Cyborg and bionic systems (Washington, D.C.)最新文献_第7页

Integrated Design Fabrication and Control of a Bioinspired Multimaterial Soft Robotic Hand. 生物启发多材料软机械手的集成设计制造与控制

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-08-08 eCollection Date: 2023-01-01 DOI: 10.34133/cbsystems.0051

Samuel Alves, Mihail Babcinschi, Afonso Silva, Diogo Neto, Diogo Fonseca, Pedro Neto

{"title":"Integrated Design Fabrication and Control of a Bioinspired Multimaterial Soft Robotic Hand.","authors":"Samuel Alves, Mihail Babcinschi, Afonso Silva, Diogo Neto, Diogo Fonseca, Pedro Neto","doi":"10.34133/cbsystems.0051","DOIUrl":"10.34133/cbsystems.0051","url":null,"abstract":"Machines that mimic humans have inspired scientists for centuries. Bioinspired soft robotic hands are a good example of such an endeavor, featuring intrinsic material compliance and continuous motion to deal with uncertainty and adapt to unstructured environments. Recent research led to impactful achievements in functional designs, modeling, fabrication, and control of soft robots. Nevertheless, the full realization of life-like movements is still challenging to achieve, often based on trial-and-error considerations from design to fabrication, consuming time and resources. In this study, a soft robotic hand is proposed, composed of soft actuator cores and an exoskeleton, featuring a multimaterial design aided by finite element analysis (FEA) to define the hand geometry and promote finger's bendability. The actuators are fabricated using molding, and the exoskeleton is 3D-printed in a single step. An ON-OFF controller keeps the set fingers' inner pressures related to specific bending angles, even in the presence of leaks. The FEA numerical results were validated by experimental tests, as well as the ability of the hand to grasp objects with different shapes, weights, and sizes. This integrated solution will make soft robotic hands more available to people, at a reduced cost, avoiding the time-consuming design-fabrication trial-and-error processes.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0051"},"PeriodicalIF":10.5,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10408382/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9973572","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

Bioprinting Methods for Fabricating In Vitro Tubular Blood Vessel Models. 制造体外管状血管模型的生物打印方法。

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-08-01 eCollection Date: 2023-01-01 DOI: 10.34133/cbsystems.0043

Seon-Jin Kim, Min-Gyun Kim, Jangho Kim, Jessie S Jeon, Jinsoo Park, Hee-Gyeong Yi

{"title":"Bioprinting Methods for Fabricating In Vitro Tubular Blood Vessel Models.","authors":"Seon-Jin Kim, Min-Gyun Kim, Jangho Kim, Jessie S Jeon, Jinsoo Park, Hee-Gyeong Yi","doi":"10.34133/cbsystems.0043","DOIUrl":"10.34133/cbsystems.0043","url":null,"abstract":"Dysfunctional blood vessels are implicated in various diseases, including cardiovascular diseases, neurodegenerative diseases, and cancer. Several studies have attempted to prevent and treat vascular diseases and understand interactions between these diseases and blood vessels across different organs and tissues. Initial studies were conducted using 2-dimensional (2D) in vitro and animal models. However, these models have difficulties in mimicking the 3D microenvironment in human, simulating kinetics related to cell activities, and replicating human pathophysiology; in addition, 3D models involve remarkably high costs. Thus, in vitro bioengineered models (BMs) have recently gained attention. BMs created through biofabrication based on tissue engineering and regenerative medicine are breakthrough models that can overcome limitations of 2D and animal models. They can also simulate the natural microenvironment in a patient- and target-specific manner. In this review, we will introduce 3D bioprinting methods for fabricating bioengineered blood vessel models, which can serve as the basis for treating and preventing various vascular diseases. Additionally, we will describe possible advancements from tubular to vascular models. Last, we will discuss specific applications, limitations, and future perspectives of fabricated BMs.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0043"},"PeriodicalIF":10.5,"publicationDate":"2023-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10393580/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9987113","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

