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Prior work has demonstrated the presence of hysteresis effects in the control of affordance-guided behavior, in that behavioral transitions around a critical action boundary vary with directions of change in said action boundary. To date, research on this topic has overlooked the influence of the global context on these phenomena. We employ an affordance-based reaching task, whereby participants were asked to move a target to a goal by passing through one of two apertures (size variable or size constant). It was found that the direction of change in the size of the variable aperture influenced the point of behavioral transitions, and this effect interacted with the location of a given goal. In addition, we considered fluctuations in the entropy of participants' reach trajectories as a window into the nature of the behavioral phase transitions. Differences in the structure of entropy were found depending on the direction of change in the size variable aperture. These results are discussed in light of a dynamical systems approach, and recommendations for future work are made. [ABSTRACT FROM AUTHOR]

This study aimed to clarify the differences in muscular coordination during butterfly swimming between high- and low-performance swimmers using muscle synergy analysis. Eight female competitive swimmers and 8 female recreational swimmers participated in this study. The participants swam a 25-m butterfly stroke with maximum effort. Surface electromyography was measured from 12 muscles and muscle synergy analysis was performed from the data using nonnegative matrix factorization algorithms. From the results of the muscle synergy analysis, 4 synergies were extracted from both groups. Synergies 1 and 2 were characterized by coactivation of the upper and lower limb muscles in the recreational swimmers, whereas only synergy 1 was characterized by this in the competitive swimmers. Synergy 3 was involved in arm recovery in both groups. Synergy 4 was only involved in the downward kick in the competitive swimmers. From these results, it can be concluded that muscle synergies with combined coordination of upper and lower limb muscles were extracted more in the recreational swimmers and that the competitive swimmers controlled the downward kick with an independent synergy and that the adjustment of the timing of the downward kick may be an important factor for the efficient performance of butterfly swimming. [ABSTRACT FROM AUTHOR]

Altering baseball pitching mechanics affects both performance and the risk of injury. The purpose of this study is to investigate the relationships of shoulder external over internal rotation ratio (SEIR) and other shoulder rotational properties during physical exam and biomechanics of pitching for 177 collegiate baseball pitchers. The shoulder range of motion was quantitatively measured using a custom-made wireless device. Pitching motion data were collected at 240 Hz, and a custom program was created to calculate the throwing arm motion and loading during baseball pitching. Linear regression and analysis of variance tests were performed to investigate the relationships between the shoulder physical exam outcomes and throwing arm biomechanics. SEIR had significant correlations with shoulder horizontal adduction angle at foot contact, maximum shoulder external rotation angle, maximum shoulder linear velocity, and elbow angle at ball release. SEIR groups had significant differences in shoulder proximal force, adduction torque, internal rotation torque, and horizontal adduction torque, and in elbow medial force and varus torque. Glenohumeral internal rotation deficit and total rotational motion deficit had no relationships with throwing arm motions or joint loadings. Shoulder health should be monitored to improve understanding of pitching mechanics in collegiate baseball pitchers. [ABSTRACT FROM AUTHOR]

Foot stance and club type's relationship with lead knee joint biomechanics and possible involvement with injury incidences in amateur golfers have not been evaluated. This study included 16 male right-handed amateur golfers who performed golf swings with 2 different foot stances (straight and open) using 4 different club types (driver, 3 iron, 6 iron, and 9 iron) while standing on 2 force plates in a motion capture laboratory. A custom program calculated the kinematics and kinetics of the lead knee. Overall, the open stance reduced most translations, rotations, forces, and torques of the lead knee in all 4 club types when compared with the straight stance. The open stance reduced the rotation motion (−28%), compressive force (−5%), and rotation torque (−9%) when compared with the straight stance, which are the highest contributors to grinding of cartilage. The driver club had significantly larger values in most translations, rotations, forces, and torques when compared among the 4 club types. The open stance reduced the rotation motion, compressive force, and rotation torque in the lead knee joint compared with the straight stance. Lead knee joint biomechanics should be monitored to reduce injury in amateur golfers. [ABSTRACT FROM AUTHOR]

Deficits in movement patterns during cutting while running might place soccer players at risk of injury. The objective was to compare joint angles and intersegment coordination between sexes and ages during an unanticipated side-step cutting task in soccer players. This cross-sectional study recruited 11 male (four adolescents and seven adults) and 10 female (six adolescents and four adults) soccer players. Three-dimensional motion capture was used to measure lower-extremity joint and segment angles as participants performed an unanticipated cutting task. Hierarchical linear models examined relationships between joint angle characteristics with age and sex. Continuous relative phase was used to quantify intersegment coordination amplitude and variability. These values were compared between age and sex groups using analysis of covariance. Adult males had greater hip flexion angle excursions than adolescent males, while adult females had smaller excursions than adolescent females (p = .011). Females had smaller changes in hip flexion angles (p = .045), greater hip adduction angles (p = .043). and greater ankle eversion angles (p =.009) than males. Adolescents had greater hip internal rotation (p = .044) and knee flexion (p = .033) angles than adults, but smaller changes in knee flexion angles at precontact compared with stance/foot off (p < .001). For intersegment coordination, females were more out-of-phase than males in the foot/shank segment in the sagittal plane. There were no differences in intersegment coordination variability between groups. Differences in joint motion during an unanticipated cutting task were present between age groups and sexes. Injury prevention programs or training programs may be able target specific deficits to lower injury risk and improve performance. [ABSTRACT FROM AUTHOR]

Sprint performance is a critical factor in soccer. While previous studies have extensively explored the biomechanical, physiological, and metabolic determinants of sprinting, the impact of anthropometric variables in team sports contexts, especially soccer, remains underexplored. This study aims to investigate the influence of anthropometric and mechanical variables on sprint performance in young soccer players. Fifty-eight young soccer players were evaluated in anthropometry and a 30-meter (m) sprint using radar technology. Split times in 5, 15, and 30 m were determined, in addition to the assessment of the force-velocity profile proposed by Morin and Samozino. Results: Key anthropometric variables associated with improved sprint performance included lower-limb muscle mass at distances 5 and 15 m (R 2 = 0.08 and R 2 = 0.09, respectively, both with small effects). Additionally, body composition, particularly a lower % body fat, was crucial across all sprint distances (ES: large). Among the mechanical variables, max power (R 2 = 0.997, ES: large) and maximum velocity (R 2 = 0.553, ES: large) are the mechanical variables that were most strongly associated with sprint performance over distances greater than 30 m. Soccer coaches, athletic trainers, and strength and conditioning specialists working with young athletes can apply the findings of this study to their training programming. [ABSTRACT FROM AUTHOR]

Evaluating complicated stress across the elbow under joint motion remains difficult. Here, we aimed to evaluate the distribution of the subchondral bone density in the normal elbow bones and further characterize their spatial relationships during elbow motion to estimate the loading stress across the articular surface using three-dimensional computed tomography bone models. The normal elbow joint exhibited a consistent distribution pattern of subchondral bone density. High-density regions were distributed in the capitellum and posterior humeral trochlea, sagittal ridge of the ulnar trochlear notch and ulnar-volar side of the radial head. Motion analyses revealed that the high-density regions proximate with elbow flexion with forearm pronation in the radiocapitellar joint and in the fully extended position in the ulnohumeral joint. This reasonably reflects the stress acting on the joint surface under actual loading conditions. These findings suggest that daily activities involving lifting or carrying objects in these positions are stress-prone activities. [ABSTRACT FROM AUTHOR]

