Search Results (361)

Large-sized components with numerous small key local features are essential in advanced manufacturing. Achieving high-precision quality control necessitates accurate and highly efficient three-dimensional (3D) measurement techniques. A flexible measurement system integrating a fringe-projection-based 3D scanner with an industrial robot is developed to enable the rapid measurement of large object surfaces. To enhance overall measurement accuracy, we propose an enhanced calibration method utilizing a multidimensional ball-based calibrator to simultaneously calibrate for hand-eye transformation and robot kinematic parameters. Firstly, a preliminary hand-eye calibration method is introduced to compensate for measurement errors at observation points, leveraging geometric-constraint-based optimization and a virtual single point derived via the barycentric calculation method. Subsequently, a distance-constrained calibration method is proposed to jointly estimate the hand-eye transformation and robot kinematic parameters, wherein a distance error model is constructed to link parameter errors with the measured deviations of a virtual single point. Finally, calibration and validation experiments were carried out, and the results indicate that the maximum and average measurement errors were reduced from 1.053 mm and 0.814 mm to 0.421 mm and 0.373 mm, respectively, thereby confirming the effectiveness of the proposed method. Full article

Motion analysis can be useful for multiplanar analysis of hand kinematics. The carpometacarpal (CMC) joint has been traditionally difficult to capture with surface-based motion analysis but is the most commonly arthritic joint of the hand and is of particular clinical interest. Traditional 3D motion capture of the CMC joint using multiple cameras and reflective markers and manual goniometer measurement has been challenging to integrate into clinical workflow. We therefore propose a markerless single-camera artificial intelligence (AI)-assisted motion capture method to provide real-time estimation of clinically relevant parameters. Our study enrolled five healthy subjects, two male and three female. Fourteen clinical parameters were extracted from thumb interphalangeal (IP), metacarpal phalangeal (MP), and CMC joint motions using manual goniometry and live motion capture with the Google AI MediaPipe Hands landmarker model. Motion capture measurements were assessed for accuracy, precision, and correlation with manual goniometry. Motion capture demonstrated sufficient accuracy in 11 and precision in all 14 parameters, with mean error of −2.13 ± 2.81° (95% confidence interval [CI]: −5.31, 1.05). Strong agreement was observed between both modalities across all subjects, with a combined Pearson correlation coefficient of 0.97 (p < 0.001) and an intraclass correlation coefficient of 0.97 (p < 0.001). The results suggest AI-assisted live motion capture can be an accurate and practical thumb assessment tool, particularly in virtual patient encounters, for enhanced range of motion (ROM) analysis. Full article

This paper presents the development of a fuzzy-PID control able to adapt to several robot–patient interaction modes by monitoring patient evolution during the rehabilitation procedure. This control system is designed to provide targeted rehabilitation therapy through three interaction modes: passive; active–assistive; and resistive. By integrating a fuzzy inference system into the classical PID architecture, the FPID controller dynamically adjusts control gains in response to tracking error and patient effort. The simulation results indicate that, in passive mode, the FPID controller achieves a 32% lower RMSE, reduced overshoot, and a faster settling time compared to the conventional PID. In the active–assistive mode, the FPID demonstrates enhanced responsiveness and reduced error lag when tracking a sinusoidal reference, while in resistive mode, it more effectively compensates for imposed load disturbances. A rehabilitation scenario simulating repeated motion cycles on a healthy subject further confirms that the FPID controller consistently produces a lower overall RMSE and variability. Full article