Neural Decoding for Intracortical Brain-Computer Interfaces. 皮层内脑机接口的神经解码

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-07-28 eCollection Date: 2023-01-01 DOI: 10.34133/cbsystems.0044

Yuanrui Dong, Shirong Wang, Qiang Huang, Rune W Berg, Guanghui Li, Jiping He

引用次数: 0

Cross-Frequency Coupling and Intelligent Neuromodulation. 跨频耦合与智能神经调制

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-05-31 eCollection Date: 2023-01-01 DOI: 10.34133/cbsystems.0034

Chien-Hung Yeh, Chuting Zhang, Wenbin Shi, Men-Tzung Lo, Gerd Tinkhauser, Ashwini Oswal

{"title":"Cross-Frequency Coupling and Intelligent Neuromodulation.","authors":"Chien-Hung Yeh, Chuting Zhang, Wenbin Shi, Men-Tzung Lo, Gerd Tinkhauser, Ashwini Oswal","doi":"10.34133/cbsystems.0034","DOIUrl":"10.34133/cbsystems.0034","url":null,"abstract":"Cross-frequency coupling (CFC) reflects (nonlinear) interactions between signals of different frequencies. Evidence from both patient and healthy participant studies suggests that CFC plays an essential role in neuronal computation, interregional interaction, and disease pathophysiology. The present review discusses methodological advances and challenges in the computation of CFC with particular emphasis on potential solutions to spurious coupling, inferring intrinsic rhythms in a targeted frequency band, and causal interferences. We specifically focus on the literature exploring CFC in the context of cognition/memory tasks, sleep, and neurological disorders, such as Alzheimer's disease, epilepsy, and Parkinson's disease. Furthermore, we highlight the implication of CFC in the context and for the optimization of invasive and noninvasive neuromodulation and rehabilitation. Mainly, CFC could support advancing the understanding of the neurophysiology of cognition and motor control, serve as a biomarker for disease symptoms, and leverage the optimization of therapeutic interventions, e.g., closed-loop brain stimulation. Despite the evident advantages of CFC as an investigative and translational tool in neuroscience, further methodological improvements are required to facilitate practical and correct use in cyborg and bionic systems in the field.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0034"},"PeriodicalIF":10.5,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10231647/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9559675","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

Engineering In vitro Models: Bioprinting of Organoids with Artificial Intelligence. 工程体外模型:人工智能类器官生物打印。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-01-01 DOI: 10.34133/cbsystems.0018

Hyungseok Lee

{"title":"Engineering In vitro Models: Bioprinting of Organoids with Artificial Intelligence.","authors":"Hyungseok Lee","doi":"10.34133/cbsystems.0018","DOIUrl":"https://doi.org/10.34133/cbsystems.0018","url":null,"abstract":"In the last decade, organoids have gained popularity for developing mini-organs to support advancements in the study of organogenesis, disease modeling, and drug screening and, subsequently, in the development of new therapies. To date, such cultures have been used to replicate the composition and functionality of organs such as the kidney, liver, brain, and pancreas. However, depending on the experimenter, the culture environment and cell conditions may slightly vary, resulting in different organoids; this factor significantly affects their application in new drug development, especially during quantification. Standardization in this context can be achieved using bioprinting technology-an advanced technology that can print various cells and biomaterials at desired locations. This technology offers numerous advantages, including the manufacturing of complex three-dimensional biological structures. Therefore, in addition to the standardization of organoids, bioprinting technology in organoid engineering can facilitate automation in the fabrication process as well as a closer mimicry of native organs. Further, artificial intelligence (AI) has currently emerged as an effective tool to monitor and control the quality of final developed objects. Thus, organoids, bioprinting technology, and AI can be combined to obtain high-quality in vitro models for multiple applications.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0018"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10057937/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9282383","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: 3

