检索结果-内蒙古大学图书馆

Electronic Information Engineering and computer Communication (EIECC), International Conference on

作者： Huang Wu Jun Xiao Chenxin Xue Di Chen Jiahui Pan Yuanqing Li School of Automation Science and Engineering South China University of Technology Guangzhou China School of Electric Power Engineering South China University of Technology Guangzhou China School of Software South China Normal University Guangzhou China Pazhou Laboratory Research Center for Brain–Computer Interface Guangzhou China

The JFK Coma Recovery Scale-Revised (JFK CRSR) is a clinical behavioral method for assessing patients with disorders of consciousness (DOC). However, due to severe brain injury, the DOC patients may lack sufficient behavioral responses, leading to a relatively high clinical misdiagnosis rate of the JFK CRS-R. To address this limitation, this study developed a portable and wearable brain-computer interface (BCI) to evaluate the visual tracking abilities of the DOC patients and enhance the diagnostic accuracy of the JFK CRS-R. During the experiment, patients wore an Electroencephalogram headband, and the Graphical User interface of the BCI presented four human images with a background captured by a camera. A target human image was randomly selected, then the four images alternately flashed until the target moved to its initial position. The system guided patients to concentrate their attention on the moving target. In a case study, the BCI system was applied to a patient diagnosed with a minimally conscious state (MCS). In contrast to the lack of visual tracking behavior in CRS-R, our experiment result showed a significant accuracy of 60% achieved by the MCS patient, emphasizing the visual tracking abilities of the MCS patients and highlighting the effectiveness of the system.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Enhanced Assessment of Auditory Perception Function in Disorders of Consciousness Using a Minimalist Wearable brain-computer interface

Enhanced Assessment of Auditory Perception Function in Disor...

引用

computer, Big Data and Artificial Intelligence (ICCBD+AI), International Conference on

作者： Chenxin Xue Jun Xiao Huang Wu Li Hu Jiahui Pan Yuanqing Li School of Automation Science and Engineering South China University of Technology Guangzhou China School of Electric Power Engineering South China University of Technology Guangzhou China School of Software South China Normal University Guangzhou China Research Center for Brain-Computer Interface Pazhou Laboratory Guangzhou China

ISBN: (数字)9798350373233

ISBN: (纸本)9798350373240

The Coma Recovery Scale-Revised (CRS-R) is a clinical behavioral method for assessing the levels of consciousness and perceptual abilities in patients with Disorders of Consciousness (DOC). However, due to severe impairment of motor functions in DOC patients and subjective factors of clinical evaluators, the misdiagnosis rate of the CRS-R is very high. brain-computer interfaces (BCIs) can directly detect patients’ brain activity in response to external stimuli, independent of patients’ behavioral representation, thereby achieving a more objective assessment. In this study, we introduced a minimalist wearable BCI system grounded in the auditory oddball paradigm to enhance assessment of auditory perception function in DOC patients. In the experiments, sinusoidal tones and the complex sound of clapping were selected as standard stimuli occurring frequently and occasional deviant stimuli, respectively. The specific event-related potentials evoked by the auditory stimuli facilitated the assessment of auditory perceptual function. The experimental results indicate that the DOC patients with auditory perception functions can also be detected by the BCI system. As a result, the BCI could serve as a valuable adjunct tool in clinical practice of the CRS-R.

关键词： brain External stimuli Medical services Big Data Motors brain-computer interfaces Electroencephalography

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Learning Rate Q-Learning Algorithm Based on Kalman Filter Inspired by Pigeon Pecking-Color Learning 14th

An Adaptive Learning Rate Q-Learning Algorithm Based on Kalm...

引用

14th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2019

作者： Li, Zhihui Shi, Li Yang, Lifang Shang, Zhigang Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology School of Electrical Engineering Zhengzhou University Zhengzhou450001 China Department of Automation Tsinghua University Beijing100000 China

ISBN: (纸本)9789811534140

The speed and accuracy of the Q-learning algorithm are critically affected by the learning rate. In most Q-learning application, the learning rate is usually set as a constant or decayed in a predetermined way, so it cannot meet the needs of dynamic and rapid learning. In this study, the learning process of pigeon pecking-color task was analyzed. We observed that there was epiphany phenomenon during pigeon’s learning process. The learning rate did not change gradually, but was large in the early stage and disappeared in the middle and late stage. Inspired by these phenomena, an adaptive learning rate Q-learning algorithm based on Kalman filter model (ALRKF Q-learning) is proposed in this paper. Q-learning are represented in the framework of Kalman filter model, and the learning rate is equivalent to Kalman gain, which dynamically weighs the fluctuation of environmental reward and the cognitive uncertainty of the agent to the value of pairs. The cognitive uncertainty in the model is determined by the variance of measurement residual and of environmental reward, and is set to zero when it is less than the variance of the environmental reward. The results tested by the two-armed Bandit task showed that the proposed algorithm not only can adaptively learn the statistical characteristics of environmental rewards, but also can quickly and accurately approximate the expected value of pairs. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Kalman filters

