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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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Research on Relay Contact Conversion Model Based on Nonlinear Least Square Method

Research on Relay Contact Conversion Model Based on Nonlinea...

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International Conference on Electromechanical control Technology and Transportation (ICECTT)

作者： Cong Li Zhiwei Li Tao Li JunChao Zhu Jianwen Li Baofeng Zhang Tianjin Key Laboratory for Control Theory & Applications in Complicated System Tianjin University of Technology Tianjin China Industrial Product Safety Technology Center Tianjin Customs District P. R. China Tianjin China

ISBN: (数字)9781728199283

ISBN: (纸本)9781728199290

The reliable switching of the AC filament conversion relay plays a decisive role in normal working of the railway signal light. Firstly, this paper analyzes contact conversion feature of the AC filament conversion relay and establishes the contact conversion model. Then, the nonlinear least square method is used to fit model parameters. Furthermore, the contact switching time is confirmed and the contact switching time is calculated accurately in accordance with the residual law. Finally, this paper compares the algorithm with the rapid calculation of AC voltage peak. Effectiveness and accuracy of the model are verified by simulation result and measured data.

关键词： Relays Electromagnetics Analytical models Switches Least mean squares methods Curve fitting Rail transportation

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Tool Path Generation Method for Three-dimensional Vibration-assisted Machining 16

Tool Path Generation Method for Three-dimensional Vibration-...

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16th IEEE International Conference on Mechatronics and Automation, ICMA 2019

作者： Wang, Guilian Lv, Bingrui Liu, Bin Mu, Haozhi Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology China Tianjin Laboratory of Control Theory and Applications in Complicated System Tianjin300384 China School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9781728116983

In this paper, a new tool path generation method is proposed for the 3D (three-dimensional) vibration-assisted 6-DOF (six degree of freedom) machine tool machining system. The tool feed path is generated by the tangent point method and the coordinate transformation theory. It is worth noting that this method needle is only used when the tool and workpiece surface topography can be mathematically described. Finally, a numeric simulation method is used to simulate the tool path which is required when machining workpiece surfaces with different topography tools. The results show that the tool path generation method is widely applicable to tools and workpieces of various shapes, and it is of great significance to reveal the influences of different tool shapes on the tool path. © 2019 IEEE.

关键词： Machine tools

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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

引用

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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Research on DC motor control based on predictive PI algorithm

Research on DC motor control based on predictive PI algorith...

引用

International Conference on Mechatronics and Intelligent Robotics, ICMIR 2018

作者： Zhou, Jinpeng Ma, Xu Xu, Zhang Zhou, Qi Tianjin University of Technology Tianjin300384 China Tianjin Key Laboratory for Control Theory and Applications in Complicated System the School of Electrical and Electronics Engineering Tianjin University of Technology Tianjin300384 China School of Mechanical Engineering Tianjin University of Technology and Education Tianjin300130 China School of Mechanical Engineering Hebei University of Technology Tianjin300130 China

ISBN: (纸本)9783030002138

In minimally invasive surgery, manual manipulation of the catheter is inaccurate which requires the worker to manipulate the catheter flexibly and effectively and exposes the surgeon to intense radiation. The author’s goal was to develop a robotic catheter operating system that would be hand-accurate on behalf of the surgeon. With the increasing demand for flexibility and rapid response to control systems, predictive PI control can play an important role. We proposed a practical application which is based on predictive PI control to the remote operation of this development system. And compare with the traditional PID control method for simulation. Demonstrate the feasibility and effectiveness of the control method. In this remote operation, in the synchronous control performance, use predictive PI control is much better than control using traditional PID control. © Springer Nature Switzerland AG 2019.

关键词： Three term control systems

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Design of LT-Med seawater desalination temperature control system based on dynamic matrix predictive fuzzy PID control algorithm 15

Design of LT-Med seawater desalination temperature control s...

