Complex Motion Research Articles

Incompatible Geometry Regulation of Nanowire Assemblies Enabled Light-Driven Shape Morphing and Motions.

Photoresponsive shape-changing materials have significant applications in miniaturized smart robotics and biomedicine powered in a remote and wireless manner. Existing light-fuelled soft materials suffer from limited continuous shape manipulation and constrained mobility and locomotive modes. One promising solution is developing a hierarchical structure design approach to integrate rapid, reversible photoactive molecular alignment and mechanically incompatible geometry in a macroscopic system. Here, a nanowire assemblies-induced geometry engineering method is reported for the fabrication of silver nanowire-incorporated nematic liquid crystalline elastomers with prominent anisotropic structures at multi-length scales and incompatible elasticity that show sharp morphological transitions among the rings, helicoids, and spirals with diverse helical configurations. The engineered composite films can realize complex light-driven motions including rotating, rolling, and jumping with the controlled directionality and magnitude that are pre-encoded in their both molecular and macroscopic configurations. Owing to the great controllability of multimodal locomotion, a spiral robot can undertake task-specific configuration to climb up complex terrains. The complete regulatory relationship among molecular orientation, shape geometry, and light-driven motions is also established. This study may open an avenue for elaborate design and precise fabrication of novel shape-morphing materials for future applications in intelligent robotic systems.

Dynamic 3D Measurement Based on Camera-Pixel Mismatch Correction and Hilbert Transform

In three-dimensional (3D) measurement, the motion of objects inevitably introduces errors, posing significant challenges to high-precision 3D reconstruction. Most existing algorithms for compensating motion-induced phase errors are tailored for object motion along the camera’s principal axis (Z direction), limiting their applicability in real-world scenarios where objects often experience complex combined motions in the X/Y and Z directions. To address these challenges, we propose a universal motion error compensation algorithm that effectively corrects both pixel mismatch and phase-shift errors, ensuring accurate 3D measurements under dynamic conditions. The method involves two key steps: first, pixel mismatch errors in the camera subsystem are corrected using adjacent coarse 3D point cloud data, aligning the captured data with the actual spatial geometry. Subsequently, motion-induced phase errors, observed as sinusoidal waveforms with a frequency twice that of the projection fringe pattern, are eliminated by applying the Hilbert transform to shift the fringes by π/2. Unlike conventional approaches that address these errors separately, our method provides a systematic solution by simultaneously compensating for camera-pixel mismatch and phase-shift errors within the 3D coordinate space. This integrated approach enhances the reliability and precision of 3D reconstruction, particularly in scenarios with dynamic and multidirectional object motions. The algorithm has been experimentally validated, demonstrating its robustness and broad applicability in fields such as industrial inspection, biomedical imaging, and real-time robotics. By addressing longstanding challenges in dynamic 3D measurement, our method represents a significant advancement in achieving high-accuracy reconstructions under complex motion environments.

A biokinetic approach in primary knee osteoarthritis prevention and management-exploring movement profiles and kinetic chain interactions: Current concepts.

Knee osteoarthritis (OA) is a chronic disease characterized by increasing prevalence and significant physical, psychological, and economic burdens. Despite extensive research, the definition, risk factors, and effective cost-efficient treatments for knee OA remain unclear. This article aims to revisit primary knee OA, understanding its etiology, and focusing on prevention and individualized nonoperative treatment modalities. This study reviews various aspects of knee OA, including its global prevalence, economic impact, and current treatment strategies. It explores the role of mechanical loading pathways in the disease's onset, highlighting the importance of considering not only the knee but the entire kinetic chain in diagnosis and treatment. Also, it discusses knee anatomy and biomechanics during functional activities, emphasizing the role of neuromuscular control and the influence of proximal and distal joints on knee health. Current treatments focus mainly on symptom management, with limited success in disease prevention and curative interventions. This review underlines the importance of understanding the biomechanical risk factors contributing to knee OA and the necessity of individualized interventions based on biokinetic profile analysis. Knee OA management and prevention necessitate a paradigm shift from viewing it as a localized knee disease to recognizing related mechanical overloads of the human complex motion system. Identifying individual inductive elements is paramount for effective knee OA prevention, management, and rehabilitation. Future research should endeavor to identify movement profile subgroups to establish an early-stage prognosis and the impact of interventions for each group. LEVEL OF EVIDENCE V: Expert opinion based on nonsystematic review.

