Name
Title | ||
|---|---|---|
Phase-synchrony evaluation of EEG signals for Multiple Sclerosis diagnosis based on bivariate empirical mode decomposition during a visual task. |
Abstract | ||
|---|---|---|
•The presented research is a step forward in the development of automated MS diagnosis systems using event-related EEGs.•Phase-synchrony information derived from bivariate empirical mode decomposition was used for MS diagnosis.•.Higher levels of networks synchronization in the posterior regions of the brain were seen among the MS group. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.compbiomed.2019.103596 | Computers in Biology and Medicine |
Keywords | DocType | Volume |
Bivariate empirical mode decomposition,Electroencephalography,Multiple sclerosis,Mean phase coherence,Phase-synchrony,reliefF,Visual task | Journal | 117 |
ISSN | Citations | PageRank |
0010-4825 | 0 | 0.34 |
References | Authors | |
0 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Khadijeh Raeisi | 1 | 0 | 0.34 |
| Maryam Mohebbi | 2 | 0 | 0.34 |
| Mohammad Khazaei | 3 | 0 | 0.34 |
| Masoud Seraji | 4 | 0 | 0.34 |
| Ali Yoonessi | 5 | 0 | 0.34 |