Objective This study aimed to explore whether behavioral synchrony (BS) and inter-brain synchrony (IBS) could serve as potential biomarkers for alliance quality or outcomes among clients with different adult attachment styles. Method: We assessed the clients' self-report working alliance and clinical outcomes as well as simultaneously measured BS using motion energy analysis (MEA) and IBS with functional near-infrared spectroscopy (fNIRS) among 37 secure (N = 21) or dismissing (N = 16) clients with their counselors during the first psychological counseling meeting. Results: Dismissing dyads manifested significantly higher late-stage counselor-led and client-led IBS (p =.018) than secure dyads. Adult attachment style served as the moderators in the correlation of both whole-stage client-led BS with bond dimension of alliance (p =.015) as well as in the correlation of both whole-stage no-lag IBS with CORE-10 score changes (p =.022). Moreover, increases in the whole-stage client-led BS were significantly associated with decreases in early-stage, late-stage and whole-stage no-lag IBS (all ps ≤ 0.01). Conclusion: These findings revealed the potentially impeding role of interpersonal synchrony in alliance quality for dismissing clients, at least during the first psychological counseling meetings. They also might partially validate the relationship between different modalities of interpersonal synchrony. [ABSTRACT FROM AUTHOR]

This study analyzes the steady-state dynamics and stability of a structure with a particle damper considering the friction effect between the particle and container, with a focus on whether the system can maintain stable-state motion for an extended period. The determination of friction's contribution and the maximum allowable gap clearance for steady-state motion is demonstrated through the solution of motion of the primary structure with a particle damper subjected to low-frequency vibration conditions. Additionally, stability analysis is conducted to assess if initial disturbances cause deviations from the original stable state and identify necessary parameters for stability when the system parameters are uncertain. Analytical descriptions for the stability of the system are derived. The effects of friction on the dynamics and stability regions of the particle dampers are systematically revealed, where the theoretical and numerical models are mutually verified and supported by the cases of previous studies. Results show that the inclusion of the rolling friction effect will disrupt the steady-state motion as gap clearance approaches the optimal value. As the coefficient of rolling friction increases, the stability region's area gradually decreases with a notable leftward shift of its right boundary. This shift ultimately leads to a leftward shift in the optimal vibration reduction curve. In the range of gap clearance variation allowing for steady-state motion with two symmetrical impacts per cycle, the relative velocity of the particle is more effective and intuitive to reveal the vibration reduction mechanism of particle dampers than other perspectives such as momentum, energy, and phase. [ABSTRACT FROM AUTHOR]

In this paper, we study state estimation of multi-visual-inertial systems (MVIS) and develop sensor fusion algorithms to optimally fuse an arbitrary number of asynchronous inertial measurement units (IMUs) or gyroscopes and global and/or rolling shutter cameras. We are especially interested in the full calibration of the associated visual-inertial sensors, including the IMU/camera intrinsics and the IMU-IMU/camera spatiotemporal extrinsics as well as the image readout time of rolling-shutter cameras (if used). To this end, we develop a new analytic combined IMU integration with inertial intrinsics—termed ACI3—to pre-integrate IMU measurements, which is leveraged to fuse auxiliary IMUs and/or gyroscopes alongside a base IMU. We model the multi-inertial measurements to include all the necessary inertial intrinsic and IMU-IMU spatiotemporal extrinsic parameters, while leveraging IMU-IMU rigid-body constraints to eliminate the necessity of auxiliary inertial poses and thus reducing computational complexity. By performing observability analysis of MVIS, we prove that the standard four unobservable directions remain—no matter how many inertial sensors are used, and also identify, for the first time, degenerate motions for IMU-IMU spatiotemporal extrinsics and auxiliary inertial intrinsics. In addition to extensive simulations that validate our analysis and algorithms, we have built our own MVIS sensor rig and collected over 25 real-world datasets to experimentally verify the proposed calibration against the state-of-the-art calibration method Kalibr. We show that the proposed MVIS calibration is able to achieve competing accuracy with improved convergence and repeatability, which is open sourced to better benefit the community. [ABSTRACT FROM AUTHOR]

Obesity is a known risk factor for development of osteoarthritis (OA). Numerical tools like finite‐element (FE) models combined with degenerative algorithms have been developed to understand the interplay between OA and obesity. In this study, we aimed to predict knee cartilage degeneration in a cohort of obese adults to investigate the importance of patient‐specific information on degeneration predictions. We used a validated FE modeling approach and three different age‐dependent functions (step‐wise, exponential, and linear) to simulate cartilage degradation under overloading in the knee joint. Gait motion analysis and magnetic resonance imaging data from 115 obese individuals with knee OA were used for musculoskeletal and FE modeling. Cartilage degeneration predictions were contrasted with Kellgren–Lawrence (KL) and Boston–Leeds Osteoarthritis Knee Score (BLOKS) grades. The findings show that overall, the similarities between numerical predictions and clinical measures were better for the medial (average area under the curve (AUC) = 0.62) compared to the lateral compartment (average AUC = 0.52) of the knee. Classification results for KL grades, full patient‐specific models and patient‐specific geometry with generic gait data showed higher AUC values (AUC = 0.71 and AUC = 0.68, respectively) compared to generic geometry and patient‐specific gait (AUC = 0.48). For BLOKS grades, AUC values for both full patient‐specific models and for patient‐specific geometry with generic gait locomotion were higher (AUC = 0.66 and AUC = 0.64, respectively) compared to when the generic geometry and patient‐specific gait were used (AUC = 0.53). In summary, our study highlights the importance of considering individual information in knee OA prediction. Nevertheless, our findings suggest that personalized gait play a smaller role in the OA prediction and classification capacity than personalized joint geometry. [ABSTRACT FROM AUTHOR]

In this study we introduce an innovative mathematical and statistical framework for the analysis of motion energy dynamics in psychotherapy sessions. Our method combines motion energy dynamics with coupled linear ordinary differential equations and a measurement error model, contributing new clinical parameters to enhance psychotherapy research. Our approach transforms raw motion energy data into an interpretable account of therapist–patient interactions, providing novel insights into the dynamics of these interactions. A key aspect of our framework is the development of a new measure of synchrony between the motion energies of therapists and patients, which holds significant clinical and theoretical value in psychotherapy. The practical applicability and effectiveness of our modelling and estimation framework are demonstrated through the analysis of real session data. This work advances the quantitative analysis of motion dynamics in psychotherapy, offering important implications for future research and therapeutic practice. [ABSTRACT FROM AUTHOR]

