Search Results (721)

With the development of electrification and intelligent technologies in vehicles, ride comfort issues represented by motion sickness have become a key constraint on the performance of autonomous driving. The occurrence of motion sickness is influenced by the comprehensive movement of the vehicle in the longitudinal, lateral, and vertical directions, involving ACC, LKA, active suspension, etc. Existing motion sickness control method focuses on optimizing the longitudinal, lateral, and vertical directions separately, or coordinating the optimization control of the longitudinal and lateral directions, while there is relatively little research on the coupling effect and coupled optimization of the longitudinal and vertical directions. This study proposes a coupled framework of ACC and active suspension control system based on MPC. By adding pitch angle changes caused by longitudinal acceleration to the suspension model, a coupled state equation of half-car vertical dynamics and ACC longitudinal dynamics is constructed to achieve integrated optimization of ACC and suspension for motion suppression. The suspension active forces and vehicle acceleration are regulated coordinately to optimize vehicle vertical, longitudinal, and pitch dynamics simultaneously. Simulation experiments show that compared to decoupled control of ACC and suspension, the integrated control framework can be more effective. The research results confirm that the dynamic coordination between the suspension and ACC system can effectively suppress the motion sickness, providing a new idea for solving the comfort conflict in the human vehicle environment coupling system. Full article

Basketball requires intense movements like jumping and sudden changes in direction, increasing the risk of slips and falls due to poor shoe–court traction. Therefore, a significant demand is for good traction performance in basketball shoes, particularly in the heel region on different court surfaces, to prevent slipping. This study examined the traction performance of fifteen common basketball shoe designs that were considered and developed using thermoplastic polyurethane to assess the available coefficient of friction (ACOF) on popular floorings (hardwood, synthetic, and polyurethane) under dry and wet conditions using a robotic slip tester. Results indicate that the hardwood flooring provided better traction, followed by the synthetic flooring, while the polyurethane flooring showed reduced friction. The study also examined the traction with apparent contact areas. Shoes with herringbone and circular tread patterns demonstrated the highest traction on all flooring in dry conditions. This research is anticipated to help basketball shoemakers choose safer shoes for player safety and performance, providing a foundation for future research on shoe flooring interaction in basketball. Full article

Localization is one of the essential problems in the Internet of Things (IoT). Dynamic changes in the radio environment may lead to poor localization accuracy or discontinuous localization in non-line-of-sight (NLOS) scenarios. To address this problem, this paper proposes a localization enhancement method based on direct-path identification and tracking. More specifically, the proposed method significantly reduces the range error and localization error by quickly identifying the line-of-sight (LOS) to NLOS transition and effectively tracking the direct path. In a large testing hall, localization experiments based on the ultra-wideband (UWB) signal have been carried out. Experimental results show that the proposed method achieves a root mean square localization error of less than 0.3 m along the user equipment (UE) movement trajectory with serious NLOS propagation conditions. Compared with conventional methods, the proposed method significantly improves localization accuracy while ensuring continuous localization. Full article

During the process of flexible aerial refueling, the flexible structure of the hose drogue assembly is affected by internal and external interference, such as docking maneuvering, deformation of the hose, attitude changes, and body vibrations, causing the hose to swing and the whipping phenomenon, which greatly limits the success rate and safety of aerial refueling operations. Based on a 2.4 m transonic wind tunnel, high-speed wind tunnel test technology of a flexible aerial refueling hose–drogue system was established to carry out experimental research on the coupling characteristics of aerodynamics and multi-body dynamics. Based on the aid of Videogrammetry Model Deformation (VMD), high-speed photography, dynamic balance, and other wind tunnel test technologies, the dynamic characteristics of the hose–drogue system in a high-speed airflow and during the approach of the receiver are obtained. Adopting flexible multi-body dynamics, a dynamic system of the tanker, hose, drogue, and receiver is modeled. The cable/beam model is based on an arbitrary Lagrange–Euler method, and the absolute node coordinate method is used to describe the deformation, movement, and length variation in the hose during both winding and unwinding. The aerodynamic forces of the tanker, receiver, hose, and drogue are modeled, reflecting the coupling influence of movement of the tanker and receiver, the deformation of the hose and drogue, and the aerodynamic forces on each other. The tests show that during the approach of the receiver (distance from 1000 mm to 20 mm), the sinking amount of the drogue increases by 31 mm; due to the offset of the receiver probe, the drogue moves sideways from the symmetric plane of the receiver. Meanwhile, the oscillation magnitude of the drogue increases (from 33 to 48 and from 48 to 80 in spanwise and longitudinal directions, respectively). The simulation results show that the shear force induced by the oscillation of the hose and the propagation velocity of both the longitudinal and shear waves are affected by the hose stiffness and Mach number. The results presented in this work can be of great reference to further increase the safety of aerial refueling. Full article

