Biomimetics最新文献

{"title":"Power Restoration Optimization Strategy for Active Distribution Networks Using Improved Genetic Algorithm.","authors":"Pengpeng Lyu, Qiangsheng Bu, Yu Liu, Jiangping Jing, Jinfeng Hu, Lei Su, Yundi Chu","doi":"10.3390/biomimetics10090618","DOIUrl":"10.3390/biomimetics10090618","url":null,"abstract":"<p><p>During feeder outages in the distribution network, localized power restoration using distribution resources (e.g., PVs) can ensure supply to critical loads and mitigate adverse impacts, especially when main grid support is unavailable. This study presents a power restoration strategy aiming at maximizing the restoration duration of critical loads to ensure their prioritized recovery, thereby significantly improving power system reliability. The methodology begins with load enumeration via breadth-first search (BFS) and utilizes a long short-term memory (LSTM) neural network to predict microgrid generation output. Then, an adaptive multipoint crossover genetic solving algorithm (AMCGA) is proposed, which can dynamically adjust crossover and mutation rates, enabling rapid convergence and requiring fewer parameters, thus optimizing island partitioning to prioritize critical load demands. Experimental results show that AMCGA improves convergence speed by 42.5% over the traditional genetic algorithm, resulting in longer restoration durations. Compared with other strategies that do not prioritize critical load recovery, the proposed strategy has shown superior performance in enhancing critical load restoration, optimizing island partitioning, and reducing recovery fluctuations, thereby confirming the strategy's effectiveness in maximizing restoration and improving stability.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 9","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-09-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467194/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147575","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Learning Models Optimization for Gait Phase Identification from EMG Data During Exoskeleton-Assisted Walking.","authors":"Roberto Soldi, Bruna Maria Vittoria Guerra, Stefania Sozzi, Leo Russo, Serena Pizzocaro, Renato Baptista, Alessandro Marco De Nunzio, Micaela Schmid, Stefano Ramat","doi":"10.3390/biomimetics10090617","DOIUrl":"10.3390/biomimetics10090617","url":null,"abstract":"<p><p>Exoskeletons are a fast-growing technology that enables multiple use-cases in clinical scenarios. They can be useful tools for the rehabilitation of patients with motor dysfunctions caused by neurological conditions, aging or trauma. Assistive exoskeletons modulate the torque exerted by the electrical motors moving their joints to allow the patients wearing them to achieve an intended movement, such as gait, correctly. Their effectiveness, therefore, requires accurate online control of such torques to complement those generated by the patient. Hereby we explored Deep Learning (DL) models to generate an online prediction of the gait phase, i.e., stance or swing, during assisted walking with a lower-limb exoskeleton based on surface electromyography (sEMG) data. We leveraged the lead of muscular activation with respect to the movement of the limbs to adjust the labeling based on joints kinematics. The cross-subject design allowed to generalize over subjects not considered for training A hyperparameter optimization algorithm was also implemented to further explore the capabilities of DL models of a reduced size. We simulated a use case scenario to assess whether online implementation of the proposed technique is feasible. We also proposed a new metric called trade-of score (<i>TOS</i>) for evaluating the cost-performance compromise of the optimized models which lead to identifying a DL model capable of classifying gait phases with an accuracy of about 95% while significantly reducing the number of parameters compared to the full architecture. Its mean computational time of less than 10 ms offers the opportunity for accurate, online exoskeleton control based on sEMG data.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 9","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467064/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design and Machine Learning Modeling of a Multi-Degree-of-Freedom Bionic Pneumatic Soft Actuator.","authors":"Yu Zhang, Linghui Peng, Wenchuan Zhao, Ning Wang, Zheng Zhang","doi":"10.3390/biomimetics10090615","DOIUrl":"10.3390/biomimetics10090615","url":null,"abstract":"<p><p>A novel multi-degree-of-freedom bionic Soft Pneumatic Actuator (SPA) inspired by the shoulder joint of a sea turtle is proposed. The SPA is mainly composed of a combination of oblique chamber actuator units capable of omnidirectional bending and bi-directional twisting, which can restore the multi-modal motions of a sea turtle's flipper limb in three-dimensional space. To address the nonlinear behavior of the complex structure of SPA, traditional modeling is difficult. The attitude information of each axis of the actuator is extracted in real time using a high-precision Inertial Measurement Unit (IMU), and the attitude outputs of the SPA are modeled using six machine learning methods. The results show that the XGBoost model performs best in attitude modeling. Its R² can reach 0.974, and the average absolute errors of angles in Roll, Pitch, and Yaw axes are 1.315°, 1.543°, and 1.048°, respectively. The multi-axis attitude of the SPA can be predicted with high accuracy in real time. The studies on deformation capability, actuation output performance, and underwater validation experiments demonstrate that the SPA meets the bionic sea turtle shoulder joint requirements. This study provides a new theoretical foundation and technical path for the development, control, and bionic application of complex multi-degree-of-freedom SPA systems.