Background: Serious videogames have already demonstrated their positive impact on rehabilitation and of particular interest is the virtual reality (VR) technology. This immersive technology has been used in this study to create a neuroaesthetic experience based on the Michelangelo effect for the rehabilitation of patients with spinal cord injury. The aim of this study was to test the usability of a system for virtual art therapy and its capacity to assess patients’ deficits performances. Methods: A VR headset was worn by the participants who experienced a painting simulation of famous artworks (artistic stimuli) against a coloring canvas (non-artistic stimuli). The trajectories of the hand were studied to obtain different kinematic and spectral parameters to evaluate the user performances. A total of 13 healthy subjects and 13 patients with spinal cord injury participated in this study. Results: Significative differences were obtained for most of the parameters between the two groups, except for the normalized jerk and energy of the spectrum. Analysis in the frequency domain showed that both groups preferred horizontal movements for painting the canvas. The NASA and USEQ scores reported a comfortable and user-friendly system according to the patients’ point of view. Conclusions: The system can be a usable tool, the rehabilitative efficacy of which should be tested in patients with spinal cord injury. The kinematic and spectral parameters would allow for the evaluation of the performances alongside the clinical scales, distinguish pathological and physiological performances. Full article

The advent of mixed reality (MR) systems has revolutionized human–computer interactions by seamlessly integrating virtual elements with the real world. Devices like the HoloLens 2 (HL2) enable intuitive, hands-free interactions through advanced hand-tracking technology, making them valuable in fields such as education, healthcare, engineering, and training simulations. However, despite the growing adoption of MR, there is a noticeable lack of comprehensive comparisons between the hand-tracking accuracy of the HL2 and high-precision benchmarks like motion capture systems. Such evaluations are essential to assess the reliability of MR interactions, identify potential tracking limitations, and improve the overall precision of hand-based input in immersive applications. This study aims to assess the accuracy of HL2 in tracking hand position and measuring kinematic hand parameters, including joint angles and lateral pinch span (distance between thumb and index fingertips), using its tracking data. To achieve this, the Vicon motion capture system (VM) was used as a gold-standard reference. Three tasks were designed: (1) finger tracing of a 2D pattern in 3D space, (2) grasping various common objects, and (3) lateral pinching of objects with varying sizes. Task 1 tests fingertip tracking, Task 2 evaluates joint angle accuracy, and Task 3 examines the accuracy of pinch span measurement. In all tasks, HL2 and VM simultaneously recorded hand positions and movements. The data captured in Task 1 were analyzed to evaluate HL2’s hand-tracking capabilities against VM. Finger rotation angles from Task 2 and lateral pinch span from Task 3 were then used to assess HL2’s accuracy compared to VM. The results indicate that the HL2 exhibits millimeter-level errors compared to Vicon’s tracking system in Task 1, spanning in a range from 2 mm to 4 mm, suggesting that HL2’s hand-tracking system demonstrates good accuracy. Additionally, the reconstructed grasping positions in Task 2 from both systems show a strong correlation and an average error of 5°, while in Task 3, the accuracy of the HL2 is comparable to that of VM, improving performance as the object thickness increases. Full article

Assistive technologies, particularly multi-fingered robotic hands (MFRHs), are critical for enhancing the quality of life for individuals with upper-limb disabilities. However, achieving precise and stable control of such systems remains a significant challenge. This study proposes an Improved Grey Wolf Optimization (IGWO)-tuned Linear Quadratic Regulator (LQR) to enhance the control performance of an MFRH. The MFRH was modeled using Denavit–Hartenberg kinematics and Euler–Lagrange dynamics, with micro-DC motors selected based on computed torque requirements. The LQR controller, optimized via IGWO to systematically determine weighting matrices, was benchmarked against PID and PID-PSO controllers under diverse input scenarios. For step input, the IGWO-LQR achieved a settling time of 0.018 s with zero overshoot for Joint 1, outperforming PID (settling time: 0.0721 s; overshoot: 6.58%) and PID-PSO (settling time: 0.042 s; overshoot: 2.1%). Similar improvements were observed across all joints, with Joint 3 recording an IAE of 0.001334 for IGWO-LQR versus 0.004695 for PID. Evaluations under square-wave, sine, and sigmoid inputs further validated the controller’s robustness, with IGWO-LQR consistently delivering minimal tracking errors and rapid stabilization. These results demonstrate that the IGWO-LQR framework significantly enhances precision and dynamic response. Full article

