Time-Distributed Attention Network for EEG-Based Motor Imagery Decoding From the Same Limb
A brain-computer interface (BCI) based on motor imagery (MI) from the same limb can provide an intuitive control pathway but has received limited attention. It is still a challenge to classify multiple MI tasks from the same limb. The goal of this study is to propose a novel decoding method to class...
Saved in:
Main Authors: | Xuelin Ma (Author), Shuang Qiu (Author), Huiguang He (Author) |
---|---|
Format: | Book |
Published: |
IEEE,
2022-01-01T00:00:00Z.
|
Subjects: | |
Online Access: | Connect to this object online. |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
EISATC-Fusion: Inception Self-Attention Temporal Convolutional Network Fusion for Motor Imagery EEG Decoding
by: Guangjin Liang, et al.
Published: (2024) -
Decoding Multi-Class Motor Imagery From Unilateral Limbs Using EEG Signals
by: Fenqi Rong, et al.
Published: (2024) -
SincNet-Based Hybrid Neural Network for Motor Imagery EEG Decoding
by: Chang Liu, et al.
Published: (2022) -
Motor Imagery EEG Decoding Based on Multi-Scale Hybrid Networks and Feature Enhancement
by: Xianlun Tang, et al.
Published: (2023) -
A Multi-Domain Convolutional Neural Network for EEG-Based Motor Imagery Decoding
by: Hongyi Zhi, et al.
Published: (2023)