来源：评论

学校读者我要写书评

暂无评论

Kinetic and Kinematic Sensors-free Approach for Estimation of Continuous Force and Gesture in sEMG Prosthetic Hands

arXiv

引用

arXiv 2024年

作者： Liu, Gang Wang, Zhenxiang Xi, Chuanmei He, Ziyang Guo, Shanshan Zhang, Rui Yao, Dezhong School of Electrical and information Engineering Zhengzhou University Zhengzhou450001 China Henan Key Laboratory of Brain Science and Brain Computer Interface Technology Zhengzhou University Zhengzhou450001 China Engineering Department of International College Zhengzhou University 450001 China School of Cyber Science and Engineering Zhengzhou University Zhengzhou450000 China Shanghai Key Laboratory of Brain-Machine Intelligence for Information Behavior Shanghai International Studies University China Clinical Hospital of Chengdu Brain Science Institute MOE Key Laboratory for NeuroInformation University of Electronic Science and Technology of China Chengdu China Research Unit of NeuroInformation Chinese Academy of Medical Sciences Chengdu China

Regression-based sEMG prosthetic hands are widely used for their ability to provide continuous kinetic and kinematic parameters. However, establishing these models requires complex sensors systems to collect corresponding kinetic and kinematic data in synchronization with sEMG, which is cumbersome and user-unfriendly. This paper proposes a kinetic and kinematic sensors-free approach for controlling sEMG prosthetic hands, enabling continuous decoding and execution of three hand movements: individual finger flexion/extension, multiple finger flexion/extension, and fist opening/closing. This approach utilizes only two data points (-1 and 1), representing maximal finger flexion force label and extension force label respectively, and their corresponding sEMG data to establish a near-linear model based on sEMG data and labels. The model's output labels values are used to control the direction and magnitude of fingers forces, enabling the estimation of continuous gestures. To validate this approach, we conducted offline and online experiments using four models: Dendritic Net (DD), Linear Net (LN), Multi-Layer Perceptron (MLP), and Convolutional neural Network (CNN). The offline analysis assessed each model's ability to classify finger force direction and interpolate intermediate force values, while online experiments evaluated real-time control performance in controlling gestures and accurately adjusting forces. Our results demonstrate that the DD and LN models provide excellent real-time control of finger forces and gestures, highlighting the practical potential of this sensors-free approach for prosthetic applications. This study significantly reduces the complexity of collecting kinetic and kinematic parameters in sEMG-based regression prosthetics, thus enhancing the usability and convenience of prosthetic hands. © 2024, CC BY-NC-SA.

关键词： Multilayer neural networks

来源：评论

学校读者我要写书评

暂无评论

Determination of Effective Response Time Window to Visual Object in Object-oriented Task of Birds

Determination of Effective Response Time Window to Visual Ob...

引用

第40届中国控制会议

作者： Xiaoke Niu Shangfei Yang Zhenyang Jiang Yanyan Peng Hong Yang Henan Key Laboratory of Brain Science and Brain Computer Interface Technology School of Electrical EngineeringZhengZhou University The First Affiliated Hospital of Zhengzhou University ZhengZhou University

Determination of effective visual response time window is premise of studying object cognition and decision-making mechanisms in avian object-oriented ***,it is difficult to determine the effective response time window for freely moving *** this study,video data of pigeon’s face in the target-oriented task was collected,and a neural network algorithm based on Faster RCNN was applied to train pigeon face prediction model,which was further used to predict the time window of pigeon observing the specific image *** length of time window were estimated based on the statistical results of 177 trials,and the specific time window for each trial was then determined by combining the start frame that contained pigeon’s frontal ***,the proposed method was verified using data from two pigeons trained for object-oriented *** the firing rates feature population recorded from pigeon’s ectostriatum as an example,the mean firing rate during the estimated effective time window and the original mean firing rate without the time window were sent to SVM and KNN classifier respectively to decode the observed object *** comparison results showed that the classification accuracy of both classifiers were significantly improved with our method,proving that the proposed method could obtained effective response to specific visual object for freely moving birds.

