Cargando…

An improved model using convolutional sliding window-attention network for motor imagery EEG classification

INTRODUCTION: The classification model of motor imagery-based electroencephalogram (MI-EEG) is a new human-computer interface pattern and a new neural rehabilitation assessment method for diseases such as Parkinson's and stroke. However, existing MI-EEG models often suffer from insufficient ric...

Descripción completa

Detalles Bibliográficos
Autores principales:	Huang, Yuxuan, Zheng, Jianxu, Xu, Binxing, Li, Xuhang, Liu, Yu, Wang, Zijian, Feng, Hua, Cao, Shiqi
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Frontiers Media S.A. 2023
Materias:	Neuroscience
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10469504/ https://www.ncbi.nlm.nih.gov/pubmed/37662108 http://dx.doi.org/10.3389/fnins.2023.1204385

Ejemplares similares

Local and global convolutional transformer-based motor imagery EEG classification
por: Zhang, Jiayang, et al.
Publicado: (2023)

A Parallel Multiscale Filter Bank Convolutional Neural Networks for Motor Imagery EEG Classification
por: Wu, Hao, et al.
Publicado: (2019)

Motor Imagery EEG Signal Recognition Using Deep Convolution Neural Network
por: Xiao, Xiongliang, et al.
Publicado: (2021)

Electroencephalogram-Based Motor Imagery Classification Using Deep Residual Convolutional Networks
por: Huang, Jing-Shan, et al.
Publicado: (2021)

Early-stage fusion of EEG and fNIRS improves classification of motor imagery
por: Li, Yang, et al.
Publicado: (2023)

Coherence based graph convolution network for motor imagery-induced EEG after spinal cord injury
por: Li, Han, et al.
Publicado: (2023)

Motor Imagery EEG Classification Based on Transfer Learning and Multi-Scale Convolution Network
por: Chang, Zhanyuan, et al.
Publicado: (2022)

Classification of Motor Imagery EEG Signals Based on Data Augmentation and Convolutional Neural Networks
por: Xie, Yu, et al.
Publicado: (2023)

A Multi-Branch Convolutional Neural Network with Squeeze-and-Excitation Attention Blocks for EEG-Based Motor Imagery Signals Classification
por: Altuwaijri, Ghadir Ali, et al.
Publicado: (2022)

A Generalizable and Discriminative Learning Method for Deep EEG-Based Motor Imagery Classification
por: Huang, Xiuyu, et al.
Publicado: (2021)

EEG channel selection based on sequential backward floating search for motor imagery classification
por: Tang, Chao, et al.
Publicado: (2022)

Improving Generalization Based on l(1)-Norm Regularization for EEG-Based Motor Imagery Classification
por: Zhao, Yuwei, et al.
Publicado: (2018)

A Novel Two-Stage Refine Filtering Method for EEG-Based Motor Imagery Classification
por: Yan, Yuxin, et al.
Publicado: (2021)

Parallel Spatial–Temporal Self-Attention CNN-Based Motor Imagery Classification for BCI
por: Liu, Xiuling, et al.
Publicado: (2020)

Spatial-Frequency Feature Learning and Classification of Motor Imagery EEG Based on Deep Convolution Neural Network
por: Miao, Minmin, et al.
Publicado: (2020)

Recognition of single upper limb motor imagery tasks from EEG using multi-branch fusion convolutional neural network
por: Zhang, Rui, et al.
Publicado: (2023)

Gaze Estimation Based on Convolutional Structure and Sliding Window-Based Attention Mechanism
por: Li, Yujie, et al.
Publicado: (2023)

Data Augmentation: Using Channel-Level Recombination to Improve Classification Performance for Motor Imagery EEG
por: Pei, Yu, et al.
Publicado: (2021)

Analysis of the Relationship Between Motor Imagery and Age-Related Fatigue for CNN Classification of the EEG Data
por: Li, Xiangyun, et al.
Publicado: (2022)

Temporal-frequency-phase feature classification using 3D-convolutional neural networks for motor imagery and movement
por: Fan, Chengcheng, et al.
Publicado: (2023)

Motor Imagery EEG Classification Using Capsule Networks†
por: Ha, Kwon-Woo, et al.
Publicado: (2019)

EEG sensorimotor rhythms’ variation and functional connectivity measures during motor imagery: linear relations and classification approaches
por: Stefano Filho, Carlos A., et al.
Publicado: (2017)

Stability of mental motor-imagery classification in EEG depends on the choice of classifier model and experiment design, but not on signal preprocessing
por: Rosenfelder, Martin Justinus, et al.
Publicado: (2023)

Multiclass Classification Based on Combined Motor Imageries
por: Lindig-León, Cecilia, et al.
Publicado: (2020)

Multi-Class Motor Imagery EEG Decoding for Brain-Computer Interfaces
por: Wang, Deng, et al.
Publicado: (2012)

A Motor Imagery Signals Classification Method via the Difference of EEG Signals Between Left and Right Hemispheric Electrodes
por: Lun, Xiangmin, et al.
Publicado: (2022)

A Decoding Scheme for Incomplete Motor Imagery EEG With Deep Belief Network
por: Chu, Yaqi, et al.
Publicado: (2018)

EEG-based detection of the locus of auditory attention with convolutional neural networks
por: Vandecappelle, Servaas, et al.
Publicado: (2021)

Closed-loop motor imagery EEG simulation for brain-computer interfaces
por: Shin, Hyonyoung, et al.
Publicado: (2022)

Subject-Independent EEG Classification of Motor Imagery Based on Dual-Branch Feature Fusion
por: Dong, Yanqing, et al.
Publicado: (2023)

Bridging the BCI illiteracy gap: a subject-to-subject semantic style transfer for EEG-based motor imagery classification
por: Kim, Da-Hyun, et al.
Publicado: (2023)

EEG oscillatory patterns and classification of sequential compound limb motor imagery
por: Yi, Weibo, et al.
Publicado: (2016)

Multiclass Posterior Probability Twin SVM for Motor Imagery EEG Classification
por: She, Qingshan, et al.
Publicado: (2015)

EEG feature comparison and classification of simple and compound limb motor imagery
por: Yi, Weibo, et al.
Publicado: (2013)

Motor Imagery Classification Based on EEG Sensing with Visual and Vibrotactile Guidance
por: Batistić, Luka, et al.
Publicado: (2023)

Unimodal Versus Bimodal EEG-fMRI Neurofeedback of a Motor Imagery Task
por: Perronnet, Lorraine, et al.
Publicado: (2017)

Motor Imagery Analysis from Extensive EEG Data Representations Using Convolutional Neural Networks
por: Lomelin-Ibarra, Vicente A., et al.
Publicado: (2022)

Relevant Feature Integration and Extraction for Single-Trial Motor Imagery Classification
por: Li, Lili, et al.
Publicado: (2017)

MSATNet: multi-scale adaptive transformer network for motor imagery classification
por: Hu, Lingyan, et al.
Publicado: (2023)

Predicting Motor Imagery Performance From Resting-State EEG Using Dynamic Causal Modeling
por: Lee, Minji, et al.
Publicado: (2020)

Cannot write session to /tmp/vufind_sessions/sess_t05fpd9sbp88u6ot6l7ql1n5st