, whereas the effect is less significant near the tooth tip. Increasing the addendum length generally reduces stiffness. In some cases, a rise in contact ratio results in up to a 25% increase in mesh stiffness. These findings demonstrate that single tooth and mesh stiffness can be optimized through precise control of gear geometry. Ultimately, the study provides valuable insights for improving gear performance and durability through informed design choices. Full article

Three-dimensional (3D) reconstruction using images is one of the most significant topics in computer vision and photogrammetry, with wide-ranging applications in robotics, augmented reality, and mapping. This study investigates methods of 3D reconstruction using video (especially monocular video) data and focuses on techniques such as Structure from Motion (SfM), Multi-View Stereo (MVS), Visual Simultaneous Localization and Mapping (V-SLAM), and videogrammetry. Based on a statistical analysis of SCOPUS records, these methods collectively account for approximately 6863 journal publications up to the end of 2024. Among these, about 80 studies are analyzed in greater detail to identify trends and advancements in the field. The study also shows that the use of video data for real-time 3D reconstruction is commonly addressed through two main approaches: photogrammetry-based methods, which rely on precise geometric principles and offer high accuracy at the cost of greater computational demand; and V-SLAM methods, which emphasize real-time processing and provide higher speed. Furthermore, the application of IMU data and other indicators, such as color quality and keypoint detection, for selecting suitable frames for 3D reconstruction is investigated. Overall, this study compiles and categorizes video-based reconstruction methods, emphasizing the critical step of keyframe extraction. By summarizing and illustrating the general approaches, the study aims to clarify and facilitate the entry path for researchers interested in this area. Finally, the paper offers targeted recommendations for improving keyframe extraction methods to enhance the accuracy and efficiency of real-time video-based 3D reconstruction, while also outlining future research directions in addressing challenges like dynamic scenes, reducing computational costs, and integrating advanced learning-based techniques. Full article

Accurate environmental perception is fundamental to safe autonomous driving; however, most existing multimodal systems rely on fixed or heuristic sensor fusion strategies that cannot adapt to scene-dependent variations in sensor reliability. This paper proposes Cross-Modal Adaptive Attention (CMAA), a unified end-to-end Bird’s-Eye-View (BEV) perception framework that dynamically fuses camera, LiDAR, and RADAR information through learnable, context-aware modality gating. Unlike static fusion approaches, CMAA adaptively reweights sensor contributions based on global scene descriptors, enabling the robust integration of semantic, geometric, and motion cues without manual tuning. The proposed architecture jointly performs 3D object detection, multi-object tracking, and motion forecasting within a shared BEV representation, preserving spatial alignment across tasks and supporting efficient real-time deployment. Experiments conducted on the official nuScenes validation split demonstrate that CMAA achieves 0.528 mAP and 0.691 NDS, outperforming fixed-weight fusion baselines while maintaining a compact model size and efficient inference. Additional tracking evaluation using the official nuScenes tracking devkit reports improved tracking performance, while motion forecasting experiments show reduced trajectory displacement errors (minADE and minFDE). Ablation studies further confirm the complementary contributions of adaptive modality gating and bidirectional cross-modal refinement, and a stratified dynamic analysis reveals consistent reductions in velocity estimation error across object classes, motion regimes, and environmental conditions. These results demonstrate that adaptive multimodal fusion improves robustness, motion reasoning, and perception reliability in complex traffic environments while remaining computationally efficient for deployment in safety-critical autonomous driving systems. Full article

This review systematically examines major research advances in AUV path planning over recent years, covering several mainstream methodologies: sample-based path planning (e.g., PRM and RRT along with their asymptotically optimal variants, suitable for high-dimensional space exploration), graph-search-based path planning (e.g., A-series and D-series algorithms, achieving global optimization and dynamic replanning through environmental modeling), optimization-based approaches (including artificial potential field (APF), nonlinear programming (NLP), and model predictive control (MPC), designed to satisfy stringent dynamic constraints on AUV motion), swarm intelligence-based planning methods (such as genetic algorithms and ant colony optimization), and learning-based intelligent methods (such as deep reinforcement learning (DRL) for real-time decision-making in unknown and dynamic environments). Through in-depth analysis of these methods’ principles, improvement strategies, and AUV path planning contexts, this review highlights current research trends toward hybrid cooperative planning, dynamic environmental adaptability, and high-precision trajectory optimization. Finally, the paper outlines future directions for AUV path planning, emphasizing multi-AUV collaboration and higher-level intelligent decision-making as key research priorities. Full article

