Investigation of the trade-off between time window length, classifier update rate and classification accuracy for restorative brain-computer interfaces.
Sam DarvishiMichael C. RiddingDerek AbbottMathias BaumertPublished in: EMBC (2013)
Keyphrases
- brain computer interface
- trade off
- classification accuracy
- feature selection
- feature set
- training data
- feature space
- training set
- support vector
- high classification accuracy
- classification rate
- feature subset
- healthy subjects
- improvement in classification accuracy
- eeg signals
- multimodal interaction
- feature reduction
- motor imagery
- highest accuracy
- improving classification accuracy
- spinal cord injury
- brain activity
- svm classification
- bayesian network classifiers
- brain signals
- class labels
- naive bayes
- decision trees
- computer screen
- training set size
- signal processing
- extracted features
- classification algorithm
- classification method
- eeg data
- multiple classifier systems
- data sets
- support vector machine
- learning algorithm