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A convolutional neural network-based diagnostic method using resting-state electroencephalograph signals for major depressive and bipolar disorders

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Biomedical Signal Processing and control 2022年第PartB期72卷 103370-103370页

作者： Lei, Yu Belkacem, Abdelkader Nasreddine Wang, Xiaotian Sha, Sha Wang, Changming Chen, Chao Beijing Institute of Basic Medical Sciences Beijing China Department of Computer and Network Engineering College of Information Technology United Arab Emirates University Al Ain United Arab Emirates School of Artificial Intelligence Xidian University Xian China National Clinical Research Center for Mental Disorders & Beijing Key Laboratory of Mental Disorders Beijing Anding Hospital Capital Medical University Beijing China Brain-inspired Intelligence and Clinical Translational Research Center/Department of Neurosurgery Xuanwu Hospital Capitap Medical University Beijing China Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology China Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin China

Background: Early and accurate diagnosis of bipolar and major depressive disorders is important in clinical practice. However, no diagnostic biomarkers can discriminate bipolar from major depressive disorder with high accuracy at present. Methods: We propose a novel convolutional neural network architecture using multichannel raw resting-state electroencephalograph signals to differentiate bipolar disorder from major depressive disorder. This method has great potential in diagnosing mental disorders. In total, 101 patients with major depressive disorder, 82 patients with bipolar disorder, and 81 healthy controls were assessed. Clinical diagnosis was performed by psychiatrists based on the Diagnostic and Statistical Manual of Mental Disorders, fifth edition. Participants were instructed to fix their eyes on a cross on the monitor during the collection of resting-state electroencephalograph signals. Results: A classification mean accuracy of 96.88% was achieved using the resting-state electroencephalograph signals with the 10-fold cross-validation method. The results indicate that deep neural networks could learn efficient feature patterns automatically without manual feature selections. Both statistical analysis and feature visualization on different brain regions showed that the classification performance and the learned features of the proposed model were consistent with that obtained in neurobiological studies on bipolar and major depressive disorders. Conclusions: The combined use of deep neural networks and electroencephalograph signals is an effective approach for the computer-aided diagnosis of bipolar and major depressive disorders. © 2021 Elsevier Ltd

关键词： Deep neural networks

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Study on the Active Movement Capsule Robot for Biopsy

Study on the Active Movement Capsule Robot for Biopsy

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IEEE International Conference on Mechatronics and Automation

作者： Shuxiang Guo Fang Huang Jian Guo Qiang Fu Tianjin Key Laboratory for Control Theory & Application in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Binshui Xidao Extention 391 Tianjin China Kagawa University Takamatsu Kagawa Japan

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

In this paper, a novel biopsy robot is proposed. In order to solve the problem of the single function of the commercial capsule endoscope, this paper proposes a novel biopsy capsule robot driven by an external magnetic field. The module includes two radial magnetized magnetic rings and a biopsy mechanism. Without considering the addition energy consumption, using the coupling effect of the three-axis Helmholtz coil and the robot's built-in magnet, the crank slider mechanism converts the torque acting on the magnet by a uniform rotating magnetic field into the cutting force during biopsy. The magnetic switch used to control the switching between the motion function of the anchor biopsy robot and the anchor biopsy function. Finally, the functional modules in the pipeline of anchored biopsy robot is verified by experiments. The results show that the biopsy robot can realize the robot's anchoring in the intestine while performing the biopsy function. The realization of the biopsy capsule robot has important medical diagnostic significance.

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Evaluation Performance of the Magnetic Rotational Field for Magnetically Actuated Microrobot System

Evaluation Performance of the Magnetic Rotational Field for ...

