A Robust Multi-Branch CNN-LSTM Architecture for Cross-Subject Motor Imagery Classification
Brain–computer interfaces (BCIs) based on motor imagery (MI) aim to convert electroencephalographic (EEG) activity into reliable device commands across users and recording setups. However, low signal-to-noise ratio and strong inter-subject variability still limit true “plug-and-play” deployment with...
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| Principais autores: | , , |
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| Format: | Artigo |
| Sprog: | Inglês |
| Udgivet: |
MDPI AG
2026-05-01
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| Serier: | Sensors |
| Fag: | |
| Online adgang: | https://www.mdpi.com/1424-8220/26/11/3310 |
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