Name
Abstract | ||
|---|---|---|
•New features from phase space trajectories of EEG nonlinear dynamics are proposed.•Moment invariant features allow robust description of phase space trajectory.•Distance series transforms trajectory to 1D signal to be used as features.•Experimental results indicate potential for new features in BCI applications.•Proposed features allow real-time performance needed for BCI applications. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1016/j.bspc.2017.05.007 | Biomedical Signal Processing and Control |
Keywords | Field | DocType |
Brain-Computer Interface (BCI),Electroencephalogram (EEG),Distance series (DS),Moment invariants,Phase space reconstruction (PSR) | Computer vision,Nonlinear system,Computer science,Phase space,Brain–computer interface,Artificial intelligence,Trajectory,Mental state,Online processing,Machine learning,Computation | Journal |
Volume | ISSN | Citations |
38 | 1746-8094 | 3 |
PageRank | References | Authors |
0.37 | 12 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Khaled S. Sayed | 1 | 3 | 1.04 |
| Mahmoud Kamel | 2 | 13 | 1.60 |
| Mohammed J. Alhaddad | 3 | 76 | 8.55 |
| Hussein Malibary | 4 | 3 | 0.70 |
| Y. M. Kadah | 5 | 192 | 18.80 |