Skip to main navigation
Skip to search
Skip to main content
Korea University Pure Home
Home
Profiles
Research units
Equipment
Research output
Press/Media
Search by expertise, name or affiliation
Novel BCI classification method using cross-channel-region CSP features
Yongkoo Park
,
Wonzoo Chung
*
*
Corresponding author for this work
Research output
:
Chapter in Book/Report/Conference proceeding
›
Conference contribution
21
Citations (Scopus)
Overview
Fingerprint
Fingerprint
Dive into the research topics of 'Novel BCI classification method using cross-channel-region CSP features'. Together they form a unique fingerprint.
Sort by
Weight
Alphabetically
Keyphrases
Classification Methods
100%
Cross-channel
100%
Subchannel
66%
Motor Imagery Classification
33%
Motor Imagery
33%
Single Channel
33%
Performance Improvement
33%
Classification Accuracy
33%
EEG-BCI
33%
Regional Data
33%
Sensor Space
33%
Locally Produced
33%
Measuring Channel
33%
LS-SVM Classifier
33%
Engineering
Brain-Computer Interface
100%
Classification Method
100%
Channel Region
100%
Motor Imagery
40%
Single Channel
20%
Classification Accuracy
20%
Performance Improvement
20%
Computer Science
Classification Method
100%
Channel Region
100%
Support Vector Machine
20%
Classification Accuracy
20%
Performance Improvement
20%