Search Results (840)

Wearable biosensing is moving beyond single-signal activity tracking toward multimodal, AI-assisted health monitoring that combines biophysical streams with biochemical information from sweat, interstitial fluid, tears, and other accessible biofluids. Recent work has accelerated progress in flexible optical materials, programmable DNA-based sensing architectures, biosafety-aware sweat patches, and edge AI pipelines capable of denoising, calibration, personalization, and low-latency inference. This review synthesizes current advances across general biosensor platforms, vital-sign monitoring, biochemical sweat sensing, motion and biomechanics sensing, and edge AI/data analytics. Particular attention is given to the translational bottlenecks that now dominate the field, including motion artifacts, sensor drift, biofouling, subject-to-subject variability, limited sweat-to-blood equivalence, insufficient external validation, and uneven regulatory readiness. The central argument of this updated review is that the next phase of progress will not be driven by sensitivity alone but by robust multimodal fusion, clinically anchored validation, interoperable data pipelines, and energy-efficient on-device intelligence. By linking materials, electronics, algorithms, and deployment constraints, the review identifies the wearable biosensing strategies most likely to progress from promising laboratory demonstrations to reliable personalized-health tools. Full article

This paper proposes a norm-based admissibility criterion formulated in the frequency domain for evaluating whether translational and rotational motion amplitudes of a ship moored at a quay remain within operational limits prescribed by port authorities. The approach is built on a linear six-degree-of-freedom model that includes hydrodynamic added-mass and radiation-damping effects, wave excitation forces, and aerodynamic wind loads, as well as linearized reactions of mooring lines and quay fenders, including an equivalent viscous representation of hull–fender friction. Instead of explicitly inverting the full system matrix to compute the complete response, the admissibility assessment is derived from row-wise norm bounds of the frequency-domain system, yielding a computationally efficient admissibility criterion for compliance with motion limits. The criterion naturally enables a port-oriented decision index and an operational safety margin that can be evaluated for each degree of freedom and used to compare alternative mooring arrangements. Numerical verification is performed for a bulk carrier under storm wave excitation and different loading conditions, demonstrating the sensitivity of admissibility to mooring geometry and pretension. The results confirm that the proposed criterion provides a practical engineering tool for rapid go/no-go decisions regarding cargo operations and supports the selection of mooring arrangements that improve operational robustness under adverse environmental loading conditions. In addition, a Monte Carlo-based uncertainty analysis is performed to evaluate the robustness of the proposed admissibility criterion with variable mooring stiffness and damping parameters. The proposed criterion is intended as a rapid engineering screening tool to complement conventional frequency-domain response analysis. Full article

Background: The natural motion of the human knee involves a combination of rotation and translation, resulting in a variable Instantaneous Center of Rotation (ICR) throughout the gait cycle. Traditional prosthetic knee designs often fail to reproduce this complex kinematic behavior. Objectives: This study aims to propose a customized, biomimetic knee mechanism through the synthesis of a four-bar linkage capable of approximating the physiological ICR trajectory with high precision. Methods: A Genetic Algorithm (GA) was implemented to optimize the geometric parameters of the four-bar mechanism, specifically its link lengths and inter-link angles. The optimization process is based on Freudenstein’s equation, which analytically relates the input and output angles of the linkage to the lengths of its links. The desired ICR trajectory was derived from experimental data, and the objective function minimized the Euclidean error between the generated and target trajectories. Results: The proposed method yielded customized mechanisms that closely approximate the target ICR curves, achieving an overall mean Euclidean tracking error of 1.95% (±1.68%) across diverse patient profiles, with a best-case optimization error as low as 0.355%. Furthermore, the GA demonstrated high computational efficiency, converging on optimal geometric configurations in an average execution time of just 3.98 min. Conclusions: These numerical results validate the robustness of the GA in navigating the design space while strictly adhering to kinematic constraints, Grashof’s condition, and anatomical motion limits. The integration of Freudenstein’s equation with GA-based optimization techniques enables the customized synthesis of four-bar linkages with a high capacity to reproduce the physiological kinematics of the knee. This computational approach could be highly beneficial for the design of polycentric knee prostheses, as it reduces design and manufacturing time by providing the initial parameters for the development of the four-bar mechanism, ultimately ensuring a better biomechanical fit between prosthetic and natural human movement. Full article

