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ETCNet:基于EEG的运动图像分类模型,结合了高效的道注意力和时间卷积网络.

Yuxin Qin1, Baojiang Li1, Wenlong Wang1

  • 1The School of Electrical Engineering, Shanghai Dianji University, Shanghai, China; Intelligent Decision and Control Technology Institute, Shanghai Dianji University, Shanghai, China.

Brain research
|November 13, 2023
PubMed
概括

这项研究引入了一种新的深度学习网络,用于使用脑电图 (EEG) 信号的脑电脑接口 (BCI). 高效的道注意力和时间卷积网络模型提高了运动图像分类的准确性,为残疾人提供了潜在的潜力.

关键词:
大脑与计算机的接口.分类 分类 分类 分类.有效的频道注意力.功能提取 功能提取运动图像中的运动图像.时间卷积网络的时间卷积网络.

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