Journal of Bionic Engineering最新文献

Tactile feedback is critical for human interaction with external information. Similarly, tactile feedback can enrich the user’s sensations when using prosthesis. To explore a potential scheme for tactile feedback, this study applied a non-invasive Transcutaneous Electrical Nerve Stimulation (TENS) to elicit tactile sensations in the hand, which involved median nerve, ulnar nerve, and radial nerve. Ten able-bodied subjects (8 males, 2 females) were recruited to participate in the study. An array of 4 (times ) 2 electrodes was positioned on the medial aspect of the brachii muscle’s short head in the upper arm, which is in proximity to the median nerve, ulnar nerve, and radial nerve. Different electrode pairs were randomly selected to elicit distinct sensations at various positions on the hand, and the subjects reported the sensory areas. Then, the sensory areas and sensory thresholds were confirmed through psychophysical methods. According to the experimental results, tactile sensations were elicited at different locations on the subjects’ hand through TENS of different electrode pairs. All subjects reported extensive and detailed sensory areas in the fingers, palm, and dorsum, corresponding to the sensory innervation areas of different nerves. The study effectively demonstrated the ability of TENS in evoking tactile feedback in the hand, paving the way for future optimization and development of prosthetic hands.

In this study, we developed a novel bilayered scaffold consisting of a bottom layer composed of the Decellularized Bovine Pericardium (DP) coated with Polyaniline Nanoparticles (PANINPs) and a top layer made of an electrospun Poly(lactic-co-glycolic acid)/Gelatin (PLGA/Gel) membrane incorporated with Vascular Endothelial Growth Factor (VEGF) and hawthorn extract. Functionally, the DP supplies native Extracellular Matrix (ECM) components and mechanical support, while PANINPs provide conductivity. The electrospun PLGA/Gel layer mimics fibrous ECM. It incorporates bioactives, with VEGF promoting pro-angiogenic stimulation and hawthorn extract enhancing anticoagulant activity, as well as increasing surface hydrophilicity. The tissue adhesive ensures the interfacial integrity between the two layers. Decellularization efficiency was confirmed histologically using 4′,6-diamidino-2-phenylindole (DAPI) and Hematoxylin–Eosin (H&E) staining. The DP exhibited a DNA content of 115.9 ± 47.8 ng/mg DNA, compared to 982.88 ± 395.42 ng/mg in Native Pericardium (NP). The PANINPs had an average particle size of 104.94 ± 13.7 nm. The conductivity of PANINPs-coated decellularized pericardium was measured to be 9.093 ± 8.6 × 10^− 4 S/cm using the four-point probe method. PLGA/Gel membranes containing hawthorn extract (1%, 5%, 10%, and 15% w/v) and VEGF (0.1 µg/mL, 0.5 µg/mL, and 1 µg/mL) were fabricated by electrospinning, resulting in fiber diameters between 850 and 1200 nm and pore sizes between 14 and 20 μm. The anticoagulant efficiency of the membranes containing hawthorn extract reached 430 s in the Activated Partial Thromboplastin Time Assay (aPTT). Mechanical testing revealed a tensile strength of 22.70 ± 6.33 MPa, an elongation of 53.58 ± 10.63%, and Young’s modulus of 0.67 ± 0.10 MPa. The scaffold also exhibited over 91% cell viability and excellent cardiomyocyte adhesion. The hemolysis ratio was determined to be 0.421 ± 0.191%, which confirms its blood compatibility. Our results indicate that the proposed bilayered scaffold can be a promising candidate for cardiac patch applications.

