Search Results (372)

Transcranial Magnetic Stimulation (TMS) is a non-invasive technique for neurological research and therapy, but its effectiveness depends on accurate and stable coil placement. Manual localization based on anatomical landmarks is time-consuming and operator-dependent, while state-of-the-art robotic and neuronavigation systems achieve high accuracy using optical tracking with head-mounted markers and infrared cameras, at the cost of increased system complexity and setup burden. This study presents a cost-effective, markerless robotic-assisted TMS system that combines a 3D depth camera and textile capacitive sensors to assist coil localization and contact control. Facial landmarks detected by the depth camera are used to estimate the motor cortex (C3) location without external tracking markers, while a dual textile-sensor suspension provides compliant “soft-landing” behavior, contact confirmation, and coil-tilt estimation. Experimental evaluation with five participants showed reliable C3 targeting with valid motor evoked potentials (MEPs) obtained in most trials after initial calibration, and tilt-verification experiments revealed that peak MEP amplitudes occurred near balanced sensor readings in 12 of 15 trials (80%). The system employs a collaborative robot designed in accordance with international human–robot interaction safety standards, including force-limited actuation and monitored stopping. These results suggest that the proposed approach can improve the accessibility, safety, and consistency of TMS procedures while avoiding the complexity of conventional optical tracking systems. Full article

Falls are a leading cause of bone fractures among the elderly, particularly hip fractures resulting from side falls. This research deals with the feasibility of application of shear-thickening fluids (STFs) to design self-protective wearable devices to rapidly respond to sudden impact due to falls. The device consists of a lightweight, flexible foam structure embedded with STF-filled compartments, which remain soft during normal movements but stiffen upon sudden impact, effectively dissipating energy and reducing force trans-mission to the bones. First, a foam-based sandwich panel filled with STF is fabricated and subjected to several falling scenarios through a ball drop test. The induced strain of the device with and without STF is measured using Fiber Bragg Grating (FBG) sensors. Then, the effect of localized STF is explored by fabricating a soft 3D-printed (TPU) sandwich panel filled with STF at selected cavities. It was observed that the application of STF reduces the induced strain by approximately 50% for the TPU skin device and 30% for the foam-based device. This adaptive response mechanism offers a balance between comfort and protection, ensuring wearability for daily use while significantly lowering fracture risks. The proposed solution aims to enhance fall-related injury prevention for the elderly, improving their quality of life and reducing healthcare burdens associated with fall-related fractures. Full article

Transparent conductive oxides (TCOs), such as indium tin oxide (ITO), are essential for flexible electronics; however, conventional vacuum-based deposition is costly and thermally aggressive for polymers. This study investigated the surface functionalization of PET substrates with ITO thin film-based forced hydrolysis as a low-cost, reproducible alternative. $\mathrm{S}\mathrm{n}{\mathrm{O}}_2$ nanoparticles were synthesized by forced hydrolysis at 180 °C for 3 h and 6 h, yielding crystalline nanoparticles with a cassiterite phase and an average crystallite size of 20.34 nm. The process showed high reproducibility, enabling consistent structural properties without complex equipment or high-temperature treatments. The $\mathrm{S}\mathrm{n}{\mathrm{O}}_2$ sample obtained at 3 h was incorporated into commercial ${\mathrm{I}\mathrm{n}}_2{\mathrm{O}}_3$ to form a mixed In–Sn–O oxide, which was subsequently deposited onto PET substrates by spin coating onto UV-activated PET. The resulting 1.1 µm ITO films demonstrated good adhesion (4B according to ASTM D3359), a low resistivity of 1.27 × 10⁻⁶ Ω·m, and an average optical transmittance of 80% in the visible range. Although their resistivity is higher than vacuum-processed films, this route provides a superior balance of mechanical robustness, featuring a hardness of (H) of 3.8 GPa and an elastic modulus (E) of 110 GPa. These results highlight forced hydrolysis as a reproducible route for producing ITO/PET thin films. The thickness was strategically optimized to act as a structural buffer, preventing crack propagation during bending. Forced hydrolysis-driven PET sheet functionalization is an effective route for producing durable ITO/PET electrodes that are suitable for flexible sensors and solar cells. Full article

