Search Results (3,323)

Driven by orchard labor shortages and rising demand for intelligent harvesting, automated apple picking requires a balance between conformal enveloping and slip-resistant stability. To reduce damage and slippage caused by fragile skins, variable morphologies, and motion disturbances, this study proposes a multi-joint pneumatic flexible apple-picking hand with adjustable circumferential configuration. Based on structural configuration determining grasping stability, six apple-morphology-based finger-base supports were designed. Parametric analysis of soft gripper cavities identified an isosceles trapezoidal profile as the best configuration. Using the Yeoh constitutive model, an equivalent joint model for conformal gripping was developed, and genetic algorithm (GA) optimization selected the four-joint design as the preferred configuration. Static finite element simulations determined an operating pressure of 20.32 kPa. Grasping stability was quantified by relative slip displacement in rigid–flexible coupled dynamic simulations. Among the tested support configurations within 60–110°, the 90° bracket produced the most stable slip response under vertical and horizontal disturbances. Thin-film pressure tests showed an asymmetric but stable three-finger load-sharing pattern. Field trials in a high-density dwarf spindle orchard achieved an 83.98% harvesting success rate. After 72 h of cold storage, no obvious surface browning, epidermal abrasion, or compression marks were observed during visual inspection. This assessment was limited to visible external damage and did not include quantitative evaluation of internal bruising, firmness degradation, flesh browning, or long-term storage quality. These results demonstrate stable grasping performance and low visible external damage under the tested conditions. Full article

This study presents a damage-based comparative assessment of reinforced concrete buildings affected by the 1992 Erzincan earthquake (Mw 6.8) and the 2023 Kahramanmaraş earthquake sequence (Pazarcık, Mw 7.7; Elbistan, Mw 7.6), two destructive earthquake events in Türkiye separated by nearly three decades. A distinctive contribution of the study is the presentation of original color photographs from the 1992 Erzincan earthquake, systematically documented and comparatively evaluated for the first time and directly compared with post-earthquake field observations from Malatya following the 2023 earthquake sequence. To complement the field-based evidence, representative strong ground motion records from both earthquake events were processed and compared using standard seismic intensity and spectral response parameters. The spectral evaluation indicates that the 1992 Erzincan ground motion and the 2023 Elbistan-related motion recorded in Malatya imposed comparable seismic demands relevant to typical reinforced concrete buildings, thereby providing a rational basis for cross-event damage interpretation. Despite substantial advances in Turkish seismic design codes, recurrent damage mechanisms were observed in both building stocks, particularly soft-story formation, short-column effects, inadequate transverse reinforcement, poor beam–column joint performance, and deficiencies in material quality and detailing. The findings demonstrate that seismic safety cannot be improved through code development alone unless design provisions are consistently translated into construction quality, detailing practice, inspection, and field implementation. Full article

Arthrogenic muscle inhibition (AMI), neurophysiological suppression of voluntary quadriceps activation triggered by joint effusion and inflammation, is consistently initiated within hours of any form of knee surgery. If not actively counteracted during the first two postoperative weeks, AMI may drive a cascade of neuromuscular, morphological, and biomechanical deficits that can persist for years, substantially increasing the risk of post-traumatic osteoarthritis, reinjury, and long-term functional disability. Emerging evidence indicates that preoperative patient-related factors, including baseline quadriceps strength, age, body mass index, and physical fitness, further modulate the rehabilitation response and should be considered in planning early postoperative protocols. This narrative review, which was not designed as a systematic review or meta-analysis and therefore does not include formal quality assessment or pooled statistical analysis, evaluates evidence for seven early-phase (0–2 weeks postoperative) knee muscle activation interventions: neuromuscular electrical stimulation (NMES), isometric quadriceps exercise, blood flow restriction (BFR) training, electromyographic (EMG) biofeedback, open and closed kinetic chain (OKC/CKC) exercise, cryotherapy, and continuous passive motion (CPM). Findings are synthesized against six clinically relevant dimensions, safety in the 0–2 week window, home-based usability, capacity to overcome AMI, requirement for volitional effort, objective monitoring capability, and progressive resistance, to characterize a consistent pattern: no single existing modality simultaneously meets all combined requirements for home deployment, volitional engagement, objective monitoring, and progressive resistance from postoperative day one. This collective unmet need provides direction for future device development and clinical research. Full article

