Výsledky vyhľadávania - "EEG decoding algorithm"

SMMTM: Motor imagery EEG decoding algorithm using a hybrid multi-branch separable convolutional self-attention temporal convolutional network Autor Cao, DianGuo, Yu, ZhenYuan, Wang, Jinqiang, Wu, Yuqiang

“…Motor imagery (MI) is a brain-computer interface (BCI) technology with the potential to change human life in the future. MI signals have been widely applied in…”
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SMMTM: Motor imagery EEG decoding algorithm using a hybrid multi-branch separable convolutional self-attention temporal convolutional network Autor DianGuo Cao, ZhenYuan Yu, Jinqiang Wang, Yuqiang Wu

“…Motor imagery (MI) is a brain-computer interface (BCI) technology with the potential to change human life in the future. MI signals have been widely applied in…”
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Combining multi-scale convolutional neural network and Transformers for EEG-Based RSVP detection Autor Lu, Gai, Zhang, Yifan, Chu, Xingxing, Liu, Yingxin, Yu, Yang

“… It is necessary to develop an EEG decoding algorithm with robust generalization ability and high recognition accuracy…”
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Sparse Bayesian Learning for End-to-End EEG Decoding Autor Wang, Wenlong, Qi, Feifei, Wipf, David, Cai, Chang, Yu, Tianyou, Li, Yuanqing, Yu, Zhuliang, Wu, Wei

“… To address this fundamental limitation, this paper proposes a novel end-to-end EEG decoding algorithm that utilizes a low-rank weight matrix to encode both spatio-temporal filters and the classifier…”
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A classification algorithm of an SSVEP brain-Computer interface based on CCA fusion wavelet coefficients Autor Ma, Pengfei, Dong, Chaoyi, Lin, Ruijing, Ma, Shuang, Jia, Tingting, Chen, Xiaoyan, Xiao, Zhiyun, Qi, Yongsheng

“…In the study of brain-computer interfaces (BCIs) based on steady-state visual evoked potentials (SSVEPs), how to improve the classification accuracies of BCIs…”
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Boosting-LDA algriothm with multi-domain feature fusion for motor imagery EEG decoding Autor Zhang, Yue, Chen, Weihai, Lin, Chun-Liang, Pei, Zhongcai, Chen, Jianer, Chen, Zuobing

“… Understanding EEG differences between healthy people and stroke patients is important. A Novel EEG decoding algorithm is proposed based on this present situation…”
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Brain–Machine Interface and Visual Compressive Sensing-Based Teleoperation Control of an Exoskeleton Robot Autor Qiu, Shiyuan, Li, Zhijun, He, Wei, Zhang, Longbin, Yang, Chenguang, Su, Chun-Yi

“…This paper presents a teleoperation control for an exoskeleton robotic system based on the brain-machine interface and vision feedback. Vision compressive…”
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A Novel Motor Imagery EEG Decoding Approach via Sparse Latent-Space Regression With Multi-Norm Regularization Autor Hou, Ruizhe, Dong, Shi, Wang, Wenlong, Yu, Tianyou, Yu, Zhuliang, Gu, Zhenghui

“… To address these limitations, we introduce a fast and robust MI EEG decoding algorithm that captures spectral power features from the latent-space…”
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EEG features of the interaction between sense of agency and body ownership: a motor imagery BCI case study Autor Arpaia, Pasquale, D'Angelo, Mariano, D'Errico, Giovanni, De Paolis, Lucio Tommaso, Esposito, Antonio, Grassini, Sabrina, Moccaldi, Nicola, Natalizio, Angela, Nuzzo, Benito Luigi

“…The sense of body ownership, i.e., the experience of one's body as one's own, and the sense of agency, i.e., the feeling of control over bodily actions, are…”
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An Algorithm for Motor Imagery Classification Based on Transfer Learning and Feature Fusion Autor Wang, Shuaibin, Wu, Jinglong, Zhang, Deyu, Suo, Dingjie, Yan, Tianyi