This paper introduces a novel nature-inspired metaheuristic algorithm called the Gekko japonicus algorithm. The algorithm draws inspiration mainly from the predation strategies and survival behaviors of the Gekko japonicus. The mathematical model is developed by simulating various biological behaviors of the Gekko japonicus, such as hybrid locomotion patterns, directional olfactory guidance, implicit group advantage tendencies, and the tail autotomy mechanism. By integrating multi-stage mutual constraints and dynamically adjusting parameters, GJA maintains an optimal balance between global exploration and local exploitation, thereby effectively solving complex optimization problems. To assess the performance of GJA, comparative analyses were performed against fourteen state-of-the-art metaheuristic algorithms using the CEC2017 and CEC2022 benchmark test sets. Additionally, a Friedman test was performed on the experimental results to assess the statistical significance of differences between various algorithms. And GJA was evaluated using multiple qualitative indicators, further confirming its superiority in exploration and exploitation. Finally, GJA was utilized to solve four engineering optimization problems and further implemented in robotic path planning to verify its practical applicability. Experimental results indicate that, compared to other high-performance algorithms, GJA demonstrates exceptional performance as a powerful optimization algorithm in complex optimization problems. We make the code publicly available at: https://github.com/zhy1109/Gekko-japonicusalgorithm

Rough micro-nano structures and low surface energy chemical compositions are two essential conditions for constructing superhydrophobic surfaces. However, for low surface tension liquids, which are extremely easy to spread and wet on solid surfaces, the design of cantilever structures with internal concavity is the third important parameter to achieve their superomniphobic, whose negative geometrical inflections can effectively lock the solid-liquid-gas three phase contact line, maximize the upward component of capillary force of the suspended droplets, and provide a larger breakthrough pressure for the structured surfaces to avoid the low surface tension liquids from collapsing on the solid surfaces. Based on this, microfabrication was used to prepare mushroom structured surfaces. By precisely controlling the etching parameters, mushroom structures with diameter of 3 μm and circular centre distance of 8 μm were prepared. The mushroom structure not only achieves super-repellent from high surface tension water (72.8 mN/m) to ultra-low surface tension perfluorohexane (10 mN/m), but also achieves complete rebound even to the high-speed impact of liquid droplets, including water droplets with an impact height of 7.9 cm and perfluorohexane with a height of 3 mm. This fabrication technology helps to build a robust superomniphobic surface for use in harsh environments such as high-speed droplet impacts.

A mass on-line control type impact inertial piezoelectric actuator with a bionic wheat structure is proposed in this work. Inspired by the anisotropic friction mechanism of natural wheat awns, a bioinspired mechanism is used to achieve the designed driving strategy based on the asymmetric-mass control method that mimics bidirectional motion characteristics of wheat awn. A lumped parameter theoretical model is established, and the numerical simulation results have verified the designed bionic working principle and revealed the key system parameters. Experimental results show that the prototype has the bi-directional motion ability inherited from anisotropic friction of wheat awn, with theoretically infinite stroke and can easily obtain the required step displacement and velocity by conveniently adjusting the voltage. It can achieve a resolution of 0.7 μm, and a forward and backward maximum velocity of 12.7 μm/s and 90.72 μm/s respectively. In addition, the actuator also has the advantages of good stability, control convenience, and ease of integration. Besides, the actuator is capable of adjusting motion direction via voltage, providing a significant advantage in precise bidirectional control. This study confirms that the proposed mass on-line control type actuator embodies a successful bionic translation from plant morphology to precision engineering, and adds a new member to the family of impact inertial piezoelectric actuators, which completes the last piece of the puzzle for the impact inertial driving mechanism. It promotes the further development of inertial precision driving and control technology and is expected to expand the scope of application. Future work will focus on optimizing performance and developing applications.

