Search Results (158)

A 16-channel dual-sided flexible electrode based on a polyimide substrate was designed and fabricated using micro-electromechanical system (MEMS) technology. The electrode exhibited an average impedance of 5.9 kΩ at 1 kHz and a charge storage capacity (CSC) of 10.63 mC/cm². Concurrently, a three-dimensional finite element model incorporating electrical stimulation and micromotion-induced damage was established. The simulation results demonstrated that the implantation trauma caused by the bilateral electrode was significantly lower compared with silicon-based and cylindrical electrodes, while also enabling directional stimulation. Furthermore, leveraging the design of experiments (DOE) methodology, a multivariate regression model was developed to investigate the influence of key stimulation parameters—namely, current amplitude, frequency, and pulse width—on the volume of tissue activated (VTA). The results indicated that the regression model provided accurate predictions of VTA (R² = 0.912). Among the parameters, current amplitude and pulse width exerted a statistically significant influence on VTA size (p < 0.001), whereas the effect of frequency was comparatively minor (p = 0.387 > 0.05). This study presents the first successful fabrication and comprehensive dose–response analysis of a flexible bilateral DBS electrode. Its attributes of low implantation trauma, multi-channel capability, and directional stimulation offer a novel paradigm for precise neuromodulation. Additionally, the established stimulation parameter–VTA response model provides a robust theoretical foundation for optimizing therapeutic parameters in subsequent clinical applications. Full article

Wi-Fi sensing leverages variations in CSI (channel state information) to infer human activities in a contactless and low-cost manner, with growing applications in smart homes, healthcare, and security. While deep learning has advanced macro-motion sensing tasks, micro-motion sensing such as keypad stroke recognition remains underexplored due to subtle inter-class CSI variations and significant intra-class variance. These challenges make it difficult for existing deep learning models typically relying on fully connected MLPs to accurately recognize keypad inputs. To address the issue, we propose a novel approach that combines a discriminative feature extractor with a Kolmogorov–Arnold Network (KAN)-based classifier. The combined model is trained to reduce intra-class variability by clustering features around class-specific centers. The KAN classifier learns nonlinear spline functions to efficiently delineate the complex decision boundaries between different keypad inputs with fewer parameters. To validate our method, we collect a CSI dataset with low-cost Wi-Fi devices (ESP8266 and Raspberry Pi 4) in a real-world keypad sensing environment. Experimental results verify the effectiveness and practicality of our method for keypad input sensing applications in that it outperforms existing approaches in sensing accuracy while requiring fewer parameters. Full article

The two-stage proportional valve is a key control component in heavy-duty equipment, where its signal-flow characteristics critically influence operational performance. This study proposes an innovative flow characteristic regulation method using variable-gain feedback grooves. Unlike conventional throttling notch optimization, the core mechanism actively adjusts pilot–main valve mapping through feedback groove shape and area gain adjustments to achieve the desired flow curves. This approach avoids complex throttling notch issues while retaining the valve’s high dynamics and flow capacity. Mathematical modeling elucidated the underlying mechanism. Subsequently, trapezoidal and composite feedback grooves are designed and investigated via simulation. Finally, composite feedback groove spools tailored to construction machinery operating conditions are developed. Comparative experiments demonstrate the following: (1) Pilot–main mapping inversely correlates with area gain; increasing gain enhances micro-motion control, while decreasing gain boosts flow gain for rapid actuation. (2) This method does not significantly increase pressure loss or energy consumption (measured loss: 0.88 MPa). (3) The composite groove provides segmented characteristics; its micro-motion flow gain (2.04 L/min/0.1 V) is 61.9% lower than conventional valves, significantly improving fine control. (4) Adjusting groove area gain and transition point flexibly modifies flow gain and micro-motion zone length. This method offers a new approach for high-performance valve flow regulation. Full article

Achieving high-precision positioning operations in a small space was of great significance in aerospace, biomedical, and other fields. In order to obtain smaller displacements with higher accuracy, this paper focused on the design, optimization, and performance analysis of a two-stage reduction micro-drive mechanism. Using the principle of lever and the principle of balanced additional force, a two-stage reduction micro-motion mechanism without parasitic motion and non-motion directional force was designed, and the structure optimization of the mechanism was completed by employing the particle swarm algorithm. A finite element analysis was conducted to assess the strength, dynamics, and kinematic properties of the mechanism. Experimental methods were also employed to analyze its dynamic and kinematic properties. The analysis results demonstrated that the mechanism met the design requirements in terms of strength and dynamic properties, with a maximum error of 9.02% and a maximum kinematic error of 0.0267 μm. The achieved reduction ratio was 24.73:1. These results indicated that the mechanism possesses excellent strength and dynamic performance, a large reduction ratio, high motion accuracy, and good linearity. This paper contributes significantly to the advancement of research in precision mechanical motion and micro-drive mechanisms. Full article