The development of the Drag-Free and Attitude Control System is crucial for space-based gravitational wave detectors. The Drag-Free and Attitude Control System includes for spacecraft attitude control, drag-free control, moving optical subassemblies pointing control, and test masses electrostatic control during multiple phases of the mission lifetime. An accurate model of the spacecraft dynamics model is not only a precondition for the control design of Drag-Free and Attitude Control System, but also can serve as a valuable reference to assess the noise budget of gravitational wave detectors. This paper presents a generic, nonlinear mathematical model that describes the multi-body dynamics for the gravitational wave detectors. The model fully considers the couplings between the bodies involved, with a particular focus on the impact of the moving optical subassemblies on the spacecraft attitude. Additionally, a corresponding reduced model for the control design of the science mode is divided. Both models are validated numerically by Monte Carlo simulations and motion analysis, respectively. • Introduce a spacecraft dynamics model that fully describes the motion coupling. • Simscape simulation has validated the accuracy of the dynamics model. • The spacecraft dynamics model is applicable to multiple phases of motion. • Monte Carlo simulations have validated the applicability to different parameters. [ABSTRACT FROM AUTHOR]

Many scientific studies on tennis stroke recognition are based on datasets, that have been developed for particular studies, using video or motion capture techniques. The importance of such datasets has been increasing due to the athlete performance evaluation needs. The primary contribution of this study is to present a state-of-the-art 3DTennisDS storing four tennis moves: backhand, forehand, volley backhand as well as volley forehand. The strokes were registered using the Vicon optical motion capture and contain a 39 – marker player and a 7 – marker tennis racket models. The potential and quality of this unique dataset has been verified using spatial-temporal graph neural networks, because this type of network topology matches to the human body structure. The presented 3DTennisDS has been compared with two well-known datasets: the THETIS and the Tennis-Mocap. They contain tennis movements in a form of motion capture data, registered using markerless and marker-based systems. The classification of tennis movements has been performed to verify how different types of data acquisition (marker-based and marker-less ones) as well as the structure of the data affect the accuracy of human action recognition. In this study ONI files from THETIS, bvh from Tennis-Mocap and c3d data from 3DTennisDS were considered. Moreover, the impact of input data fuzzification was examined. The obtained results showed that the classification using 3DTennisDS achieved the best results, both for fuzzy and non-fuzzy inputs. These outcomes indicate that the way of capturing data, its preparation and structure have great influence on classification accuracy. The developed 3DTennisDS has a great potential in further motion capture analysis. [ABSTRACT FROM AUTHOR]

One of the key challenges in Big Data for clinical research and healthcare is how to integrate new sources of data, whose relation to disease processes are often not well understood, with multiple classical clinical measurements that have been used by clinicians for years to describe disease processes and interpret therapeutic outcomes. Without such integration, even the most promising data from emerging technologies may have limited, if any, clinical utility. This paper presents an approach to address this challenge, illustrated through an example in Parkinson's Disease (PD) management. We show how data from various sensing sources can be integrated with traditional clinical measurements used in PD; furthermore, we show how leveraging Big Data frameworks, augmented by Artificial Intelligence (AI) algorithms, can distinctively enrich the data resources available to clinicians. We showcase the potential of this approach in a cohort of 50 PD patients who underwent both evaluations with an Integrated Motion Analysis Suite (IMAS) composed of a battery of multimodal, portable, and wearable sensors and traditional Unified Parkinson's Disease Rating Scale (UPDRS)-III evaluations. Through techniques including Principal Component Analysis (PCA), elastic net regression, and clustering analysis we demonstrate how this combined approach can be used to improve clinical motor assessments and to develop personalized treatments. The scalability of our approach enables systematic data generation and analysis on increasingly larger datasets, confirming the integration potential of IMAS, whose use in PD assessments is validated herein, within Big Data paradigms. Compared to existing approaches, our solution offers a more comprehensive, multi-dimensional view of patient data, enabling deeper clinical insights and greater potential for personalized treatment strategies. Additionally, we show how IMAS can be integrated into established clinical practices, facilitating its adoption in routine care and complementing emerging methods, for instance, non-invasive brain stimulation. Future work will aim to augment our data repositories with additional clinical data, such as imaging and biospecimen data, to further broaden and enhance these foundational methodologies, leveraging the full potential of Big Data and AI. [ABSTRACT FROM AUTHOR]

Background: Sagittal balance, commonly impaired in lumbar spinal stenosis (LSS) patients, is typically assessed using the sagittal vertical axis (SVA) with EOS imaging. However, to limit X-ray exposure and medical costs, it could be interesting to evaluate the capacity of quantified motion analysis to estimate the 3D modeling of SVA in patients with symptomatic LSS. Methods: An estimation of the SVA in patients with LSS was performed with 3D motion analysis. SVA and "C7_PSI" (orthogonal horizontal distance between the vertical lines through the markers of the C7 vertebra and the middle of the posterosuperior iliac spine) were measured on 37 LSS patients using EOS radiography and postural and 3D motion analysis, respectively. Multiple stepwise linear regressions were performed with EOS SVA according to age, body mass index, C7_PSI and/or postural variables. Results: A highly significant relationship was found between SVA and C7_PSI, mediolateral amplitude of CoP displacements and age (adjusted R²=0.69, p < 0.0001). While the postural analysis did not reveal significant relationships, the model using 3D parameters revealed significant relationships between radiographic SVA and C7_PSI and age (adjusted R²=0.65, p < 0.0001). 3D motion parameters with or without postural parameters may explain more than 65% of the variance seen in EOS imaging performed on LSS patients. Conclusions: These promising results in LSS patients suggest that the estimation of SVA with 3D motion analysis offers an alternative to EOS. In addition, SVA could be assessed at rest and during dynamic tasks. Trial registration: This study has been published in Clinical Trial registration (reference NCT03194607). [ABSTRACT FROM AUTHOR]

• fMRI bilateral motor control task was used to evaluate longitudinal changes in brain activity. • Neuromuscular training induced movement adaptations in MC and HxSRC groups. • MCs demonstrate increased cerebellar activity associated with improved frontal plane ROM. • HxSRCs demonstrate increased somatosensory activity associated with improved frontal plane ROM. Sports-related concussion (SRC) in adolescent athletes is associated with an increased risk of subsequent lower extremity injury. Neuromuscular training (NMT) has shown promise for reducing lower extremity injuries following SRC, however, neural adaptations in response to changes in lower extremity biomechanics following NMT in athletes with a history of SRC (HxSRC) remains poorly understood. Therefore, the purpose of this study was to identify changes in neural activity associated with lower extremity movement adaptations following a six-week NMT intervention in athletes with a HxSRC. Thirty-two right-hand/foot-dominant female adolescent athletes (16 with self-reported HxSRC, 16 age- and anthropometrically-matched controls) completed a bilateral leg press task with 3D motion analysis during functional magnetic resonance imaging (fMRI). Movement adaptations were defined as a change in frontal and sagittal plane range of motion (ROM) during the fMRI bilateral leg press task. Significant pre- to post-NMT reductions were observed in the non-dominant (left) mean frontal plane ROM. Whole-brain neural correlate analysis revealed that increased cerebellar activity was significantly associated with reduced mean left-knee frontal ROM for matched controls. Exploratory within group analyses identified neural correlates in the postcentral gyrus for the HxSRC group which was associated with reduced mean left-knee frontal plane ROM. These distinct longitudinal changes provide preliminary evidence of differential neural activity associated with NMT to support knee frontal plane control in athletes with and without a HxSRC. [ABSTRACT FROM AUTHOR]