关键词： Pigeon Face Recognition Faster-RCNN Goal-Oriented Visual Decoding

来源：评论

学校读者我要写书评

暂无评论

Boosters of the metaverse: a review of augmented reality-based brain-computer interface

引用

brain-Apparatus Communication: A Journal of Bacomics 2024年第1期3卷

作者： Zongxin Xu Gaoxing Chen Rui Zhang Henan Key Laboratory of Brain Science and Brain-Computer Interface Technology School of Electrical Engineering Zhengzhou University Zhengzhou P. R. China

IntroductionThe ultimate objective of the metaverse is to create a new digital life system using brain-computer interface (BCI) technology that integrates and even enhances reality and virtuality, among which the efficient and natural interaction technology between the virtual and real world is one of the key technologies of the metaverse. Augmented reality-based BCI (AR-BCI) technology provides a channel for direct interaction between the brain and the virtual world by decoding the human brain's response to AR stimuli in real-time, thus the development of the metaverse requires the advancement of AR-BCI *** paper began with the concepts and interrelationships between the metaverse, BCI, and AR technologies. Then the technical characteristics and potential applications of AR-BCI were introduced, and the research progress of three typical AR-BCI paradigms, including SSVEP, P300, and MI, were then *** survey results indicated that the use of optical see-through glasses to present the SSVEP paradigm has become the key breakthrough direction of AR-BCI research at present. Medical care and robot control are currently the main application areas of AR-BCI. And in the future, AR-BCI will be an important booster to promote the rapid evolution of the metaverse.

关键词： Metaverse augmented reality brain-computer interface SSVEP brain–apparatus conversation

来源：评论

学校读者我要写书评

暂无评论

Neuron-astrocyte coupling in lateral habenula mediates depressive-like behaviors

引用

Cell 2025年第12期188卷 3291-3309.e24,27页

作者： Xin, Qianqian Wang, Junying Zheng, Jinkun Tan, Yi Jia, Xiaoning Ni, Zheyi Xu, Zijie Feng, Jiesi Wu, Zhaofa Li, Yulong Li, Xiao-Ming Ma, Huan Hu, Hailan Department of Neurobiology Affiliated Mental Health Center & Hangzhou Seventh People's Hospital Zhejiang University School of Medicine Hangzhou 310058 China Nanhu Brain-Computer Interface Institute Liangzhu Laboratory MOE Frontier Science Center for Brain Science and Brain-Machine Integration State Key Laboratory of Brain-Machine Intelligence New Cornerstone Science Laboratory Zhejiang University Hangzhou 311121 China Department of Psychiatry and International Institutes of Medicine The Fourth Affiliated Hospital Zhejiang University School of Medicine Yiwu 322000 China State Key Laboratory of Membrane Biology Peking University School of Life Sciences Beijing 100871 China

The lateral habenula (LHb) neurons and astrocytes have been strongly implicated in depression etiology, but it was not clear how the two dynamically interact during depression onset. Here, using multi-brain-region calcium photometry recording in freely moving mice, we discover that stress induces a most rapid astrocytic calcium rise and a bimodal neuronal response in the LHb. LHb astrocytic calcium requires the α_1A-adrenergic receptor and depends on a recurrent neural network between the LHb and locus coeruleus (LC). Through the gliotransmitter glutamate and ATP/adenosine, LHb astrocytes mediate the second-wave LHb neuronal activation and norepinephrine (NE) release. Activation or inhibition of LHb astrocytic calcium signaling facilitates or prevents stress-induced depressive-like behaviors, respectively. These results identify a stress-induced positive feedback loop in the LHb-LC axis, with astrocytes being a critical signaling relay. The identification of this prominent neuron-glia interaction may shed light on stress management and depression prevention. © 2025 Elsevier Inc.

