Cyborg and bionic systems (Washington, D.C.)最新文献_第6页

Biomimetic Peripheral Nerve Stimulation Promotes the Rat Hindlimb Motion Modulation in Stepping: An Experimental Analysis. 仿生外周神经刺激促进大鼠后肢在迈步中的运动调节：实验分析

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-07-04 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0131

Pengcheng Xi, Qingyu Yao, Yafei Liu, Jiping He, Rongyu Tang, Yiran Lang

{"title":"Biomimetic Peripheral Nerve Stimulation Promotes the Rat Hindlimb Motion Modulation in Stepping: An Experimental Analysis.","authors":"Pengcheng Xi, Qingyu Yao, Yafei Liu, Jiping He, Rongyu Tang, Yiran Lang","doi":"10.34133/cbsystems.0131","DOIUrl":"10.34133/cbsystems.0131","url":null,"abstract":"Peripheral nerve stimulation is an effective neuromodulation method in patients with lower extremity movement disorders caused by stroke, spinal cord injury, or other diseases. However, most current studies on rehabilitation using sciatic nerve stimulation focus solely on ankle motor regulation through stimulation of common peroneal and tibial nerves. Using the electrical nerve stimulation method, we here achieved muscle control via different sciatic nerve branches to facilitate the regulation of lower limb movements during stepping and standing. A map of relationships between muscles and nerve segments was established to artificially activate specific nerve fibers with the biomimetic stimulation waveform. Then, characteristic curves depicting the relationship between neural electrical stimulation intensity and joint control were established. Finally, by testing the selected stimulation parameters in anesthetized rats, we confirmed that single-cathode extraneural electrical stimulation could activate combined movements to promote lower limb movements. Thus, this method is effective and reliable for use in treatment for improving and rehabilitating lower limb motor dysfunction.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0131"},"PeriodicalIF":10.5,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11223769/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141536074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Augmented Recognition of Distracted Driving State Based on Electrophysiological Analysis of Brain Network. 基于脑网络电生理分析的分心驾驶状态增强识别。

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-07-04 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0130

Geqi Qi, Rui Liu, Wei Guan, Ailing Huang

{"title":"Augmented Recognition of Distracted Driving State Based on Electrophysiological Analysis of Brain Network.","authors":"Geqi Qi, Rui Liu, Wei Guan, Ailing Huang","doi":"10.34133/cbsystems.0130","DOIUrl":"10.34133/cbsystems.0130","url":null,"abstract":"In this study, we propose an electrophysiological analysis-based brain network method for the augmented recognition of different types of distractions during driving. Driver distractions, such as cognitive processing and visual disruptions during driving, lead to distinct alterations in the electroencephalogram (EEG) signals and the extracted brain networks. We designed and conducted a simulated experiment comprising 4 distracted driving subtasks. Three connectivity indices, including both linear and nonlinear synchronization measures, were chosen to construct the brain network. By computing connectivity strengths and topological features, we explored the potential relationship between brain network configurations and states of driver distraction. Statistical analysis of network features indicates substantial differences between normal and distracted states, suggesting a reconfiguration of the brain network under distracted conditions. Different brain network features and their combinations are fed into varied machine learning classifiers to recognize the distracted driving states. The results indicate that XGBoost demonstrates superior adaptability, outperforming other classifiers across all selected network features. For individual networks, features constructed using synchronization likelihood (SL) achieved the highest accuracy in distinguishing between cognitive and visual distraction. The optimal feature set from 3 network combinations achieves an accuracy of 95.1% for binary classification and 88.3% for ternary classification of normal, cognitively distracted, and visually distracted driving states. The proposed method could accomplish the augmented recognition of distracted driving states and may serve as a valuable tool for further optimizing driver assistance systems with distraction control strategies, as well as a reference for future research on the brain-computer interface in autonomous driving.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0130"},"PeriodicalIF":10.5,"publicationDate":"2024-07-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11222012/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141536073","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advances in Prostate Cancer Biomarkers and Probes. 前列腺癌生物标志物及探针研究进展

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-06-27 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0129