Most multiple object tracking algorithms depend on the output of the detector. Aiming at the problem that the higher detection quality model is restricted by the computing power, and the robustness of the lightweight detection model is easily affected by motion blur, this paper proposes a lightweight moving object detector based on improved YOLOv8 combined with dynamic confidence compensation algorithm. The algorithm combines various technical means such as network structure optimization, lightweight design, self‐knowledge distillation, loss function improvement and dynamic confidence compensation. ByteTrack is used as a tracker to conduct experiments on PASCAL VOC07+12 data set and UA‐DETRAC test sequence. Compared with the baseline YOLOv8n+ByteTrack, the proposed algorithm improves the HOTA by 1.3% when the single frame tracking delay is reduced by 1.1%. Mostly tracked target is improved by 79.7%, mostly lost target is reduced by 10.9%, and the detection effect is better than the original detector and other popular object detectors. The YOLODCC model achieves a balance between lightweight and multi‐object motion blur. [ABSTRACT FROM AUTHOR]

The quality of images we perceive visually is heavily impacted by the settings used for camera exposure. When these settings are imbalanced, it can result in an undesired prominent phenomenon known as blur effects. To address this problem, an ExposureNet project has been undertaken, which aims to develop an autonomous camera exposure settings control system for blur effects prevention. The proposed ExposureNet model is a CNN/Transformer hybrid neural structure, created and trained in a comprehensive manner to effectively predict the ideal exposure settings based on the semantic features of the scene being captured. This system is designed to learn the necessary steps for processing, such as identifying relevant scene features, using only two camera exposure parameters (shutter speed (SHS) and ISO) as training signals. As a result, this system can associate the semantic features of a scene with the appropriate exposure parameter adjustments, customized to the scene's dynamics and lighting conditions. By simultaneously optimizing all processing steps and bypassing traditional post‐processing stages, the proposed system is designed to achieve faster performance, reduced computational cost, and lower power consumption. Experimental results demonstrate that the proposed system significantly outperforms existing methods and achieves cutting‐edge performance. [ABSTRACT FROM AUTHOR]

The control of hand movement during sailing is important for performance. To quantify the amount of regularity and the unpredictability of hand fluctuations during the task, the mathematical algorithm Approximate Entropy (ApEn) of the hand acceleration can be used. Approximate Entropy is a mathematical algorithm that depends on the combination of two input parameters including (1) the length of the sequences to be compared (m), and (2) the tolerance threshold for accepting similar patterns between two segments (r). The aim of this study is to identify the proper combinations of 'm' and 'r' parameter values for ApEn measurement in the hand movement acceleration data during sailing. Inertial Measurement Units (IMUs) recorded acceleration data for both the mainsail (non-dominant) and tiller (dominant) hands across the X-, Y-, and Z-axes, as well as vector magnitude. ApEn values were computed for 24 parameter combinations, with 'm' ranging from 2 to 5 and 'r' from 0.10 to 0.50. The analysis revealed significant differences in acceleration ApEn regularity between the two hands, particularly along the Z-axis, where the mainsail hand exhibited higher entropy values (p = 0.000673), indicating greater acceleration complexity and unpredictability. In contrast, the tiller hand displayed more stable and predictable acceleration patterns, with lower ApEn values. ANOVA results confirmed that parameter 'm' had a significant effect on acceleration complexity for both hands, highlighting differing motor control demands between the mainsail and tiller hands. These findings demonstrate the utility of IMU sensors and ApEn in detecting nuanced variations in acceleration dynamics during sailing tasks. This research contributes to the understanding of hand-specific acceleration patterns in sailing and provides a foundation for further studies on adaptive sailing techniques and motor control strategies for both novice and expert sailors. [ABSTRACT FROM AUTHOR]

Motion sickness is a common issue in electric vehicles, significantly impacting passenger comfort. This study aims to develop a functional brain network analysis model by integrating electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) signals to evaluate motion sickness symptoms. During real-world testing with the Feifan F7 series of new energy-electric vehicles from SAIC Motor Corp, data were collected from 32 participants. The EEG signals were divided into four frequency bands: delta-range, theta-range, alpha-range, and beta-range, and brain oxygenation variation was calculated from the fNIRS signals. Functional connectivity between brain regions was measured to construct functional brain network models for motion sickness analysis. A motion sickness detection model was developed using a graph convolutional network (GCN) to integrate EEG and fNIRS data. Our results show significant differences in brain functional connectivity between participants in motion and non-motion sickness states. The model that combined fNIRS data with high-frequency EEG signals achieved the best performance, improving the F1 score by 11.4% compared to using EEG data alone and by 8.2% compared to using fNIRS data alone. These results highlight the effectiveness of integrating EEG and fNIRS signals using GCN for motion sickness detection. They demonstrate the model's superiority over single-modality approaches, showcasing its potential for real-world applications in electric vehicles. [ABSTRACT FROM AUTHOR]

The disturbance of the coal caving mechanism is the main method to solve the problem of coal falling into an arch during the top coal caving process, and the clearance in the caving mechanism is an important factor affecting its disturbance. To study the influence of clearance on the hydraulic supports, the dynamic analysis of hydraulic supports with two-level and three-level caving mechanisms is conducted considering the clearance. Based on Lagrange's equations of first kind, the mathematical model is constructed, and the equivalent spring stiffness of the oil cylinder is solved. The dynamic response of hydraulic support is studied by solving the mathematical model, and the relative position changes of the journal and bearing are compared. The research results prove that clearance has a better disturbance effect on the three-level caving mechanism. At the same time, the influence of clearance size and motion process on the motion error of the three-level caving mechanism is analyzed. Using the Kriging surrogate model and polynomial interpolation, the motion prediction model for the secondary tail beam with different clearance sizes is proposed, and the predicted values of the test samples are compared with the numerical solution values to prove the feasibility. [ABSTRACT FROM AUTHOR]

Introduction: Currently, using machine learning methods for precise analysis and improvement of swimming techniques holds significant research value and application prospects. The existing machine learning methods have improved the accuracy of action recognition to some extent. However, they still face several challenges such as insufficient data feature extraction, limited model generalization ability, and poor real-time performance. Methods: To address these issues, this paper proposes an innovative approach called Swimtrans Net: A multimodal robotic system for swimming action recognition driven via Swin-Transformer. By leveraging the powerful visual data feature extraction capabilities of Swin-Transformer, Swimtrans Net effectively extracts swimming image information. Additionally, to meet the requirements of multimodal tasks, we integrate the CLIP model into the system. Swin-Transformer serves as the image encoder for CLIP, and through fine-tuning the CLIP model, it becomes capable of understanding and interpreting swimming action data, learning relevant features and patterns associated with swimming. Finally, we introduce transfer learning for pre-training to reduce training time and lower computational resources, thereby providing real-time feedback to swimmers. Results and discussion: Experimental results show that Swimtrans Net has achieved a 2.94% improvement over the current state-of-the-art methods in swimming motion analysis and prediction, making significant progress. This study introduces an innovative machine learning method that can help coaches and swimmers better understand and improve swimming techniques, ultimately improving swimming performance. [ABSTRACT FROM AUTHOR]