This study investigates a polymorphic underwater vehicle designed to combine long-range cruising with stable underwater operation, reducing dependence on surface support vessels. By introducing a foldable polymorphic structure, the vehicle can switch configurations, including serial and parallel. However, underwater environments often contain obstacles, and the vehicle may collide with them during the folding process. To prevent collisions between the vehicle and surrounding obstacles during the folding process, this paper investigates the motion envelope of the vehicle and examines how motion parameters and mass distribution influence the motion envelope. In this work, the polymorphic underwater vehicle is modeled as a multibody system operating under a neutrally buoyant condition. Based on space robot modeling methodologies and the linear and angular momentum theorems, the equations of motion of the polymorphic underwater vehicle are derived and verified using the Adams software 2020. In summary, the present study establishes a clear relationship between motion parameters, mass distribution, hydrodynamic effects, and the resulting motion envelope of a polymorphic underwater vehicle. The results show that the attitude of the vehicle during the folding process is uniquely determined by the joint angles, and a larger relative speed between the outer and inner folding motions produces a more compact attitude during the folding process. Mass distribution further influences the motion envelope of the vehicle: concentrating mass toward the center of the vehicle shifts the overall motion envelope upward, whereas concentrating mass toward both ends of the vehicle shifts it downward. In addition, hydrodynamic forces introduce an upward velocity component of the vehicle in the vertical direction during the folding process, which leads to an upward shift in the overall center of mass of the vehicle. Full article

This work presents the kinematic analysis of a redundant planar parallel manipulator within the framework of screw theory. The main contribution of this work is the introduction and kinematic modeling of a novel redundant planar parallel manipulator topology composed exclusively of revolute joints. The proposed architecture is motivated by the search for structurally simple mechanisms with favorable analytical properties for screw-theoretic formulation and potential applications in robotic systems requiring compact and efficient planar motion. For completeness, the displacement analysis is included. Thanks to the simple topology of the otherwise complex mechanism, the inverse–forward displacement problem is resolved through straightforward quadratic equations. The velocity input–output relationship is derived without reliance on passive joint rate velocities, and the acceleration input–output equation is obtained independently of passive joint rate accelerations. These simplifications are achieved by exploiting reciprocal line properties. Numerical examples are provided to illustrate the robustness and effectiveness of the proposed kinematic analysis method across the main topics addressed in this contribution. Full article

The evaluation of wearable robotic systems remains a challenge, particularly in real-world environments where laboratory-based methods are impractical. Existing approaches rely on external instrumentation, such as surface electromyography (sEMG) or motion capture, which are difficult to deploy continuously and do not directly measure key internal metrics such as joint loading or spinal forces. This work introduces a new paradigm for exoskeleton evaluation in which biomechanical assessment is embedded directly within the device’s sensing and computational architecture. We present the ExoMetrix system, a platform that integrates onboard sensing, real-time data acquisition, cloud-based processing, and user-facing analytics into a unified workflow for continuous evaluation of human–exoskeleton interaction. Sensor data from the device are streamed and processed using physics-based models. The resulting outputs are translated into estimates of internal biomechanical quantities, including joint torques, spinal compression and shear forces, and muscle loading. By enabling real-time feedback and longitudinal monitoring without external instrumentation, this approach transforms evaluation from an external, episodic process into an embedded and continuous capability, supporting safer and more scalable deployment of exoskeleton technologies. Full article

Marker-based motion capture systems are considered the gold standard for biomechanical analysis of movements associated with anterior cruciate ligament (ACL) injury risk; however, their cost and technical requirements limit their use for large-scale athlete screening. Markerless motion capture has emerged as a potential alternative, using pose estimation algorithms or depth cameras to quantify movement without reflective markers. This systematic review evaluated the accuracy and validity of markerless motion capture systems for measuring lower-limb kinematics during jump-landing tasks commonly used in ACL injury screening. MEDLINE, Embase, and Web of Science were searched from 1990 to March 2025 for studies comparing markerless and marker-based systems in healthy participants. Extracted outcomes included Bland-Altman plots, root mean square error, mean absolute error, Pearson’s correlation coefficient, coefficient of multiple correlation, and intraclass correlation coefficient. Across studies, markerless systems demonstrated moderate to high validity for several lower-limb kinematic measures, particularly in the sagittal plane, although validity varied across joints, movement phases, and task complexity. These findings suggest markerless motion capture shows potential for biomechanical assessment in ACL injury screening, but further validation is required before widespread implementation. Full article