Development of a Rehabilitation Apparatus for Frozen Shoulder Enabling Total Motion of Shoulder Complex

This article describes an apparatus developed by the authors as a substitution for physical therapists regarding mechanical movements in the rehabilitation of frozen shoulder. In particular, the performance of this apparatus is improved in comparison with existing methods in terms of the following two major points: (1) realization of individual rehabilitation for the patient’s scapula by an innovative parallel–serial hybrid linkage design and supporting parts that can fix and move the patient’s scapula; and (2) the addition of a “teaching” and “playback” mode to enable the apparatus to record the motion of rehabilitation, allowing it to be customized for each patient by physical therapists and reproduce the recorded motion accurately, thus freeing physical therapists from repetitive rehabilitation routines. With the introduction of the whole system, experimental results are shown and discussed to verify and evaluate the performance of the developed apparatus.

A Carpometacarpal Thumb Tracking Device for Telemanipulation of a Robotic Thumb: Development, Prototyping, and Evaluation

Hand−tracking systems are widely employed for telemanipulating grippers with high degrees of freedom (DOFs) such as an anthropomorphic robotic hand (ARH). However, tracking human thumb motion is challenging due to the complex motion of the carpometacarpal (CMC) joint. Existing hand−tracking systems can track the motion of simple joints with one DOF, but most fail to track the motion of the CMC joint, or to do so, there is a need for expensive and intricately set up hardware systems. This research introduces and realizes an affordable and personalizable tracking device to capture the CMC joint Flexion/Extension and Abduction/Adduction motions. Tracked human thumb motion is mapped to a robot thumb in a hybrid approach: the proposed algorithm maps the CMC joint motion to the first two joints of the robot thumb, while joint mapping is established between the metacarpophalangeal and interphalangeal joints to the last two joints. When the tracking device is paired with a flex glove outfitted with bend sensors, the developed system provides the means to telemanipulate an ARH with a four-DOF thumb and one-DOF underactuated digits. A three-stage framework is proposed to telemanipulate the fully actuated robot thumb. The tracking device and framework were evaluated through a device operation and personalization test, as well as a framework verification test. Two volunteers successfully personalized, calibrated, and tested the device using the proposed mapping algorithm. One volunteer further evaluated the framework by performing hand poses and grasps, demonstrating effective control of the robot thumb for precision and power grasps in coordination with the other digits. The successful results support expanding the system and further evaluating it as a research platform for studying human–robot interaction in grasping tasks or in manufacturing, assistive, or medical domains.

Investigation into the Motion Characteristics and Impact Loads of Buoy Water Entry Under the Influence of Combined Waves and Currents

As a crucial component in marine monitoring, meteorological observation, and navigation systems, studying the motion characteristics and impact loads of buoy water entry is vital for their long-term stability and reliability. When deployed, buoys undergo a complex motion process, including the impact of entering the water and a stable floating stage. During the water entry impact phase, the motion characteristics and impact loads involve interactions between the buoy and the water, the trajectory of motion, and dynamic water pressure, among other factors. In this paper, the VOF model is used to calculate the buoy’s water entry motion characteristics, and then the STAR-CCM+&ABAQUS bidirectional fluid–structure interaction (FSI) method is used to calculate the water entry impact load of the buoy under different water surface conditions and different initial throwing conditions, considering the influence of the flow field on the structure and the influence of the structure deformation on the flow field. The study finds that under the influence of wave and current impacts, changes in wave height significantly affect the buoy’s heave motions. Under different parametric conditions, due to the specific direction of wave and current impacts, the buoy’s pitch amplitude is relatively more intense compared to its roll amplitude, yet both pitch and roll motions exhibit periodic patterns. The buoy’s pitch motion is sensitive to changes in the entry angle; even small changes in this angle result in significant differences in pitch motion. Additionally, the entry angle significantly impacts the peak vertical overload on the buoy. Instantaneous stress increases sharply at the moment of water entry, particularly at the joints between the crossplate and the upper and lower panels, and where the mast connects to the upper panel, creating peak stress concentrations. In these concentrated stress areas, as the entry speed and angle increase, the maximum equivalent stress peak at the monitoring points rises significantly.