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 9","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467428/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147591","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Graduate Student Evolutionary Algorithm: A Novel Metaheuristic Algorithm for 3D UAV and Robot Path Planning.","authors":"Xiaoxuan Liu, Shaobo Li, Yongming Wu, Zijun Fu","doi":"10.3390/biomimetics10090616","DOIUrl":"10.3390/biomimetics10090616","url":null,"abstract":"<p><p>In recent years, numerical optimization, UAVs, and robot path planning have become hot research topics. Solving these fundamental artificial intelligence problems is crucial for further advancements. However, traditional methods struggle with complex nonlinear problems, prompting researchers to explore intelligent optimization algorithms. Existing approaches, however, still suffer from slow convergence, low accuracy, and poor robustness. Inspired by graduate students' daily behavior, this paper proposes a novel intelligent optimization algorithm, the Graduate Student Evolutionary Algorithm (GSEA). By simulating key processes such as searching for research directions and concentrating on studies, a mathematical model of GSEA is established. The algorithm's convergence behavior is analyzed qualitatively, and its performance is evaluated against competitive algorithms on the CEC2017 and CEC2022 test sets. Statistical tests confirm GSEA's effectiveness and robustness. To further validate its practical applicability, GSEA is applied to UAV and robot path planning problems, with experimental results demonstrating its superiority in solving real-world optimization challenges.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 9","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467384/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147671","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Human Activity Recognition with Noise-Injected Time-Distributed AlexNet.","authors":"Sanjay Dutta, Tossapon Boongoen, Reyer Zwiggelaar","doi":"10.3390/biomimetics10090613","DOIUrl":"10.3390/biomimetics10090613","url":null,"abstract":"<p><p>This study investigates the integration of biologically inspired noise injection with a time-distributed adaptation of the AlexNet architecture to enhance the performance and robustness of human activity recognition (HAR) systems. It is a critical field in computer vision which involves identifying and interpreting human actions from video sequences and has applications in healthcare, security and smart environments. The proposed model is based on an adaptation of AlexNet, originally developed for static image classification and not inherently suited for modelling temporal sequences for video action classification tasks. While our time-distributed AlexNet efficiently captures spatial and temporal features and suitable for video classification. However, its performance can be limited by overfitting and poor generalisation to unseen scenarios, to address these challenges, Gaussian noise was introduced at the input level during training, inspired by neural mechanisms observed in biological sensory processing to handle variability and uncertainty. Experiments were conducted on the EduNet, UCF50 and UCF101 datasets. The EduNet dataset was specifically designed for educational environments and we evaluate the impact of noise injection on model accuracy, stability and overall performance. The proposed bio-inspired noise-injected time-distributed AlexNet achieved an overall accuracy of 91.40% and an F1 score of 92.77%, outperforming other state-of-the-art models. Hyperparameter tuning, particularly optimising the learning rate, further enhanced model stability, reflected in lower standard deviation values across multiple experimental runs. These findings demonstrate that the strategic combination of noise injection with time-distributed architectures improves generalisation and robustness in HAR, paving the way for resource-efficient and real-world-deployable deep learning systems.