This study evaluates the tracking performance of structural damages in disaster environments by combining YOLOv8 detection with the BoT-SORT tracker. Cracks and exposed rebar, characterized by fine and irregular structures, showed high sensitivity to viewpoint changes, with camera motion compensation (CMC) improving $IoU$ by +19.63% and +20.23%. For exposed rebar, the joint use of CMC and re-identification (Re-ID) further increased $IDF1$ by +37.73%, emphasizing the effectiveness of appearance-based matching. In contrast, delamination and concrete debris, with stable morphology and clear boundaries, exhibited limited benefits from CMC, improving $IoU$ by +11.17% and +3.28%. Analysis of $MOTA$, $IDF1$, and $HOTA$ confirms that fine-grained damages require motion- and appearance-based strategies, while stable types maintain high performance through detection consistency. These results highlight the importance of tailored tracking strategies for enhancing disaster-response robots and structural monitoring systems. Full article

Tire-Derived Aggregate (TDA) is a recycled fill material made by cutting scrap tires into small pieces that satisfy the gradation requirements in ASTM D 6270. Since its introduction to civil engineering applications, TDA fill and TDA backfill have been successfully implemented in many projects. However, the dynamic behavior of the TDA backfill under significant earthquakes has not been substantially addressed. The present study used nonlinear time-history Finite Element Analysis (FEA) to analyze the dynamic behavior of a retaining wall with TDA backfill captured from the full-scale shake table test. Unlike typical soil failure observed in a similar retaining wall with conventional soil backfill, significant wall sliding occurred because lightweight TDA contributed to reducing the friction resistance of the wall footing. Therefore, the analysis required modeling capability of rigid body motion and impact loading from the separation between the wall stem and the backfill. With adequate friction models and softened contact models, the FEA generated the dynamic motion of the retaining wall that matched well with the measured responses, including the wall sliding. The friction model between the wall footing and soil was most critical in accurately reproducing wall sliding motion. It was determined to use different friction coefficients for the two different earthquakes used in the study in order to simplify the rate dependence of the coefficient. Also, the softened contact model generated more reasonable impact force by allowing overclosure and finite stiffness during impact. The FEA model and modeling technique in the present study can be used for the seismic design of various field-scale retaining walls with TDA backfill. Full article

Home based telerehabilitation has expanded after COVID-19, but delivering timely guidance and monitoring exercise performance outside the clinic remains difficult. Traditional physiotherapy often relies on repeated execution of simple routines, yet clinicians have limited visibility into adherence and movement quality during unsupervised sessions. From a systems perspective, many telerehabilitation approaches also face constraints in accessibility, bandwidth, and computational cost that can limit practical deployment. This paper presents a modular telerehabilitation framework and prototype that captures and records rehabilitation exercise sessions for asynchronous clinician review in a 3D visualisation environment. The system integrates skeletal motion capture with plantar pressure sensing, and stores sessions as portable artefacts to support replay, inspection, and downstream analysis. A connector-based architecture enables extension to additional sensors without redesigning the core application, and the design aims to support deployment under constrained home computing and networking conditions. The manuscript contributes an implementation blueprint and reference architecture for multimodal capture and replay. Clinical effectiveness, usability outcomes, and quantitative sensor accuracy benchmarking are outside the scope of this work and are identified as necessary future evaluation. Full article

Accurate reproduction of deterministic gusts in wind tunnels is essential for studying unsteady aerodynamics and aeroelastic response in aircraft, uninhabited aerial vehicles, and wind turbines. This work presents the design, experimental characterization, and numerical modelling of a low-speed gust generator based on oscillating vanes, capable of producing high-amplitude gusts in strongly unsteady flow regimes. Cross-flow hot-wire measurements are combined with time-accurate computational fluid dynamics simulations to analyze gust formation and propagation. Classical ‘1-cos’ gusts are shown to exhibit pronounced negative velocity peaks associated with start–stop vortex shedding. A modified vane motion protocol is proposed that significantly reduces the negative peak factor while preserving a substantial gust ratio over a wide range of reduced frequencies. Measurements are supplemented with computational fluid dynamics (CFD) simulations. The CFD study included 2D and 3D URANS as well as higher fidelity DES simulations. Flow-field analysis reveals that secondary variations in gust angle arise from nonlinear interactions between vortices shed by adjacent vanes and are influenced by wind-tunnel confinement. The results provide physical insight into the limitations of oscillating-vane gust generators and guidance for the design of high-fidelity gust-generation systems. Full article