Search Results (1,305)

Background/Objectives: Accurate head positioning is essential for diagnostics of benign paroxysmal positional vertigo (BPPV). This study aimed to quantify the head angles and angular velocities during traditional manual BPPV diagnostics in patients with positional vertigo. Methods: A prospective, observational cohort study was conducted at a tertiary university hospital outpatient clinic. One trained examiner performed the Supine Roll Test (SRT) and the Dix–Hallpike test (DHT) on 198 adults with positional vertigo. The primary outcomes included head angle variability and accuracy and angular velocity variability. The secondary outcomes examined the relationship between the head angle accuracy and participant-reported limitations. Results: The absolute variability for all head angles ranged from ±8.7° to ±11.0°. The yaw axis head angles during the DHT, particularly on the left side, had the highest relative variability (left DHT: coefficient of variance 0.29). Systematic errors included the yaw axis head angles undershooting the target (90°) by 19.7–23.8° during the SRT and the pitch axis head angles undershooting the target (120°) by 7.8–8.7° during the DHT. The left-sided yaw axis in the DHT was undershot by 11.8°, while the right-sided DHT angle was slightly overshot (2.5°). Right-sided yaw axis angles in the SRT and DHT were more accurate than the left-sided ones (right SRT: 19.9°; left SRT: 23.9°; p < 0.0001) (right DHT: 7.0°; left DHT: 13.2°; p < 0.0001). The regression analysis found no association between the participant-reported limitations and head angle accuracy. Conclusions: This study highlights the substantial variability and inaccuracies in head positioning during traditional manual BPPV diagnostics, supporting the relevance of a guidance system to improve BPPV diagnostics. Level of evidence: III. Trial registration: ClinicalTrials.gov identifier: NCT05846711. Full article

Rehabilitation of gait function in post-stroke hemiplegic patients is critical for improving mobility and quality of life, requiring a comprehensive understanding of individual gait patterns. Previous studies on gait analysis using unsupervised clustering often involve manual feature extraction, which introduces limitations such as low accuracy, low consistency, and potential bias due to human intervention. This cross-sectional study aimed to identify and cluster gait patterns using an end-to-end deep learning approach that autonomously extracts features from joint angle trajectories for a gait cycle, minimizing human intervention. A total of 74 sub-acute post-stroke hemiplegic patients with lower limb impairments were included in the analysis. The dataset comprised 219 sagittal plane joint angle and angular velocity trajectories from the hip, knee, and ankle joints during gait cycles. Deep temporal clustering was employed to cluster them in an end-to-end manner by simultaneously optimizing feature extraction and clustering, with hyperparameter tuning tailored for kinematic gait cycle data. Through this method, six optimal clusters were selected with a silhouette score of 0.2831, which is a relatively higher value compared to other clustering algorithms. To clarify the characteristics of the selected groups, in-depth statistics of spatiotemporal, kinematic, and clinical features are presented in the results. The results demonstrate the effectiveness of end-to-end deep learning-based clustering, yielding significant performance improvements without the need for manual feature extraction. While this study primarily utilizes sagittal plane data, future analysis incorporating coronal and transverse planes as well as muscle activity and gait symmetry could provide a more comprehensive understanding of gait patterns. Full article

The branch of physics known as magnetohydrodynamics (MHD) emerged in the middle of the 20th century. MHD models, being substantially nonlinear, are quite challenging for theoretical study and allow nontrivial consideration only in particular limited cases. Thus, due to the exceptional growth of calculation power, research on MHD is now primarily concentrated on numerical modeling. The achievements are considerable; however, there is a possibility of overlooking some phenomena or missing an optimal approach to modeling and calculating that could be identified with theoretical guidance. The paper presents a theoretical study of a particular class of boundary and initial conditions. The flow of a viscous, electrically conductive fluid on a rotating plate in the presence of a magnetic field is considered. The fluid and the bounding plate rotate together with a constant angular velocity around an axis that is not perpendicular to the plane. The flow is induced by sudden longitudinal vibrations of the plate, injection (suction) of the medium through the plate, and an applied magnetic field directed normal to the plate. The full equation of magnetic induction is used, taking into account both the induction effect and energy dissipation due to the flow of electric currents. An analytical solution of three-dimensional magnetohydrodynamics equations in a half-space bounded by a plate is presented. The solution is given in the form of a superposition of plane waves propagating with certain wave numbers along the y-coordinate axis. For certain regions of system parameters, the vibration of the bounding plate does not cause waves in the media. Full article

