Cyborg and bionic systems (Washington, D.C.)最新文献_第4页

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

A Versatile Continuum Gripping Robot with a Concealable Gripper. 带有隐蔽式抓手的多功能连续抓取机器人

IF 10.5

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-01-01 Epub Date: 2023-02-24 DOI: 10.34133/cbsystems.0003

Shuailong Zhang, Fenggang Li, Rongxin Fu, Hang Li, Suli Zou, Nan Ma, Shengyuan Qu, Jian Li

{"title":"A Versatile Continuum Gripping Robot with a Concealable Gripper.","authors":"Shuailong Zhang, Fenggang Li, Rongxin Fu, Hang Li, Suli Zou, Nan Ma, Shengyuan Qu, Jian Li","doi":"10.34133/cbsystems.0003","DOIUrl":"10.34133/cbsystems.0003","url":null,"abstract":"Continuum robots with their inherent compliance provide the potential for crossing narrow unstructured workspace and safely grasping various objects. However, the display gripper increases the size of the robots, and therefore, it tends to get stuck in constrained environments. This paper proposes a versatile continuum grasping robot (CGR) with a concealable gripper. The CGR can capture large objects with respect to the robot's scale using the continuum manipulator and can grasp various objects using the end concealable gripper especially in narrow and unstructured workspaces. To perform the cooperative operation of the concealable gripper and the continuum manipulator, a global kinematic model based on screw theory and a motion planning approach referred to as \"multi-node synergy method\" for the CGR are presented. The simulation and experimental results show that objects of different shapes and sizes can be captured by the same CGR even in complex and narrow environments. Finally, in the future, the CGR is expected to serve for satellite capture in harsh space environments such as high vacuum, strong radiation, and extreme temperatures.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0003"},"PeriodicalIF":10.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076060/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9289766","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

Movement Optimization for a Cyborg Cockroach in a Bounded Space Incorporating Machine Learning. 结合机器学习的有界空间半机械蟑螂运动优化。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-01-01 DOI: 10.34133/cbsystems.0012

Mochammad Ariyanto, Chowdhury Mohammad Masum Refat, Kazuyoshi Hirao, Keisuke Morishima

{"title":"Movement Optimization for a Cyborg Cockroach in a Bounded Space Incorporating Machine Learning.","authors":"Mochammad Ariyanto, Chowdhury Mohammad Masum Refat, Kazuyoshi Hirao, Keisuke Morishima","doi":"10.34133/cbsystems.0012","DOIUrl":"https://doi.org/10.34133/cbsystems.0012","url":null,"abstract":"Cockroaches can traverse unknown obstacle-terrain, self-right on the ground and climb above the obstacle. However, they have limited motion, such as less activity in light/bright areas and lower temperatures. Therefore, the movement of the cyborg cockroaches needs to be optimized for the utilization of the cockroach as a cyborg insect. This study aims to increase the search rate and distance traveled by cockroaches and reduce the stop time by utilizing automatic stimulation from machine learning. Multiple machine learning classifiers were applied to classify the offline binary classification of the cockroach movement based on the inertial measuring unit input signals. Ten time-domain features were chosen and applied as the classifier inputs. The highest performance of the classifiers was implemented for the online motion recognition and automatic stimulation provided to the cerci to trigger the free walking motion of the cockroach. A user interface was developed to run multiple computational processes simultaneously in real time such as computer vision, data acquisition, feature extraction, automatic stimulation, and machine learning using a multithreading algorithm. On the basis of the experiment results, we successfully demonstrated that the movement performance of cockroaches was importantly improved by applying machine learning classification and automatic stimulation. This system increased the search rate and traveled distance by 68% and 70%, respectively, while the stop time was reduced by 78%.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0012"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10019993/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9643132","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: 6

Field-Controlled Microrobots Fabricated by Photopolymerization. 光聚合制备的场控微型机器人。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-01-01 DOI: 10.34133/cbsystems.0009

Xiyue Liang, Zhuo Chen, Yan Deng, Dan Liu, Xiaoming Liu, Qiang Huang, Tatsuo Arai

{"title":"Field-Controlled Microrobots Fabricated by Photopolymerization.","authors":"Xiyue Liang, Zhuo Chen, Yan Deng, Dan Liu, Xiaoming Liu, Qiang Huang, Tatsuo Arai","doi":"10.34133/cbsystems.0009","DOIUrl":"https://doi.org/10.34133/cbsystems.0009","url":null,"abstract":"Field-controlled microrobots have attracted extensive research in the biological and medical fields due to the prominent characteristics including high flexibility, small size, strong controllability, remote manipulation, and minimal damage to living organisms. However, the fabrication of these field-controlled microrobots with complex and high-precision 2- or 3-dimensional structures remains challenging. The photopolymerization technology is often chosen to fabricate field-controlled microrobots due to its fast-printing velocity, high accuracy, and high surface quality. This review categorizes the photopolymerization technologies utilized in the fabrication of field-controlled microrobots into stereolithography, digital light processing, and 2-photon polymerization. Furthermore, the photopolymerized microrobots actuated by different field forces and their functions are introduced. Finally, we conclude the future development and potential applications of photopolymerization for the fabrication of field-controlled microrobots.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0009"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10243896/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9954549","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: 2

Learning Rat-Like Behavioral Interaction Using a Small-Scale Robotic Rat. 用小型机器老鼠学习老鼠的行为互动。

Cyborg and bionic systems (Washington, D.C.) Pub Date : 2023-01-01 DOI: 10.34133/cbsystems.0032

Hongzhao Xie, Zihang Gao, Guanglu Jia, Shingo Shimoda, Qing Shi

{"title":"Learning Rat-Like Behavioral Interaction Using a Small-Scale Robotic Rat.","authors":"Hongzhao Xie, Zihang Gao, Guanglu Jia, Shingo Shimoda, Qing Shi","doi":"10.34133/cbsystems.0032","DOIUrl":"https://doi.org/10.34133/cbsystems.0032","url":null,"abstract":"In this paper, we propose a novel method for emulating rat-like behavioral interactions in robots using reinforcement learning. Specifically, we develop a state decision method to optimize the interaction process among 6 known behavior types that have been identified in previous research on rat interactions. The novelty of our method lies in using the temporal difference (TD) algorithm to optimize the state decision process, which enables the robots to make informed decisions about their behavior choices. To assess the similarity between robot and rat behavior, we use Pearson correlation. We then use TD-λ to update the state value function and make state decisions based on probability. The robots execute these decisions using our dynamics-based controller. Our results demonstrate that our method can generate rat-like behaviors on both short- and long-term timescales, with interaction information entropy comparable to that between real rats. Overall, our approach shows promise for controlling robots in robot-rat interactions and highlights the potential of using reinforcement learning to develop more sophisticated robotic systems.","PeriodicalId":72764,"journal":{"name":"Cyborg and bionic systems (Washington, D.C.)","volume":"4 ","pages":"0032"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10278959/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"10086098","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