Background: Soccer performance is largely dependent on high-intensity, unilateral actions such as sprints, jumps, and changes of direction. These demands can lead to strength and power differences between limbs, highlighting the importance of individualised assessment in professional players. Rotational inertial devices offer a valuable method to evaluate and train these mechanical variables separately for each leg. The aim of this study was twofold: (a) to characterise the mechanical variables derived from several lower-body strength exercises performed on rotational inertial devices, all targeting the same muscle group; and (b) to compare the mechanical variables between the dominant and non-dominant leg for each exercise. Methods: Twenty-six male professional soccer players (age = 26.3 ± 5.1 years; height = 182.3 ± 0.6 cm; weight = 75.9 ± 5.9 kg; body mass index = 22.8 ± 1.1 kg/m²; fat mass percentage = 9.1 ± 0.6%; fat-free mass = 68.8 ± 5.3 kg), all belonging to the same professional Belgian team, voluntarily participated in this study. The players completed a single assessment session consisting of six unilateral exercises (i.e., quadriceps hip, hamstring knee, adductor, quadriceps knee, hamstring hip, and abductor). For each exercise, they performed two sets of eight repetitions with each leg (i.e., dominant and non-dominant) in a randomised order. Results: The quadriceps hip exercise resulted in higher mechanical values compared to the quadriceps knee exercise in both limbs (p < 0.004). Similarly, the hamstring hip exercise produced greater values across all variables and limbs (p < 0.004), except for peak force, where the hamstring knee exercise exhibited higher values (p < 0.004). The adductor exercise showed higher peak force values for the dominant limb (p < 0.004). The between-limb comparison revealed differences only in the abductor exercise (p < 0.004). Conclusions: These findings suggest the necessity of prioritising movement selection based on targeted outcomes, although it should be considered that the differences between limb differences are very limited. Full article

Background: The coordination between the upper and lower limbs is essential for athletic performance. However, the structural features that influence coordination difficulty remain insufficiently understood. Few studies have systematically analyzed how task components such as the directional congruence or rhythm structure affect inter-limb coordination. Objective: This study aimed to clarify the structural factors that influence the difficulty of upper–lower limb coordination tasks under rhythmic constraints and to explore the feasibility of applying such tasks in future coordination assessments. Methods: Eighty-six male high school baseball players performed six Rhythm Jump tasks combining fixed upper limb movements with varying lower limb patterns. The task performance was analyzed using three indices: full task success, partial success, and average successful series. One year later, a follow-up test involving 27 participants was conducted to evaluate the reproducibility and sensitivity to the performance change. Results: The task difficulty was significantly affected by structural features, including directional incongruence, upper limb static holding, and rhythmic asynchrony. The tasks that exhibited these features had lower success rates. Some tasks demonstrated moderate reproducibility and captured subtle longitudinal changes in the performance. Conclusions: The results highlight the key structural factors contributing to coordination difficulty and support the potential applicability of Rhythm Jump tasks as a basis for future assessment tools. Although further validation is necessary, this study provides foundational evidence for the development of practical methods for evaluating inter-limb coordination. Full article

