Journal of Bionic Engineering最新文献

Accurate detection of driver fatigue is essential for improving road safety. This study investigates the effectiveness of using multimodal physiological signals for fatigue detection while incorporating uncertainty quantification to enhance the reliability of predictions. Physiological signals, including Electrocardiogram (ECG), Galvanic Skin Response (GSR), and Electroencephalogram (EEG), were transformed into image representations and analyzed using pretrained deep neural networks. The extracted features were classified through a feedforward neural network, and prediction reliability was assessed using uncertainty quantification techniques such as Monte Carlo Dropout (MCD), model ensembles, and combined approaches. Evaluation metrics included standard measures (sensitivity, specificity, precision, and accuracy) along with uncertainty-aware metrics such as uncertainty sensitivity and uncertainty precision. Across all evaluations, ECG-based models consistently demonstrated strong performance. The findings indicate that combining multimodal physiological signals, Transfer Learning (TL), and uncertainty quantification can significantly improve both the accuracy and trustworthiness of fatigue detection systems. This approach supports the development of more reliable driver assistance technologies aimed at preventing fatigue-related accidents.

Treating bone defects complicated by bacterial infections remains a significant clinical challenge. Drawing inspiration from the human body’s bone repair mechanisms, the use of biomimetic methods to design tissue engineering scaffolds is of great significance for bone repair. This study synthesized copper (Cu)-doped mesoporous silica nanoparticles (Cu@MSN) modified with hydroxyethyl methacrylate to obtain methacrylated Cu@MSN (Cu@MSNMA). Furtheremore, biomimetic nanocomposite hydrogels were prepared by adding Cu@MSNMA to a GelMA/gelatin solution. This hydrogel achieves multi-modal bone tissue biomimicry: (i) GelMA/gelatin mimics the matrix components in bone ECM, ensuring biocompatibility while promoting cellular behavior (such as adhesion, proliferation, and differentiation); (ii) GelMA/gelatin and the crosslinking sites introduced by Cu@MSNMA form a stable porous network structure, achieving structural and mechanical biomimicry to provide necessary support for bone defects; (iii) The elemental biomimicry of Si and Cu in Cu@MSNMA achieves efficient osteogenic induction. The effect of different proportions of Cu@MSNMA on the physical properties of the composite hydrogels was investigated to determine the optimal proportion. The results indicated that the mechanical properties of hydrogel were enhanced with the increasing Cu@MSNMA mass ratio. Notably, 5% NPs/GelMA/gelatin hydrogel exhibited excellent mechanical property compared to the GelMA/gelatin hydrogel. In vitro and vivo cellular experiments demonstrated a significant enhancement in antibacterial and osteogenic induction with Cu@MSNMA addition. In conclusion, the proposed nanocomposite hydrogel with biomimetic components and ion-regulating properties can serve as a multifunctional scaffold, offering antimicrobial properties for infected bone regeneration, and guide for future research in bone regeneration and three-dimensional printing.

Soft grippers research is gaining increasing attention for their flexibility. However, the conventional soft gripper primarily focuses on soft fingers, without considering the palm. This makes grasping forces concentrated in the fingertip areas, resulting in objects being prone to damage and instability during handling, especially for delicate items. Additionally, pre-transportation classification faces challenges: tactile methods are complex, visual methods are environment-sensitive, and both struggle with similar objects. To address these problems, inspired by the human hand’s transition between finger grasp and palm support and the lotus’s hierarchical structure, this paper proposes a dual-layer gripper, named IOSGripper. It features four pneumatic soft fingers and a rotational soft-rigid palm. Through coordinated control of the fingers and palm, it transitions concentrated fingertip squeeze force to distributed palm support force, reducing squeeze force and squeeze duration. Moreover, it integrates a range sensor and four load cells, enabling stable and accurate measurements of the object’s height and weight. Furthermore, a classifier is developed based on K-nearest neighbor algorithm, allowing real-time object classification. Experiments demonstrate that compared to only using soft fingers, the IOSGripper significantly reduces the squeeze force on the objects (with 0 N squeeze force during palm support) and damage on the delicate object, while improving grasping stability. Its height and weight measurement errors are within 2 mm and 1 g, respectively. And it achieves high accuracy in three test scenarios, including classifying similar objects. This study provides useful insights for the design of soft grippers capable of human-like grasping and sorting tasks.

The net capturing method holds great potential for space debris removal due to its adaptability to the various target shapes and high fault tolerance. However, the capture mechanisms of current rope nets, which rely solely on a passive wrapping mechanism, limit their capacity to capture objects within a specific size range and make it challenging to handle unexpected situations. Inspired by spider webs, which combine wrapping and adhering to capture prey of various sizes, we present a new type of net (envelope diameter: 208.49 mm) for on-orbit capture. This net adopts a spiral symmetric structure similar to spider webs, incorporates electrostatic-microstructure hybrid adhesives, and increases the maximum contact area by 38.31%, allowing it to capture debris ranging from fragments smaller than the mesh size (envelope diameter: 2.7 mm - 4.4 mm) to larger objects (envelope diameter: 270 mm), and effectively grasps flexible items (450 mm²), planar items (350 mm²) and three-dimensional items (160 mm³). Moreover, to validate the net’s capability for wrapping and adhesion, simulations and experiments are demonstrated that this dual capture method can effectively handle various targets.