Background: Advanced sensor insoles and motion capture technology can significantly enhance the monitoring of rehabilitation progress for patients with distal tibial fractures. This study leverages the potential of these innovative tools to provide a more comprehensive assessment of a patient’s gait and weight-bearing capacity following surgical intervention, thereby offering the possibility of improved patient outcomes. Methods: A patient who underwent distal medial tibial plating surgery in August 2023 and subsequently required revision surgery due to implant failure, involving plate removal and the insertion of an intramedullary nail in December 2023, was meticulously monitored over a 12-week period. Initial assessments in November 2023 revealed pain upon full weight-bearing without crutches. Following the revision, precise weekly measurements were taken, starting two days after surgery, which instilled confidence in accurately tracking the patient’s progress from initial crutch-assisted walking to full recovery. The monitoring tools included insoles, hand pads for force absorption of the crutches, and a motion capture system. The patient was accompanied throughout all steps of his daily life. Objectives: The study aimed to evaluate the hypothesis that the approximation and formation of a healthy gait curve are decisive tools for monitoring healing. Specifically, it investigated whether cadence, imbalance factors, and ground reaction forces could be significant indicators of healing status and potential disorders. Results: The gait parameters, cadence, factor of imbalance ground reaction forces, and the temporal progression of kinematic parameters significantly correlate with the patient’s recovery trajectory. These metrics enable the early identification of deviations from expected healing patterns, facilitating timely interventions and underscoring the transformative potential of these technologies in patient care. Conclusions: Integrating sensor insoles and motion capture technology offers a promising approach for monitoring the recovery process in patients with distal tibial fractures. This method provides valuable insights into the patient’s healing status, potentially predicting and addressing healing disorders more effectively. Future studies are recommended to validate these findings in a larger cohort and explore the potential integration of these technologies into clinical practice. Full article

Virtual reality (VR) is a promising tool in spinal cord injury (SCI) rehabilitation, particularly through virtual adaptations of functional tests like the Box and Block test (BBT). However, a comprehensive dynamic comparison between real and virtual BBT is lacking. This study investigates the kinematic and electromyographic (EMG) differences between healthy individuals and SCI patients performing both real (RBBT) and virtual (VBBT) versions of the BBT. An electromagnetic motion-tracking system, an instrumented glove, and surface EMG electrodes were used to capture hand trajectories, joint angles, and forearm muscle activation. The analysis included cycle-averaged and temporal kinematic and EMG parameters. Our findings reveal that both groups showed increased trajectory length and velocity peaks during the VBBT, with more pronounced increases in SCI patients. Unlike healthy individuals, SCI patients also showed increased finger and thumb flexion during VBBT. Cycle-averaged EMG values were lower in healthy participants during VBBT, likely due to reduced motor demands and lack of real grasping. Conversely, SCI patients exhibited higher muscle activity, suggesting impaired coordination and compensatory overactivation. Healthy individuals showed consistent temporal kinematic synergies and muscle activation, whereas they were altered in SCI patients, especially during reaching. These findings highlight the need for rehabilitation strategies to improve motor control and feedback integration. Full article

Soft anthropomorphic robotic grippers are attractive because of their inherent compliance, allowing them to adapt to the shape of grasped objects and the overload protection needed for safe human–robot interaction or gripping delicate objects with sophisticated control. The anthropomorphic design allows the gripper to benefit from the biological evolution of the human hand to create a multi-functional robotic end effector. Entirely soft grippers could be more efficient because they yield under high loads. A trending solution is a hybrid gripper combining soft and rigid elements. This work describes a prototype of an anthropomorphic, underactuated five-finger gripper with a direct pneumatic drive from soft bending actuators and an integrated resistive tactile sensor array. It is a hybrid construction with soft robotic structures and rigid skeletal elements, which reinforce the body, focus the direction of the actuator’s movement, and make the finger joints follow the forward kinematics. The hand is equipped with a resistive tactile dielectric elastomer sensor array that directly triggers the hand’s actuation in the sense of reflexes. The hand can execute precision grips with two and three fingers, as well as lateral grip and strong grip types. The softness of the actuation allows the finger to adapt to the shape of the objects. Full article