UVC: An Unified Deep Video Compression Framework

Recently, many works have applied deep learning techniques to video compression tasks, achieving promising results and advancing the field of deep learning video compression (DLVC). However, the architecture design of existing DLVC is rigid and limited in terms of flexibility. Specifically, different networks must be designed for different scenarios, such as delay-constrained or non-delay-constrained scenarios. Frequent switching between networks would reduce the speed of modern deep learning platforms and increase maintenance costs. To address this problem, we propose a unified deep video compression (UVC) framework that can be freely switched to different application scenarios without changing the network architecture. Our proposed UVC framework is based on the explicit-compression and implicit-generation perspective, which contains two sub-networks: the explicit reference frame compression network (ERFCN) and the implicit reference frame generation network (IRFGN). The aim of ERFCN is to compress the current frame with the help of the reference frame. To improve the performance of ERFCN, we first introduce the Transformer in this network, which can fully remove the spatial redundancy of the input image and is beneficial for the following inter-prediction process. We also develop a novel long-range motion estimation module for inter-prediction to generate motion vectors based on global motion information between two frames, which can handle long-range complex motion relations. The aim of IRFGN is to capture the temporal relationship between forward and backward reconstructed frames and synthesize a high-quality implicit reference frame for the current frame. To achieve this, we design the split spatial-temporal attention and multi-scale prediction module. We conduct extensive experiments on three widely used video compression databases (HEVC, UVG, and MCL-JVC), and the results demonstrate the superiority of our approach over other related DLVC methods.

Dynamics of dual-orbit rotations of nanoparticles induced by spin–orbit coupling

Abstract Spin–orbit coupling (SOC) in tightly focused optical fields offers a powerful mechanism for manipulating the complex motion of particles. However, to date, such a mechanism has only been applied to the single-orbit motion for particles, while multi-orbital dynamics have not yet been experimentally demonstrated. Here, the theoretical and experimental realization of dual-orbit rotational dynamics of nanoparticles in a tightly focused circularly polarized Laguerre-Gaussian beam is reported. Analyses reveal that the dual-orbit rotation of nanoparticles originates from SOC in a tightly focused vortex beam, with the motion velocity and direction determined by the topological charge of the beam. Experimentally, the dual-orbit rotation of polystyrene nanoparticles was observed for the first time using an inverted optical tweezer. In addition, the rotation velocity showed a clear linear dependence on the topological charge of the incident beam. This work reveals the pivotal role of SOC in enabling precise dual-orbit control at the nanoscale, paving the way for applications in optical sorting, grinding and delivery of microparticles.

Wearable Pressure Sensor Based on Triboelectric Nanogenerator for Information Encoding, Gesture Recognition, and Wireless Real‐Time Robot Control

AbstractWearable sensor has attracted a broad interesting in application prospect of human‐machine interaction (HMI). However, most of sensors are assembled in the shape of gloves to accurately capture complex hand motion information, thereby seriously blocking the hand to complete complex tasks. Herein, a wearable pressure sensor based on drum‐structured triboelectric nanogenerator (DS‐TENG) is developed to capture subtle pressure signals for physiological signal detection, information encoding, gesture recognition, and wireless real‐time robot control. The DS‐TENG enables a limit of detection down to 3.9 Pa pressure, which can sensitively capture human micromotion signals of pulse, throat sounds, and wrist muscles contraction. Especially, combined with a microprocessor and Morse code, the DS‐TENG worn on wrist can detect single‐finger motion signals to translate into regular voltage signals, which is employed to encode information of 26 letters and subsequently decode into the corresponding letters. Furthermore, with an aid of machine learning, the DS‐TENG array (2 × 2) can successfully achieve gesture recognition with high accuracy of 92% to wirelessly perform real‐time robot control. Consequently, the wearable pressure sensor based on DS‐TENG can capture subtle pressure signals for information encoding and wireless real‐time robot control, which demonstrates extreme potential in the field of HMI and artificial intelligence.