Soft robotic grippers provide compliant and adaptive manipulation, but most existing designs address actuation speed, adaptability, modularity, or sensing individually rather than in combination. This paper presents an electro-actuated customizable stacked Fin Ray gripper that integrates these capabilities within a single design. The gripper employs a compact solenoid for fast grasping, multiple vertically stacked Fin Ray segments for improved 3D conformity, and interchangeable silicone or TPU fins that can be tuned for task-specific stiffness and geometry. In addition, a light-guided, vision-based sensing approach is introduced to capture deformation without embedded sensors. Experimental studies—including free-fall object capture and optical shape sensing—demonstrate rapid solenoid-driven actuation, adaptive grasping behavior, and clear visual detectability of fin deformation. Complementary simulations using Cosserat-rod modeling and bond-graph analysis characterize the deformation mechanics and force response. Overall, the proposed gripper provides a practical soft-robotic solution that combines speed, adaptability, modular construction, and straightforward sensing for diverse object-handling scenarios. Full article

The rising global demand for prosthetic limbs, driven by approximately 185,000 amputations annually in the United States, underscores the need for innovative and cost-efficient solutions. This study explores the integration of hybrid materials, advanced 3D printing techniques, and smart sensing technologies to enhance prosthetic finger production. A Taguchi-based design of experiments (DoE) approach using an L09 orthogonal array was employed to systematically evaluate the effects of infill density, infill pattern, and print speed on the tensile behavior of FDM-printed PLA components. Findings reveal that higher infill densities (90%) and hexagonal patterns significantly enhance yield strength, ultimate tensile strength, and stiffness. Additionally, the rheological properties of polydimethylsiloxane (PDMS) were optimized at various temperatures (30–70 °C), characterizing its viscosity, shear-thinning factors, and stress behaviors for 3D bioprinting of flexible sensors. Barium titanate (BaTiO₃) was incorporated into PDMS to fabricate a flexible tactile sensor, achieving reliable open-circuit voltage readings under applied forces. Structural and functional components of the finger prosthesis were fabricated using FDM, stereolithography (SLA), and extrusion-based bioprinting (EBP) and assembled into a functional prototype. This research demonstrates the feasibility of integrating hybrid materials and advanced printing methodologies to create cost-effective, high-performance prosthetic components with enhanced mechanical properties and embedded sensing capabilities. Full article

The center of pressure (CoP) is a key biomechanical indicator for assessing balance and fall risk; however, force plates, the gold standard for CoP measurement, are costly and impractical for widespread use. Low-cost alternatives such as inertial units or pressure sensors are limited by drift, sparse sensor coverage, and directional performance imbalances, with previous supervised learning approaches reporting ML-AP NRMSE differences of 3.2–4.7% using 1D time-series models on sparse sensor arrays. Therefore, we propose a tactile sensor-based CoP estimation system using deep learning models that can extract 2D spatial features from each pressure distribution image with CNN/ResNet encoders followed by a Bi-LSTM for temporal patterns. Using data from 23 healthy adults performing four balance protocols, we compared ResNet-Bi-LSTM and CNN-Bi-LSTM with baseline CNN-LSTM and Bi-LSTM models used in previous studies. Model performance was validated using leave-one-out cross-validation (LOOCV) and evaluated with RMSE, NRMSE, and R². The ResNet-Bi-LSTM with angular features achieved the best performance, with RMSE values of 18.63 ± 4.57 mm in the mediolateral (ML) direction and 17.65 ± 3.48 mm in the anteroposterior (AP) direction, while reducing the ML/AP NRMSE difference to 1.3% compared to 3.2–4.7% in previous studies. Under dynamic protocols, ResNet-Bi-LSTM maintained the lowest RMSE across models. These findings suggest that tactile sensor-based systems may provide a cost-effective alternative to force plates and hold potential for applications in gait analysis and real-time balance monitoring. Future work will validate clinical applicability in patient populations and explore real-time implementation. Full article