Keyi Li, Qiao Wang, Xiaoying Tang, Ozioma Udochukwu Akakuru, Ruobing Li, Yan Wang, Renran Zhang, Zhenqi Jiang, Zhuo Yang

{"title":"Advances in Prostate Cancer Biomarkers and Probes.","authors":"Keyi Li, Qiao Wang, Xiaoying Tang, Ozioma Udochukwu Akakuru, Ruobing Li, Yan Wang, Renran Zhang, Zhenqi Jiang, Zhuo Yang","doi":"10.34133/cbsystems.0129","DOIUrl":"https://doi.org/10.34133/cbsystems.0129","url":null,"abstract":"Prostate cancer is one of the most prevalent malignant tumors in men worldwide, and early diagnosis is essential to improve patient survival. This review provides a comprehensive discussion of recent advances in prostate cancer biomarkers, including molecular, cellular, and exosomal biomarkers. The potential of various biomarkers such as gene fusions (TMPRSS2-ERG), noncoding RNAs (SNHG12), proteins (PSA, PSMA, AR), and circulating tumor cells (CTCs) in the diagnosis, prognosis, and targeted therapies of prostate cancer is emphasized. In addition, this review systematically explores how multi-omics data and artificial intelligence technologies can be used for biomarker discovery and personalized medicine applications. In addition, this review provides insights into the development of specific probes, including fluorescent, electrochemical, and radionuclide probes, for sensitive and accurate detection of prostate cancer biomarkers. In conclusion, this review provides a comprehensive overview of the status and future directions of prostate cancer biomarker research, emphasizing the potential for precision diagnosis and targeted therapy.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0129"},"PeriodicalIF":10.5,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12063729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144051327","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Survey on 3D Skeleton-Based Action Recognition Using Learning Method. 使用学习方法进行基于 3D 骨架的动作识别研究。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-05-16 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0100

Bin Ren, Mengyuan Liu, Runwei Ding, Hong Liu

{"title":"A Survey on 3D Skeleton-Based Action Recognition Using Learning Method.","authors":"Bin Ren, Mengyuan Liu, Runwei Ding, Hong Liu","doi":"10.34133/cbsystems.0100","DOIUrl":"https://doi.org/10.34133/cbsystems.0100","url":null,"abstract":"Three-dimensional skeleton-based action recognition (3D SAR) has gained important attention within the computer vision community, owing to the inherent advantages offered by skeleton data. As a result, a plethora of impressive works, including those based on conventional handcrafted features and learned feature extraction methods, have been conducted over the years. However, prior surveys on action recognition have primarily focused on video or red-green-blue (RGB) data-dominated approaches, with limited coverage of reviews related to skeleton data. Furthermore, despite the extensive application of deep learning methods in this field, there has been a notable absence of research that provides an introductory or comprehensive review from the perspective of deep learning architectures. To address these limitations, this survey first underscores the importance of action recognition and emphasizes the significance of 3-dimensional (3D) skeleton data as a valuable modality. Subsequently, we provide a comprehensive introduction to mainstream action recognition techniques based on 4 fundamental deep architectures, i.e., recurrent neural networks, convolutional neural networks, graph convolutional network, and Transformers. All methods with the corresponding architectures are then presented in a data-driven manner with detailed discussion. Finally, we offer insights into the current largest 3D skeleton dataset, NTU-RGB+D, and its new edition, NTU-RGB+D 120, along with an overview of several top-performing algorithms on these datasets. To the best of our knowledge, this research represents the first comprehensive discussion of deep learning-based action recognition using 3D skeleton data.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0100"},"PeriodicalIF":0.0,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11096730/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140960067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Advances in the Model Structure of In Vitro Vascularized Organ-on-a-Chip. 体外血管化器官芯片模型结构研究进展。

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-04-25 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0107

Hongze Yin, Yue Wang, Na Liu, Songyi Zhong, Long Li, Quan Zhang, Zeyang Liu, Tao Yue