Background: Prevention and clinical management of musculoskeletal injuries have historically focused on the assessment and training of modifiable physical factors, but perceptual decision-making has only recently been recognized as a potentially important capability. Immersive virtual reality (VR) systems can measure the speed, accuracy, and consistency of body movements corresponding to stimulus–response instructions for the completion of a forced-choice task. Methods: A cohort of 26 female college soccer players (age 19.5 ± 1.3 years) included 10 players who participated in a baseline assessment, 10 perceptual-response training (PRT) sessions, a post-training assessment that preceded the first soccer practice, and a post-season assessment. The remaining 16 players completed an assessment prior to the team’s first pre-season practice session, and a post-season assessment. The assessments and training sessions involved left- or right-directed neck rotation, arm reach, and step-lunge reactions to 40 presentations of different types of horizontally moving visual stimuli. The PRT program included 4 levels of difficulty created by changes in initial stimulus location, addition of distractor stimuli, and increased movement speed, with ≥90% response accuracy used as the criterion for training progression. Perceptual latency (PL) was defined as the time elapsed from stimulus appearance to initiation of neck rotation toward a peripheral virtual target. The speed–accuracy tradeoff was represented by Rate Correct per Second (RCS) of PL, and inconsistency across trials derived from their standard deviation for PL was represented by intra-individual variability (IIV). Perceptual Decision Efficiency (PDE) represented the ratio of RCS to IIV, which provided a single value representing speed, accuracy, and consistency. Statistical procedures included the bivariate correlation between RCS and IIV, dependent t-test comparisons of pre- and post-training metrics, repeated measures analysis of variance for group X session pre- to post-season comparisons, receiver operating characteristic analysis, and Kaplan–Meier time to injury event analysis. Results: Statistically significant (p < 0.05) results were found for pre- to post-training change, and pre-season to post-season group differences, for RCS, IIV, and PDE. An inverse logarithmic relationship was found between RCS and IIV (Spearman’s Rho = −0.795). The best discriminator between injured and non-injured statuses was PDE ≤ 21.6 (93% Sensitivity; 42% Specificity; OR = 9.29). Conclusions: The 10-session PRT program produced significant improvement in perceptual decision-making that appears to provide a transfer benefit, as the PDE metric provided good prospective prediction of musculoskeletal injury. Full article

Aiming at the problem that the whole row of reciprocating seedling picking mechanism is prone to inertial impacts during operation due to its excessive mass, causing seedling damage and positioning errors, this study builds a motion control system with a PLC controller as the core and proposes a composite motion control strategy based on planned S-curve acceleration and deceleration and fuzzy PID to achieve rapid response, precise positioning, and smooth operation of the seedling picking mechanism. By establishing the objective function and constraint conditions and taking into account the dynamic change of the seedling picking displacement, the S-curve acceleration and deceleration control algorithm is planned in six and seven stages to meet the requirements of a smooth transition of the speed and continuous change of the acceleration curve of the seedling picking mechanism during movement. A fuzzy PID positioning control system is designed, the control system transfer function is constructed, and fuzzy rules are formulated to dynamically compensate for the error and its rate of change to meet the requirements of fast response and no overshoot oscillation of the positioning control system. The speed and acceleration of the seedling picking mechanism under the six-segment and seven-segment S-curve acceleration and deceleration motion control conditions were simulated using MATLAB2024a simulation software and compared with the trapezoidal acceleration and deceleration motion control. The planned S-curve acceleration and deceleration control algorithm has a more stable control effect on the seedling picking mechanism when it operates under the conditions of the dynamic change of the displacement, and it meets the design requirements of seedling picking efficiency. The positioning control system was modeled and simulated using the Simulink simulation platform. When KP = 15, KI = 3, and KD = 1, the whole-row seedling picking control system ran stably, responded quickly, and had no overshoot. Compared with the PID control system with fixed parameters, the fuzzy PID control system reduced the time consumption in the rising stage by 24.5% and shortened the overall stabilization process by 17.6%. The zero overshoot characteristic was ensured, and the response speed was faster. When a disturbance signal is added, the overshoot of the fuzzy PID control system is reduced by 2.4%, and the response speed is increased by 6.8% compared with the fixed-parameter PID control system. The dynamic response rate and anti-disturbance performance are better than those of the fixed-parameter PID control system. A bench comparison test was carried out. The results showed that the S-curve acceleration and deceleration motion control algorithm reduced the average mass loss rate of seedlings by 46.19% compared with the trapezoidal acceleration and deceleration motion control algorithm, and the seedling picking efficiency met the design requirements. Fuzzy PID positioning control was used, and the maximum displacement error of the end effector during seedling picking was −1.4 mm, and the average relative error rate was 0.22%, which met the positioning accuracy requirements of the end effector in the X-axis direction and verified the stability and accuracy of the designed control system. The designed control system was tested in the field, and the average comprehensive success rate of seedling picking and throwing reached 96.2%, which verified the feasibility and practicality of the control system. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder leading to movement impairment, cognitive decline, and psychiatric symptoms. Key manifestations of PD include bradykinesia (the slowness of movement), changes in voice or speech, and gait disturbances. The quantification of neurological disorders through voice analysis has emerged as a rapidly expanding research domain, offering the potential for non-invasive and large-scale monitoring. This review explores existing research on the application of machine learning (ML) in speech, voice, and language processing for the diagnosis of PD. It comprehensively analyzes current methodologies, highlights key findings and their associated limitations, and proposes strategies to address existing challenges. A systematic review was conducted following PRISMA guidelines. We searched four databases: PubMed, Web of Science, Scopus, and IEEE Xplore. The primary focus was on the diagnosis, detection, or identification of PD through voice, speech, and language characteristics. We included 34 studies that used ML techniques to detect or classify PD based on vocal features. The most used approaches involved free speech and reading-speech tasks. In addition to widely used feature extraction toolkits, several studies implemented custom-built feature sets. Although nearly all studies reported high classification performance, significant limitations were identified, including challenges in comparability and incomplete integration with clinical applications. Emerging trends in this field include the collection of real-world, everyday speech data to facilitate longitudinal tracking and capture participants’ natural behaviors. Another promising direction involves the incorporation of additional modalities alongside voice analysis, which may enhance both analytical performance and clinical applicability. Further research is required to determine optimal methodologies for leveraging speech and voice changes as early biomarkers of PD, thereby enhancing early detection and informing clinical intervention strategies. Full article