We investigate the relativistic jet of the powerful radio-emitting blazar J1429+5406 at redshift $z=3.015$. Our understanding of jet kinematics in $z\ge 3$ quasars is still rather limited, based on a sample of less than about 50 objects. The blazar J1429+5406 was observed at a high angular resolution using the method of very long baseline interferometry over more than two decades, between 1994 and 2018. These observations were conducted at five radio frequencies, covering a wide range from $1.7$ to 15 GHz. The outer jet components at ∼20–40 milliarcsecond (mas) separations from the core do not show discernible apparent motion. On the other hand, three jet components within the central 10 mas region exhibit significant proper motion in the range of (0.045–0.16) mas year⁻¹, including one that is among the fastest-moving jet components at $z\ge 3$ known to date. Based on the proper motion of the innermost jet component and the measured brightness temperature of the core, we estimated the Doppler factor, the bulk Lorentz factor, and the inclination angle of the jet with respect to the line of sight. The core brightness temperature is at least $3.6\times {10}^{11}$ K, well exceeding the equipartition limit, indicating Doppler-boosted radio emission. The low jet inclination (≲5.4°) firmly places J1429+5406 into the blazar category. Full article

The analysis of the influence of microhotplate size on the convective heat exchange of gas sensors is presented. Usually, the role of convection in the heat exchange of gas sensors is not considered in thermal simulation models because of the complexity of the convection process. As a result, the contribution of this process to the overall heat loss of sensors remains without detailed analysis. We analyzed convection issues in two groups of gas sensors: semiconductor and thermocatalytic (calorimetric) sensors and, on the other hand, in the oxygen sensors of the thermomagnetic type. It is demonstrated that there is a critical size leading to the formation of convective heat exchange flow. Below this critical value, only thermal conductivity of ambient air, IR (infrared) radiation from the heated microhotplate surface, and thermal conductivity of the microhotplate-supporting elements should be considered as channels for heat dissipation by the microhotplate, and the contribution of free convection can be neglected. The expression for the critical size contains only fundamental constants of air, d_cr~$4·\sqrt[3]{\raisebox{1ex}{$\nu ·D$}\!\left/ \!\raisebox{-1ex}{$g$}\right.}$, where ν is the kinematic viscosity of air, D is the diffusion coefficient, and g is the acceleration of free fall, d_cr~0.5 cm. Therefore, if the size of the microhotplate d <<d_cr, the influence of convection heat exchange can be neglected. Similar results were obtained in the analysis of the behavior of thermal magnetic sensors of oxygen, which use paramagnetic properties of molecular oxygen for the determination of O₂ concentration. In this case, the critical size of the sensor is also of significance; if the size of the magnetic sensor is much below this value, the oxygen concentration value measured with such a device is independent of the orientation of the sensor element. The results of the simulation were compared with the measurement of heat loss in micromachined gas sensors. The optimal dimensions of the sensor microhotplate are given as a result of these simulations and measurements. Full article

We propose a novel geometry-constrained learning-based method for camera-in-hand visual servoing systems that eliminates the need for camera intrinsic parameters, depth information, and the robot’s kinematic model. Our method uses a cerebellar model articulation controller (CMAC) to execute online Jacobian estimation within the control framework. Specifically, we introduce a fixed-dimension, uniform-magnitude error function based on the projective homography matrix. The fixed-dimension error function ensures a constant Jacobian size regardless of the number of feature points, thereby reducing computational complexity. By not relying on individual feature points, the approach maintains robustness even when some features are occluded. The uniform magnitude of the error vector elements simplifies neural network input normalization, thereby enhancing online training efficiency. Furthermore, we incorporate geometric constraints between feature points (such as collinearity preservation) into the network update process, ensuring that model predictions conform to the fundamental principles of projective geometry and eliminating physically impossible control outputs. Experimental and simulation results demonstrate that our approach achieves superior robustness and faster learning rates compared to other model-free image-based visual servoing methods. Full article