{"title":"Advances in the Model Structure of In Vitro Vascularized Organ-on-a-Chip.","authors":"Hongze Yin, Yue Wang, Na Liu, Songyi Zhong, Long Li, Quan Zhang, Zeyang Liu, Tao Yue","doi":"10.34133/cbsystems.0107","DOIUrl":"https://doi.org/10.34133/cbsystems.0107","url":null,"abstract":"Microvasculature plays a crucial role in human physiology and is closely related to various human diseases. Building in vitro vascular networks is essential for studying vascular tissue behavior with repeatable morphology and signaling conditions. Engineered 3D microvascular network models, developed through advanced microfluidic-based techniques, provide accurate and reproducible platforms for studying the microvasculature in vitro, an essential component for designing organ-on-chips to achieve greater biological relevance. By optimizing the microstructure of microfluidic devices to closely mimic the in vivo microenvironment, organ-specific models with healthy and pathological microvascular tissues can be created. This review summarizes recent advancements in in vitro strategies for constructing microvascular tissue and microfluidic devices. It discusses the static vascularization chips' classification, structural characteristics, and the various techniques used to build them: growing blood vessels on chips can be either static or dynamic, and in vitro blood vessels can be grown in microchannels, elastic membranes, and hydrogels. Finally, the paper discusses the application scenarios and key technical issues of existing vascularization chips. It also explores the potential for a novel organoid chip vascularization approach that combines organoids and organ chips to generate better vascularization chips.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0107"},"PeriodicalIF":10.5,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12063728/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144029711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Magnetic Soft Microrobot Design for Cell Grasping and Transportation. 用于细胞抓取和运输的磁性软微型机器人设计

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-04-25 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0109

Fanghao Wang, Youchao Zhang, Daoyuan Jin, Zhongliang Jiang, Yaqian Liu, Alois Knoll, Huanyu Jiang, Yibin Ying, Mingchuan Zhou

{"title":"Magnetic Soft Microrobot Design for Cell Grasping and Transportation.","authors":"Fanghao Wang, Youchao Zhang, Daoyuan Jin, Zhongliang Jiang, Yaqian Liu, Alois Knoll, Huanyu Jiang, Yibin Ying, Mingchuan Zhou","doi":"10.34133/cbsystems.0109","DOIUrl":"https://doi.org/10.34133/cbsystems.0109","url":null,"abstract":"Manipulating cells at a small scale is widely acknowledged as a complex and challenging task, especially when it comes to cell grasping and transportation. Various precise methods have been developed to remotely control the movement of microrobots. However, the manipulation of micro-objects necessitates the use of end-effectors. This paper presents a study on the control of movement and grasping operations of a magnetic microrobot, utilizing only 3 pairs of electromagnetic coils. A specially designed microgripper is employed on the microrobot for efficient cell grasping and transportation. To ensure precise grasping, a bending deformation model of the microgripper is formulated and subsequently validated. To achieve precise and reliable transportation of cells to specific positions, an approach that combines an extended Kalman filter with a model predictive control method is adopted to accomplish the trajectory tracking task. Through experiments, we observe that by applying the proposed control strategy, the mean absolute error of path tracking is found to be less than 0.155 mm. Remarkably, this value accounts for only 1.55% of the microrobot's size, demonstrating the efficacy and accuracy of our control strategy. Furthermore, an experiment involving the grasping and transportation of a zebrafish embryonic cell (diameter: 800 μm) is successfully conducted. The results of this experiment not only validate the precision and effectiveness of the proposed microrobot and its associated models but also highlight its tremendous potential for cell manipulation in vitro and in vivo.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0109"},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11052606/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140869636","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

MonoAux: Fully Exploiting Auxiliary Information and Uncertainty for Monocular 3D Object Detection. MonoAux：充分利用辅助信息和不确定性进行单目三维物体检测

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2024-03-27 eCollection Date: 2024-01-01 DOI: 10.34133/cbsystems.0097