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 9","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467874/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147682","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"IDP-Head: An Interactive Dual-Perception Architecture for Organoid Detection in Mouse Microscopic Images.","authors":"Yuhang Yang, Changyuan Fan, Xi Zhou, Peiyang Wei","doi":"10.3390/biomimetics10090614","DOIUrl":"10.3390/biomimetics10090614","url":null,"abstract":"<p><p>The widespread application of organoids in disease modeling and drug development is significantly constrained by challenges in automated quantitative analysis. In bright-field microscopy images, organoids exhibit complex characteristics, including irregular morphology, blurred boundaries, and substantial scale variations, largely stemming from their dynamic self-organization that mimics in vivo tissue development. Existing convolutional neural network-based methods are limited by fixed receptive fields and insufficient modeling of inter-channel relationships, making them inadequate for detecting such evolving biological structures. To address these challenges, we propose a novel detection head, termed Interactive Dual-Perception Head (IDP-Head), inspired by hierarchical perception mechanisms in the biological visual cortex. Integrated into the RTMDet framework, IDP-Head comprises two bio-inspired components: a Large-Kernel Global Perception Module (LGPM) to capture global morphological dependencies, analogous to the wide receptive fields of cortical neurons, and a Progressive Channel Synergy Module (PCSM) that models inter-channel semantic collaboration, echoing the integrative processing of multi-channel stimuli in neural systems. Additionally, we construct a new organoid detection dataset to mitigate the scarcity of annotated data. Extensive experiments on both our dataset and public benchmarks demonstrate that IDP-Head achieves a 5-percentage-point improvement in mean Average Precision (mAP) over the baseline model, offering a biologically inspired and effective solution for high-fidelity organoid detection.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 9","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467187/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An Improved Greater Cane Rat Algorithm with Adaptive and Global-Guided Mechanisms for Solving Real-World Engineering Problems.","authors":"Yepei Chen, Zhangzhi Tian, Kaifan Zhang, Feng Zhao, Aiping Zhao","doi":"10.3390/biomimetics10090612","DOIUrl":"10.3390/biomimetics10090612","url":null,"abstract":"<p><p>This study presents an improved variant of the greater cane rat algorithm (GCRA), called adaptive and global-guided greater cane rat algorithm (AGG-GCRA), which aims to alleviate some key limitations of the original GCRA regarding convergence speed, solution precision, and stability. GCRA simulates the foraging behavior of the greater cane rat during both mating and non-mating seasons, demonstrating intelligent exploration capabilities. However, the original algorithm still faces challenges such as premature convergence and inadequate local exploitation when applied to complex optimization problems. To address these issues, this paper introduces four key improvements to the GCRA: (1) a global optimum guidance term to enhance the convergence directionality; (2) a flexible parameter adjustment system designed to maintain a dynamic balance between exploration and exploitation; (3) a mechanism for retaining top-quality solutions to ensure the preservation of optimal results.; and (4) a local perturbation mechanism to help escape local optima. To comprehensively evaluate the optimization performance of AGG-GCRA, 20 separate experiments were carried out across 26 standard benchmark functions and six real-world engineering optimization problems, with comparisons made against 11 advanced metaheuristic optimization methods. The findings indicate that AGG-GCRA surpasses the competing algorithms in aspects of convergence rate, solution precision, and robustness. In the stability analysis, AGG-GCRA consistently obtained the global optimal solution in multiple runs for five engineering cases, achieving an average rank of first place and a standard deviation close to zero, highlighting its exceptional global search capabilities and excellent repeatability. Statistical tests, including the Friedman ranking and Wilcoxon signed-rank tests, provide additional validation for the effectiveness and importance of the proposed algorithm. In conclusion, AGG-GCRA provides an efficient and stable intelligent optimization tool for solving various optimization problems.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 9","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467549/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147475","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Cam-Based Simple Design of Constant-Force Suspension Backpack to Isolate Dynamic Load.","authors":"Haotian Ju, Zihang Guan, Junchen Liu, Yao Huang, Kerui Sun, Lele Li, Weimao Wang, Tianjiao Zheng, Quan Xiong, Jie Zhao, Yanhe Zhu","doi":"10.3390/biomimetics10090607","DOIUrl":"10.3390/biomimetics10090607","url":null,"abstract":"<p><p>Prolonged load carriage with ordinary backpacks (OBs) can cause muscle fatigue and skeletal injuries. Research indicates that suspended backpacks can effectively reduce energy expenditure; however, existing elastic rope-based suspension backpacks struggle to adapt to different speeds, while active suspension backpacks gain significant additional weight due to the incorporated motors and batteries. This paper presents a novel cam-based constant-force suspension backpack (CCSB). The CCSB employs a cam-spring mechanism with near-zero suspension stiffness to minimize the inertial forces generated by load oscillations. A test platform was constructed to evaluate the constant-force performance of the mechanism, showing a maximum error of less than 1.96%. Load-carrying experiments were conducted at different walking speeds. Laboratory test results show that, compared with OBs, the CCSB reduces peak accelerative vertical force by an average of 84.47% and reduces human metabolic costs by 10.58%. Outdoor tests show that the CCSB can reduce transportation consumption by 8.26%. The CCSB's compact structure makes it more suitable for commercialization and demonstrates significant potential for practical applications.