This article aims to describe a novel workflow designed for generating a new family of minimal surface-based lattice structures with improved performance in terms of material budget compared to the well-known cells like Gyroid and Schwartz. The implemented method is based on the iterative resolution of a dynamic model, where proper forces are applied to generate minimal surface lattices, considering the boundary conditions and the constraint configurations. The novelty of the approach is given by the ability to create a minimal surface without resolving the partial differential equation and without knowing the exact minimal surface generative function. The starting geometry used for the lattice generation is the hypercube, parametrized to create different lattice configurations. Creating five different starting geometries and two constraint configurations, ten different lattice cells were created. For the comparison, a representative parameter of the material budget has been introduced and used to define the two best cells. The material budget is crucial for particle accelerator components, sensors, and detectors. These cells have been compared with Gyroid and Schwartz of the same thickness and bounding box, highlighting improvements of a factor of 2.3 and 1.7, respectively, in terms of material budget. The same cells have also been 3D-printed and tested under compression, and the obtained force–displacement curves were compared with those from a finite element analysis, demonstrating good agreement in the elastic region. Full article

Objectives: Shoulder joint strength and muscle activation during overhead reaching are critical for ergonomic task design, rehabilitation, and exoskeleton support. The objective of this study was to characterize maximum shoulder torque and flexor muscle activation profiles across functional elevation angles in healthy adult males. Methods: A total of 14 healthy male participants performed maximum voluntary isometric contractions at eight arm elevation angles (90–160°, sagittal plane, and standing). Shoulder torque was measured using a calibrated force sensor and normalized to each participant’s overall maximum. Electromyography (EMG) was recorded from the anterior deltoid, medial deltoid, biceps brachii, and clavicular pectoralis major; EMG for the medial deltoid, biceps brachii, and pectoralis major was normalized to muscle-specific isometric MVCs, whereas the anterior deltoid was normalized to the peak value at 90° during the main task. All EMG signals were smoothed using a 0.5 s RMS-based moving average window. Linear regression was used to analyze the torque–angle relationship, and linear mixed-effects models were used to test EMG differences across angles. Summary statistics included mean ± SD, coefficient of variation, R², p-values (significance threshold: p < 0.05), Cohen’s d, and 95% confidence intervals where appropriate. Results: Maximum torque declined with elevation angle (y = −0.6317x + 157.21; R² = 0.99), from 77.2 Nm at 90° to 43.2 Nm at 160°, with normalized values from 99.6% to 55.3%. Medial deltoid activation increased significantly with elevation (p < 0.001, from 87.5 ± 19.9% at 90° to 109.4 ± 25.6% at 150°), while pectoralis major declined sharply (p < 0.001, from 68.9 ± 24.2% at 90° to 19.8 ± 5.6% at 160°). Anterior deltoid and biceps brachii activations were high and showed no systematic change with angle (p = 0.37 and 0.81, respectively), remaining within approximately 95–102% and 70–85% of their reference levels across 90–160°. Normalization reduced inter-participant variability, clarifying muscle-specific trends. Conclusions: This study provides preliminary biomechanical reference values for shoulder torque and muscle activation across elevation angles in healthy males under isometric standing conditions, confirming an inverse torque–angle relationship and distinct muscle activation strategies at higher positions. These findings may inform ergonomic assessment and exoskeleton design, while recognizing that generalization to dynamic tasks and other populations requires caution. Full article