Learning through cooperation with conspecifics—'cooperative learning'—is critical to cultural evolution and survival. Recent progress has established that interbrain synchronization (IBS) between individuals predicts success in cooperative learning. However, the likely sources of IBS during learning interactions remain poorly understood. To address this dearth of knowledge, we tested whether movement synchrony serves as an exogenous factor that drives IBS, taking an embodiment perspective. We formed dyads of individuals with varying levels of prior knowledge (high–high (HH), high–low (HL), low–low (LL) dyads) and instructed them to collaboratively analyse an ancient Chinese poem. During the task, we simultaneously recorded their brain activity using functional near-infrared spectroscopy and filmed the entire experiment to parse interpersonal movement synchrony using the computer-vision motion energy analysis. Interestingly, the homogeneous groups (HH and/or LL) exhibited stronger movement synchrony and IBS compared with the heterogeneous group. Importantly, mediation analysis revealed that spontaneous and synchronized body movements between individuals contribute to IBS, hence facilitating learning. This study therefore fills a critical gap in our understanding of how interpersonal transmission of information between individual brains, associated with behavioural entrainment, shapes social learning. This article is part of the theme issue 'Minds in movement: embodied cognition in the age of artificial intelligence'. [ABSTRACT FROM AUTHOR]

We systematically reviewed and synthesized the evidence for the relationship between hip strength and hip and knee biomechanics during single-leg tasks in uninjured and injured populations. We searched CINAHL, EMBASE, PubMed, SportDiscus, and Web of Science from inception to July 2024. We included cross-sectional studies with uninjured and/or injured participants that reported correlations between hip strength and hip or knee kinematics during a single-leg task. We identified 41 articles that reported the correlations between hip strength and hip or knee kinematics during a single–leg task for uninjured (n = 33) and/or injured (n = 12) populations. We identified moderate–to-strong evidence for no-to-poor relationships between most hip strength and hip and knee kinematics during a single-leg task for uninjured (r = –0.33–0.45) and injured populations (r = –0.24–0.24). We observed limited-to-moderate evidence for fair-to-moderate negative relationships between concentric and eccentric hip abduction strength and hip adduction (r = –0.52) and knee abduction kinematics (r = –0.45–0.59) for uninjured populations. Isometric hip strength may not play as important of a role in controlling lower extremity motion during single-leg tasks as previously perceived, but isokinetic strength may be a better indicator of lower extremity motion during single-leg tasks. Trial Registration:PROSPERO#CRD42020153166. [ABSTRACT FROM AUTHOR]

Estimating human joint angles is a crucial task in motion analysis, gesture recognition, and motion intention prediction. This paper presents a novel model-based approach for generating reliable and accurate human joint angle estimation using a dual-branch network. The proposed network leverages combined features derived from encoded sEMG signals and RGB-D image data. To ensure the accuracy and reliability of the estimation algorithm, the proposed network employs a convolutional autoencoder to generate a high-level compression of sEMG features aimed at motion prediction. Considering the variability in the distribution of sEMG signals, the proposed network introduces a vision-based joint regression network to maintain the stability of combined features. Taking into account latency, occlusion, and shading issues with vision data acquisition, the feature fusion network utilizes high-frequency sEMG features as weights for specific features extracted from image data. The proposed method achieves effective human body joint angle estimation for motion analysis and motion intention prediction by mitigating the effects of non-stationary sEMG signals. [ABSTRACT FROM AUTHOR]

Addressing the risk of musculoskeletal disorders (MSDs) during a tennis serve is a challenge for both protecting athletes and maintaining performance. The aim of this study was to investigate the risk of MSD occurrence using the rapid whole-body assessment (REBA) ergonomic tool at each time step, using 3D kinematic analysis of joint angles for slow and fast serves. Two force platforms (750 Hz) and an optoelectronic system including 10 infrared cameras (150 Hz, 82 markers located on the whole body and on the racket) were used to capture the kinematics of the six REBA joint areas over five services in two young male and two young female ranked players. The mean REBA score was 9.66 ± 1.11 (ranging from 7.75 to 11.85) with the maximum value observed for the loading and cocking stage (REBA score > 11). The intermediate scores for each of the six joint areas ranged between 2 and 3 and the maximum value of their respective scales. The lowest scores were observed for the shoulder. Neck rotation and shoulder flexion are parameters that could be taken into account when analyzing performance in the context of MSD prevention. [ABSTRACT FROM AUTHOR]

An inertial measurement system, using a combination of accelerometers, gyroscopes and magnetometers, is of great interest to capture tennis movements. We have assessed the key biomechanical moments of the serve phases and events, as well as the kinematic metrics during the serve, to analyze their influence on serve speed. Eighteen male competitive tennis players, equipped with the inertial measurement units, performed a prolonged serve game consisting of 12 simulated points. Participants were divided into groups A and B in accordance with their positioning above or below the sample average serve speed. Group A (compared with their counterparts) presented with lower back hip adduction and knee flexion, and a higher leftward thoracic tilt during the impact event (−14.9 ± 6.9 vs. 13.8 ± 6.4, 2.8 ± 5.9 vs. 14.3 ± 13.0 and −28.9 ± 6.3 vs. 28.0 ± 7.3°). In addition, group A exhibited higher maximal angular velocities in the wrist and thorax, as well as a lower maximal angular velocity in the back hip than group B (427.0 ± 99.8 vs. 205.4 ± 9.7, 162.4 ± 81.7 vs. 193.5 ± 43.8, 205.4 ± 9.7 vs. 308.3 ± 111.7, 193.5 ± 43.8 vs. 81.1 ± 49.7°/s). The relevant biomechanical differences during the serve were identified, highlighting the changes in joint angles and angular velocities between the groups, providing meaningful information for coaches and players to improve their serve proficiency. [ABSTRACT FROM AUTHOR]

In this article, using conditional power, we extended the widely used classical Brownian motion (Bm) technique for monitoring clinical trial data to a larger class of stochastic processes fractional Brownian motion (fBm) with drift, and compare these results. We applied a Bayesian method to estimate parameters. The simulation study is presented as an example to illustrate scenarios under classical and fractional Brownian motion. We demonstrated the drift fractional Brownian motion in sequential monitoring of clinical trials and provided a formula for calculating conditional power under an alternative hypothesis for interim analysis. We investigated cases commonly used in clinical trials, with the Hurst parameter H = 0.5 and H > 0.5, respectively. Our simulation study suggests that the conditional power under the fBm assumption is generally higher than that under the Bm assumption when H > 0.5 and also matches better with our empirical results. [ABSTRACT FROM AUTHOR]

Most recently, metro rigid overhead wire-pantograph systems are subjected to severe wear of overhead wires and current collectors throughout China, which are difficult to completely solve up to now. The severe wear of metro rigid overhead wire-pantograph systems is probably brought about by the medium-high frequency vibration of the metro rigid overhead wire-pantograph systems. Coincidentally, corrugation is frequently found in rigid overhead wire systems, but rarely in flexible catenary systems. A frictional self-excited vibration model of a rigid overhead wire-pantograph system was set up. The self-excited vibration characteristics were investigated using the transient analysis and the motion stability analysis. Results show that when the friction coefficient is greater than 0.07, the rigid overhead wire-pantograph system is more prone to self-excited vibration. The self-excited vibration frequencies cover a range of 20–1000 Hz. The simulated overhead wire corrugation approaches the measured corrugation in wavelength. The influence factor analysis displays that the friction coefficient, zigzag layout of rigid catenary wires, and sliding direction of pantographs have significant effects on overhead wire corrugation, and but the train speed, normal force, main spring stiffness, and span of two positioning clips have a little effect. [ABSTRACT FROM AUTHOR]