The growing population of hand dysfunction patients necessitates advanced rehabilitation technologies. Current robotic solutions face limitations in motion compatibility and systematic design frameworks. This study develops a rigid–soft coupling rehabilitation robot integrating linkage mechanisms with soft components. A machine vision system captures natural grasping trajectories, analyzed through polynomial regression. Hierarchical constraint modeling and an improved artificial bee colony algorithm optimize linkage dimensions and control strategies, achieving enhanced human–robot kinematic matching. Finite element simulations using a Yeoh hyperelastic model refine soft component geometry for balance compliance and coordination. Prototype validation demonstrates high-precision trajectory tracking, grasping across 20–70 mm objects, and steady fingertip forces during training. Experimental results confirm the system’s ability to replicate physiological motion patterns and adapt to multiple rehabilitation scenarios. Full article

To address the limitations of single-chamber soft grippers, such as constant curvature, insufficient motion flexibility, and restricted fingertip movement, this study proposes a soft gripper inspired by the structure of the human hand. The designed soft gripper consists of three fingers, each comprising three soft joints and four phalanges. The air chambers in each joint are independently actuated, enabling flexible grasping by adjusting the joint air pressure. The constraint layer is composed of a composite material with a mass ratio of 5:1:0.75 of PDMS base, PDMS curing agent, and PTFE, which enhances the overall finger stiffness and fingertip load capacity. A nonlinear mathematical model is established to describe the relationship between the joint bending angle and actuation pressure based on the constant curvature assumption. Additionally, the kinematic model of the finger is developed using the D–H parameter method. Finite element simulations using ABAQUS analyze the effects of different joint pressures and phalange lengths on the grasping range, as well as the fingertip force under varying actuation pressures. Bending performance and fingertip force tests were conducted on the soft finger actuator, with the maximum fingertip force reaching 2.21 N. The experimental results show good agreement with theoretical and simulation results. Grasping experiments with variously sized fruits and everyday objects demonstrate that, compared to traditional single-chamber soft grippers, the proposed humanoid joint-inspired soft gripper significantly expands the grasping range and improves grasping force by four times, achieving a maximum grasp weight of 0.92 kg. These findings validate its superior grasping performance and potential for practical applications. Full article

Introduction: Additive manufacturing has emerged as a promising solution for improving the accessibility and affordability of upper limb prostheses. Despite the growing need, traditional prosthetic devices remain costly and often inaccessible, particularly in underserved regions. This review examines the current landscape of 3D-printed upper limb prostheses, focusing on their design, functionality, and cost-effectiveness. It aims to assess the potential of 3D-printing upper limb prostheses in addressing current accessibility barriers. Methods: A two-phase approach was used to analyze the literature on 3D-printed upper limb prostheses. The first phase involved a literature search using keywords related to 3D printing and upper limbs prostheses. The second phase included data collection from online platforms such as Enabling the Future, Thingiverse, and NIH 3D Print Exchange. Studies focusing on the design, fabrication, and clinical application of 3D-printed prostheses were included. The results were organized into categories based on design characteristics, kinematic features, and manufacturing specifications. Results: A total of 35 3D-printed upper limb prostheses were reviewed, with the majority being hand prostheses. Devices were categorized based on their range of motion, actuation mechanism, materials, cost, and assembly complexity. The e-NABLE open-source platform has played a significant role in the development and dissemination of these devices. Prostheses were classified into cost categories (low, moderate, and high), with 64% of models costing under USD 50. Most designs were rated as easy to moderate in terms of assembly, making them accessible for non-specialist users. Conclusions: Three-dimensional printing offers an effective, low-cost alternative to traditional prosthetic manufacturing. However, variability in design, a lack of standardized manufacturing protocols, and limited clinical validation remain challenges. Future efforts should focus on establishing standardized guidelines, improving design consistency, and validating the clinical effectiveness of 3D-printed prostheses to ensure their long-term viability as functional alternatives to traditional devices. Full article