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

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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Research on intelligent monitoring system ofgreenhouse intensity and CO2 concentration based on STM32 15

Research on intelligent monitoring system ofgreenhouse inten...

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

作者： Li, Shuanzeng School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin Key Laboratory of complex system control theory and Application Binshui Xidao 391 Tianjin300384 China

ISBN: (纸本)9781538660720

Because the stability and accuracy of the traditional greenhouse monitoring system are not high enough, the light intensity and the grape canopy of the intelligent monitoring system are established for this phenomenon. It is based on the C02 concentration of STM32 single chip to monitor the intensity of light and C02 concentration and show it at the same time. Serial communication is used to send test results to MCGS touch screen to achieve real-time monitoring and warning of light intensity and C02 concentration in greenhouse. The result of long term test shows the precision of the light intensity detection of the system is 940lux, C02 concentration measurement accuracy 40ppm. Compared with the traditional automatic monitoring system, the system runs stably and costs less, and the accuracy meets the requirements of grape greenhouse. In conclusion, the system proposed in this paper is suitable for agriculture. © 2018 IEEE.

关键词： Greenhouses

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energy Consumption Data Prediction Analysis based on EEMD-ARMA Model

Energy Consumption Data Prediction Analysis based on EEMD-AR...

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IEEE International Conference on Mechatronics and Automation

作者： Ji Li Xudong Jiang Lei Shao Hongli Liu Chao Chen Gang Wang Dongdong Du Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems Tianjin University of Technology Binshui Xidao 391 Tianjin China Tianjin Economic and Technological Development Zone Binhai New Area Continental Automotive (System) Tianjin Co. Ltd. Continental Automotive (System) Tianjin Co. Ltd No.2 Bohai Road Tianjin China China Academy of Industrial Internet Institute of Data management and application Beijing Block B East Lake International Center No. 6 Lize West Street Chaoyang District Beijing

ISBN: (数字)9781728164168

ISBN: (纸本)9781728164175

energy consumption data prediction model based on EEMD-ARMA prediction model is used to predict the nonlinear and non-stationary characteristics of industrial energy consumption data, which leads to the difficulty of data prediction and low prediction accuracy. This paper improves empirical mode decomposition (empirical mode decomposition, EMD) by ensemble empirical mode decomposition (ensemble empirical mode decomposition, EEMD) and predicts energy consumption by combining auto regressive sliding average model (auto regressive and moving average model, ARMA). Finally, the historical data of a certain system is selected as a sample, and the comparative analysis of EMD-ARMA and EEMD-ARMA prediction results is used to verify that the EEMD-ARMA algorithm used is more accurate than the prediction algorithm, and its prediction results have certain reference value for the control of energy consumption data in enterprises.

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FPGA Based Design and Implementation of Improved Edge Detection Algorithm using LOG Operator

FPGA Based Design and Implementation of Improved Edge Detect...

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IEEE International Conference on Mechatronics and Automation

作者： Enzeng Dong Kaifeng Li Jigang Tong Complex System Control Theory and Application Key Laboratory Tianjin University of Technology (TJUT) Tianjin China

Detection speed and precision are key indicators of the edge detection systems. To increase the precision of edge detection and enhance its engineering practicability, an improved edge detection algorithm based on Laplace of Gaussian (LOG) operator is proposed in this paper. In this algorithm, the first order partial derivative in different direction is calculated to judge the direction of the gradient. Then, the position of zero crossing point is positioned according to the value of LOG operator in the gradient direction. Furthermore, according to the number of zero crossing points of the adjacent points in the direction of the gradient normal vector, the image is filtered and breakpoints are connected. For convenience in engineering application of digital image processing, this proposed edge detection algorithm is implemented on Field-Programmable Gate Array (FPGA) chip. The experiment results show that this proposed algorithm is easy to be implemented on hardware and has much higher accuracy in edge detection performance. Due to the parallel processing capability of FPGA chip, the designed edge detection system is suitable for real-time image processing applications.

关键词： Image edge detection Field programmable gate arrays SDRAM Real-time systems Laplace equations Convolution Cameras

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Moving targets detection based on improved single Gaussian background model

Moving targets detection based on improved single Gaussian b...

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IEEE International Conference on Mechatronics and Automation

作者： Enzeng Dong Bo Han Xiao Yu Shengzhi Du Complex System Control Theory and Application Key Laboratory Tianjin University of Technology (TJUT) Tianjin China

In order to improve the detection effect of the single Gaussian background model (SGM), an improved SGM algorithm is proposed to detect moving targets in this paper, which has made three improvements on the base of SGM. Firstly, the algorithm adopts adaptive background learning rate instead of using a fixed learning rate. Secondly, we use a new update strategy of Gaussian background model, which makes the Gaussian background model has good convergence and stability. Finally, the moving targets are detected according to the principle of Gaussian distribution and the image morphology filtering. Experimental results show that the background model of improved SGM can adapt well to background changes, and the target detection integrity is higher than that of the traditional SGM.

关键词： Adaptation models Computational modeling Morphology Filtering Feature extraction Object detection Gaussian distribution

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Research on Intelligent Monitoring system of Greenhouse Intensity and CO2 Concentration Based on STM32

Research on Intelligent Monitoring System of Greenhouse Inte...