Recent context-aware streaming 3D reconstruction frameworks provide a promising solution for online vehicle perception by maintaining anchor references, local pose windows, and trajectory memory. However, directly applying such frameworks to intelligent rail vehicles remains challenging because rail transit scenes are dominated by long straight motion, low-parallax visual observations, repetitive trackside structures, weak textures, and illumination variations. These characteristics may cause redundant context accumulation, unstable frame registration, and gradual trajectory drift. To address this problem, this paper proposes a motion-aware geometric context adaptation method for streaming 3D reconstruction of intelligent rail vehicles in low-parallax scenes. Instead of requiring task-specific large-scale retraining, the proposed method adapts the inference-stage geometric context using scale-normalized visual motion cues, including scale-normalized translational displacement, turning tendency, and inter-frame viewpoint variation. A motion-aware keyframe selection strategy suppresses redundant low-parallax frames while preserving geometrically informative observations in curved or pose-changing segments. An adaptive local pose reference window further regulates recent visual context to improve frame registration consistency. Experiments on rail transit sequences and the Oxford Spires dataset show that the proposed method achieves lower trajectory error than LingBot-Map and VIPE, while reducing redundant keyframe storage and preserving the qualitative continuity of rail-related structures. The method provides a practical motion-aware streaming 3D perception solution for rail transit inspection and digital infrastructure management. Full article

Background: Oromucosal films are thin polymeric dosage forms designed to hydrate rapidly in the oral cavity and enable local or systemic drug delivery. Their performance depends on coupled processes including wetting, swelling, polymer relaxation, matrix softening, and structural failure. Because these phenomena depend strongly on the formulation composition and polymer-network organization, a mechanistic framework linking conventional characterization data to film performance is needed. This study aimed to develop a Madelung-type multifractal swelling–disintegration–release-readiness model for chitosan/hydroxypropyl methylcellulose (HPMC) films and to examine its relevance using a twelve-formulation experimental series. Methods: Twelve films based on chitosan (film-forming polysaccharide), HPMC K-4M (hydrophilic swelling polymer), glycerin (plasticizer), and starch (disintegrant) were prepared via solvent casting. The films were characterized for loss on drying, surface pH, mass and thickness uniformity, wetting time, swelling behavior, structural-disintegration onset, elongation response, rupture resistance, folding endurance, and surface roughness. The proposed model described water uptake, swelling-front motion, matrix integrity, local release-readiness activation, and hydration-induced loading as coupled fields across the film thickness. Results: Formulation markedly influenced hydration behavior, mechanical performance, structural stability, and surface morphology. Films F2 and F7 emerged as the most promising complementary unloaded matrix platforms for future active-compound incorporation and experimental release evaluation. F2 behaved as a high-swelling, mechanically stable starch-free matrix, whereas F7 combined faster wetting, starch-assisted structural destabilization, and favorable flexibility. Conclusions: This framework provides a quantitative link between empirical film characterization and formulation-level mechanistic interpretation. It translates conventional characterization parameters into descriptors related to the apparent water penetration, swelling capacity, matrix-failure tendency, mechanical suitability, and structural heterogeneity. The present results support candidate selection for future Active Pharmaceutical Ingredient-loaded studies but do not constitute validation of drug-release kinetics. Full article

Accurate trajectory tracking of quadrotor unmanned aerial vehicles (UAVs) remains a very challenging problem because of their inherent nonlinear, strongly coupled and underactuated dynamics. In order to overcome these limitations, a real-time Model Reference Adaptive Control (MRAC) strategy is proposed in this paper for better tracking performance in the presence of parametric uncertainties and external disturbances. The controller is cascaded, and adaptive laws based on Lyapunov stability theory are used to control the translational and rotational motions separately and guarantee closed-loop stability. The proposed approach is benchmarked against a tuned Particle Swarm Optimisation (PSO) PID controller under the same operating conditions to evaluate its efficacy. The validation is performed via extensive numerical simulations and real-time Hardware-in-the-Loop (HIL) experiments on an OPAL-RT platform, confirming enhanced disturbance rejection and transient response in the studied deterministic HIL conditions. The results show that the MRAC controller converges faster and has higher tracking accuracy than the PSO-based PID controller. Settling times are reduced from 9–12 s to 5–7 s with negligible steady-state error in setpoint tracking tests. The tracking errors for the multi-axis trajectory-tracking experiments, including the square and three-dimensional trajectories, are kept within 0.1–0.3 m; larger tracking deviations are observed with the benchmark controller. The quantitative performance evaluation demonstrates approximately 60–70% reduction in RMSE together with lower MAE, IAE, and ITAE values compared with the optimised PSO-based PID controller. Also, disturbance experiments under 1 N external force demonstrate the improved disturbance-rejection performance of the adaptive controller with performance degradation of about 25–30% compared to 38–45% for the PSO-based PID controller. The overall results obtained under deterministic real-time HIL conditions indicate that the proposed MRAC strategy provides improved trajectory-tracking performance compared to the benchmark PSO-based PID controller. Further statistical validation and physical flight experiments will be considered in future works. Full article