Lead zirconate titanate (PZT) piezoelectric ceramics are widely used functional materials due to their strong and stable piezoelectric properties. A leveling method based on lead zirconate titanate piezoelectric ceramics is proposed for the high level of accuracy required in microelectromechanical fields such as aerospace, industrial robotics, biomedical, and photolithography. A leveling mechanism consisting of core components such as piezoelectric ceramic actuators and sensors is designed. The closed-loop leveling of the working platform is performed using the electromechanical coupling effect of the PZT piezoelectric material. Combined with the theory of the dielectric inverse piezoelectric effect in electric fields, a simulation is used to analyze the four force and deformation cases generated by the drive legs when the load is attached at different positions of the working platform, and the leveling is realized by applying the drive voltage to generate micro-motion displacement. Simulation and calculation results show that the leveling method can reduce the tilt angle of the working platform by 60% when the driving voltage is in the range of 10~150 V. The feasibility of the leveling method and the uniformity of the theoretical calculation and simulation are verified. Full article

This study establishes a standardized geometric model of the tibiotalar joint based on anatomical morphology and validates its statistical representativeness. Using this model, a novel fusion implant was developed and evaluated for its biomechanical performance through nonlinear finite element (FE) analysis compared to traditional fixation methods. A morphological database of the tibiotalar joint was built using 30 computed tomography (CT) scans to determine key dimensional parameters, and a novel fusion implant was designed to match the joint’s natural curvature. FE analysis compared three fixation strategies: (1) the novel implant with an anterior plate, (2) the anterior plate alone, and (3) three compression screws. Biomechanical parameters, including joint contact area, micromotion, and stress distribution, were analyzed under simulated loading conditions. The novel implant achieved the highest joint contact area (95.0%) and lowest tibial micromotion (0.033 mm), significantly reducing stress concentration compared to anterior plate fixation (49.8% contact; 0.068 mm micromotion) and compression screws (78.2% contact; 0.355 mm micromotion). Constructing a standardized tibiotalar joint model with verified normal distribution is crucial for ensuring broad implant applicability. FE analysis demonstrated that the novel implant enhances joint contact, reduces micromotion, and optimizes stress distribution, offering a promising approach for improving surgical outcomes in tibiotalar joint fusion. Full article

Advancements in load-bearing tissue repair increasingly demand biomaterials that not only support structural integrity but also interact dynamically with the physiological environment. This review examines the latest progress in smart biomaterials designed for skeletal reconstruction, with emphasis on mechanoresponsive scaffolds, bioactive composites, and integrated microsensors for real-time monitoring. We explore material formulations that enhance osseointegration, resist micromotion-induced loosening, and modulate inflammatory responses at the bone–implant interface. Additionally, we assess novel fabrication methods—such as additive manufacturing and gradient-based material deposition—for tailoring stiffness, porosity, and degradation profiles to match host biomechanics. Special attention is given to sensor-augmented platforms capable of detecting mechanical strain, biofilm formation, and early-stage implant failure. Together, these technologies promise a new class of bioresponsive, diagnostic-capable constructs that extend beyond static support to become active agents in regenerative healing and post-operative monitoring. This multidisciplinary review integrates insights from materials science, mechanobiology, and device engineering to inform the future of implantable systems in skeletal tissue repair. Full article

Background/Objectives: Proximal interphalangeal joint (PIJ) arthrodesis is a common surgical intervention for patients with PIJ osteoarthritis or trauma-related joint destruction. The objective of this study was to evaluate the biomechanical stability of various arthrodesis techniques under forces comparable to activities of daily living (ADL) to assess their suitability for early active movement protocols. Methods: In this in vitro study, composite cylinders simulating PIJ arthrodesis were subjected to standardized fusion angles of 40° using different fixation techniques, including crossed K-wires, compression screws, cerclage wires, tension band wiring, anatomical fixation plates, and locking grid plates. Forces representing ADLs such as typing, holding a pencil, carrying weight, and opening a jar were applied using a universal testing machine in a four-point bending setup. Micromotion and gap clearance were calculated and analyzed. Results: Techniques involving compression, such as compression screws, tension bands, and cerclage wires, exhibited lower micromotion and gap clearance under forces up to 17 N, suggesting potential suitability for early active movement protocols. In contrast, fixation plates demonstrated structural failure or excessive clearance during early active motion ADLs. K-wires showed intermediate results with moderate gap clearance and micromotion. Conclusions: Compression-based fixation techniques for PIJ arthrodesis may permit early active movement without external stabilization, while fixation plates are prone to failure under ADL forces. Further dynamic biomechanical testing and clinical studies are recommended to confirm these findings. Full article