Markerless motion capture (MMC) offers a non-invasive method for monitoring external load in sports where wearable devices are restricted; however, its validity in 3x3 basketball contexts remains unverified. The viability and measurement precision of a multi-camera RTMPose-based MMC system for single-player tasks in 3x3 basketball performance monitoring were evaluated in this study. Recorded on a standard half-court, eight cameras (60 fps) captured ten collegiate athletes executing basketball-specific activities including linear sprints, curved runs, T-tests, and vertical jumps. The 3D coordinates of hip and ankle keypoints were reconstructed from multiple synchronized camera views using Direct Linear Transformation (DLT), from which horizontal displacement and average speed were derived. These values were validated using tape-measure distance and time–motion analysis. The MMC system demonstrated high accuracy, with coefficients of variation (CVs) below 5%, mean bias under 3.5%, and standard error of estimate (SEE) below 3% across most tasks. Speed estimates revealed great consistency with time–motion analysis (ICC = 0.97–1.00; standardized change in mean [SCM] varied from trivial to small). The Bland–Altman graphs verified no proportional error and little bias. These results confirm the MMC system as a consistent, non-invasive method for gathering movement data in outdoor basketball environments. Future studies should assess the system’s performance during live competitive play with several athletes and occlusions and compare it to a laboratory-grade motion capture system. Full article

Objective: This study examined the effects of a short-duration plyometric training program during physical education on neuromuscular ballistic performance in youth. Methods: Thirty-two students were assigned to a control group (CG; n = 16; age: 16.76 ± 0.72 years; height: 1.66 ± 0.09 m; body mass: 61.38 ± 6.07 kg) or an experimental group (EG; n = 16; age: 16.56 ± 0.62 years; height: 1.69 ± 0.09 m; body mass: 61.90 ± 7.83 kg). Both groups completed pre- and post-intervention Countermovement Jump (CMJ) tests using force plates. Over a four-week period, the EG completed eight sessions. Both the EG and the CG participated in 40 min sessions incorporating speed games, directional changes, and agility exercises. Paired t-tests and Cohen’s d were used for analysis. Results: The EG showed significant improvements in jump height (p = 0.006, ES = 0.83), jump momentum (p = 0.008, ES = 0.80), and take-off velocity (p = 0.003, ES = 0.93), with a decrease in peak propulsive power (p = 0.01, ES = 0.77). In contrast, the CG exhibited declines in multiple metrics, including jump height, jump momentum, and take-off velocity. Conclusions: These findings suggest that integrating plyometric training into physical education classes can effectively enhance neuromuscular performance in youth. Implementing structured training protocols within school programs may optimize strength, power, and movement efficiency, benefiting long-term athletic development. Full article