Kienböck disease, osteonecrosis of the lunate of uncertain aetiology, presents with progressive pain, stiffness, and grip loss in dominant-hand-using adults during their most productive working years, yet its rehabilitation literature has lagged behind its surgical counterpart. This narrative review synthesises current rehabilitation evidence across conservative and post-operative pathways, mapping recommendations to disease stage and to surgical procedure. Following SANRA-aligned methods with selected PRISMA 2020 transparency elements, we appraise immobilisation and orthotic management, dart-throwing-motion-plane mobilisation, sensorimotor retraining, oedema and pain control, psychosocial screening, and procedure-specific protocols that span joint-levelling osteotomy, vascularised bone grafting (including medial femoral trochlea flap), limited intercarpal arthrodeses, proximal row carpectomy, wrist denervation, and salvage arthrodesis or arthroplasty. Patient-reported, performance-based, and occupational outcome instruments are reviewed, with explicit declaration that no Kienböck-validated MCIDs exist. We also set out an integrative reference frame that cross-walks osseous, articular, and tissue-healing axes, offered as clinical orientation rather than as a validated algorithm. The most pressing evidence gaps (Kienböck-specific functional movement screens, sustained return-to-work data, and procedure-specific rehabilitation cohorts) are translated into four registered, powered, COMET-aligned trial proposals. Full article

This paper presents a preliminary technical feasibility study of a landmark-based motion analysis system designed for potential future application in home-based rehabilitation monitoring for frozen shoulder (adhesive capsulitis), developed using computer vision (CV) and human–computer interaction (HCI) principles. The proposed system utilizes real-time body landmark detection to quantify shoulder joint kinematics and provide rule-based automated feedback on exercise execution. The system combines automated and manual components: while shoulder angle assessment, cosine similarity analysis, and keyframe matching are automated, manual researcher input is required to define keyframes corresponding to movement states (start, midpoint, peak) for each therapeutic pose. The CV-driven perception is translated into HCI output, including quantitative movement scores and rule-based feedback indicators, demonstrating the technical potential for objective evaluation of rehabilitation exercise execution without specialized wearable sensors. Technical validation was conducted with 14 healthy volunteers (not frozen shoulder patients) executing standardized shoulder rehabilitation activities, demonstrating shoulder angle measurement with an overall mean absolute error (MAE) of 7.03° against general goniometry and 6.61° against clinical goniometry (RMSE: 8.50° and 8.79°, respectively). Movement similarity classification achieved F1-scores ranging from 0.870 (flexion) to 1.0 (internal rotation) when compared against expert evaluation, though these results are based on a controlled and largely imbalanced dataset with limited incorrect movement examples. The system additionally incorporates a facial expression recognition (FER) module, previously developed and validated in the authors’ prior work, as a supplementary component to support future integration of pain monitoring; this module was not independently validated in the present study. This preliminary technical feasibility study contributes to rehabilitation engineering by demonstrating the potential of semi-automated CV-based motion analysis and rule-based HCI feedback for shoulder movement assessment. The findings indicate technical feasibility for future investigation in home-based exercise monitoring; however, clinical utility cannot be claimed at this stage, as validation with actual frozen shoulder patient cohorts is required. Full article

Background and Objectives: Accelerated rehabilitation after anterior cruciate ligament reconstruction (ACLR) is widely implemented, yet its definition and distinguishing characteristics remain inconsistently described in the literature. This scoping review examined how accelerated rehabilitation after ACLR is defined, described common protocol features, and identified elements distinguishing it from conventional rehabilitation. Materials and Methods: A scoping review was conducted using systematic searches of Medline (PubMed), Embase, and Web of Science from 1 April 1967 to 26 October 2025. Studies including patients aged 16 years or older who underwent primary ACLR that reported any form of accelerated rehabilitation or early progression relative to conventional protocols were eligible for inclusion. Results: Of 6002 screened records, 64 studies met the inclusion criteria. Accelerated rehabilitation was consistently characterized by early restoration of knee range of motion, early full weight-bearing, rapid gait normalization, early initiation of closed and open kinetic chain exercises, and avoidance of prolonged immobilization. However, definitions varied substantially across studies. Substantial heterogeneity was observed in progression timelines, bracing and crutch use, and return-to-sport criteria. Conclusions: Accelerated rehabilitation after ACLR appears to represent a brace-free, criterion-based, function-oriented approach emphasizing early restoration of knee extension, progressive loading, and individualized progression rather than simply shortened timelines. Establishing consensus definitions and standardized reporting is necessary to improve comparability across studies and facilitate translation into clinical practice. Full article

