Towards Brain-based Interface for Communication and Control by Skin Touch
Author:
Affiliation:
1. Korea University LG Display,Dept. Artificial Intelligence,Seoul,Republic of Korea
2. Korea University,Dept. Brain and Cognitive Engineering,Seoul,Republic of Korea
3. Korea University,Dept. Artificial Intelligence,Seoul,Republic of Korea
Funder
Interface
National Research Foundation of Korea
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10078410/10078447/10078458.pdf?arnumber=10078458
Reference13 articles.
1. Subject-Independent Brain–Computer Interfaces Based on Deep Convolutional Neural Networks
2. Brain-Controlled Robotic Arm System Based on Multi-Directional CNN-BiLSTM Network Using EEG Signals
3. A High Performance Spelling System based on EEG-EOG Signals With Visual Feedback
4. Decoding Movement-Related Cortical Potentials Based on Subject-Dependent and Section-Wise Spectral Filtering
5. A Subject-Transfer Framework Based on Single-Trial EMG Analysis Using Convolutional Neural Networks
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