引用

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

作者： Liu, Hongli Song, Lulu Shao, Lei Tan, Zhenhai Chen, Xiaoqi Tianjin University of Technology Tianjin Key Laboratory of Complex System Control Theory and Applications Tianjin University of Technology Binshui Xidao 391 Tianjin China

ISBN: (纸本)9781538660720

This article takes the "Twelfth Five-Year"50t/d MED pilot plant as the research background. According to the characteristics of nonlinearity, large inertia, large delay, and difficulty in establishing accurate mathematical models of temperature control systems in low-temperature multiple-effect (LT-MED) desalination plants, we have analyzed dynamic matrix predictive control and self-tuning fuzzy PID control methods. It is proposed to combine the two methods to achieve the effect of temperature *** the simulation test, the results show that the dynamic matrix fuzzy PID controller is more effective than the general fuzzy PID controller. For example, the adjustment time is effectively reduced, overshoot is almost zero enhances and the anti-interference ability is also *** fuzzy controller added to the dynamic matrix can better achieve the control effect we need in industrial production. © 2018 IEEE.

关键词： Temperature control

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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

引用

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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Path Planning for Mobile Robots Based on Improved RRT Algorithm

Path Planning for Mobile Robots Based on Improved RRT Algori...

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IEEE International Conference on Mechatronics and Automation

作者： Lei Shao Hanze Liu Chao Chen Dongdong Du Ji Li Hongli Liu Tianjin Key Laboratory for Control Theory & Applications in Complicated system Tianjin University of Technology Binshui Xidao 391 Tianjin China China Academy of Industrial Internet Institute of Data management and application Beijing Tower B East Bay International Center No.6 Liza West Street Chaoyang District Beijing

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

Aiming at the shortcomings of the basic RRT algorithm, such as the random search ability is relatively strong, and the calculation result is usually not the shortest path, etc., an improved RRT path optimization algorithm is proposed, which uses the ant colony algorithm to obtain the basic RRT algorithm. The path is iterated and optimized, and eventually converges to a shortest path, improving the efficiency of planning the shortest path in advance, and conducting in-depth research on this algorithm. A large number of simulation results show that the improved algorithm has certain feasibility and effectiveness. In multiple iterations, it can eventually converge to a path with a better distance.

关键词：

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Development of permanent magnet synchronous motor RCP based on hardware-in-the-loop simulation 15

Development of permanent magnet synchronous motor RCP based ...

引用

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

作者： Zhao, Gang Zhang, Shizhong Tianjin Key laboratory for Control Theory and Applications in Complicated System Tianjin University of Technology 391 Binshui Xidao Xiqing District Tianjin300384 China

ISBN: (纸本)9781538660720

This paper carries out a study on a high efficiency permanent magnet synchronous motor (PMSM) development method-rapid control prototype (RCP). A specific introduction of the support of hardware-in-the-loop simulation platform for RCP and the development process are given. Hardware in the loop simulation model is built by comparing and analysing of the characteristics of the two control methods and using the hardware and software environment of the system. The conversion from simulation model to code model is realized by using MATLAB and CCS and the application layer code is integrated with the hardware underlying driver code of the hardware-in-the-loop simulation platform. The automatic code generation is downloaded to the hardware-in-the-loop simulation platform to verify the accuracy of the theoretical calculation. The results show that the mathematical model performed as same as the hardware-in-loop simulation with the same PID parameters, which achieves the expected effect. © 2018 IEEE.

关键词： Hardware-in-the-loop simulation

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Model-reference scheduling and control Co-design with two paths 15

Model-reference scheduling and control Co-design with two pa...

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

作者： Zhao, Shunli Ji, Yuehui Tianjin Key Laboratory for Control Theory and Applications in Complicated System Tianjin University of Technology Tianjin China School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin China

ISBN: (纸本)9781538660720

There have been growing concerns in networked control system with communication constraints. In the paper, a novel scheduling strategy, model-reference scheduling scheme, is proposed for dealing with the distribution of the network resource for the case that network exists not only in forward path but also in feedback path. The states and the control signals gain the access to the network by computing the difference between the real system and the ideal one. The stability analysis and the control and scheduling co-design are given by formulating the problem as a linear equality equation. The proposed strategy is demonstrated through a simple simulation. © 2018 IEEE.

关键词： Networked control systems

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