Spectral line shapes are used to diagnose parameters of white dwarfs and neutron stars in particular. In magnetized plasmas, the motion of the radiating atom in the plasma needs to be considered in the collision process as the electronic structure of the atom depends on its center-of-mass translational momentum. More broadly, collision models do not explicitly or fully account for the motion of the nucleus, accounting for deflection through conservation of momentum. Traditionally, the correlation between electronic and nuclear motion has been captured through mass-polarization terms involving momenta scalar products between different electrons. We reformulate the collision problem accounting for the motion of the nucleus, taking advantage of unitary transformations. In this new formulation, Coulomb interactions between the atom and projectile/plasma particle become displaced Coulomb interactions, and exchange interactions include corrections of order $1/M_A$. We demonstrate the resulting impact on the elastic scattering T-matrices of the $1s$ state of hydrogen, where the lowest-energy electrons increase the real part by 20–30% while leaving the imaginary part practically unaltered. Lastly, we present a formulation so that the atomic motion can be explicitly included in the collision problem for magnetic-field applications. Full article

The relationship between athletes and equipment in the sport of speed skating is critical. A speed skater’s equipment, namely their skates, is an integral part of a dynamic system that facilitates the translation of human motion to on-ice racing. Although it is common practice to customize the setup of long track speed skates, empirical evidence supporting best practices is relatively undocumented. The exploratory nature of this investigation was intended to address two purposes: (i) profiling skate metrics in a competitive cohort of long track speed skaters and (ii) exploring the association between skate metrics and on-ice race times. Two databases were populated for the purpose of analysis: one for skate metrics and another for on-ice race times. Data were linked to the skates of thirty-one provincial-level long track speed skaters (male n = 19; female n = 12). The skate metrics database was populated by a single equipment technician, trained using measurement protocols consistent with the industry’s standards, and the metrics were grouped into three categories: (i) boot dimensions (n = 4), (ii) blade dimensions (n = 7), and (iii) skate setup (n = 5). The on-ice race time database was populated and collated using a secondary data source and included an aggregate time based on the mean of the three fastest race times per athlete by distance (500 m, 1000 m, and 1500 m) collected from the 2019–2023 seasons. Statistical analyses were conducted within and across the databases to (i) determine the variation in skate metrics and race times across athletes, and (ii) explore the association between skate metrics and race times. Analysis of the skate metrics database revealed coefficients of variance (CVs) for all metrics including the following: boot dimensions (6.95–8.69%), blade dimensions (0.00–14.24%), and skate setup metrics (8.63–17.05%). Of significant interest were large CVs for pivot point position (14.54%) and blade offset (8.63–17.05%), suggesting inconsistency and a potential lack of understanding of the impact of skate setup on performance. No significant correlations were revealed between skate setup metrics and race times. Across the three race distances, regression models were not statistically significant and explained only a small proportion of variance, highlighting the limited understanding between skate setup metrics and race times in practice. Profiling skate metrics and understanding their relationship with race times provides equipment technicians, coaches, and athletes with a baseline to inform decisions when customizing skate setup. Full article

Emotional design is increasingly recognised within landscape architecture, particularly in the context of sustainable and user-centred environments; however, systematic and data-driven approaches that translate users’ emotional responses into concrete design parameters remain limited. To address this gap, the aim of this study is to systematically integrate users’ emotional expectations into landscape design by applying Kansei Engineering, using ornamental pools as a case study. A semantic differential survey was conducted with 91 participants, including landscape design students and experts. The experimental stimuli were developed based on a Taguchi L8 orthogonal array, enabling the systematic evaluation of five design factors (depth, interior surface colour, surface planting, form, and motion) across eight configurations. The collected data were analysed using the Taguchi method and Analysis of Variance (ANOVA) to identify optimal design combinations and quantify the relative influence of each factor. The results reveal that surface planting is the dominant factor influencing perceptions such as captivating and legible, while motion plays a key role in shaping mental restoration. The optimal configuration, characterised by shallow depth, light colour, vegetation, natural form, and dynamic water, evoked strong positive responses including captivating, aesthetically pleasing, and satisfying. This study proposes a data-driven framework for linking emotional perception with landscape design variables, contributing to the development of more socially and psychologically sustainable, user-centred, and emotionally responsive landscape environments. Full article