This study aimed to determine the characteristics of the elite skiers and the techniques required to improve their performance in the men's giant slalom alpine skiing competition by conducting a three-dimensional (3D) motion analysis. The top nine skiers were compared with the next nine skiers using 3D motion analysis in a single-gate section with an average slope of 25.6°. The results revealed the following characteristics of superior skiing techniques. (1) The skiers started the turn from a high position relative to the gate and obtained high velocity by skiing in a gentle arc using potential energy. (2) By quickly rotating and edging the skis, the skiers were able to gain centripetal force early, enter the gate, ski in the direction of the fall line, and change skiing direction timely. (3) The skiers had quick inward leaning of the body and early lowering of the pelvis on the outside ski to form an angulation posture to resist the large external forces acting on the body during the turn. [ABSTRACT FROM AUTHOR]

Liquefaction can significantly alter the ground response. However, no existing design spectrum accounts for the severity of soil liquefaction. This work aims to develop correction factors that can be used to adjust code-based design spectra to reflect the specific liquefaction susceptibility of a site. The correction factor is derived as the ratio of response spectra calculated by two types of 1D nonlinear site response analyses: effective stress analysis, which can model porewater pressure (PWP) generation, and total stress analysis. We considered seven real profiles and 200 motions in our analysis. Four combinations of soil nonlinear models and PWP generation models are also utilized to account for epistemic uncertainties. Results show that the response spectral ratio for liquefied sites typically falls below one for periods less than 1–2 s and rises above one for longer periods. Meanwhile, the response spectral ratio reflects the overall liquefaction susceptibility influenced by PWP, factor of safety, and liquefiable layer depth, while the liquefaction potential index (LPI) captures their complex interplay. Accordingly, we propose four LPI-dependent factors: three correction factors for peak ground acceleration, 0.2 s spectral acceleration (Sa), and 1.0 s Sa, and a long-period adjustment factor applicable for periods exceeding 1 s. The correction factors linearly decrease with increasing LPI, while the adjustment factor exhibits the opposite trend. A design spectrum for a liquefiable site can be readily constructed by adjusting the code-based design spectrum using the proposed correction factor, as illustrated in the example. This approach is applicable as long as LPI is available from a simplified liquefaction analysis or a liquefaction hazard map. [ABSTRACT FROM AUTHOR]

Few studies have reported on the validity of a sensor-based lower-limb kinematics evaluation during the timed up and go (TUG) test. This study aimed to determine the validity of a wearable gait sensor system for measuring lower-limb kinematics during the TUG test. Ten young healthy participants were enrolled, and lower-limb kinematics during the TUG test were assessed using a wearable gait sensor system and a standard optical motion analysis system. The angular velocities of the hip, knee, and ankle joints in sit-to-stand and turn-to-sit phases were significantly correlated between the two motion analysis systems (R = 0.612–0.937). The peak angles and ranges of motion of hip, knee, and ankle joints in the walking-out and walking-in phases were also correlated in both systems (R = 0.528–0.924). These results indicate that the wearable gait sensor system is useful for evaluating lower-limb kinematics not only during gait, but also during the TUG test. [ABSTRACT FROM AUTHOR]

Motion perception is crucial in competitive sports like dance, basketball, and diving. However, evaluations in these sports heavily rely on professionals, posing two main challenges: subjective assessments are uncertain and can be influenced by experience, making it hard to guarantee timeliness and accuracy, and increasing labor costs with multi-expert voting. While video analysis methods have alleviated some pressure, challenges remain in extracting key points/frames from videos and constructing a suitable, quantifiable evaluation method that aligns with the static–dynamic nature of movements for accurate assessment. Therefore, this study proposes an innovative intelligent evaluation method aimed at enhancing the accuracy and processing speed of complex video analysis tasks. Firstly, by constructing a keyframe extraction method based on musical beat detection, coupled with prior knowledge, the beat detection is optimized through a perceptually weighted window to accurately extract keyframes that are highly correlated with dance movement changes. Secondly, OpenPose is employed to detect human joint points in the keyframes, quantifying human movements into a series of numerically expressed nodes and their relationships (i.e., pose descriptions). Combined with the positions of keyframes in the time sequence, a standard pose description sequence is formed, serving as the foundational data for subsequent quantitative evaluations. Lastly, an Action Sequence Evaluation method (ASCS) is established based on all action features within a single action frame to precisely assess the overall performance of individual actions. Furthermore, drawing inspiration from the Rouge-L evaluation method in natural language processing, a Similarity Measure Approach based on Contextual Relationships (SMACR) is constructed, focusing on evaluating the coherence of actions. By integrating ASCS and SMACR, a comprehensive evaluation of dancers is conducted from both the static and dynamic dimensions. During the method validation phase, the research team judiciously selected 12 representative samples from the popular dance game Just Dance, meticulously classifying them according to the complexity of dance moves and physical exertion levels. The experimental results demonstrate the outstanding performance of the constructed automated evaluation method. Specifically, this method not only achieves the precise assessments of dance movements at the individual keyframe level but also significantly enhances the evaluation of action coherence and completeness through the innovative SMACR. Across all 12 test samples, the method accurately selects 2 to 5 keyframes per second from the videos, reducing the computational load to 4.1–10.3% compared to traditional full-frame matching methods, while the overall evaluation accuracy only slightly decreases by 3%, fully demonstrating the method's combination of efficiency and precision. Through precise musical beat alignment, efficient keyframe extraction, and the introduction of intelligent dance motion analysis technology, this study significantly improves upon the subjectivity and inefficiency of traditional manual evaluations, enhancing the scientificity and accuracy of assessments. It provides robust tool support for fields such as dance education and competition evaluations, showcasing broad application prospects. [ABSTRACT FROM AUTHOR]

The Internet of Health Things (IoHT) is a broader version of the Internet of Things. The main goal is to intervene autonomously from geographically diverse regions and provide low-cost preventative or active healthcare treatments. Smart wearable IMUs for human motion analysis have proven to provide valuable insights into a person's psychological state, activities of daily living, identification/re-identification through gait signatures, etc. The existing literature, however, focuses on specificity i.e., problem-specific deep models. This work presents a generic BiGRU-CNN deep model that can predict the emotional state of a person, classify the activities of daily living, and re-identify a person in a closed-loop scenario. For training and validation, we have employed publicly available and closed-access datasets. The data were collected with wearable inertial measurement units mounted non-invasively on the bodies of the subjects. Our findings demonstrate that the generic model achieves an impressive accuracy of 96.97% in classifying activities of daily living. Additionally, it re-identifies individuals in closed-loop scenarios with an accuracy of 93.71% and estimates emotional states with an accuracy of 78.20%. This study represents a significant effort towards developing a versatile deep-learning model for human motion analysis using wearable IMUs, demonstrating promising results across multiple applications. [ABSTRACT FROM AUTHOR]