The sign of the maximal almost sure Lyapunov exponent determines the stability of stochastic systems, while its numerical computation for three-dimensional linear Stratonovich stochastic differential equations remains challenging due to the failure of classical two-dimensional strategies. The spherical angular motion of 3D systems produces a Fokker–Planck equation with intractable mixed partial derivatives, preventing conventional analytical solutions. This paper develops a unified computational framework for three-dimensional linear Stratonovich stochastic systems using analytical derivation for degenerate cases and physics-informed neural network (PINN) approximation for general non-degenerate scenarios. For degenerate systems, we reduce the coefficient matrix to a lower triangular form via orthogonal transformation and establish tight upper bounds based on the logarithmic growth property of the Wiener process, yielding closed-form expressions for the maximal almost sure Lyapunov exponent under all parameter sign configurations. For non-degenerate systems, we reformulate the Fokker–Planck equation in spherical coordinates and construct a customized PINN with trigonometric encoding to enforce periodic boundary conditions. The network is trained by joint loss functions of equation residuals, boundary constraints and normalization consistency, and the converged stationary density is substituted into the Furstenberg–Khasminskii formula to calculate the exponent via Gauss–Legendre quadrature. Monte Carlo simulations confirm the accuracy and robustness of the proposed method, which reliably identifies the sign of the maximal almost sure Lyapunov exponent even in near-critical regimes. Numerical experiments on a 3D stochastic Hopf bifurcation model show that noise negatively shifts the bifurcation point, with the offset linearly proportional to the squared noise intensity. This work extends Lyapunov stability analysis from two-dimensional to three-dimensional linear Stratonovich stochastic systems, offering an effective tool for stability evaluation of general three-dimensional stochastic dynamical models. Full article

Background/Objectives: Tissue flossing (TF) with elastic bands (floss bands) is a therapeutic strategy to improve joint range of motion (ROM). While TF has demonstrated 3–7% ROM improvements in ankle and shoulder joints, its effects on knee flexion remain underexplored. Therefore, the objective of this study was to investigate the acute effects of TF on active and passive knee flexion range of motion in healthy adults. Methods: Sixty healthy participants (median age 23.0 [IQR 2.0] years; 30 male, 30 female) were randomized to an intervention group (IG; n = 30) receiving floss band (COMPRE Sanctband^®, Level 1; 50% tension, 50% overlap) application combined with knee mobilization (20 active/passive repetitions over 2 min), or a control group (CG; n = 30) performing the same mobilization without band application. Active (AROM) and passive (PROM) knee flexion were measured pre- (M0) and post-intervention (M1) using a validated smartphone goniometer (Goniometer Pro), by a blinded assessor. Results: Baseline characteristics (age, body mass index) did not differ between groups (p > 0.05); however, baseline AROM differed significantly between groups (p = 0.041). The IG showed significantly greater improvements than CG in AROM (Δ5.0° [4.0%] vs. Δ0.0°, p < 0.001) and PROM (Δ6.0° [4.5%] vs. Δ1.0° [0.8%], p < 0.001). Conclusions: TF combined with mobilization produced greater immediate increases in knee flexion ROM than mobilization alone, with large effect sizes. These findings support adequately powered, sham-controlled trials in clinical populations before clinical effectiveness can be inferred. Full article