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 9","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467801/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced Robust Heading Control for Unmanned Surface Vessels Using Hybrid Metaheuristic-Optimized Variable Universe Fuzzy PID with Enhanced Smith Predictor.","authors":"Siyu Zhan, Qiang Liu, Zhao Zhao, Shen'ao Zhang, Yaning Xu","doi":"10.3390/biomimetics10090611","DOIUrl":"10.3390/biomimetics10090611","url":null,"abstract":"<p><p>With the increasing deployment of unmanned surface vessels (USVs) in complex marine operations such as ocean monitoring, search and rescue, and military reconnaissance, precise heading control under environmental disturbances and system delays has become a critical challenge. This paper presents an advanced robust heading control strategy for USVs operating under these demanding conditions. The proposed approach integrates three key innovations: (1) an enhanced Smith predictor for accurate time-delay compensation, (2) a variable-universe fuzzy PID controller with self-adaptive scaling domains that dynamically adjust to error magnitude and rate of change, and (3) a hybrid metaheuristic optimization algorithm combining beetle antennae search, harmony search, and genetic algorithm (BAS-HSA-GA) for optimal parameter tuning. Through comprehensive simulations using a Nomoto first-order time-delay model under combined white noise and second-order wave disturbances, the system demonstrates superior performance with over 90% reduction in steady-state heading error and ≈30% faster settling time compared to conventional PID and single-optimization fuzzy PID methods. Field trials under sea-state 4 conditions confirm 15-25% lower tracking error in realistic operating scenarios. The controller's stability is rigorously verified through Lyapunov analysis, while comparative studies show significant improvements in S-shaped path tracking performance, achieving better IAE/ITAE metrics than DRL, ANFC, and ACO approaches. This work provides a comprehensive solution for high-precision, delay-resilient USV heading control in dynamic marine environments.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 9","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467373/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Non-Bactericidal Antifouling Coating Inspired by the \"Swinging Effect\" of Coral Tentacles in Waves.","authors":"Yue Yin, Jianfu Wang, Xu Zheng","doi":"10.3390/biomimetics10090606","DOIUrl":"10.3390/biomimetics10090606","url":null,"abstract":"<p><p>Inspired by the free swing of coral tentacles driven by water currents to actively repel microbial attachment, we have identified a unique physical anti-fouling strategy: coral \"swinging effect\" anti-fouling. Taking the fleshy soft coral (<i>Sarcophyton trocheliophorum</i>) as an example, its surface is covered with numerous soft tentacles. These coral tentacles utilize the force of water current fluctuations to freely sway, resembling a \"feather duster\" waving to repel microorganisms attempting to settle and establish themselves. Based on this characteristic, this study delves into the living habits of corals, observing the expansion and contraction cycles of their tentacles. Simultaneously, simulations of the anti-fouling performance of coral tentacles were conducted. It demonstrates that the \"swinging effect\" of the tentacles can effectively prevent the attachment of fouling organisms. Furthermore, this study uses <i>S. trocheliophorum</i> as a biomimetic prototype to design and prepare an artificial coral-mimic substrate (ACMS). It employs the common marine Gram-negative bacterium <i>Paracoccus pantotrophus</i> as a microbial sample to test anti-fouling performance in both pure static water environments and low-flow water environments. The results showed that the 13 mm-long ACMS could bend and overlap the surface of the rear tentacles to the greatest extent under the unidirectional scouring action of low-speed water flow (3.5 m/s), forming an anti-fouling protective layer. Additionally, the \"swinging effect\" phenomenon generated by the tentacles under water flow scouring demonstrated excellent anti-fouling effects. This study not only provides further evidence for research on coral antifouling performance but also offers new concepts and ideas for antifouling strategies in low-flow water environments, such as stationary ships in ports and underwater infrastructure facilities at docks.</p>","PeriodicalId":8907,"journal":{"name":"Biomimetics","volume":"10 9","pages":""},"PeriodicalIF":3.9,"publicationDate":"2025-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12467940/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145147554","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}