A Decoding Scheme for Incomplete Motor Imagery EEG With Deep Belief Network

A Decoding Scheme for Incomplete Motor Imagery EEG With Deep Belief Network

High accuracy decoding of electroencephalogram (EEG) signal is still a major challenge that can hardly be solved in the design of an effective motor imagery-based brain-computer interface (BCI), especially when the signal contains various extreme artifacts and outliers arose from data loss. The conv...

Full description

Bibliographic Details
Main Authors: Yaqi Chu, Xingang Zhao, Yijun Zou, Weiliang Xu, Jianda Han, Yiwen Zhao
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-09-01
Series:Frontiers in Neuroscience
Subjects:
brain-computer interface
decoding scheme
incomplete motor imagery EEG
power spectral density
deep belief network
Online Access:https://www.frontiersin.org/article/10.3389/fnins.2018.00680/full

Similar Items

Similar Items