An Imaging Method for Marine Targets in Corner Reflector Jamming Scenario Based on Time–Frequency Analysis and Modified Clean Technique

In the corner reflector jamming scenario, the ship target and the corner reflector array have different degrees of defocusing in the synthetic aperture radar (SAR) image due to their complex motions, which is unfavorable to the subsequent target recognition. In this manuscript, we propose an imaging method for marine targets based on time–frequency analysis with the modified Clean technique. Firstly, the motion models of the ship target and the corner reflector array are established, and the characteristics of their Doppler parameter distribution are analyzed. Then, the Chirp Rate–Quadratic Chirp Rate Distribution (CR-QCRD) algorithm is utilized to estimate the Doppler parameters. To address the challenges posed by the aggregated scattering points of the ship target and the overlapping Doppler histories of the corner reflector array, the Clean technique is modified by short-time Fourier transform (STFT) filtering and amplitude–phase distortion correction using fractional Fourier transform (FrFT) filtering. This modification aims to improve the accuracy and efficiency of extracting scattering point components. Thirdly, in response to the poor universality of the traditional Clean iterative termination condition, the kurtosis of the residual signal spectrum amplitude is adopted as the new iterative termination condition. Compared with the existing imaging methods, the proposed method can adapt to the different Doppler distribution characteristics of the ship target and the corner reflector array, thus realizing better robustness in obtaining a well-focused target image. Finally, simulation experiments verify the effectiveness of the algorithm.

A systematic review of the effectiveness of leaded glasses for ensuring safety among healthcare professionals in fluoroscopy.

Currently, there is an increase in procedures across various clinical specialties involving the use of ionising radiation. The primary objective of this systematic review is to analyse and compare the existing literature regarding the effectiveness of leaded glasses for healthcare professionals. Comprehensive literature searches were conducted for relevant studies published between 2018 and 2023 using the Scopus, PubMed, and Web of Science databases according to preferred reporting items for systematic reviews and meta-analyses (PRISMA) methodology. After the complete text screening, 11 articles were deemed suitable for inclusion in the review. Leaded glasses significantly reduce eye radiation exposure, with studies showing shielding effects ranging from 10 % to 88,9 %, depending on the configuration and thickness of the glasses. For instance, lightweight glasses achieved a shielding effect of 61.4 %, while thicker lead equivalents (≥0.5 mm) offered up to ninefold dose reductions. Studies also noted the importance of lateral shielding and ergonomic designs for optimal protection. Leaded glasses significantly reduce eye lens doses but are most effective when combined with other protective measures. Factors such as head orientation, procedural complexity, and operator movement influence their performance. The findings underscore the need for standardised guidelines on protective eyewear use and further research under real-world clinical conditions. It is essential to ensure the proper use of leaded glasses to minimize the risks of ionising radiation for healthcare professionals in fluoroscopy procedures.

Evolution of parsec-scale jet directions in active galaxies

Abstract We analyze the variability of the parsec-scale jet directions in active galactic nuclei (AGNs). Our analysis involves 317 AGNs at frequencies ranging from 2 to 43 GHz, and is made possible by developing an automatic jet direction measurement procedure. We find strong significant variations in a one quarter of these AGNs; the effect is likely ubiquitous, and not detected in the rest due to a limited sensitivity and observations epoch coverage. Apparent jet rotation speeds range from 0.21 deg yr−1 at 2 GHz to 1.04 deg yr−1 at 43 GHz. This strong frequency dependence indicates that the variability cannot be explained by jet components propagating ballistically without acceleration: more complex jet shapes or motion patterns are required. Still, we demonstrate that the apparent direction changes are predominantly caused by the jet nozzle rotations, and not by individual components propagating transversely to the jet. In this work, we focus on variability scales much longer than the times of observations, that is ≳ 50 years. Using our measurements, we bound potential periods to less than 1000 years in the source rest frame for 90% AGNs in the sample. These timescales constrain jet direction variation mechanisms, with the most likely explanations being the plasma instabilities, the precession caused by the accretion disk with density ∼r−1, and the orbital motion of binary systems.