Parkinson’s Disease (PD) is a neurodegenerative disorder in which gait abnormalities serve as key indicators of motor impairment and disease progression. Although wearable sensor-based gait analysis has advanced, existing methods still face challenges in modeling multi-sensor spatial relationships, extracting adaptive multi-scale temporal features, and effectively integrating time–frequency information. To address these issues, this paper proposes a multi-sensor gait neural network that integrates biomechanical priors with time–frequency collaborative learning for the automatic assessment of PD gait severity. The framework consists of three core modules: (1) BGS-GAT (Biomechanics-Guided Graph Attention Network), which constructs a sensor graph based on plantar anatomy and explicitly models inter-regional force dependencies via graph attention; (2) AMS-Inception1D (Adaptive Multi-Scale Inception-1D), which employs dilated convolutions and channel attention to extract multi-scale temporal features adaptively; and (3) TF-Branch (Time–Frequency Branch), which applies Real-valued Fast Fourier Transform (RFFT) and frequency-domain convolution to capture rhythmic and high-frequency components, enabling complementary time–frequency representation. Experiments on the PhysioNet multi-channel foot pressure dataset demonstrate that the proposed model achieves 0.930 in accuracy and 0.925 in F1-score for four-class severity classification, outperforming state-of-the-art deep learning models. Full article

Background/Objectives: To determine the optimal site preparation and placement protocols for immediate implant positioning in robot-assisted surgeries. Methods: In vitro models of immediate and healed extraction sockets were created using 3D printing. A robotic system was used for implant site preparation and implant placement. The implant surgeries were allocated into eight experimental groups using 12 printed models in total. Each model incorporated two implant sites, an immediate site (tooth 21) and a healed site (tooth 26), resulting in 24 implants overall. With 3 implants assigned to each group, the 24 implant placements were evenly distributed across the 8 groups. For each group, the lateral force experienced during surgery was recorded by the haptic sensor on the robotic arm, and implant positional deviations were assessed by superimposing post-surgical CBCT images with the virtual implant planning. Results: Healed sites showed significantly higher accuracy than immediate sites, with reduced platform and apical deviations (p < 0.001) and markedly lower lateral force experienced by drills. In fully guided procedures, thread tapping greatly improved accuracy in immediate sites but had limited benefit in healed sites. Compared with partially guided workflows, fully guided rCAIS markedly enhanced accuracy in immediate sites (≈0.8 mm reduction in platform/apical deviation, p < 0.001), while no meaningful differences were observed in healed sites. Fully guided protocols also reduced insertion force in healed sites. Conclusions: Immediate sites showed lower implant positional accuracy and experienced higher lateral forces during surgery than healed sites. In immediate sites, thread tapping and fully guided rCAIS improved placement accuracy. Full article

Additive manufacturing offers several advantages, such as rapid prototyping, cost-efficient production, and flexibility in constructing components. This work presents the design and fabrication of a strain sensor capable of generating electrical signals under applied mechanical loads, enabling potential failure prediction. The sensor was manufactured using the Fused Deposition Modeling 3D-printing process, combining acrylonitrile-styrene-acrylate as structural and protective layers with a conductive polylactic acid matrix containing carbon nanotubes as the sensing element. To assess its performance, the sensor was embedded within a Glass Fiber-Reinforced Polyester composite and subjected to bending tests. The results demonstrate a reliable sensing response, characterized by a measurable increase in electrical resistance under bending load. Moreover, the change in resistance increased with applied bending force, demonstrating the sensor’s feasibility for structural health monitoring applications. Full article

Background: The back kick is a key scoring technique in taekwondo, often exhibiting bilateral asymmetry in lower limb function. Understanding these differences is crucial for optimizing training and minimizing injury risk. Methods: This study recruited twelve elite taekwondo athletes to perform back kicks using both their dominant and non-dominant legs under standardized conditions. Kinematic, kinetic, and surface electromyographic data were synchronously collected using a 3D motion capture system, force plate, and sEMG sensors. Paired t-tests and effect sizes assessed bilateral differences. Results: During the leg-lifting phase (P1), attacking leg peak hip power was significantly greater on the non-dominant side (p < 0.01); knee flexion angle was greater on the dominant side (p < 0.01), yet peak knee power was higher on the non-dominant side (p < 0.01). Support leg knee flexion angle was greater on the dominant side (p < 0.01), while knee flexion torque was higher on the non-dominant side (p < 0.05); ankle extension moment (p < 0.05) and plantar flexion power (p < 0.01) favored the dominant side. In the kicking phase (P2), dominant knee power was significantly higher (p < 0.01). The biceps femoris on the non-dominant side showed significantly higher iEMG and RMS values (p < 0.05), and dominant striking speed was faster (p < 0.05). Conclusions: These findings confirm marked functional asymmetry, suggesting training should emphasize non-dominant leg development to improve performance and reduce injury risk. Full article