Portable monitoring devices based on Inertial Measurement Units (IMUs) have the potential to serve as quantitative assessments of human movement. This article proposes a new method to identify the optimal placements of the IMUs and quantify the smoothness of the gait. First, it identifies gait events: foot-strike (FS) and foot-off (FO). Second, it segments the signals of linear acceleration and angular velocities obtained from the IMUs at four locations into steps and strides. Finally, it applies three smoothness metrics (SPARC, PM, and LDLJ) to determine the most reliable metric and the best location for the sensor, using data from 20 healthy subjects who walked an average of 25 steps on a flat surface for this study (117 measurements were processed). All events were identified with less than a 2% difference from those obtained with the photogrammetry system. The smoothness metric with the least variance in all measurements was SPARC. For the smoothness metrics with the least variance, we found significant differences between applying the metrics with the complete signal (C) and the signal segmented by strides (S). This method is practical, time-effective, and low-cost in terms of computation. Furthermore, it is shown that analyzing gait signals segmented by strides provides more information about gait progression. Full article

(1) Background: This study examines the association between asymmetrical movements of an assembly line and machining workers and their overall well-being. The primary aim is to quantify the extent to which asymmetrical movements serve as predictors of work-related musculoskeletal disorders (WMSDs) among these workers and their overall well-being. The study emphasises the predictive relationships between asymmetry metrics and health outcomes. (2) Methods: The study included 86 employees from an automotive manufacturing plant, categorised into machining workers (MWEs) and assembly workers (AWEs). The employment duration spanned from 6 months to 40 years. Inertial motion capture technology was employed alongside the Goldberg 28-item General Health Questionnaire for a retrospective observational analysis and assessment of worker well-being. Movement dynamics were evaluated using a Motion Activity Index (MAI) to measure movement intensity, asymmetry, and quality. (3) Results: The machining group demonstrated nearly double the range of motion (median ROM: 36.6° vs. 25.5°, p = 0.019) and peak angular velocities up to eight times higher (median: 40°/s vs. 5°/s) in lumbar and thoracic rotations compared to the assembly group. Significant differences in ROM and movement speeds were observed (p < 0.001). The MAI showed higher dynamic and symmetrical movements in the machining group (36.6% vs. 25.5%, p = 0.019). No significant mental health issues were identified, aside from complaints related to somatic symptoms. (4) Conclusions: This study highlights significant occupational risks due to movement asymmetry in industrial settings, revealing substantial differences in joint angular displacements, velocities, and accelerations between machining and assembly workers. The findings emphasise the importance of targeted ergonomic interventions to enhance worker well-being and advocate for preventive health measures in occupational environments. Full article

A cascade control structure (CCS) is still the most commonly used control scheme in variable speed control (VSC) electrical drives with alternating current (AC) motors. Several tuning methods are used to select the coefficients of controllers applied in CCS. These approaches can be divided into analytical, empirical, and heuristic ones. Regardless of the tuning method used, there is still a question of whether the CCS is tuned optimally in terms of considered performance indicators to provide high-performance behavior of the electrical drive. Recently, artificial intelligence-based methods, e.g., swarm-based metaheuristic algorithms (SBMAs), have been extensively examined in this field, giving promising results. Moreover, the intensive development of artificial intelligence (AI) assistants based on large language models (LLMs) supporting decision-making processes is observed. Therefore, it is worth examining the ability of LLMs to tune the CCS in the VSC electrical drive. This paper investigates tuning methods for the cascade control structure equipped with PI-type current and angular velocity controllers for PMSM drive. Sets of CCS parameters from electrical engineers with different experiences are compared with reference solutions obtained by using the SBMA approach and LLMs. The novel LLM-based Tuning Assistant (TA) is developed and trained to improve the quality of responses. Obtained results are assessed regarding the drive performance, number of attempts, and time required to accomplish the considered task. A quantitative analysis of LLM-based solutions is also presented. The results indicate that AI-based tuning methods and the properly trained Tuning Assistant can significantly improve the performance of VSC electrical drives, while state-of-the-art LLMs do not guarantee high-performance drive operation. Full article

Background: The kinematics of table tennis is a growing topic of scientific research. This study aimed to assess the kinematics and determine the coordination of the movements of most body segments during the execution of two types of serves (short and long) in table tennis, as well as to indicate the main differences between these serves when performed by high-level athletes. Methods: The study involved 15 male table tennis players. Each participant performed two tasks, performing short and long forehand serves with back-sidespin rotation, with up to 10 hits in the designated field for each type. The players’ movements were registered using an IMU system. Results and Conclusion: The research allowed for the development of a model for executing two types of serves in table tennis. The differences between short and long serves were mainly in the ranges of movement and angular velocities (higher for long serves). These were found in the shoulder rotation, elbow joint and wrist joint (primarily the flexion–extension movement), hand supination, and movement in the elbow joint, which also played an important role. Coaches and players should seriously consider these joints and movements in the training process. In the coordinated movement of the performed serves, a phenomenon of movement variability was observed, manifested by a large variability in execution and a low variability in the maximum speeds of the hand with the racket. Full article

