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Alternative TitleConvolutional neural network based on temporal-spatial feature learning for motor imagery eeg signal decoding
褚亚奇1,2,3; 朱波1,2,3; 赵新刚1,2; 赵忆文1,2
Source Publication生物医学工程学杂志
Contribution Rank1
Funding Organization国家自然科学基金(61573340,61773369,U1813214) ; 中国科学院前沿科学重点研究项目(QYZDY-SSWJSC005) ; 辽宁省“兴辽英才计划”项目(XLYC1908030)
Keyword运动想象脑电 脑机接口 时空特征 卷积神经网络 信号解码


Other Abstract

With the advantage of providing more natural and flexible control manner, brain-computer interface systems based on motor imagery electroencephalogram (EEG) have been widely used in the field of human-machine interaction. However, due to the lower signal-noise ratio and poor spatial resolution of EEG signals, the decoding accuracy is relative low. To solve this problem, a novel convolutional neural network based on temporal-spatial feature learning (TSCNN) was proposed for motor imagery EEG decoding. Firstly, for the EEG signals preprocessed by band-pass filtering, a temporal-wise convolution layer and a spatial-wise convolution layer were respectively designed, and temporal-spatial features of motor imagery EEG were constructed. Then, 2-layer two-dimensional convolutional structures were adopted to learn abstract features from the raw temporal-spatial features. Finally, the softmax layer combined with the fully connected layer were used to perform decoding task from the extracted abstract features. The experimental results of the proposed method on the open dataset showed that the average decoding accuracy was 80.09%, which is approximately 13.75% and 10.99% higher than that of the state-of-the-art common spatial pattern (CSP) + support vector machine (SVM) and filter bank CSP (FBCSP) + SVM recognition methods, respectively. This demonstrates that the proposed method can significantly improve the reliability of motor imagery EEG decoding.

Document Type期刊论文
Corresponding Author赵新刚
Recommended Citation
GB/T 7714
褚亚奇,朱波,赵新刚,等. 基于时空特征学习卷积神经网络的运动想象脑电解码方法[J]. 生物医学工程学杂志,2021,38(1):1-9.
APA 褚亚奇,朱波,赵新刚,&赵忆文.(2021).基于时空特征学习卷积神经网络的运动想象脑电解码方法.生物医学工程学杂志,38(1),1-9.
MLA 褚亚奇,et al."基于时空特征学习卷积神经网络的运动想象脑电解码方法".生物医学工程学杂志 38.1(2021):1-9.
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