Name
Abstract | ||
|---|---|---|
To realize asynchronous control of a brain-computer interface (BCI) system, a fast brain switch with low false positive rate (FPR) is required. This paper proposed a brain switch based on code-modulated visual-evoked potential (c-VEP), in which seven 8-bit pseudorandom codes were used to modulate the electroencephalogram (EEG) signal. This study optimized and demonstrated the control strategy through an offline and an online experiments. By decoding the brain state continuously with the task-related component analysis (TRCA) algorithm, the brain switch achieved an average reaction time (RT) of 1.72 seconds and an average idle time of 183.53 seconds without false positive events in the online experiment. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1109/EMBC.2019.8857617 | 2019 41ST ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY (EMBC) |
Field | DocType | Volume |
Computer vision,False positive rate,Asynchronous communication,Class Code,Computer science,Brain–computer interface,Artificial intelligence,Decoding methods,Computer hardware,Component analysis,Electroencephalography,Pseudorandom number generator | Conference | 2019 |
ISSN | Citations | PageRank |
1557-170X | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Li Zheng | 1 | 0 | 0.34 |
| Yijun Wang | 2 | 308 | 46.68 |
| Weihua Pei | 3 | 64 | 13.18 |
| Hongda Chen | 4 | 99 | 20.06 |