Beef cattle behavior provides valuable information regarding their health status. Recently, deep convolutional network-based methods have achieved considerable results in beef cattle behavior recognition. However, their robustness under low-light or dark conditions remains limited, which restricts their application in real farm environments. To address this issue, this study constructed a realistic beef cattle behavior dataset in the dark, named Dark Beef Cattle Actions, which was collected under real nighttime farm conditions. The constructed dataset contains 1097 video clips collected from 30 beef cattle and covers 6 behavioral classes, including running, feeding, drinking, grooming, mounting, and fighting. Based on this dataset, we proposed a novel neural network architecture based on spatio-temporal dark enhancement and dynamic fusion for beef cattle behavior recognition in the dark. First, a spatio-temporal dark enhancement module was designed to improve dark video quality while preserving motion features. Second, a dynamic fusion module was introduced to adaptively fuse features from different branches and obtain more discriminative representations. In addition, a joint loss was adopted to optimize both dark enhancement and action recognition. Experimental results on the constructed dataset show that the proposed method achieved a weighted-averaged precision score of 88.47%, a weighted-averaged recall score of 80.18%, an accuracy score of 83.80%, and a weighted-averaged F1-score of 84.12%. Compared with other state-of-the-art methods, the proposed method achieved competitive performance in the recognition of night-time beef cattle behavior. These findings would provide support for intelligent livestock behavior recognition and monitoring in precision farming. Full article

Accelerometer sensors and artificial intelligence (AI) are reshaping automated behavior monitoring in precision livestock management, yet their joint deployment on extensive rangelands is constrained by energy and bandwidth budgets. Low-Power Long-Range Wide-Area Network (LoRaWAN) collars address these constraints by compressing the raw tri-axial signal on the device into a single scalar per reporting interval, the Motion Index (MI). This onboard compression preserves enough signal to separate active behaviors but discards the per-axis and frequency content that fine-grained classification typically relies on. On a dataset of 9222 labeled observations from 24 cows across four breeds, MI distinguishes walking from grazing reliably but fails to separate ruminating from resting; both correspond to a stationary animal and yield near-zero, statistically indistinguishable distributions. Earlier MI-only models reached only about 65% four-class accuracy, and ruminating was commonly merged into resting. We show that much of this loss can be recovered by treating the MI stream as a time series. Session-aware lag features, rolling statistics, and an autoregressive previous-behavior feature lift four-class macro-F1 from 0.647 to 0.94, with per-class F1 of 0.95 for ruminating and 0.92 for resting (and at least 0.92 for every behavior). In autonomous deployment the previous behavior must be predicted rather than observed; for this setting we add a Viterbi sequence-decoding step that combines the classifier’s per-step outputs with a learned behavior-transition model, recovering a substantial part of the ruminating signal from the activity stream alone while keeping walking and grazing reliable. The gain is consistent across seven classifiers and four genetically distinct breeds, indicating that it is driven by the features rather than by a specific model. Full article

Long-horizon mobile manipulation requires a robot to execute a sequence of heterogeneous subtasks such as navigation, picking, and articulated-object manipulation in indoor environments. Standard reinforcement learning suffers from reward sparsity and inefficient exploration in this setting, and hierarchical methods often fail at the hand-off between consecutive subtasks when the terminal state of one subtask is kinematically infeasible for the next. We propose a motion planning-augmented hierarchical reinforcement learning architecture to resolve the fundamental trade-offs between sample efficiency and hand-off reliability in long-horizon mobile manipulation. The mission is decomposed into subtasks via a Semi-Markov Decision Process; within each subtask, a collision-free reference trajectory generated by RRT* in the full joint configuration space is embedded into the reward as a per-step shaping signal; and a region-goal mechanism, defined analytically from inverse kinematics feasibility, replaces rigid coordinate hand-offs with a continuous feasible region. The architecture is evaluated in the ManiSkill-HAB simulation under teleport-free sequential execution and challenging initialization. The proposed method improves subtask success rate and sample efficiency over the baseline across all six evaluated subtasks, and the advantage compounds along the long-horizon task chain. Full article

