SMANet: A Model Combining SincNet, Multi-Branch Spatial—Temporal CNN, and Attention Mechanism for Motor Imagery BCI
Building a brain-computer interface (BCI) based on motor imagery (MI) requires accurately decoding MI tasks, which poses a significant challenge due to individual discrepancy among subjects and low signal-to-noise ratio of EEG signals. We propose an end-to-end deep learning model, Sinc-multibranch-a...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Transactions on Neural Systems and Rehabilitation Engineering |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10965876/ |
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