Paper Info
Title
Does A Subject Independent Dynamic Stopping Model for P300 Speller Work on Different Flash Durations and Inter Stimulus Intervals?
Abstract
Event-related potential (ERP)-based brain- computer interfacing (BCI) is an effective communication method. However, calibration itself can be unintuitive and tedious for users. The no-calibration Subject Independent Brain Computer Interface (SIBCI) is a popular solution to the lengthy calibration. Researches have proved the subject independent model is efficient in some P300 spellers, but it is still need to be explored whether the subject independent model works when the flash durations (FDs) and the inter stimulus intervals (ISIs) are changed in a P300 speller. This study introduces a subject independent dynamical stopping model (SIDSM), which based on a subject independent model to dynamically stop the data collection process. The performance of the SIDSM is studied by modifying the FDs and ISIs in online experiments for 8 subjects. Results showed the SIDSM has an average accuracy of 92.45% for different settings. This research proved that the SIDSM is very robust to different stimulus parameters as good performance is observed across all experimental sessions.
Year
DOI
Venue
2018
10.1109/EMBC.2018.8512602
EMBC
Field
DocType
Volume
Training set,Computer vision,Data collection,Data modeling,Computer science,Brain–computer interface,Interfacing,Speech recognition,Artificial intelligence,Stimulus (physiology),Electroencephalography,Calibration
Conference
2018
Citations 
PageRank 
References 
0
0.34
0
Authors
6
Name
Order
Citations
PageRank
Yuqi Xue100.34
Jiabei Tang213.42
Peng Zhou3136.25
Minpeng Xu42717.17
Dong Ming510551.47
Hongzhi Qi64920.61