Background and Objectives: Robotic-assisted total knee arthroplasty (rTKA) is being increasingly used to improve surgical precision, soft-tissue balancing, and functional recovery. However, evidence comparing rTKA with conventional manual TKA (mTKA) across functional, patient-reported, neuromotor, and safety outcomes remains heterogeneous. Materials and Methods: This narrative (non-systematic) review synthesises studies evaluating functional outcomes, patient-reported outcome measures (PROMs), joint awareness, range of motion (ROM), neuromotor recovery, and complications following rTKA versus mTKA. Study inclusion was based on author judgement and data accessibility. The reviewed evidence included five randomised controlled trials, 9 retrospective studies, six prospective non-randomised studies, two meta-analyses, one cross-sectional study, and one umbrella review, covering CT-based and imageless robotic platforms, including semi-active and active systems such as MAKO, NAVIO, CORI, ROSA, ROBODOC, CUVIS Joint, SkyWalker, TSolution One, AKEC, JIANJIA, and YUANHUA. Results: rTKA consistently demonstrated outcomes comparable to mTKA in PROMs (OKS, KOOS, WOMAC, KSS), with some studies reporting modest early improvements in pain and function. Joint awareness and patient satisfaction showed the most consistent early advantages for rTKA. Early postoperative ROM and neuromotor recovery, including balance and gait symmetry, were improved with rTKA, likely due to enhanced alignment and soft-tissue balancing; however, mid- and long-term outcomes were similar. Complication rates were low and comparable, with robotic-specific issues being rare and self-limited. Conclusions: rTKA provides small but reproducible early benefits in joint awareness, neuromotor function, and patient satisfaction, without clear long-term superiority. These early advantages may translate into meaningful population-level benefits, including faster recovery and potential healthcare cost reduction. Further high-quality studies are needed to assess long-term clinical and economic outcomes. Full article

Patellofemoral pain (PFP) in athletes is associated with lower-limb kinetic-chain constraints, yet rehabilitation strategies targeting both hip and ankle mobility remain insufficiently examined. This assessor-blinded randomized controlled trial investigated the effects of a 6-week hip and ankle mobility-based rehabilitation program in male collegiate athletes with PFP. Forty-eight participants were assigned using computer-generated 1:1 randomization to an intervention group (n = 24) or a control group (n = 24). The intervention group completed supervised hip and ankle mobility rehabilitation three times weekly, whereas the control group maintained regular sport-specific training only. Co-primary outcomes were pain intensity assessed using a 10-cm visual analog scale (VAS) and knee-related function assessed using the Kujala score. Secondary outcomes included hip rotation range of motion, weight-bearing ankle dorsiflexion, vastus medialis–vastus lateralis (VM–VL) onset timing, Y-Balance Test (YBT) composite score, and countermovement jump (CMJ) height. Significant group × time interactions favored the intervention group for VAS (p < 0.0001; partial η² = 0.436; change difference: −1.54 cm; 95% CI: −2.06 to −1.02) and Kujala score (p < 0.0001; partial η² = 0.285; change difference: 8.00 points; 95% CI: 4.24 to 11.76). Significant interactions were also observed for hip internal and external rotation range of motion, weight-bearing ankle dorsiflexion, VM–VL onset timing during a controlled squat task, and YBT composite score (all p ≤ 0.0405; partial η² = 0.088–0.374). No significant group × time interaction was observed for CMJ height (p = 0.0511; partial η² = 0.080). These findings suggest that, compared with regular sport-specific training alone, adding a supervised hip and ankle mobility-based rehabilitation program may improve pain, knee-related function, targeted mobility outcomes, VM–VL onset timing during a controlled squat task, and dynamic balance in the short term. However, because the control group did not receive an active or attention-matched intervention, these findings should be interpreted as the added effect of the supervised rehabilitation program rather than as definitive evidence of mobility-specific treatment effects. In addition, because patellar tracking, knee kinematics, joint kinetics, and patellofemoral joint loading were not directly measured, the findings should be interpreted as clinical and functional outcome changes rather than direct evidence of a confirmed biomechanical mechanism. Trial registration: NCT07542236. Full article

This paper develops a generalized kinematic model for a lever-link-type flat pressing mechanism used in food processing applications for compacting the coagulate. The study aims to highlight the influence of the geometric parameter that defines the position of the intermediate coupling on the driving element on the mechanism’s configuration and on the main kinematic variables of the active pressing point. Under an idealized representation—assuming rigid links, perfect joints, and a vertical constraint acting on the active element—general analytical expressions for displacement, velocity, and acceleration were established using the vector-kinematic method. The results show that modifying the position of the intermediate coupling produces nonlinear variations in the length of the connecting element, its spatial orientation, and the vertical motion of the active point. Increased values of this parameter are associated with a greater effective stroke and higher vertical velocities toward the end of the motion, while the calculated accelerations remain relatively low, indicating a smooth kinematic evolution. The model establishes analytical relationships that describe the influence of geometric parameters on the kinematic behavior of the mechanism and can serve as a basis for further developments involving dynamic analysis and experimental validation. Full article