The main cable is the primary load-bearing component of a suspension bridge, continuously exposed to harsh environmental conditions, such as wind and rain, throughout the year. These adverse conditions contribute to varying degrees of degradation and damage to the main cable, necessitating regular inspections to prevent catastrophic failures. Traditional manual inspection methods not only suffer from low efficiency but also pose significant safety risks to personnel. To address these challenges and ensure the safe and effective inspection of suspension bridge main cables, this study introduces a novel cooperative climbing robot, designated as Main Cable Robot Version II (CCRobot-M-II), inspired by the locomotion of the inchworm. The robot employs an alternating opening and closing mechanism of four gripper sets, mimicking the inchworm’s movement to achieve efficient crawling along the suspension bridge handrails. This paper provides a comprehensive analysis of the structural design, key components, and motion mechanisms of CCRobot-M-II. A detailed force analysis of the robot’s crawling process is also presented, followed by the design of the control system and the development of an efficient motion control algorithm. Laboratory experiments demonstrate that the robot achieves a positional error of 0–0.64% during crawling, with a maximum average crawling speed of 7.6 m/min. Furthermore, the biomimetic design enables the robot to overcome obstacles up to 30 mm in height and possess the capability to handle suspension bridge cables with spans ranging from 740 to 1100 mm. Finally, CCRobot-M-II successfully conducted an inspection of the main cable on a suspension bridge, marking the world’s first successful deployment of a climbing robot for main cable inspection on a suspension bridge.

Soft robotic manipulators represent a rapidly evolving field characterized by inherent compliance, adaptability, and safe interactions within unstructured environments. Over the past decade (2015–2025), significant advancements have transformed their capabilities through novel designs inspired by biological systems, advanced modeling frameworks, sophisticated control strategies, and integration into diverse real-world applications. Recent innovations in multifunctional materials and emerging actuation technologies have markedly expanded manipulator performance, reliability, and dexterity. Concurrently, developments in modeling have progressed from simplified geometric methods toward highly accurate physics-based and hybrid data-driven approaches, substantially improving real-time prediction and controllability. Coupled with these developments, adaptive and robust control strategies–including learning-based techniques–have enabled unprecedented autonomy and precision in challenging application domains such as Minimally Invasive Surgery (MIS), precision agriculture, deep-sea exploration, disaster recovery, and space missions. Despite these remarkable strides, key challenges remain, notably regarding scalability, long-term material durability, robust integrated sensing, and standardized evaluation procedures. This review comprehensively synthesizes recent advances, critically evaluates state-of-the-art methodologies, and systematically identifies existing gaps to provide a clear roadmap and targeted research directions, guiding future developments toward the broader adoption and optimal utilization of soft robotic manipulators.

Microrobotic systems are emerging as transformative technology for minimally invasive medicine, driven by innovations in actuation mechanisms, advanced fabrication paradigms, and multifunctional system integration. This comprehensive review analyzes the evolution of microrobotic technologies through three critical dimensions: (1) actuation modalities, including magnetic, optical, acoustic, chemical, and biological actuation, with a focus on the synergistic advantages of hybrid actuation strategies in complex internal physiological environments; (2) Fabrication methods cover technologies such as photolithography, microinjection molding, self-assembly, and 3D printing, emphasizing innovative strategies involving multi-technology integration and collaborative manufacturing of bio/non-bio hybrid materials; (3) Internal physiological applications involve disease diagnosis, targeted drug delivery, minimally invasive surgery, tissue engineering, and cell manipulation, highlighting the broad prospects of microrobots in precision medicine. Despite remarkable progress, critical challenges remain, including low actuation efficiency, as seen in acoustic systems, limited biocompatibility, exemplified by the toxicity of hydrogen peroxide in chemical actuation, delayed clinical translation, and other related challenges that must be addressed to advance the field.

Bamboo is a natural composite that has inspired the design of biomimetic composites due to its unique multi-scale structure and outstanding mechanical properties. This paper first presents the structural features of bamboo, detailing the hydrophobic wax and silica layer of the surface, the functionally graded vascular bundles of the wall for optimized toughness, and the hollow, multi-node architecture of the stem for overall stability and bending resistance. Subsequently, this study surveys recent sustainability and designability advances in bamboo-inspired composites. Inspiration from the bamboo surface has spurred the creation of materials with enhanced functionalities, such as transparent composites and high-stiffness structural materials. Imitation of the wall structure has led to the development of high-strength and tough materials, with the discussion covering examples such as hydrogels, polymer composites, and metal-matrix composites. Inspiration from the stem structure has yielded lightweight composites with excellent energy absorption and stability, exemplified by advanced linear materials like resilient yarns and tendon sutures, as well as functional structures like flexible sensors. These biomimetic designs show significant potential across numerous fields, including construction, healthcare, urban rail transit, wearable electronics, and mechanical engineering. Finally, this paper discusses the current limitations and challenges to understanding bamboo’s structural characteristics towards the development of bamboo-inspired composites. Future research directions are proposed, including understanding bamboo’s structure, designing novel biomimetic composites, and optimizing their structure to develop bamboo-inspired functional materials.

The soft actuator is characterized by high safety, flexibility, and adaptability. It is capable of both active and passive deformations. This paper presents a discrete degree of freedom (DOF) method for soft actuators to reveal DOF characteristics. The method draws on the superposition mechanism of the deformation characteristics of the sarcomere in the skeletal muscles of living organisms. Firstly, the multi-DOF deformation characteristics of the soft actuator are discretized into superimposed combinations of single-DOF micro-units. Then, the soft actuator was determined to contain deformation characteristics such as extension-contraction, bending, and twisting. Eighteen types of micro-units with basic deformation characteristics were obtained depending on the axis and orientation. Further, the mapping relationship between the combination of micro-units and the motion characteristics of the soft actuator based on the (G_{F}) set theory was established. Finally, an active–passive DOF co-structured soft actuator (APCSA) was developed. The graphical approach analyzes the experimental results, and it can be concluded that active and passive DOFs can coexist in the composite deformation of the soft actuator.