A novel transformer for attention decoding using EEG

A novel transformer for attention decoding using EEG

Electroencephalography (EEG) attention classification plays a crucial role in brain-computer interface (BCI) applications. This paper introduces EEG-PatchFormer, a novel deep learning model leveraging transformers to achieve superior EEG attention decoding. We posit that transformers’ strength in ca...

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Bibliographic Details
Main Author: Lee, Joon Hei
Other Authors: Guan Cuntai
Format: Final Year Project (FYP)
Language:English
Published: Nanyang Technological University 2024
Subjects:
Computer and Information Science
EEG
Deep learning
Attention
Brain-computer interface
Online Access:https://hdl.handle.net/10356/175057

Internet

https://hdl.handle.net/10356/175057

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