Protective hardware is essential for mitigating damage caused by unavoidable falls in humanoid robots. Despite notable progress in fall protection hardware, the theoretical foundation for modeling and the feasibility of conducting full-scale fall experiments on robots or their surrogates remain somewhat limited. This paper proposes a method for optimizing the thickness of Expandable Polyethylene (EPE), which is used as back protection for the Chubao humanoid robot, based on small-scale impact test data to predict full-scale behavior. The optimal thickness is defined as a balance between compact design and protective effectiveness. An equivalent impact model characterized by four parameters: contact area S, mass m, fall height h, and cushioning material thickness d is introduced to describe impact conditions. The relationship between the peak impact acceleration ({a}_{p}) and material thickness d, which forms the core of the method and gives rise to the name AP-D, is analyzed through their plotted curves. After introducing three characteristic parameters and two correction factors, the relationship among the aforementioned variables is derived. Subsequently, both the optimal thickness ({d}^{o}) and its corresponding peak impact acceleration ({a}_{p}^{o}) are predicted via nonlinear and linear regression models. Finally, the accuracy and effectiveness of the theoretically derived optimal thickness are validated on both a dummy and the actual robot. With the cushioning material applied, the peak chest acceleration is reduced to 41.57g for the dummy and 32.08g for the robot.

To address the critical challenge of risk perception and assessment for autonomous vehicles in dynamic interactive environments, this study proposes a semi-supervised spatiotemporal interaction risk cognition network with attention mechanism (SS-SIRCN), inspired by the behavioral adaptation patterns of biological groups under external threats. First, by thoroughly analyzing the dynamic interaction characteristics exhibited by typical biological collectives when exposed to risk, the study reveals the underlying patterns of trajectory changes influenced by external danger. Then, an attention-based spatiotemporal risk cognition network is designed to establish a mapping between driving behavior features and potential driving risks.Finally, a semi-supervised learning framework is employed to enable risk assessment for autonomous vehicles using only a small amount of labeled data.Experimental results on real-world vehicle trajectory datasets demonstrate that the proposed method achieves a risk prediction accuracy of 90.76%, outperforming other baseline models in performance.

Soft robots, as a modern gateway to unlocking the mysteries of underwater realms, present new complexities. Modeling their behavior when in contact with external forces, whether point-based or distributed, is a primary challenge due to the nature of soft bodies. To obtain a holistic view of the system’s behavior determining the governing dynamics is deemed necessary. This paper proposes a new technique to simulate the dynamic lateral undulation of a soft robotic fish with a cable-driven soft tail. By integrating the rigid finite element method with rigid-body robotics, the model represents the undulation of a finite number of rigid elements connected through a set of torsional spring and damper. Instead of directly modeling external forces, we substitute equivalent joint torques into the system dynamics, allowing us to consider external effects without complicating the model. The resulting model yields valuable insights into the system’s behavior, including propulsive and lateral forces. A comparison with experimental results shows strong agreement, with a tip amplitude error of 10% at 0.8 Hz, 5.25% at 1.6 Hz and 2.54% at 2.2 Hz flapping frequency. These findings illuminate the influence of lateral undulation on the overall dynamics, paving the way for fully autonomous robotic fish.

Backswimmers exhibit a high degree of mobility in water, and their different motion patterns have important implications for the design of micro-biomimetic underwater robots. This paper used three-dimensional high-speed cameras to extract the key points on the hind legs. The hind leg motion laws and the deformation laws of the setae were obtained in four motion patterns: rapid forward, cruising, in-motion turning, and in-place turning. The motion laws of each joint on the hind leg are modeled using a Fourier series. A kinematic model of hind legs was established based on the DH method, and the motion characteristics of hind legs under different motion patterns were analyzed. This paper provides basic data and theoretical models for micro-biomimetic robots.

A human semicircular canal (HSC) with “cupulolithiasis” (HSCC) causes abnormal perception and vertigo. Based on 3D printing technology and target tracking technology, models of a visualized bionic semicircular canal with cupulolithiasis (BSCC) were generated. The model, with careful scaling parameters, similar biomechanical responses to the vestibular-ocular reflex (VOR), and a similarly long time constant to the HSC, allows us to study the mechanics of the HSCC. The static experiments revealed that the bionic cupula of the BSCC continued to shift due to the effect of the gravity of the otolith after rotation stopped. The frequency broadband experiment indicated that the gain of the BSCC decreased as the phase difference increased, and the increase in otolith mass aggravated this trend. BSCCs can be used as a bionic model to study the pathology of human semicircular canal-related diseases and may promote the development of treatments.