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IEEE International Conference on Mechatronics and Automation

作者： Qiang Fu Zhuocong Cai Jian Guo Shuxiang Guo Tianjin Key Laboratory for Control Theory & Application in Complicated Systems and Biomedical Robot Laboratory Tianjin University of Technology Binshui Xidao391 Tianjin China Faculty of Engineering and Design Kagawa University Takamatsu Kagawa Japan

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

At present, the capsule robot for clinical examination has been widely used, which can complete the tasks that ordinary cable gastrointestinal endoscopy cannot achieve, especially the magnetic driven capsule robot has become a research trend because of its active control. However, the active control accuracy of the magnetic driven capsule robot is not high, so it is not enough to reach the level of clinical examination. In this study, in order to deal with the difficult operation of the medical magnetic driven capsule robot, a method to drive the micro robot more accurately by controlling the magnetic field is proposed. The electromagnetic simulation is consistent with the parameters of the actual platform. Moreover, its rationality can be verified by mathematical model. The magnetic field platform for medical examination can be improved through this method to achieve a more accurate control level of the capsule robot.

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Classification of Cognitive Ability of Healthy Elderly Individuals Using Resting-State Functional Connectivity Magnetic Resonance Imaging and An Extreme Learning Machine

Research Square

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Research Square 2021年

作者： Yang, Zekun Ge, Manling Abdelkader, Nasreddine Belkacem Fu, Xiaoxuan Zhang, Qirui Chen, Shenghua Xie, Chong Song, Zibo Chen, Chao State Key Laboratory of Reliability and Intelligence of Electrical Equipment Hebei University of Technology Tianjin300130 China Hebei Province Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability Hebei University of Technology Tianjin300130 China Department of Computer and Network Engineering College of Information Technology United Arab Emirates University Al Ain15551 United Arab Emirates Athinoula A. Martinos Center for Biomedical Imaging Department of Radiology Massachusetts General Hospital Harvard Medical School CharlestownMA02129 United States Department of Medical Imaging Jinling Hospital Nanjing University School of Medicine General Hospital of Eastern Theater Nanjing210002 China Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin300003 China

Purpose Quantitative determination of the correlation between cognitive ability and functional biomarkers in the elderly brain is essential. To identify biomarkers associated with cognitive performance in the elderly, this study combined an index model specific for resting-state functional connectivity (FC) magnetic resonance imaging (fcMRI) with a supervised machine learning method. Methods Performance scores on conventional cognitive test batteries and MRI data were obtained for 98 healthy elderly individuals and 90 healthy youth from two public databases. Based on the test scores, the elderly cohort was categorized into two groups: excellent and poor. An fcMRI index model was constructed for each elderly individual to determine the relative differences in FC among brain regions compared with that in the youth cohort. Brain areas sensitive to test scores could then be identified using the fcMRI indexes. To confirm the effectiveness of constructed model, the fcMRI indexes of these brain areas were used as feature matrix inputs for training an extreme learning machine. Classification accuracy was then tested in separate groups and confirmed by N-fold cross-validation. Results This learning study could effectively classify the cognitive status of healthy elderly individuals according to frontal lobe, temporal lobe, and parietal lobe FC values with a mean accuracy of 83.5%, which is substantially higher than that achieved using conventional correlation analysis. Conclusion This fcMRI classification study may facilitate early detection of age-related cognitive decline as well as help reveal the underlying pathological mechanisms. © 2021, CC BY.

关键词： Magnetic resonance imaging

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A joint call for actions to advance taxonomy in China

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Zoological Systematics 2022年第3期47卷 188-197页