Cross-Subject Emotion Recognition Brain-Computer Interface Based on fNIRS and DBJNet. 基于fNIRS和DBJNet的跨主体情绪识别脑机接口。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-01-01 DOI: 10.34133/cbsystems.0045

Xiaopeng Si, Huang He, Jiayue Yu, Dong Ming

{"title":"Cross-Subject Emotion Recognition Brain-Computer Interface Based on fNIRS and DBJNet.","authors":"Xiaopeng Si, Huang He, Jiayue Yu, Dong Ming","doi":"10.34133/cbsystems.0045","DOIUrl":"https://doi.org/10.34133/cbsystems.0045","url":null,"abstract":"Functional near-infrared spectroscopy (fNIRS) is a noninvasive brain imaging technique that has gradually been applied in emotion recognition research due to its advantages of high spatial resolution, real time, and convenience. However, the current research on emotion recognition based on fNIRS is mainly limited to within-subject, and there is a lack of related work on emotion recognition across subjects. Therefore, in this paper, we designed an emotion evoking experiment with videos as stimuli and constructed the fNIRS emotion recognition database. On this basis, deep learning technology was introduced for the first time, and a dual-branch joint network (DBJNet) was constructed, creating the ability to generalize the model to new participants. The decoding performance obtained by the proposed model shows that fNIRS can effectively distinguish positive versus neutral versus negative emotions (accuracy is 74.8%, F1 score is 72.9%), and the decoding performance on the 2-category emotion recognition task of distinguishing positive versus neutral (accuracy is 89.5%, F1 score is 88.3%), negative versus neutral (accuracy is 91.7%, F1 score is 91.1%) proved fNIRS has a powerful ability to decode emotions. Furthermore, the results of the ablation study of the model structure demonstrate that the joint convolutional neural network branch and the statistical branch achieve the highest decoding performance. The work in this paper is expected to facilitate the development of fNIRS affective brain-computer interface.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0045"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10374245/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10266866","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

Time-Varying Functional Connectivity of Rat Brain during Bipedal Walking on Unexpected Terrain. 意外地形下大鼠两足行走时脑功能连接的时变研究。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-01-01 DOI: 10.34133/cbsystems.0017

Honghao Liu, Bo Li, Pengcheng Xi, Yafei Liu, Fenggang Li, Yiran Lang, Rongyu Tang, Nan Ma, Jiping He

{"title":"Time-Varying Functional Connectivity of Rat Brain during Bipedal Walking on Unexpected Terrain.","authors":"Honghao Liu, Bo Li, Pengcheng Xi, Yafei Liu, Fenggang Li, Yiran Lang, Rongyu Tang, Nan Ma, Jiping He","doi":"10.34133/cbsystems.0017","DOIUrl":"https://doi.org/10.34133/cbsystems.0017","url":null,"abstract":"The cerebral cortex plays an important role in human and other animal adaptation to unpredictable terrain changes, but little was known about the functional network among the cortical areas during this process. To address the question, we trained 6 rats with blocked vision to walk bipedally on a treadmill with a random uneven area. Whole-brain electroencephalography signals were recorded by 32-channel implanted electrodes. Afterward, we scan the signals from all rats using time windows and quantify the functional connectivity within each window using the phase-lag index. Finally, machine learning algorithms were used to verify the possibility of dynamic network analysis in detecting the locomotion state of rats. We found that the functional connectivity level was higher in the preparation phase compared to the walking phase. In addition, the cortex pays more attention to the control of hind limbs with higher requirements for muscle activity. The level of functional connectivity was lower where the terrain ahead can be predicted. Functional connectivity bursts after the rat accidentally made contact with uneven terrain, while in subsequent movement, it was significantly lower than normal walking. In addition, the classification results show that using the phase-lag index of multiple gait phases as a feature can effectively detect the locomotion states of rat during walking. These results highlight the role of the cortex in the adaptation of animals to unexpected terrain and may help advance motor control studies and the design of neuroprostheses.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0017"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10072972/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9658055","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 Heuristically Accelerated Reinforcement Learning-Based Neurosurgical Path Planner. 基于启发式加速强化学习的神经外科路径规划。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-01-01 DOI: 10.34133/cbsystems.0026