OBJECTIVE The goal of this study was to compare the accuracy of kinematic measurements obtained using the 2-D videobased kinematic motion analysis (KMA) software Kinovea (version 0.9.5; http://www.kinovea.org) with 3-D KMA in healthy dogs. METHODS In this prospective study, 3-D marker--based KMA (VICON-Nexus, version 2.12.1, and Procalc, version 1.6; VICON Motion Systems Ltd) was performed on healthy dogs (body weight ≥ 20 kg; height at withers > 50 cm) walking on a treadmill (study period: November 2022). Simultaneously, dogs were video recorded by 1 smartphone (iPhone SE; Apple Inc) at a 1.50-m distance perpendicular to the shoulder (60 frames per second; 1,920 X 1,080 pixels) for KMA using Kinovea. Joint angle and joint angle velocity of the shoulder, elbow, carpus, hip, stifle, and tarsus were calculated for 6 synchronized gait cycles. Each gait cycle was divided into 10 increments. The difference between 3-D KMA and Kinovea was assessed for each parameter using robust linear mixed-effects models. RESULTS 34 dogs were included. The estimated joint angle difference between 3-D KMA and Kinovea was less than 2° for all shoulder and elbow gait cycle increments. For the carpus, hip, stifle, and tarsus, the difference was less than 2° in 9, 5, 4, and 4 out of 10 gait cycle increments, respectively. CONCLUSIONS Kinovea provides accurate kinematic data for the shoulder and elbow of healthy dogs. Carpal, hip, stifle, and tarsal kinematics were less accurate. CLINICAL RELEVANCE The use of Kinovea for clinical and research purposes remains limited. Future Kinovea-based studies are needed to investigate the accuracy of carpal, hip, stifle, and tarsal kinematics. [ABSTRACT FROM AUTHOR]

This study aimed to determine kinematic and kinetic key performance indicators (KPI) of swimming turn performance using principal component analysis (PCA) and multiple linear regression analysis and provide reference values using percentiles. Touch and tumble turn performances of male (n = 68) and female (n = 48) Swiss national team members from three age categories—adult (20.2 ± 2.7 yrs, 790 ± 57 points), junior (16.2 ± 0.8 yrs, 729 ± 53 points) and youth swimmers (14.4 ± 1.0 years of age, 667 ± 53 World Aquatics swimming points, respectively)—were assessed with a motion analysis system equipped with a force plate on the pool wall, one over- and four underwater cameras sampling forces at 500 Hz and footages at 100 Hz. The PCA reduced the 27 original variables by up to 15% depending on turn type and age category using Varimax component loading of >0.6 and explained up to 91% of the total variance. The highest Varimax component loadings for each principal component were used to determine KPI for each turn type and age category using multiple-regression analysis with total turn time as dependent variable. These KPI should be used to interpret turn performances and identify individual swimmers’ strengths, weaknesses and future potentials with the help of the percentiles as reference values. [ABSTRACT FROM AUTHOR]

In cross-country ski skating, both the G2 and G4 sub-techniques involve one pole push for every second ski push but are used at largely different speed-slope ranges. The aim of this study was to compare temporal and kinematic patterns between G2 and G4 at both identical and different speed-slope conditions. A mixed model was used to analyse spatio-temporal parameters, while a combination of dynamic time warping and statistical parametric mapping was used to compare time traces. Main spatio-temporal parameters, such as cycle time, ski contact time and swing time, differed between G2 and G4 (all p < 0.01). Moreover, two forward and more pronounced acceleration phases of the centre of mass (CoM) were visible in G4 while only one acceleration phase was present in G2. The more continuous propulsion in G2 allows for maintaining a more constant speed at steep slopes and low speeds where this sub-technique is preferred. In contrast, the achievement of high speeds while skiing on flatter terrain seem to require more dynamic motion with shorter, more explosive propulsion periods allowed for in G4. In conclusion, G2 and G4 are two unique movements as characterised by fundamentally different CoM motion and should be denoted as two different sub-techniques. [ABSTRACT FROM AUTHOR]

Achilles tendinopathy is prevalent among Irish dancers, believed to be due to aesthetic technical requirements and high-impact landing tasks. However, the peak Achilles tendon force during Irish dancing-specific landing tasks has not been quantified. Furthermore, the influence of fatigue is unclear. This study aimed to quantify the peak Achilles tendon force during three common Irish dancing landing tasks and investigate the effects of fatigue on this force. Twelve nationally competitive Irish dancers completed the landing tasks prior to and following a fatigue protocol. A Vicon motion analysis system and AMTI force plates were used to calculate sagittal plane ankle joint kinematics during landing to estimate peak Achilles tendon force. Three independent measures (Rating-of-Fatigue scale, Flight time: Contraction during a counter movement jump and jump height during the landing trials) were used to evaluate participant fatigue between conditions. Results revealed a significant difference in peak Achilles tendon force between the three landing tasks, however, no significant difference was observed between pre- and post-fatigue. Further research is required to investigate the effects of the landing technique used in Irish Dancing on peak Achilles tendon force with the aim to reduce peak Achilles tendon force and the risk of developing Achilles tendinopathy. [ABSTRACT FROM AUTHOR]

This study aimed to examine the intra-season variation and the effects of contextual variables on total distance (TD), high-intensity running distance (HIRD) and high-speed distance (HSD) covered by Spanish football teams. The sample included 20 professional teams that competed in the Spanish LaLiga during the 2021--2022 season. Data were recorded using the TRACAB (ChyronHego, New York, USA) multicamera computerized optical tracking system. Multilevel linear mixed models were used to examine the effects of five contextual variables (1: phase of the season in six periods, 2: match location, 3: opponent ranking, 4: team ranking and 5: congested schedule) on TD, HIRD and HSD. Teams increased the running performance from period 1 to 5 of the season in TD (+2.2%; P < 0.05) and from period 1 to 4 in HIRD (+7.2%; P < 0.05), while a declining effect was found in period 6 for both TD (-1.2%; P < 0.05) and HIRD (-5.8%; P < 0.05). More HIRD (+1.5) and HSD (+5.3) were covered at home (P < 0.05), and more TD and HIRD were covered when playing against opponents ranked in the first (+2.4% and +5.3%, respectively; P < 0.05) and second quartile (+1.2% and +5.0%, respectively; P < 0.05), compared to teams from the fourth quartile. Football coaches and fitness specialists should note that running performance of Spanish teams increased throughout the season, but it declined during the last matches of the competition. Additionally, home matches and high-ranked opponents elicited higher running demands. [ABSTRACT FROM AUTHOR]

Background: Although My Jump 2® consistently presented excellent values of reliability and validity when compared to force platforms (FPs) and contact mats, to date no scientific investigation assessed the validity and reliability of My Jump 2® to measure jump height in visually impaired five-a-side soccer athletes. Thus, the study aimed at analyzing the validity and reliability of the My Jump 2® to measure the vertical jump of five-a-side soccer athletes. Methods: Twelve visually impaired five-a-side soccer athletes, volunteered for this study. Each player performed five countermovement jumps (CMJs) and squat jumps (SJs) on a contact platform (CP) while they were simultaneously recorded using MyJump 2®. Results: There was almost perfect agreement between the My Jump 2® and the contact platform measurements of CMJ (intraclass correlation coefficient = 0.99; p < 0.001) and SJ (intraclass correlation coefficient = 0.99; p < 0.001), heights for athletes during the first and second measurement days. Bland-Altman analysis showed a bias of 0.25 ± 0.5 cm; maximum SD = 1.3; minimum SD = −0.88 for CMJ, while that Bland-Altman analysis showed bias 0.18 ± 0.5 cm; maximum SD = 1.3; minimum SD = −0.96, for SJ. Conclusion: We can conclude that the My Jump 2® is a valid and reliable method to measure CMJ and SJ in visually impaired five-a-side soccer athletes. [ABSTRACT FROM AUTHOR]