“… This study aimed to develop an MI-EEG decoding algorithm with high performance. Specifically, we applied a transfer learning strategy to enhance transferability between EEG sessions…”
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MindMeld: Design of a Brain-Computer Interaction Rehabilitation System for Children with Autism Autor Lv, Shengye, Yang, Hongchun, Wu, Jianfeng, Liu, Xiling, Jiang, Xutao, Huang, Jiayi

“…) headband hardware, a visual game interface, and an EEG decoding algorithm for children with ASD…”
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Comparison of MI-EEG Decoding in Source to Sensor Domain Autor Fang, Tao, Song, Zuoting, Mu, Wei, Le, Song, Zhang, Yuan, Zhang, Xueze, Zhan, Gege, Wang, Pengchao, Wang, Junkongshuai, Bin, Jianxiong, Zhang, Fan, Zhang, Lihua, Kang, Xiaoyang

“… Unlike traditional EEG decoding algorithms, we perform the decoding task in the source domain rather than the sensor domain…”
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A comprehensive review of EEG-based brain-computer interface paradigms Autor Abiri, Reza, Borhani, Soheil, Sellers, Eric W, Jiang, Yang, Zhao, Xiaopeng

“…Advances in brain science and computer technology in the past decade have led to exciting developments in brain-computer interface (BCI), thereby making BCI a…”
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AMFTCNet: A multi-level attention-based multi-scale fusion temporal convolutional network for decoding MI-EEG signals Autor Huang, Qianfeng, Yang, Yuanpo, Li, Jun, Liu, Xiuling, Liu, Xiaoguang

“… Effectively utilizing training data and integrating signal features remain major challenges in MI-EEG decoding algorithms…”
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Cross-Dataset Montage Alignment via Electroencephalogram Source Imaging for Enhanced Motor Decoding Autor Xiang, Tian-Yu, Wang, Wen-Kai, Zhou, Xiao-Hu, Yang, Hong-Jun, Gui, Mei-Jiang, Xie, Xiao-Liang, Liu, Shi-Qi, Wang, Jia-Xing, Liu, Jia-Mou, Hou, Zeng-Guang

“…Limited electroencephalogram (EEG) data within an individual dataset restricts the performance of brain–computer interface (BCI) systems. Although external…”
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EEG-ReMinD: Enhancing Neurodegenerative EEG Decoding through Self-Supervised State Reconstruction-Primed Riemannian Dynamics Autor Wang, Zirui, Song, Zhenxi, Guo, Yi, Liu, Yuxin, Xu, Guoyang, Zhang, Min, Zhang, Zhiguo

“…The development of EEG decoding algorithms confronts challenges such as data sparsity, subject variability, and the need for precise annotations, all of which are vital for advancing brain-computer…”
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A Large-Scale Evaluation Framework for EEG Deep Learning Architectures Autor Heilmeyer, Felix A., Schirrmeister, Robin T., Fiederer, Lukas D. J., Volker, Martin, Behncke, Joos, Ball, Tonio

“…, (ii) a collection of different EEG decoding algorithms, and (iii) a wrapper linking the decoders to the data as well as handling structured documentation of all settings…”
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Learning Signal Representations for EEG Cross-Subject Channel Selection and Trial Classification Autor Massi, Michela C., Ieva, Francesca

“… Most EEG systems are multi-channel in nature, but multiple channels might include noisy and redundant information and increase computational times of automated EEG decoding algorithms…”
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Review of Methods of EEG Signal Classification Based Computer Brain Interface Techniques Autor Deepika, D., Rekha, G.

“…Since the beginning of the previous decade, advances in brain science and computer technology have propelled this field to the top of the applied science…”
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A large-scale evaluation framework for EEG deep learning architectures Autor Heilmeyer, Felix A, Schirrmeister, Robin T, Fiederer, Lukas D J, Völker, Martin, Joos Behncke, Ball, Tonio

“…, (ii) a collection of different EEG decoding algorithms, and (iii) a wrapper linking the decoders to the data as well as handling structured documentation of all settings…”
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