Guanglin Ji, Qian Gao, Tianwei Zhang, Lin Cao, Zhenglong Sun

{"title":"A Heuristically Accelerated Reinforcement Learning-Based Neurosurgical Path Planner.","authors":"Guanglin Ji, Qian Gao, Tianwei Zhang, Lin Cao, Zhenglong Sun","doi":"10.34133/cbsystems.0026","DOIUrl":"https://doi.org/10.34133/cbsystems.0026","url":null,"abstract":"The steerable needle becomes appealing in the neurosurgery intervention procedure because of its flexibility to bypass critical regions inside the brain; with proper path planning, it can also minimize the potential damage by setting constraints and optimizing the insertion path. Recently, reinforcement learning (RL)-based path planning algorithm has shown promising results in neurosurgery, but because of the trial and error mechanism, it can be computationally expensive and insecure with low training efficiency. In this paper, we propose a heuristically accelerated deep Q network (DQN) algorithm to safely preoperatively plan a needle insertion path in a neurosurgical environment. Furthermore, a fuzzy inference system is integrated into the framework as a balance of the heuristic policy and the RL algorithm. Simulations are conducted to test the proposed method in comparison to the traditional greedy heuristic searching algorithm and DQN algorithms. Tests showed promising results of our algorithm in saving over 50 training episodes, calculating path lengths of 0.35 after normalization, which is 0.61 and 0.39 for DQN and traditional greedy heuristic searching algorithm, respectively. Moreover, the maximum curvature during planning is reduced to 0.046 from 0.139 mm-1 using the proposed algorithm compared to DQN.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0026"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10204738/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9880534","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

Body Extension by Using Two Mobile Manipulators. 使用两个移动机械手进行身体伸展。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-01-01 DOI: 10.34133/cbsystems.0014

Yusuke Hirao, Weiwei Wan, Dimitrios Kanoulas, Kensuke Harada

引用次数: 2

An Overview of In Vitro Biological Neural Networks for Robot Intelligence. 用于机器人智能的体外生物神经网络综述。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-01-01 DOI: 10.34133/cbsystems.0001

Zhe Chen, Qian Liang, Zihou Wei, Xie Chen, Qing Shi, Zhiqiang Yu, Tao Sun

{"title":"An Overview of In Vitro Biological Neural Networks for Robot Intelligence.","authors":"Zhe Chen, Qian Liang, Zihou Wei, Xie Chen, Qing Shi, Zhiqiang Yu, Tao Sun","doi":"10.34133/cbsystems.0001","DOIUrl":"https://doi.org/10.34133/cbsystems.0001","url":null,"abstract":"In vitro biological neural networks (BNNs) interconnected with robots, so-called BNN-based neurorobotic systems, can interact with the external world, so that they can present some preliminary intelligent behaviors, including learning, memory, robot control, etc. This work aims to provide a comprehensive overview of the intelligent behaviors presented by the BNN-based neurorobotic systems, with a particular focus on those related to robot intelligence. In this work, we first introduce the necessary biological background to understand the 2 characteristics of the BNNs: nonlinear computing capacity and network plasticity. Then, we describe the typical architecture of the BNN-based neurorobotic systems and outline the mainstream techniques to realize such an architecture from 2 aspects: from robots to BNNs and from BNNs to robots. Next, we separate the intelligent behaviors into 2 parts according to whether they rely solely on the computing capacity (computing capacity-dependent) or depend also on the network plasticity (network plasticity-dependent), which are then expounded respectively, with a focus on those related to the realization of robot intelligence. Finally, the development trends and challenges of the BNN-based neurorobotic systems are discussed.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0001"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076061/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9289763","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: 7