With the advancement of deep-sea exploration, the demand for underwater manipulators capable of long-duration heavy-duty operations has intensified. Water-hydraulic systems exhibit less viscosity variation with increasing depth than oil-based systems, offering better adaptability to deep-sea conditions. Using seawater as the driving medium inherently eliminates issues such as oil contamination by water, frequent maintenance limiting underwater operation time, and environmental pollution caused by oil leaks. This paper introduces a deep-sea manipulator directly driven by seawater from the deep-sea environment. To address the challenges of weak lubrication and high corrosion associated with water hydraulics, a reciprocating plunger seal was adopted, and a water-hydraulic actuator was developed. The installation positions of actuator hinges and maximum output force requirements were optimized using particle swarm optimization (PSO), effectively reducing the manipulator's self-weight. Through kinematic and inverse kinematic analyses and joint performance tests, a six-degree-of-freedom water-hydraulic manipulator was designed with a maximum reach of 2.5 m, a lifting capacity of 5000 N, and end-effector positioning accuracy within 18 mm. [ABSTRACT FROM AUTHOR]

In order to address the problem of a high miss-seeding rate in mechanized potato planting work, a novel reseeding device is designed and analyzed. Based on dynamic and kinematic principles, the seed potato's motion analysis model in the seed preparation process was constructed. The analysis results indicate that the seed preparation performance is positively related to the seed preparation opening length l1 and inclination angle of the seed-returning pipe θ. Then, the potato's motion analysis model in the reseeding process was constructed. The analysis showed that the displacement of seeding potatoes in the horizontal direction ds is influenced by the initial seeding potato's speed v 0 t , dropping height hs, and the angle between the seeding pipe and the horizontal ground βs. The horizontal moving distance xr of the reseeding potatoes is influenced by the angle between the bottom of the reseeding pipe and horizontal ground βs2, the distance from its centroid to the reseeding door d, and the dropping height of the potato hr. The analysis results indicated that the reseeding potato can be effectively discharged into the furrow. Then, a prototype of a reseeding control system was constructed based on the STM32 microcontroller, electric pushers, and through-beam laser sensors. The simulation analysis was conducted to verify the theoretical analysis by using EDEM2020 software. The simulation results indicated that with the increase in the seeding chain speed, the seed preparation success rate initially increased slowly and then decreased gradually. The seed preparation performance can be increased by increasing the seed preparation opening length or decreasing the seed-returning pipe inclination angle. The impact on the successful seed preparation rate is ranked by significance as follows: seed preparation opening length > seed-returning pipe inclination angle > chain speed. Then, the prototype reseeding device and the corresponding seed metering device were manufactured and a series of bench tests and field tests were conducted. The bench test results showed an average successful seed preparation rate of 93.6%. The average qualified-seeding rate, miss-seeding rate, and multi-seeding rate in the field test were 89.6%, 2.46%, and 7.94%, respectively. This study can provide a theoretical reference for the design of potato reseeding devices. [ABSTRACT FROM AUTHOR]

To address the limitations of current cabbage harvesters in China, which are often designed for a single variety and lack adaptability to different cabbage varieties, we developed an electric side-mounted cabbage harvester suitable for field operations in the Jiangsu region of China. This design is informed by the statistical analysis of the physical and agronomic parameters of major cabbage varieties. The harvester consists of key components, including an extraction device, a leaf-stripping device, a clamping and conveying device, and a root-cutting device. Powered by a 120 Ah direct current (DC) power source, it is capable of performing cabbage extraction, feeding, clamping, conveying, root cutting, and boxing in a single operation for three hours. Through theoretical analysis of the key components, specific parameters were determined, and field tests were conducted to verify the design. The results of the field experiments indicate that all components of the cabbage harvester operated effectively. Optimal performance was observed when the extraction roller speed was set between 100 and 110 RPM, the conveyor belt speed at 60 RPM, and the cutter speed between 160 and 220 RPM, resulting in a low cabbage harvest loss rate. The harvest loss rates from the three experiments were 11.3%, 13.3%, and 12%, respectively, which meets the mechanical harvesting requirements for cabbage. [ABSTRACT FROM AUTHOR]

The ability of a pace bowler to deliver the cricket ball at faster speeds is linked with improved match performance as they require less deliveries to take a wicket and concede less runs per wicket taken. The aim of this study was to explore the relationship between ball release speed and selected pace bowling kinematics in 19 elite female pace bowlers. Participants bowled 18 match-intensity deliveries indoors from a full run-up. Peak ball release speed and three-dimensional pace bowling kinematic data were extracted from six deliveries that met specific selection criteria. Linear and non-linear relationships were assessed between ball release speed and selected pace bowling kinematics. Ball release speed was associated linearly with pelvis orientation at back foot contact (r2 = 0.34, p = 0.048) and non-linearly with thoraco-pelvic lateral flexion at front foot flat (r2 = 0.69, p < 0.001). Compared to their slower counterparts, faster elite female pace bowlers were more side-on at back foot contact and more upright in the frontal plane at front foot flat. A side-on pelvis orientation at back foot landing is likely to permit greater whole-body angular momentum in the transverse plane of motion. A more upright trunk orientation at front foot flat may be indicative of delayed onset of trunk flexion and representative of optimal segmental sequencing to maximise ball release speed. This knowledge is likely to be useful in the coaching and development of female pace bowlers for the purposes of enhancing ball release speed and therefore match performance. [ABSTRACT FROM AUTHOR]

The attentional focus strategy (AFS) affects drop jump (DJ) performance; however, its effects on DJ kinetics and kinematics are unclear. This study examines the effects of AFS on DJ performance, kinetics and kinematics. Forty collegiate males were divided into a DJ experienced group and a DJ inexperienced group, and they performed two trials of DJs after listening to instructions designed to elicit internal (INT), external (EXT) or neutral (NEUT) focus of attention. In the experienced group, the reactive strength index (RSI) was larger with the NEUT than with the INT. Hip joint torque and positive hip joint power in the concentric phase was smaller with the NEUT than with the INT, and the hip joint angle at the lowest centre of mass was larger with the NEUT than with the INT (p <.05). In the inexperienced group, RSI was larger with the EXT than with the INT. Further, the hip joint torque in the concentric phase was smaller with the EXT than with the INT; positive ankle joint power was larger with the EXT than with the INT; and the hip joint angles at the lowest centre of mass and take-off were larger with the EXT than with the INT (p <.05). These results showed that the AFS affected the DJ performance, kinetics and kinematics and suggested that effective DJ training may be achieved with the NEUT for DJ experienced and with the EXT for DJ inexperienced. [ABSTRACT FROM AUTHOR]

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