Minimally Invasive Surgery is often limited by the lack of tactile feedback. Indeed, surgeons have traditionally relied heavily on tactile feedback to estimate tissue stiffness - a critical factor in both diagnostics and treatment. With this in mind we present in this paper a flexible sensor foil, based on polymer optical waveguide. This sensor has been applied for real-time contact force measurement, material stiffness differentiation and surface texture reconstruction. Interrogated by a commercially available optoelectronic device, the sensor foil offers precise and reproducible feedback of contact forces up to 5 N, with a minimal detectable limit of 0.1 N. It also demonstrates distinct optical attenuation responses when indenting silicone samples of varying stiffnesses under controlled displacement. When integrated onto a 3D-printed module resembling an endoscopic camera and manipulated by a robotic arm, the sensor successfully generated spatial stiffness mapsof a phantom. Moreover, by sliding over structures with varying surface textures, the sensor foil was able to reconstruct surface profiles based on the light attenuation responses. The results demonstrate that the presented sensor foil possesses great potential for surgical applications by providing additional haptic information to surgeons. Full article

Cellular mechanical properties are critical indicators of cellular state and promising disease biomarkers. This study introduces a novel microhand system, featuring chopstick-like plate-shaped end-effectors, designed for stable and high-precision single-cell mechanical characterization. First, we automated the force sensor calibration to overcome the inefficiency and unreliability of conventional manual methods. To validate the system’s sensitivity, we precisely quantified the mechanical contributions of subcellular components, such as the actin cytoskeleton and chromatin, by measuring stiffness reductions after treatment with Cytochalasin D and Trichostatin A, respectively. Notably, when applied to a cellular model of Hutchinson–Gilford progeria syndrome, we successfully captured disease-induced mechanical alterations. A distinct population of high-stiffness cells was detected in progerin-overexpressing cells, a feature not observed in the control groups. Furthermore, by controlling the indentation speed and depth, the mechanical properties of the cytoplasm and nucleus could be distinctly evaluated. These results demonstrate that our microhand system is a highly sensitive and robust platform, capable of detecting subtle, disease-related changes and elucidating the contributions of specific subcellular structures to cell mechanics. Full article

The proliferation of wireless sensor networks in industrial Internet of Things (IIoT) applications demands sustainable power solutions that eliminate battery replacement requirements while maintaining operational reliability in varying vibration environments. This paper presents a frequency-tunable magnetoelectric (ME) energy harvester that addresses the fundamental challenge of frequency mismatch between ambient industrial vibrations and harvester resonance through position-dependent magnetic force manipulation. The proposed system employs a Terfenol-D/PMNT/Terfenol-D sandwich transducer mounted on a cantilever beam within an adjustable magnetic circuit, enabling continuous frequency tuning through air gap modification for different magnetic field configurations. A comprehensive theoretical framework incorporating position-dependent magnetic forces was developed to predict the system behavior. Additionally, Multi-walled carbon nanotube (MWCNT)-enhanced epoxy bonding layers with 2 wt.% concentration were analyzed and demonstrated six-fold power improvement over conventional epoxy. The experimental validation shows frequency tuning from 40 Hz to 65 Hz through air gap adjustment of only 1 mm, corresponds to a 62.5% tuning range. Further experimental investigation proves a ten-fold power output improvement up to 2 mW by employing a four-magnet circuit design compared to the two-magnet configuration through specific adjustment of the air gap width. Full article