关键词： astrocytes depression lateral habenula locus coeruleus norepinephrine phasic and tonic NE reboxetine SNRI stress α1A-adrenergic receptor

来源：评论

学校读者我要写书评

暂无评论

Sustained antidepressant effect of ketamine through NMDAR trapping in the LHb (vol 622, pg 802, 2023)

引用

NATURE 2023年第7988期623卷 E11-E11页

作者： Ma, Shuangshuang Chen, Min Jiang, Yihao Xiang, Xinkuan Wang, Shiqi Wu, Zuohang Li, Shuo Cui, Yihui Wang, Junying Zhu, Yanqing Zhang, Yan Ma, Huan Duan, Shumin Li, Haohong Yang, Yan Lingle, Christopher J. Hu, Hailan Department of Psychiatry and International Institutes of Medicine The Fourth Affiliated Hospital Zhejiang University School of Medicine Yiwu China Nanhu Brain–Computer Interface Institute MOE Frontier Science Center for Brain Science and Brain–Machine Integration State Key Laboratory of Brain–Machine Intelligence New Cornerstone Science Laboratory Zhejiang University Hangzhou China Department of Affiliated Mental Health Center and Hangzhou Seventh People’s Hospital and School of Brain Science and Brain Medicine Zhejiang University School of Medicine Hangzhou China Department of Anesthesiology Washington University School of Medicine St Louis MO USA

来源：评论

学校读者我要写书评

暂无评论

Short-Time Variational Mode Decomposition

arXiv

引用

arXiv 2025年

作者： Jia, Hao Cao, Pengfei Liang, Tong Caiafa, Cesar F. Sun, Zhe Kushihashi, Yasuhiro Grau, Antoni Bolea, Yolanda Duan, Feng Solé-Casals, Jordi School of Medicine Nankai University Tianjin China Tianjin Key Laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation Tianjin China Universitat Politècnica de Catalunya Barcelona Spain Mechanical Systems Engineering Nippon Institute of Technology Saitama Japan Villa Elisa Argentina Computational Bioengineering Laboratory Faculty of Health Data Science Juntendo University Tokyo Japan Data and Signal Processing Research Group University of Vic-Central University of Catalonia Vic Spain

Variational mode decomposition (VMD) and its extensions like Multivariate VMD (MVMD) decompose signals into ensembles of band-limited modes with narrow central frequencies. These methods utilize Fourier transformations to shift signals between time and frequency domains. However, since Fourier transformations span the entire time-domain signal, they are suboptimal for non-stationary time series. We introduce Short-Time Variational Mode Decomposition (STVMD), an innovative extension of the VMD algorithm that incorporates the Short-Time Fourier transform (STFT) to minimize the impact of local disturbances. STVMD segments signals into short time windows, converting these segments into the frequency domain. It then formulates a variational optimization problem to extract band-limited modes representing the windowed data. The optimization aims to minimize the sum of the bandwidths of these modes across the windowed data, extending the cost functions used in VMD and MVMD. Solutions are derived using the alternating direction method of multipliers, ensuring the extraction of modes with narrow bandwidths. STVMD is divided into dynamic and non-dynamic types, depending on whether the central frequencies vary with time. Our experiments show that non-dynamic STVMD is comparable to VMD with properly sized time windows, while dynamic STVMD better accommodates non-stationary signals, evidenced by reduced mode function errors and tracking of dynamic central frequencies. This effectiveness is validated by steady-state visual-evoked potentials in electroencephalogram signals. Copyright © 2025, The Authors. All rights reserved.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

Cross View Capture for Distributed Image Compression with Decoder Side Information

Cross View Capture for Distributed Image Compression with De...

引用

IEEE International Conference on Robotics and Automation (ICRA)

作者： Yankai Yin Zhe Sun Peiying Ruan Feng Duan Ruidong Li Chi Zhu Tianjin Key Laboratory of Interventional Brain-Computer Interface and Intelligent Rehabilitation Nankai University Tianjin China Institute of Natural Sciences Kanazawa University Ishikawa Japan Faculty of Health Data Science and Graduate School of Medicine Juntendo University Chiba Japan NVIDIA AI Technology Center NVIDIA Japan Tokyo Japan Department of Systems Life Engineering Maebashi Institute of Technology Maebashi Japan

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Image compression is increasingly important in applications like intelligent driving and smart surveillance systems. This study presents a novel cross view capture distributed image compression network (CVCDIC) to improve the compression quality by using decoder side information. The CVCDIC’s decoder utilizes feature extraction networks to extract features from both the primary image and the side information. Furthermore, a multi-level cross view attention module is designed to capture interrelated details between images at multiple hierarchical levels. Finally, a spatial refinement module, constructed on the foundation of information distillation networks, is designed to further refine the quality of reconstructed images. The results show that CVCDIC can achieve an MS-SSIM of 0.978 at 0.15 bpp, surpassing DSIN (0.925), NDIC (0.956), and ATN (0.955) on the KITTI Stereo dataset.

关键词： Measurement Image coding Fuses Surveillance Rate-distortion Feature extraction Decoding

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：