학술논문

A Training System for Brain-Computer Interfaces Based on Motor Imagery Selection
Document Type
Conference
Source
2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech) Life Sciences and Technologies (LifeTech), 2020 IEEE 2nd Global Conference on. :217-218 Mar, 2020
Subject
Bioengineering
Communication, Networking and Broadcast Technologies
Computing and Processing
General Topics for Engineers
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
electroencephalogram (EEG)
training system
motor imagery
class selection
Kullback-Leibler divergence
brain-computer interface (BCI)
Language
Abstract
This paper proposes a BCI training system based on motor imagery selection. The system selects discriminable motor imagery tasks based on the partial KL information theory and provides related feedback training. Results from training experiments showed a gradual increase in repeatability for all subjects in selected motor imagery tasks.