Liquid Crystal Polycaprolactone Copolymer Elastomer With Low Autonomous Driving Temperature

ABSTRACTLiquid crystal elastomers (LCEs) are liquid crystal polymers with moderate crosslinking that exhibit elasticity in both their isotropic and liquid crystal states. These materials can be programmed through chemical design and geometric configuration to achieve autonomous actuation at specific temperatures. Typically, the autonomous actuation temperature of LCEs exceeds the phase transition temperature of their isotropic states, with most reported LCEs requiring temperatures above 100°C. Such high temperatures pose challenges for use in soft robotics due to increased energy consumption and limited operational flexibility. In this study, we introduce a small amount of polycaprolactone (PCL) into the main chain of LCEs, effectively lowering their phase transition temperature while maintaining over 90% of the reversible shrinkage strain characteristic of pure LCEs. By adjusting the PCL content, the number of twists, and the helix density, we successfully obtained an LCE‐PCL actuator with improved autonomous actuation performance at temperatures ranging from 45°C to 105°C. Moreover, by modulating the degree of torsion and the operating temperature, the LCE‐PCL autonomous actuator demonstrates the ability to perform complex motions, such as reversing and parking. This work offers new insights into the design and application of LCEs with reduced phase transition temperatures and enhanced self‐driving capabilities.

Distinct detection and discrimination sensitivities in visual processing of real versus unreal optic flow.

We examined the intricate mechanisms underlying visual processing of complex motion stimuli by measuring the detection sensitivity to contraction and expansion patterns and the discrimination sensitivityto the location of the center of motion (CoM) in various real and unreal optic flow stimuli. We conducted two experiments (N = 20 each) and compared responses to both "real" optic flow stimuli containing information about self-movement in a three-dimensional scene and "unreal" optic flow stimuli lacking such information. We found that detection sensitivity to contraction surpassed that to expansion patterns for unreal optic flow stimuli, whereas this trend was reversed for real optic flow stimuli. Furthermore, while discrimination sensitivity to the CoM location was not affected by stimulus duration for unreal optic flow stimuli, it showed a significant improvement when stimulus duration increased from 100 to 400 ms for real optic flow stimuli. These findings provide compelling evidence that the visual system employs distinct processing approaches for real versus unreal optic flow even when they are perfectly matched for two-dimensional global features and local motion signals. These differences reveal influences of self-movement in natural environments, enabling the visual system to uniquely process stimuli with significant survival implications.

A flexible piezoresistive three-dimensional strain sensor based on laser-induced graphene/nanosilver/MWCNTs for precise human all-range motion detection

Flexible piezoresistive strain sensors are crucial for monitoring human motion, but achieving the right balance between sensitivity and operating range has always been challenging. Additionally, the complexity of muscle movements across different body parts means that relying on sensors with limited dimensional sensing is insufficient. This paper presents a flexible piezoresistive three-dimensional strain sensor (FPTDSS) designed to address these challenges. The FPTDSS features a wide operating range capable of detecting various human movements and boasts a high sensitivity, with a maximum gauge factor of 20 479. It can capture strain information along both the X- and Y-axes, as well as small vibrations along the Z-axis, through its intrinsic stretching and vibration properties. The sensor's effectiveness comes from the synergy between laser-induced graphene, silver nanoparticles (a zero-dimensional nanomaterial), and multi-walled carbon nanotubes (a one-dimensional nanomaterial). The synergistic effect of nanomaterials with different dimensions enables the FPTDSS to perform three-dimensional strain sensing, allowing for accurate detection of a broad range of complex human motions without requiring intricate circuit designs or preparation processes. This approach moves beyond limited strain information to provide a comprehensive view of three-dimensional strain, making the sensor versatile for detecting everything from subtle pulse vibrations to significant joint movements.