TEB (timed elastic band) can efficiently generate optimal trajectories that match the motion characteristics of car-like robots. However, the quality of the generated trajectories is often unstable, and they sometimes violate boundary conditions. Therefore, this paper proposes a fuzzy logic control–TEB algorithm (FLC-TEB). This method adds smoothness and jerk objectives to make the trajectory generated by TEB smoother and the control more stable. Building on this, a fuzzy controller is proposed based on the kinematic constraints of car-like robots. It uses the narrowness and turning complexity of the trajectory as inputs to dynamically adjust the weights of TEB’s internal objectives to obtain stable and high-quality trajectories in different environments. The results of real car-like robot tests show that compared to the classical TEB, FLC-TEB increased the trajectory time by 16% but reduced the trajectory length by 16%. The trajectory smoothness was significantly improved, the change in the turning angle on the trajectory was reduced by 39%, the smoothness of the linear velocity increased by 71%, and the smoothness of the angular velocity increased by 38%, with no reverse movement occurring. This indicates that when planning trajectories for car-like mobile robots, while FLC-TEB slightly increases the total trajectory time, it provides more stable, smoother, and shorter trajectories compared to the classical TEB. Full article

This paper introduces a comprehensive, data-driven framework for parametrically estimating directional ocean wave spectra from numerically simulated FPSO (Floating Production Storage and Offloading) vessel motions. Leveraging a mid-fidelity digital twin of a spread-moored FPSO vessel in the Guyana Sea, this approach integrates a wide range of statistical values calculated from the time histories of vessel responses—displacements, angular velocities, and translational accelerations. Artificial neural networks (ANNs), trained and optimized through hyperparameter tuning and feature selection, are employed to estimate wave parameters including the significant wave height, peak period, main wave direction, enhancement parameter, and directional-spreading factor. A systematic correlation analysis ensures that informative input features are retained, while extensive sensitivity tests confirm that richer input sets notably improve predictive accuracy. In addition, comparisons against other machine learning (ML) methods—such as Support Vector Machines, Random Forest, Gradient Boosting, and Ridge Regression—demonstrate the present ANN model’s superior ability to capture intricate nonlinear interdependencies between vessel motions and environmental conditions. Full article

The cavitation water jet cleaning and coating removal technique represents an innovative sustainable method for cleaning and removing coatings, with the nozzle serving as a crucial component of this technology. Developing an artificially submerged nozzle with a reliable structure and excellent cavitation performance is essential for enhancing cavitation water jets’ cleaning and coating removal efficacy in an atmosphere environment (non-submerged state). This study is based on the shear flow cavitation mechanism of an angular nozzle, the resonance principle of an organ pipe, and the jet pump principle. A dual-nozzle co-current cavitation water jet nozzle structure was designed and manufactured. The impact of the nozzle’s inlet pressure on the vapor volume percentage, as well as the axial and radial velocities inside the flow field, were examined utilizing ANSYS Fluent software with the CFD method. The dynamic change rule of the cavitation cloud is derived by analyzing the picture of the cavitation cloud in the nozzle’s outflow field utilizing pseudo-color imaging techniques. The results show that the maximum vapor volume percentage is more significant than 95% for different inlet pressures in the internal nozzle. The changes that occur in the cavitation cloud exhibit notable regularity, including the four stages of cavitation, which are inception, development, shedding, and collapse. A change period is 1.5 ms, which proves that the homemade co-current cavitation water jet nozzle can achieve good cavitation effects. Full article

This paper introduces a novel closed-form coordinate-free expression for the higher-order Cayley transform, a concept that has not been explored in depth before. The transform is defined by the Lie algebra of three-dimensional vectors into the Lie group of proper orthogonal Euclidean tensors. The approach uses only elementary algebraic calculations with Euclidean vectors and tensors. The analytical expressions are given by rational functions by the Euclidean norm of vector parameterization. The inverse of the higher-order Cayley map is a multi-valued function that recovers the higher-order Rodrigues vectors (the principal parameterization and their shadows). Using vector parameterizations of the Euler and higher-order Rodrigues vectors, we determine the instantaneous angular velocity (in space and body frame), kinematics equations, and tangent operator. The analytical expressions of the parameterized quantities are identical for both the principal vector and shadows parameterization, showcasing the novelty and potential of our research. Full article