Zhenglin Li, Wenbo Zheng, Le Yang, Liyan Ma, Yang Zhou, Yan Peng

{"title":"MonoAux: Fully Exploiting Auxiliary Information and Uncertainty for Monocular 3D Object Detection.","authors":"Zhenglin Li, Wenbo Zheng, Le Yang, Liyan Ma, Yang Zhou, Yan Peng","doi":"10.34133/cbsystems.0097","DOIUrl":"10.34133/cbsystems.0097","url":null,"abstract":"Monocular 3D object detection plays a pivotal role in autonomous driving, presenting a formidable challenge by requiring the precise localization of 3D objects within a single image, devoid of depth information. Most existing methods in this domain fall short of harnessing the limited information available in monocular 3D detection tasks. They typically provide only a single detection outcome, omitting essential uncertainty analysis and result post-processing during model inference, thus limiting overall model performance. In this paper, we propose a comprehensive framework that maximizes information extraction from monocular images while encompassing diverse depth estimation and incorporating uncertainty analysis. Specifically, we mine additional information intrinsic to the monocular 3D detection task to augment supervision, thereby addressing the information scarcity challenge. Moreover, our framework handles depth estimation by recovering multiple sets of depth values from calculated visual heights. The final depth estimate and 3D confidence are determined through an uncertainty fusion process, effectively reducing inference errors. Furthermore, to address task weight allocation in multi-task training, we present a versatile training strategy tailored to monocular 3D detection. This approach leverages measurement indicators to monitor task progress, adaptively adjusting loss weights for different tasks. Experimental results on the KITTI and Waymo dataset confirm the effectiveness of our approach. The proposed method consistently provides enhanced performance across various difficulty levels compared to the original framework while maintaining real-time efficiency.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"5 ","pages":"0097"},"PeriodicalIF":0.0,"publicationDate":"2024-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10976585/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140320040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rational Design of Bioactive Materials for Bone Hemostasis and Defect Repair. 骨止血及骨缺损修复生物活性材料的合理设计。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-10-11 eCollection Date: 2023-01-01 DOI: 10.34133/cbsystems.0058

Yuqi Gai, Yue Yin, Ling Guan, Shengchang Zhang, Jiatian Chen, Junyuan Yang, Huaijuan Zhou, Jinhua Li

{"title":"Rational Design of Bioactive Materials for Bone Hemostasis and Defect Repair.","authors":"Yuqi Gai, Yue Yin, Ling Guan, Shengchang Zhang, Jiatian Chen, Junyuan Yang, Huaijuan Zhou, Jinhua Li","doi":"10.34133/cbsystems.0058","DOIUrl":"10.34133/cbsystems.0058","url":null,"abstract":"Everyday unnatural events such as trauma, accidents, military conflict, disasters, and even medical malpractice create open wounds and massive blood loss, which can be life-threatening. Fractures and large bone defects are among the most common types of injuries. Traditional treatment methods usually involve rapid hemostasis and wound closure, which are convenient and fast but may result in various complications such as nerve injury, deep infection, vascular injury, and deep hematomas. To address these complications, various studies have been conducted on new materials that can be degraded in the body and reduce inflammation and abscesses in the surgical area. This review presents the latest research progress in biomaterials for bone hemostasis and repair. The mechanisms of bone hemostasis and bone healing are first introduced and then principles for rational design of biomaterials are summarized. After providing representative examples of hemostatic biomaterials for bone repair, future challenges and opportunities in the field are proposed.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0058"},"PeriodicalIF":0.0,"publicationDate":"2023-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10566342/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41221467","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

A Review of Energy Supply for Biomachine Hybrid Robots. 生物机械混合机器人能源供应综述。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-09-26 eCollection Date: 2023-01-01 DOI: 10.34133/cbsystems.0053

Zhiyun Ma, Jieliang Zhao, Li Yu, Mengdan Yan, Lulu Liang, Xiangbing Wu, Mengdi Xu, Wenzhong Wang, Shaoze Yan

引用次数: 0

Emulation of Brain Metabolic Activities Based on a Dynamically Controllable Optical Phantom. 基于动态可控光体的脑代谢活动仿真

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-09-13 eCollection Date: 2023-01-01 DOI: 10.34133/cbsystems.0047

Yuxiang Lin, Cheng Chen, Zhouchen Ma, Nabil Sabor, Yanyan Wei, Tianhong Zhang, Mohamad Sawan, Guoxing Wang, Jian Zhao

引用次数: 0