Unlike traditional vision-based camera tracking, human indoor localization and activity trajectory recognition also employ other methods such as infrared tracking, acoustic localization, and locators. These methods have significant environmental limitations or dependency on specialized equipment. Currently, WiFi-based human sensing is a novel and important method for human activity recognition. However, most WiFi-based activity recognition methods have limitations, such as using WiFi fingerprints to identify human activities. They either require extensive sample collection and training, are constrained by a fixed environmental layout, or rely on the precise positioning of transmitters (TXs) and receivers (RXs) within the space. If the positions are uncertain, or change, the sensing performance becomes unstable. To address the dependency of current WiFi indoor human activity trajectory reconstruction on the TX-RX position, we propose WiPIHT, a stable system for tracking indoor human activity trajectories using a small number of commercial WiFi devices. This system does not require additional hardware to be carried or locators to be attached, enabling passive, real-time, and accurate tracking and trajectory reconstruction of indoor human activities. WiPIHT is based on an innovative CSI channel analysis method, analyzing its autocorrelation function to extract location-independent real-time movement speed features of the human body. It also incorporates Fresnel zone and motion velocity direction decomposition to extract movement direction change patterns independent of the relative position between the TX-RX and the human body. By combining real-time speed and direction curve features, the system derives the shape of the human movement trajectory. Experiments demonstrate that, compared to existing methods, our system can accurately reconstruct activity trajectory shapes even without knowing the initial positions of the TX or the human body. Additionally, our system shows significant advantages in tracking accuracy, real-time performance, equipment, and cost. Full article

Research on Virtual Reality (VR) interfaces for distant object interaction has been carried out to improve user experience. Since hand-only interfaces and gaze-only interfaces have limitations such as physical fatigue or restricted usage, VR interaction interfaces using both gaze and hand input have been proposed. However, current gaze + hand interfaces still have restrictions such as difficulty in translating along the gaze ray direction, using less realistic methods, or limited rotation support. This study aims to design a new distant object interaction technique that supports hand-based interaction with high freedom of object interaction in immersive VR. In this study, we developed GazeHand2, a hand-based object interaction technique, which features a new depth control that enables free object manipulation in VR. Building on the strength of the original GazeHand, GazeHand2 can control the change rate of the gaze depth by using the relative position of the hand, allowing users to translate the object to any position. To validate our design, we conducted a user study on object manipulation, which compares it with other gaze + hand interfaces (Gaze+Pinch and ImplicitGaze). Result showed that, compared to other conditions, GazeHand2 reduced 39.3% to 54.3% of hand movements and 27.8% to 47.1% of head movements under 3 m and 5 m tasks. It also significantly increased overall user experiences (0.69 to 1.12 pt higher than Gaze+Pinch and 1.18 to 1.62 pt higher than ImplicitGaze). Furthermore, over half of the participants preferred GazeHand2 because it supports convenient and efficient object translation and hand-based realistic object manipulation. We concluded that GazeHand2 can support simple and effective distant object interaction with reduced physical fatigue and higher user experiences compared to other interfaces in immersive VR. We suggested future designs to improve interaction accuracy and user convenience for future works. Full article

A maritime mobile ad hoc network (M-MANET) is an essential part of the maritime communication network and plays a key role in many maritime scenarios. However, the topology of M-MANET dynamically changes with the movement of vessels, which leads to unstable link states and poses the risk of data transmission interruption. In this paper, a mobility model for small unmanned surface vessels based on smooth Gaussian semi-Markovian and a trajectory prediction method for large vessels based on a bi-directional long short-term memory network are proposed to better simulate the nodes’ movement in the M-MANET. Then, a link available based routing metric is proposed for M-MANET scenarios, which incorporates factors of mobility model and vessel trajectory. Experiments demonstrate that compared with the benchmark methods, the proposed mobility model depicts the movement characteristics of vessels more accurately, the proposed trajectory prediction method achieves higher prediction accuracy and stability, the proposed routing metric scheme has a reduction of 14.59% in end-to-end delay, a 1.54% increase in packet delivery fraction, and a 4.43% increase in network throughput on average. Full article

Progressive global aging has increased the number of elderly individuals living alone. The consequent rise in fall accidents has worsened physical injuries, reduced the quality of life, and increased medical expenses. Existing wearable fall-detection devices may cause discomfort, and camera-based systems raise privacy concerns. Here, we propose a non-contact fall-detection system that integrates 4D imaging radar sensors with artificial intelligence (AI) technology to detect falls through real-time monitoring and visualization using a web-based dashboard and Unity engine-based avatar, along with immediate alerts. The system eliminates the need for uncomfortable wearable devices and mitigates the privacy issues associated with cameras. The radar sensors generate Point Cloud data (the spatial coordinates, velocity, Doppler power, and time), which allow analysis of the body position and movement. A CNN model classifies postures into standing, sitting, and lying, while changes in the speed and position distinguish falling actions from lying-down actions. The Point Cloud data were normalized and organized using zero padding and k-means clustering to improve the learning efficiency. The model achieved 98.66% accuracy in posture classification and 95% in fall detection. This study demonstrates the effectiveness of the proposed fall detection approach and suggests future directions in multi-sensor integration for indoor applications. Full article