The paper addresses the dynamic modeling and numerical simulation of a novel single-rotor wind system with a planetary speed increaser and counter-rotating direct current (DC) generator, patented by authors, during the transient stage from rest. The proposed analytical dynamic algorithm involves the decomposition of the wind system into its component rigid bodies, followed by the description of their dynamic equations using the Newton–Euler method. The linear mechanical characteristics of the DC generator and wind rotor are added to these dynamic equations. These equations allow for the establishment of the close-form equation of motion of the wind system and, implicitly, the time variation of the mechanical power parameters. Numerical simulations of the obtained analytical dynamic model were performed in MATLAB-Simulink in start-up mode from rest for the case study of a 100 kW wind turbine. These results allowed highlighting the time variation of angular velocities and accelerations, torques, and powers for all system shafts, both in the transient regime and steady-state. The implementation, in this case, of the counter-rotating generator indicates a 6.4% contribution of the mobile stator to the generator’s total power. The paper’s results are useful in the design, virtual prototyping, and optimization processes of modern wind energy conversion systems. Full article

Industrial robots are widely used in welding operations because of their high production efficiency. The structure of the robot and the complex stress conditions during welding operations lead to the vibration of the end of robot, which leads to welding defects. However, current vibration suppression techniques for welding robots usually only consider the robotic performance while overlooking their impact on the welding metal forming process. Therefore, based on the influence of robot vibration on welding pool stability during the welding process, a new welding robot vibration suppression method is proposed in this paper, along with the establishment of a welding pool stability assessment model. The proposed vibration suppression algorithm is based on the optimization of the welding trajectory. To enhance the performance of the method, the Particle Swarm Optimization (PSO) algorithm is applied to optimize the joint angular velocity and angular acceleration. Finally, robot welding experiments are designed and conducted. By comparing vibration measurement data and welding quality before and after the vibration suppression, the effectiveness and stability of the proposed method are validated. Full article

Background: The ankle joint is among the most vulnerable areas for injuries during daily activities and sports. This study focuses on individuals with chronic ankle instability (CAI), comparing the biomechanical characteristics of the lower limb during side-step cutting under various conditions. The aim is to analyze the impact of kinesiology tape (KT) length on the biomechanical properties of the lower limb during side-step cutting, thereby providing theoretical support and practical guidance for protective measures against lower-limb sports injuries. Methods: Twelve subjects with CAI who met the experimental criteria were recruited. Each subject underwent testing without taping (NT), with short kinesiology tape (ST), and with long kinesiology tape (LT), while performing a 45° side-step cutting task. This study employed the VICON three-dimensional motion capture system alongside the Kistler force plate to synchronously gather kinematic and kinetic data during the side-step cutting. Visual 3D software (V6.0, C-Motion, Germantown, MD, USA) was utilized to compute the kinematic and kinetic data, while OpenSim 4.4 software (Stanford University, Stanford, CA, USA) calculated joint forces. A one-way Analysis of Variance (ANOVA) was conducted using SnPM, with the significance threshold established at p < 0.05. The Origin software 2021 was used for data graphic processing. Results: KT was found to significantly affect joint angles, angular velocities, and moments in the sagittal, frontal, and transverse planes. LT increased hip and knee flexion angles as well as angular velocity, while ST resulted in reduced ankle inversion and increased knee internal rotation. Both types of KT enhanced hip abduction moment and knee adduction/abduction moment. Additionally, LT reduced the ankle joint reaction force. Conclusions: These findings suggest that the application of KT over a short duration leads to improvements in the lower-limb performance during side-step cutting motions in individuals with CAI, thus potentially decreasing the risk of injury. Full article

Background/Objectives: This study examined the influence of competition level and player position on shooting accuracy and kinematic parameters in U18 male basketball players, focusing on two-point jump shots and free throws. Methods: Thirty-eight higher-level (HL-group) and forty-one lower-level (LL-group) participants, categorized into guard, forward, and center subgroups, completed a two-point basketball shooting test, followed by a free-throw shooting test after a 30 min interval. These tests were administered using a crossover, counterbalanced approach with the Latin square method to ensure effective randomization. Results: The results indicated that the HL group displayed significantly faster (12.5%) shot release times (RTs) and closer-to-optimal 45° (8.1%) ball entry angles (EAs) into the hoop for free throws, as well as superior (24.2%) shot success rates (SSRs) for two-point jump shots compared with the LL group. Across all groups and subgroups, a higher EA was achieved in two-point shots than in free throws, though free throws showed higher SSR. This study found no positional differences in shooting mechanics or performance, suggesting that modern training practices may foster consistency across player roles. Conclusions: These findings emphasize the potential for targeted drills to improve RTs, EAs, and SSRs, especially in LL players. Coaches can apply these insights to enhance shooting mechanics and consistency, thereby elevating performance in young basketball athletes. Future research should investigate the impact of fatigue and defensive pressure on shooting parameters across varied competitive contexts. Full article