A Synchronized Hybrid Brain-Computer Interface System for Simultaneous Detection and Classification of Fusion EEG Signals
Brain-computer interface (BCI) technology represents a fast-growing field of research and applications for disabled and healthy people, which is a direct communication pathway to translate the neural information into an active command. Owing to the complicated headset structure, low accuracies, exte...
Saved in:
Main Authors: | Dalin Yang, Trung-Hau Nguyen, Wan-Young Chung |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2020-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2020/4137283 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Synergy of Convolutional Neural Networks for Sensor-Based EEG Brain–Computer Interfaces to Enhance Motor Imagery Classification
by: Souheyl Mallat, et al.
Published: (2025-01-01) -
Effect of EOG Signal Filtering on the Removal of Ocular Artifacts and EEG-Based Brain-Computer Interface: A Comprehensive Study
by: Malik M. Naeem Mannan, et al.
Published: (2018-01-01) -
Advanced TSGL-EEGNet for Motor Imagery EEG-Based Brain-Computer Interfaces
by: Xin Deng, et al.
Published: (2021-01-01) -
Personalised Affective Classification Through Enhanced EEG Signal Analysis
by: Joseph Barrowclough, et al.
Published: (2025-12-01) -
Real-time classification of EEG signals using Machine Learning deployment
by: Swati CHOWDHURI, et al.
Published: (2024-12-01)