A Genetic Algorithm-Based Multi-Parameter Method for Asynchronous Working State Classification Under SSVEP

A Genetic Algorithm-Based Multi-Parameter Method for Asynchronous Working State Classification Under SSVEP

Working state classification, which is a critical part of an asynchronous control system based on a brain-computer interface (BCI). The traditional algorithms for the working state classification are based on the threshold of power spectral density (PSD) or the canonical correlation analysis (CCA) p...

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Bibliographic Details
Main Authors: Zhiheng Wang, Bensong Geng, Xuxian Duan, Yunsheng Mao, Qinghua Yang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Asynchronous control
brain-computer interface (BCI)
steady-state visual evoked potentials (SSVEP)
working state classification
Online Access:https://ieeexplore.ieee.org/document/10488416/

Internet

https://ieeexplore.ieee.org/document/10488416/

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