| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 6950657 | Biomedical Signal Processing and Control | 2018 | 8 Pages |
Abstract
We designed a novel P300 detection algorithm assuming that the sparsity of EEG signals could be effectively utilized to detect target event-related potentials such as P300. Our pilot study results indicate that utilizing the sparsity of EEG signals can improve the automatic spelling experience.
Keywords
P300common average referenceBCIROCAUCElectroencephalogramERPLeast absolute shrinkage and selection operatorBrain–computer interfaceBrain computer interfaceEnsemble classifiersCARarea under the curveEEGOddball paradigmEvent-related potentialsEvent-related potentialData sparsityLASSOreceiver operating characteristic
Related Topics
Physical Sciences and Engineering
Computer Science
Signal Processing
Authors
Sunghan Kim, Austin White, Fabien Scalzo, David Collier,