作者： Chaodong Zhu Arong Luo Ming Bai Michael COrr Zhonge Hou Siqin Ge Jun Chen Yibo Hu Xuming Zhou Gexia Qiao Hongzhi Kong Limin Lu Xiaohua Jin Lei Cai Xinli Wei Ruilin Zhao Wei Miao Qingfeng Wang Zhongli Sha Qiang Lin Meng Qu Jianping Jiang Jiatang Li Jing Che Xuelong Jiang Xiaoyong Chen Lianming Gao Zongxin Ren Chunlei Xiang Shixiao Luo Donghui Wu Dong Liu Yanqiong Peng Tao Su Chenyang Cai Tianqi Zhu Wanzhi Cai Xingyue Liu Hu Li Huaijun Xue Zhen Ye Xuexin Chen Pu Tang Shujun Wei Hong Pang Qiang Xie Feng Zhang Feng Zhang Xianjin Peng Aibing Zhang Taiping Gao Changfa Zhou Chen Shao Libin Ma Zhaoming Wei Yunxia Luan Ziwei Yin Wu Dai Cong Wei Xiaolei Huang Jingxian Liu Xiangsheng Chen Tianci Yi Zhisheng Zhang Zhulidezi Aishan Qin Li Hongying Hu CAS Key Laboratory of Zoological Systematics and Evolution Institute of ZoologyChinese Academy of SciencesBeijing 100101China CAS Key Laboratory of Animal Ecology and Conservation Biology Institute of ZoologyChinese Academy of SciencesBeijing 100101China State Key Laboratory of Systematic and Evolutionary Botany Institute of BotanyChinese Academy of SciencesBeijing 100093China State Key Laboratory of Mycology(SKLM) Institute of MicrobiologyChinese Academy of SciencesBeijing 100101China CAS Key Laboratory of Aquatic Biodiversity and Conservation Institute of HydrobiologyChinese Academy of SciencesWuhan 430072China Wuhan Botanical Garden Chinese Academy of SciencesWuhan 430074China Department of Marine Organism Taxonomy&Phylogeny Institute of OceanologyChinese Academy of SciencesQingdao 266071China CAS Key Laboratory of Tropical Marine Bio-resources and Ecology South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhou 510301China CAS Key Laboratory of Mountain Ecological Restoration and Bioresource Utilization&Ecological Restoration and Biodiversity Conservation Key Laboratory of Sichuan Province Chengdu Institute of BiologyChinese Academy of SciencesChengdu 610041China State Key Laboratory of Genetic Resources and Evolution&Yunnan Key Laboratory of Biodiversity and Ecological Security of Gaoligong Mountain Kunming Institute of ZoologyChinese Academy of SciencesKunming 650221China CAS Key Laboratory for Plant Diversity and Biogeography of East Asia Kunming Institute of BotanyChinese Academy of SciencesKunming 650201China CAS Key Laboratory of Plant Resource Conservation and Sustainable Utilization South China Botanical GardenChinese Academy of SciencesGuangzhou 510650China CAS Key Laboratory of Wetland Ecology and Environment Northeast Institute of Geography and AgroecologyChinese Academy of SciencesChangchun 130102China CAS Key Laboratory of Tropical Forest Ecology Xishuangbanna Tropical Botanical GardenChinese Academy of SciencesMenglunMenglaYunnan 66630

Taxonomy plays an important role in understanding the origin, evolution, and ecological functionality of biodiversity. There are large number of unknown species yet to be described by taxonomists, which together with their ecosystem services cannot be effectively protected prior to description. Despite this, taxonomy has been increasingly underrated insufficient funds and permanent positions to retain young talents. Further, the impact factordriven evaluation systems in China exacerbate this downward trend, so alternative evaluation metrics are urgently necessary. When the current generation of outstanding taxonomists retires,there will be too few remaining taxonomists left to train the next generation. In light of these challenges, all co-authors worked together on this paper to analyze the current situation of taxonomy and put out a joint call for immediate actions to advance taxonomy in China.

关键词： Endangered taxonomists morphology-based taxonomy integrative taxonomy capacity building systematics

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A Method for Obtaining Contact Force between Catheter Tip and Vascular Wall in Master-slave Robotic System

A Method for Obtaining Contact Force between Catheter Tip an...

