Multimodal Mild Depression Recognition Based on EEG-EM Synchronization Acquisition Network

Multimodal Mild Depression Recognition Based on EEG-EM Synchronization Acquisition Network

In this paper, we used electroencephalography (EEG)-eye movement (EM) synchronization acquisition network to simultaneously record both EEG and EM physiological signals of the mild depression and normal controls during free viewing. Then, we consider a multimodal feature fusion method that can best...

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Bibliographic Details
Main Authors: Jing Zhu, Ying Wang, Rong La, Jiawei Zhan, Junhong Niu, Shuai Zeng, Xiping Hu
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
EEG
eye movement
mild depression
network
classification
multimodal deep learning
Online Access:https://ieeexplore.ieee.org/document/8653893/

Internet

https://ieeexplore.ieee.org/document/8653893/

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