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IEEE International Conference on Mechatronics and Automation

作者： Shuanzeng Li School of Electrical and Electronic Engineering Tianjin Key Laboratory of complex system control theory and Application Tianjin China

Because the stability and accuracy of the traditional greenhouse monitoring system are not high enough, the light intensity and the grape canopy of the intelligent monitoring system are established for this phenomenon. It is based on the CO2 concentration of STM32 single chip to monitor the intensity of light and CO2 concentration and show it at the same time. Serial communication is used to send test results to MCGS touch screen to achieve real-time monitoring and warning of light intensity and CO2 concentration in greenhouse. The result of long term test shows the precision of the light intensity detection of the system is 9401ux, CO2 concentration measurement accuracy 40ppm. Compared with the traditional automatic monitoring system, the system runs stably and costs less, and the accuracy meets the requirements of grape greenhouse. In conclusion, the system proposed in this paper is suitable for agriculture.

关键词： Pipelines Green products Monitoring Voltage control Real-time systems Oscillators Air pollution

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Design and implementation of smart home remote monitoring system based on ARM11

Design and implementation of smart home remote monitoring sy...

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第30届中国控制与决策会议

作者： Qi Wang Yunliang Wang School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Application in Complicated System

Considering the disadvantage of smart home on wiring,maintainability and mobility,a scheme for remote monitoring of smart home is proposed based on ARM and *** home network based on ZigBee Technology,and then gateway is developed with S3 C6410 which Linux operating system is embedded,using TD-LTE wireless terminal system as external network,so that the user could see the scene of the *** ultra-low power consumption and fast ARM11 processor so that real-time monitoring data is more *** system can be widely used to monitor the environmental data of hospitals,factories and other *** has good development prospects.

关键词： smart home remote monitoring ARM11 ZigBee

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Simultaneous Location and Map Construction Based on RBPF-SLAM Algorithm

Simultaneous Location and Map Construction Based on RBPF-SLA...

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第30届中国控制与决策会议

作者： Hong He YunHui Jia Lei Sun School of Electrical and Electronic Engineering Tianjin University of Technology Tianjin Key Laboratory of Complex System Control Theory and Application

Solving the problem of simultaneous location and map construction（SLAM） is the core of robot autonomous navigation. At present, most algorithms usually only consider the odometer information of mobile robot, therefor, there exists some problems of increasing computation amount caused by a large number of sampling particles and the complexity. So, this paper developed a scheme of map construction and positioning based on RBPF-SLAM algorithm. The hardware and software platform is set up on the ROS, and it merge the odometer information of the robot into the distance information collected by the laser sensor, which effectively reduces the number of required particles and the uncertainty of the robot’s pose estimates in filter prediction phase. Through the experimental, get the conclusion: simultaneous positioning based on RBPF-SLAM algorithm and map construction system can create high-precision online raster map in real time, and it is more consistent with the actual map.

关键词： ROS RBPF-SLAM Algorithm Simultaneous Location Laser Sensor Pose Estimates

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EEG controlled Automated Writing Robotic Arm Based on Steady State Visually Evoked Potential

EEG Controlled Automated Writing Robotic Arm Based on Steady...

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IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement systems and applications

作者： Xuequan Zhu Meng Mu Abdelkader Nasreddine Belkacem Duk Shin Rui Xu Kun Wang Zhongpeng Wang Changming Wang Chao Chen Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology Tianjin China Zhonghuan Information College Tianjin University of Technology Tianjin China College of Information Technology UAE University Al Ain UAE Tokyo Polytechnic University Atsugi Japan Academy of medical Engineering and Translational medicine Tianjin University Tianjin China Beijing Key Laboratory of Mental Disorders Beijing Anding Hospital Capital Medical University Beijing China

ISBN: (数字)9781538683446

ISBN: (纸本)9781538683453

Brain-Computer Interface(BCI) refers to devices that allow people to communicate or control the outside devices only through brain waves without relying on their own output pathways, such as the human nervous system and muscle tissue. The problem of insufficient information transfer and interaction between organism and electromechanical device in electromechanical integration system is pointed out. This paper uses BP(Brain Products) equipment to collect Steady State Visual Evoked Potential (SSVEP) signals. The collected SSVEP signals were preprocessed, feature extracted and feature classified. Then it is connected with the robot arm to build a portable brain-computer interface control system. Six subjects participated in the online experiment of the system. Experimental results show that the system can write some simple Chinese characters with high accuracy, and the system is feasible and effective. Then the signal is taken by Open Brain-computer Interface (OpenBCI) to complete the connection with the robotic arm. We will realize the control of the robotic arm in the later experiment. Our research aim is to find an relatively effective control method by comparing BP and OpenBCI based control on the robotic arm.

关键词： Erbium

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Switching Power Supply Design Suitable for Motor control 29

Switching Power Supply Design Suitable for Motor Control

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第29届中国控制与决策会议

作者： Zhi-Chao Zhao Li guo-hong Tianjin University of Technology Tianjin Complex System Control Theory and Application Key Laboratory

ISBN: (纸本)9781509046584

Motor control systems require multi-channel stable output low voltage DC power *** to the needs of motor control system,a switching power supply can meet the requirements of motor control is *** topology of switching power supply and the uses of PWM control chips are *** positive and negative bias generation circuit of IGBT is *** circuit components' choices and design method of a high frequency transformer of the flyback switching power supply are ***,the basic performances of switching power supply were tested;the results show that it can meet the requirements of motor control systems.

关键词： switching power supply motor drive pulse width control chip high frequency transformer

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