Comparative analysis of features extracted from EEG spatial, spectral and temporal domains for binary and multiclass motor imagery classification.
Seung-Bo LeeHyun-Ji KimHakseung KimJi-Hoon JeongSeong-Whan LeeDong-Joo KimPublished in: Inf. Sci. (2019)
Keyphrases
- multi class
- motor imagery
- comparative analysis
- eeg signals
- binary classifiers
- extracted features
- multiclass classification
- multi class svms
- error correcting output codes
- brain computer interface
- binary classification problems
- support vector machine
- multiclass problems
- kernel fisher
- multiclass support vector machines
- multiclass learning
- multi class classification
- eeg data
- svm classifier
- multiple classes
- feature vectors
- cost sensitive classification
- feature extraction
- binary classification
- feature selection
- healthy subjects
- pairwise
- multi class classifier
- classification accuracy
- feature space
- cost sensitive
- supervised learning
- feature set
- signal processing
- pattern recognition
- pattern classification
- perceptron algorithm
- machine learning
- support vector
- brain activity
- spinal cord injury
- class imbalance