引用

IEEE International Conference on Mechatronics and Automation

作者： Xiaoliang Jin Shuxiang Guo Jian Guo Peng Shi Dapeng Song Faculty of Engineering and Design Kagawa University 2217-20 Hayashi-cho Takamatsu Kagawa Japan Key Laboratory of Convergence Medical Engineering System and Healthcare Technology the Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology Beijing China Tianjin Key Laboratory for Control Theory and Application in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

In the research of vascular interventional surgery robotic system, the force information acquisition of surgical tools (guidewires and catheters) has a significant affect on the safety of surgery, especially the contact force between the catheter tip and vascular wall. Therefore. In order to obtain this contact force, we noticed the pressure sensitive rubber because of its piezoresistive effect and easy processing into any shape. a force sensor based on the pressure sensitive rubber was developed in this paper. Once a force is applied on the force sensor attached to the catheter tip, the contact force can be approximated by the piezoresistive effect of the pressure sensitive rubber. The feasibility of the developed force sensor was verified by the experiments in “Vitro”. And the results showed that the force sensor was developed in this paper can accurately detect the contact force between the catheter tip and vascular wall at different positions in the vascular model, the extraction of contact force information of catheter tip is of great significance to the safety of surgery, and the application potential of pressure sensitive rubber.

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End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19

arXiv

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arXiv 2020年

作者： Belkacem, Abdelkader Nasreddine Ouhbi, Sofia Lakas, Abderrahmane Benkhelifa, Elhadj Chen, Chao Department of Computer and Network Engineering CIT UAEU UAE Department of Computer Science and Software Engineering CIT UAEU UAE Cloud Computing and Applications Reseach Lab Staffordshire University United Kingdom Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology China

Respiratory symptoms can be a caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus. These respiratory viruses, often, have common symptoms, including coughing, high temperature, congested nose, and difficulty breathing. However, early diagnosis of the type of the virus, can be crucial, especially in cases such as the recent COVID-19 pandemic. One of the factors that contributed to the spread of the pandemic, was the late diagnosis or confusing it with regular flu-like symptoms. Science has proved that one of the possible differentiators of the underlying causes of these different respiratory diseases is coughing, which comes in different types and forms. Therefore, a reliable lab-free tool for early and more accurate diagnosis that can differentiate between different respiratory diseases is very much needed. This paper proposes an end-to-end portable system that can record data from patients with symptom, including coughs (voluntary or involuntary) and translate them into health data for diagnosis, and with the aid of machine learning, classify them into different respiratory illnesses, including COVID-19. With the ongoing efforts to stop the spread of the COVID-19 disease everywhere today, and against similar diseases in the future, our proposed low cost and user-friendly solution can play an important part in the early diagnosis. Copyright © 2020, The Authors. All rights reserved.

关键词： Diagnosis

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Development of the Insect-inspired Biomimetic Underwater Microrobot for a Father-son Robot System

Development of the Insect-inspired Biomimetic Underwater Mic...

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IEEE International Conference on Mechatronics and Automation

作者： Wenbo Sui Shuxiang Guo Liang Zheng Ruochen An Awa Tendeng Graduate School of Engineering Kagawa University Takamatsu Kagawa Japan Faculty of Engineering and Design Kagawa University Hayashi-cho Kagawa Japan Key Laboratory of Convergence Medical Engineering System and Healthcare Technology the Ministry of Industry and Information Technology School of Life Science Beijing Institute of Technology Beijing China Tianjin Key Laboratory for Control Theory and Application in Complicated Systems and Intelligent Robot Laboratory Tianjin University of Technology Tianjin China

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

In this paper, the lifting platform structure of the father robot and the development of the insect-inspired biomimetic underwater microrobot are presented. The objective is to decrease the load of microrobot and realize more functions. In previous researchers, the platform of the father robot is fixed, which is not conducive to adopt and release the son robot. The structure of the lifting platform can effectively solve the problem in theory. The insect-inspired microrobot used wood which has high hydrophilism. It causes the body of microrobot increased weight and short-term works. The fillable structure with waterproof character which is made by a 3D printer. The new structure also can be changed weight for achieving different functions underwater efficiently. Then, two kinds of communication between the light source and microrobot like chasing rotation and fixed distance chasing are described in order to prove the feasibility of the software. In all these cases, experimental results show the performance of the microrobot.

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Implementation of automatic control system of resistance spot welding for square-rectangular steel tube packing belt 15

Implementation of automatic control system of resistance spo...