The temporal course of neuronal electric activity within brain networks, or neurodynamics, reflects the structural and functional properties of the neuronal populations that generate it. Using intracranial stereo-electroencephalography (sEEG) recordings from the public Montreal Neurological Institute (MNI) atlas, we investigated neurodynamics in the primary motor (M1), somatosensory (S1), and auditory (A1) cortices. We tested whether modifying the Higuchi fractal dimension (HFD) by replacing the Euclidean distance with the Fréchet distance could improve sensitivity to local neurodynamics by incorporating trajectory-based similarities in signal evolution. Using a conservative within-subject approach established in the previous literature, we compared signals recorded from different cortical areas within the same individuals (M1 vs. S1: # of people = 16; M1 vs. A1: # = 9; S1 vs. A1: # = 6). To delve deeper into the new measure’s meaning, it was tested on sequences with known fractal properties, the Brownian motion and the Weierstrass function. Results showed that the newly introduced Fréchet-based HFD (HFDf), similarly to standard HFD, consistently discriminated cortical areas at the intra-subject level, confirming the robustness of fractal dimension as a descriptor of region-specific neurodynamics. Contrary to our hypothesis, HFDf did not provide additional sensitivity across areas and notably, it displayed less evident reduction of values in sleep than awake. While cortical regions may share common governing principles across spatiotemporal scales, these do not necessarily translate into strict similarity in temporal signal morphology. We suggest that these findings support that the free-scale nature of neurodynamics is not a self-similar one. This refinement of quantitative tools for cortical neurodynamic mapping paves the way towards novel tools for neuroimaging-informed neuromodulation strategies. Full article

This work presents a nonlinear dynamic model and an energy-based control strategy for a coaxial vertical take-off and landing Unmanned Aerial Vehicle (UAV) equipped with independently tilting propulsion units. The proposed model captures the full six-degree-of-freedom motion of the vehicle and explicitly incorporates the forces and moments produced by the coaxial thrust-vectoring propulsion system, as well as the additional force components induced by the two-degree-of-freedom thrust vectoring mechanism. To regulate the vehicle during hover, cruise, and transition maneuvers, a passivity-based control framework formulated in terms of unit quaternions is developed. The control law simultaneously stabilizes the translational and rotational subsystems without relying on model linearization. In order to map the virtual control forces and torques into physically realizable actuator commands, a nonlinear control allocation procedure is introduced. This allocation scheme enables independent angular positioning of the propulsion units while computing the corresponding motor angular velocities. The effectiveness of the proposed modeling and control framework is assessed through three-dimensional dynamic simulations and numerical experiments, demonstrating accurate trajectory tracking, autonomous UAV landing capabilities, and smooth transitions between flight regimes for thrust-vectored UAV platforms. Full article

To achieve non-contact and continuous monitoring of body length in Micropterus salmoides and overcome the stress damage and subjective error associated with traditional manual measurement, this paper proposes an improved YOLOv8-based multi-target tracking framework for intensive recirculating aquaculture systems. The system employs a geometric measurement framework based on monocular vision that achieves conversion from pixel coordinates to actual body length through camera calibration, water-surface refraction correction, and pose projection correction. Under a collaborative optimization framework integrating detection and tracking, the model incorporates multi-scale feature enhancement, lightweight re-identification (ReID), and a robust data association mechanism, which improves system stability under conditions of high fish density, variable illumination, and turbid water. A shallow feature fusion path is introduced to enhance small-target perception, and a MobileNetV3_ReID model is adopted to extract highly discriminative appearance features, which improves identity consistency while maintaining model compactness. In the data association stage, a hybrid cost matrix integrating IoU, cosine similarity, and motion consistency is constructed, and optimal matching is realized through the Hungarian algorithm. Dynamic threshold adjustment and an exponential moving-average feature-update strategy are introduced to effectively suppress identity switching. Experiments were conducted on an overhead video dataset of Micropterus salmoides collected at a recirculating aquaculture system facility. The results show that the proposed method achieves 82.7% mAP50 while maintaining a real-time throughput of 88 FPS, with MOTA reaching 76.9% and IDF1 reaching 81.5%—the latter representing an improvement of 3.2 percentage points over BoT-SORT and 5.3 percentage points over the YOLOv8 baseline tracker. The number of identity switches (IDSW) decreased from 89 in the baseline configuration to 39, a reduction of 56.2%. Crucially, these component-level improvements translate into a body length error (BLE) of 5.2 ± 1.8% (MAE = 1.35 cm, Pearson r = 0.972), representing a 38.8% improvement over the baseline BLE of 8.5% and satisfying the 5–10% tolerance required for aquaculture growth monitoring. Ablation analysis confirms that both detection enhancements (contributing −1.3% BLE) and tracking optimizations (contributing −2.0% BLE) are necessary to achieve this application-level accuracy. Full article