This study aimed to develop a novel modular pedicle screw system incorporating an elliptical sleeve to conform the pedicle’s elliptical cross-section and enhance fixation strength with mechanical stability. The biomechanical evaluation was conducted based on fundamental mechanics principles, followed by a finite element (FE) analysis to assess stress distribution under compressive and torsional loads. Subsequently, mechanical testing was performed to evaluate static and fatigue bending performance and in vitro biomechanical fatigue in porcine vertebrae by pull-out testing after 5000 and 100,000 cycles to assess fixation stability. The FE analysis demonstrated that the elliptical sleeve design improved bending resistance by 1.21× and torsional resistance by 1.91× compared to conventional cylindrical screws. Mechanical testing revealed greater bending/torsion stiffness and fatigue resistance, with the elliptical sleeve screw withstanding 5 million cycles at 235.4 N, compared to 175.46 N for cylindrical screws. Biomechanical pull-out testing further confirmed significantly higher retention strength after 100,000 cycles (1229.75 N vs. 867.83 N, p = 0.0101), whereas cylindrical screws failed prematurely at 10,663 cycles due to excessive displacement (>2 mm). The elliptical sleeve pedicle screw system demonstrated enhanced fixation strength, reduced micromotion, and superior fatigue resistance, making it a promising alternative to conventional pedicle screws for improving long-term spinal fixation stability. Full article

A tibial implant is necessary to provide mechanical support in open-wedge high tibial osteotomy (OWHTO) treatment of knee osteoarthritis. The pore structure and porosity of implants exert significant effect on tibia stress distribution and lower limb alignment stability. In this study, finite element (FE) analysis and in vitro biomechanical experiments were utilized to evaluate the impact of different tibial implants on postoperative tibial stress distribution. The biomechanical experimental results of experiments on tibial implants exhibit similar mechanical response patterns to the established finite element model, whose maximum displacement error is 1.18% under 1500 N compressive load. The hybrid porous implant developed in this study demonstrated significant stress reductions in both tibial bone (19.97% and 15.33% lower than mono-porous configurations at 73% porosity) and implant body (31.60% and 11.83% reductions, respectively), while exhibiting diminished micromotion tendencies. This consistent performance pattern was maintained across the entire porosity spectrum (53–83%) in implanted specimens. In summary, the finite element model established using authentic tibial CT data can effectively guide the structural design of tibial implants, and optimized pore structure design can provide enhanced mechanical support effects for tibial implants. Full article

Introduction: Median sternotomy carries post-surgical risks like sternal instability, requiring careful monitoring. Ultrasonography provides a real-time, quantitative assessment of sternal micromovements and has emerged as a promising tool for clinical evaluation. However, its reliability for assessing sternal micromovements post-surgery remains unclear. This study evaluated the inter-rater, intra-rater, and test–retest reliability of ultrasound performed by physiotherapists. Methods: Ultrasound was used to measure the distance between sternal edges in sternotomized patients along the X-axis and Y-axis. Measurements were taken under a resting position, during cough, and in two supine-to-sitting postural transitions (one using a rotational modality and the other with an individual device). Real-time ultrasound imaging acquisition was followed by off-line data elaboration. Assessments were conducted by multiple physiotherapists after a brief training period. Reliability was determined using intraclass correlation coefficients (ICCs), along with the standard error of measurement (SEM) and minimum detectable change (MDC90). ICC values > 0.75 were classified as excellent. Results: A total of 33 subjects with median sternotomy were included (5 women, age 66 ± 7 years). All reliability measurements (24 total) were rated as excellent in each condition examined, with intra-rater ICCs exceeding 0.90, except for on the X-axis during the postural transition using the individual device for supine-to-sitting. SEM values ranged from 0.23 to 0.64 mm, while MDC90 values ranged from 0.54 to 1.50 mm. Conclusions: Ultrasound demonstrated excellent reliability for assessing sternal micromotions when performed by physiotherapists with brief training. Given its reliability, cost-effectiveness, and ease of use, ultrasound sternal micromotions assessment could be integrated into post-surgical rehabilitation to enhance patient care. Full article

