Title
Classifying speech related vs. idle state towards onset detection in brain-computer interfaces overt, inhibited overt, and covert speech sound production vs. idle state
Abstract
Onset detection is one of the main issues towards self-paced BCIs that can be used outside research settings. For this reason, this paper suggests a potential solution for onset detection problem by discriminating between speech related events. In this study, overt, inhibited overt and covert states were tested to classify from idle state in an off-line setting. Autoregressive model coefficients were used for feature extraction. The results showed that covert speech (vs. idle state) performed the best for all 4 participants. The true positive accuracies were 82.41%, 81.20%, 85.12% and 74.72%, respectively. The bit-transfer rates were 32.95, 16.24, 34.05 and 22.42 per minute, respectively. Compared to a previous study [1], which achieved around 73% accuracy with motor imagery versus idle, this study gave us satisfactory results.
Year
DOI
Venue
2014
10.1109/BioCAS.2014.6981789
BioCAS
Keywords
Field
DocType
auditory evoked potentials,autoregressive processes,brain-computer interfaces,electroencephalography,feature extraction,medical signal detection,medical signal processing,signal classification,speech,autoregressive model coefficient,bit-transfer rate,brain-computer interface,covert speech sound production,covert state testing,idle state classification,inhibited overt speech sound production,inhibited overt state testing,motor imagery,off-line setting,onset detection problem,self-paced bci,speech related event discrimination,speech related state classification,true positive accuracy,autoregressive model,covert speech,onset detection
Autoregressive model,Idle,Voice activity detection,Computer science,Brain–computer interface,Covert,Speech recognition,Feature extraction,Motor imagery
Conference
ISSN
Citations 
PageRank 
2163-4025
0
0.34
References 
Authors
5
2
Name
Order
Citations
PageRank
YoungJae Song100.34
Francisco Sepulveda225226.54