Multi-Object Tracking with Predictive Information Fusion and Adaptive Measurement Noise

Multi-object tracking (MOT) aims to detect objects in video sequences and associate them across frames. Currently, the mainstream research direction regarding MOT is the tracking-by-detection (TBD) framework. Tracking results are highly sensitive to detection outputs, and challenges from object occlusion and complex motion present significant obstacles in the field of MOT. To reduce dependence on detection outputs, we propose a method that integrates predictive information to improve Non-Maximum Suppression (NMS). By applying secondary modulation to the suppression scores and dynamically adjusting the suppression threshold using tracking information, our method better retains candidate boxes for occluded objects. Furthermore, to track occluding and overlapping objects more effectively, we introduce an adaptive measurement noise method that adjusts the measurement noise to mitigate the impact of object occlusion or overlap on tracking accuracy. Additionally, we enhance the affinity matrix in the association algorithm by incorporating height information, thereby improving the stability of complex moving objects. Our method outperforms the baseline model ByteTrack on the DanceTrack dataset, increasing Higher Order Tracking Accuracy (HOTA), Multi-Object Tracking Accuracy (MOTA), and the ID F1 Score (IDF1) by 10.2%, 3.0%, and 4.8%, respectively.

Investigation of trochoidal paths in physics lessons

Abstract Using the example of trochoids it is shown how Bruner’s cognitive-psychological model of modes of representations is used to introduce the kinematics and its mathematical description of a complex motion in the introductory phase of physics studies. Enactive (experimental), iconic (simulation) and symbolic (equation) representations of the rolling motion of a wheel are combined to address the different types of learning to gradually introduce the formal description of trochoids.

Ultrahigh Resolution ISAR Imaging of a Target With Unknown and Complex Motion Using SA-NCS Algorithm

Ultrahigh Resolution ISAR Imaging of a Target With Unknown and Complex Motion Using SA-NCS Algorithm

TOPIC: A Parallel Association Paradigm for Multi-Object Tracking Under Complex Motions and Diverse Scenes

TOPIC: A Parallel Association Paradigm for Multi-Object Tracking Under Complex Motions and Diverse Scenes

Human in vivo talocrural contributions to ankle joint complex kinematics during walking, running, and hopping.

The human ankle joint complex, consisting of calcaneus, talus, and tibia, is often simplified as a single functional ankle joint, neglecting the motion of the talus. Understanding the individual contributions of the talus and calcaneus is crucial for comprehending ankle joint complex function in healthy populations, and alterations in function that may exist in clinical conditions. To achieve accurate bone kinematics, high-resolution biplanar videoradiography was used with participants engaged in walking and running (n=9) and hopping (n=9) with no overlap in participants. The rotation axes for the calcaneus and talus were analysed relative to the tibia over the ankle joint dorsi-/plantar flexion phases. Contributions of the talocrural joint to overall ankle joint complex function were measured by comparing the range of motion (talus relative to calcaneus). Most of the sagittal plane motion in the ankle joint complex (80%) occurred in the talocrural joint, with the subtalar joint contributing 20%. Rotation of the calcaneus about the tibia dominated frontal and transverse plane motion during hopping. Although surprisingly large ranges of talus motion were also observed in these planes (>5deg), indicating notable inter-subject variability and that the talocrural joint is not a simple hinge joint. The study highlights the importance of directly quantifying talus motion to understand ankle joint complex function. The results showed opposing talus and calcaneus movements for many participants during different locomotor tasks, which may influence the magnitude and distribution of subtalar joint loading. In addition, the large out-of-sagittal plane movements and inter-subject variability in talus and calcaneus motion may further emphasize the need for personalised models to investigate treatments for ankle pathologies.