Time-Shift Correlation Algorithm for P300 Event Related Potential Brain-Computer Interface Implementation
Joint Authors
Liu, Ju-Chi
Chou, Hung-Chyun
Chen, Chien-Hsiu
Lin, Yi-Tseng
Kuo, Chung-Hsien
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2016, Issue 2016 (31 Dec. 2015), pp.1-22, 22 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2016-08-08
Country of Publication
Egypt
No. of Pages
22
Main Subjects
Abstract EN
A high efficient time-shift correlation algorithm was proposed to deal with the peak time uncertainty of P300 evoked potential for a P300-based brain-computer interface (BCI).
The time-shift correlation series data were collected as the input nodes of an artificial neural network (ANN), and the classification of four LED visual stimuli was selected as the output node.
Two operating modes, including fast-recognition mode (FM) and accuracy-recognition mode (AM), were realized.
The proposed BCI system was implemented on an embedded system for commanding an adult-size humanoid robot to evaluate the performance from investigating the ground truth trajectories of the humanoid robot.
When the humanoid robot walked in a spacious area, the FM was used to control the robot with a higher information transfer rate (ITR).
When the robot walked in a crowded area, the AM was used for high accuracy of recognition to reduce the risk of collision.
The experimental results showed that, in 100 trials, the accuracy rate of FM was 87.8% and the average ITR was 52.73 bits/min.
In addition, the accuracy rate was improved to 92% for the AM, and the average ITR decreased to 31.27 bits/min.
due to strict recognition constraints.
American Psychological Association (APA)
Liu, Ju-Chi& Chou, Hung-Chyun& Chen, Chien-Hsiu& Lin, Yi-Tseng& Kuo, Chung-Hsien. 2016. Time-Shift Correlation Algorithm for P300 Event Related Potential Brain-Computer Interface Implementation. Computational Intelligence and Neuroscience،Vol. 2016, no. 2016, pp.1-22.
https://search.emarefa.net/detail/BIM-1099627
Modern Language Association (MLA)
Liu, Ju-Chi…[et al.]. Time-Shift Correlation Algorithm for P300 Event Related Potential Brain-Computer Interface Implementation. Computational Intelligence and Neuroscience Vol. 2016, no. 2016 (2015), pp.1-22.
https://search.emarefa.net/detail/BIM-1099627
American Medical Association (AMA)
Liu, Ju-Chi& Chou, Hung-Chyun& Chen, Chien-Hsiu& Lin, Yi-Tseng& Kuo, Chung-Hsien. Time-Shift Correlation Algorithm for P300 Event Related Potential Brain-Computer Interface Implementation. Computational Intelligence and Neuroscience. 2016. Vol. 2016, no. 2016, pp.1-22.
https://search.emarefa.net/detail/BIM-1099627
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1099627