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15th IEEE International Conference on Mechatronics and Automation, ICMA 2018

作者： Gao, Qiang Mao, Zemin Li, Dong Cui, Jie Han, Yu Tianjin Key Laboratory for Control Theory and Application in Complicated Systems China 391 Binshui Xidao Xiqing District Tianjin China

ISBN: (纸本)9781538660720

In order to elevate the automation degree of square-rectangular steel tube packing and achieve better welding effect, a square-rectangular steel tube packing belt resistance spot welding automatic control system is designed based on OMRON CP1L in this paper. The resistance spot welding (RSW) machine and two axis servo motors are controlled by PLC. The touch screen is used to set the servo motLRQ parameters and the welding parameters of resistance spot welding. According to the local circumstance, the form of single-side single spot welding is adopted by the system. The operation form of traditional manual arc welding is converted into automatic resistance spot welding system. The system can automatically invoke the corresponding welding parameters in the light of the specification of the steel tube packing. The practical application shows that the whole system is uncomplicated, stable, efficient and environmentally friendly compared with artificial arc welding. The utilization of the system not only enhances the welding efficiency, but also reduces the cost of human and environmental governance, so that the enterprise productivity efficiency has been greatly improved. © 2018 IEEE.

关键词： Efficiency

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Association between Electroencephalographic microstates abnormalities and cognitive dysfunction in drug-naive MDD

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Brain Research 2025年 1860卷 149660-149660页

作者： Qin, Qin Liu, Xinyu Wang, Bin Wang, Xin Liang, Sixiang Chen, Chao Li, Meijia Han, Chuanliang Zhao, Xixi National Clinical Research Center for Mental Disorders & National Center for Mental Disorders Beijing Key Laboratory of Mental Disorders Beijing Anding Hospital Capital Medical University Beijing China Advanced Innovation Center for Human Brain Protection Capital Medical University Beijing China Department of Clinical Psychology Shandong Provincial Hospital affiliated to Shandong First Medical University Shandong China Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin 300384 China Faculty of Psychology and Center for Neuroscience Vrije Universiteit Brussel Brussels 1050 Belgium School of Biomedical Sciences and The Gerald Choa Neuroscience Institute The Chinese University of Hong Kong Hong Kong SAR China

Objectives: This study aims to investigate the link between Electroencephalography (EEG) microstate anomalies and cognitive impairments in individuals with drug-naive Major depressive disorder (MDD). Methods: We recruited 29 patients with drug-naive MDD and 30 healthy controls. The Hamilton Depression Rating Scale (HDRS-17) measured symptom severity, the MATRICS Consensus Cognitive Battery (MCCB) assessed neurocognitive function, and resting-state EEG data were collected using 64 scalp electrodes. Analysis of EEG microstates was conducted via the Microstate Analysis plugin for EEGLAB. Results: MDD group had lower scores in six neurocognitive MCCB domains. For EEG microstates, four similar ones (A − D) were found in both groups. Notably, microstate C duration was lower in MDD group (t = 4.549, P < 0.001), microstate D occurrence (t = 2.258, P = 0.028) and proportion (t = 3.733, P < 0.001) were lower in MDD group. There were significant differences in all 4 microstate transition probabilities between groups. For example, A − B, B − A etc. transitions were higher in MDD, while A − C, A − D etc. were lower. The proportion of microstate D was found positively correlated with Speed of processing (SOP) score (r = 0.499, df = 26, P = 0.007) and Working memory (WM) score (r = 0.451, df = 26, P = 0.016). The Occurrence of microstate D was found positively correlated with SOP score (r = 0.383, df = 26, P = 0.044) and WM score (r = 0.389, df = 26, P = 0.041). Conclusions: MDD patients show alterations in sub-second brain dynamics, characterized by a decreased proportion and occurrence of microstate D and shorter duration of microstate C, and significant shifts in microstate transition probabilities. These changes correlate with cognitive deficits across several domains, including processing speed and working memory. © 2025

关键词： Cognitive dysfunction Electroencephalographic microstates Major depressive disorder

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