The long-term effectiveness of osseointegrated implants is heavily dependent on the short-term stability, primarily achieved immediately after surgery through a mechanical connection between the bone and the implant. The most common implant designs nowadays are straight and rely on screw or press-fit fixtures. Despite the promising results achieved by current transfemoral implants, the incidence of early failures and complications is still high. Starting from the hypothesis that a patient-specific approach could lead to better primary stability immediately post-surgery, this study aims to investigate the effect of implant design on primary stability. This was performed by analyzing two patient-specific implants, customized according to the medullary canal morphology, and a simple straight implant as the reference standard. To quantitatively assess the primary stability, a comparative computational analysis was conducted to examine the effective contact area, the relative micromotion, and the stress distribution at the interface between the bone and the implant stem during a static load-bearing exercise. The results showed that implants that follow the curvature of the residual femur provide lower micromotion values and a wider contact area, with a reduction of up to 30.4% and an increase of 10.8%, respectively, compared to the straight design, leading to a more homogeneous load distribution. Patient-specific prosthetic implants allow a more homogenous contact distribution that could lead to higher primary stability by reducing micromotion at the bone–implant interface concerning the straight profile, lowering the risk of loosening related to the short-term stability. Full article

This study proposes a novel method that uses radar for markerless motion classification by using effective features derived from micro-Doppler signals. The training phase uses three-dimensional marker coordinates captured by a motion-capture system to construct basis functions, which enable modeling of micro-motions of the human body. During the testing phase, motion classification is performed without markers, relying solely on radar signals. The feature vectors are generated by applying cross-correlation between the received radar signal and the basis functions, then compressed using principal component analysis, and classified using a simple nearest-neighbor algorithm. The proposed method achieves nearly 100% classification accuracy with a compact feature set and is accurate even at high signal-to-noise ratios. Experimental results demonstrate that to optimize training data and increase computational efficiency, the sampling duration and sampling interval must be set appropriately. Full article

In the research on intelligent perception, dynamic emotion recognition has been the focus in recent years. Small samples and unbalanced data are the main reasons for the low recognition accuracy of current technologies. Inspired by circular convolution networks, this paper innovatively proposes an adaptive dynamic micro-expression recognition algorithm based on self-supervised learning, namely MADV-Net. Firstly, a basic model is pre-trained with accurate tag data, and then an efficient facial motion encoder is used to embed facial coding unit tags. Finally, a cascaded pyramid structure is constructed by the multi-level adaptive dynamic encoder, and the multi-level head perceptron is used as the input into the classification loss function to calculate facial micro-motion features in the dynamic video stream. In this study, a large number of experiments were carried out on the open-source datasets SMIC, CASME-II, CAS(ME)^2, and SAMM. Compared with the 13 mainstream SOTA methods, the average recognition accuracy of MADV-Net is 72.87%, 89.94%, 83.32% and 89.53%, respectively. The stable generalization ability of this method is proven, providing a new research paradigm for automatic emotion recognition. Full article

Lumbar interbody fusion (LIF) is a standard treatment for spinal instability, yet postoperative subsidence and adjacent segment degeneration (ASD) remain critical challenges. This study evaluates the biomechanical efficacy of personalized porous fusion cages—featuring Gyroid (G-Cage) and Voronoi (V-Cage) architectures—against classic (C-Cage) and personalized (P-Cage) designs, aiming to enhance stability and mitigate subsidence risks. A finite element model of the L3–L4 segment, derived from CT scans of a healthy male volunteer, was developed to simulate six motion modes (compression, rotation, flexion, extension, and left/right bending). Biomechanical parameters, including range of motion (ROM), cage stress, endplate stress, and displacement, were analyzed. The results demonstrated that the V-Cage exhibited superior performance, reducing ROM by 51% in extension, cage stress by 41.7% in compression, and endplate stress by 63.7% in right bending compared to the C-Cage. The porous designs (G-Cage, V-Cage) exhibited biomimetic stress distribution and minimized micromotion, which was attributed to their trabecular-like architectures. These findings highlight the Voronoi-based porous cage as a biomechanically optimized solution, offering enhanced stability and reduced subsidence risk when compared to classic implants. The study underscores the potential of patient-specific porous designs in advancing LIF outcomes, warranting further clinical validation to translate computational insights into practical applications. Full article